Molecular Geomicrobiology 9781501509551, 9780939950713

Table of contents :
COPYRIGHT
REVIEWS
DEDICATION
PREFACE
TABLE OF CONTENTS
1. The Search for a Molecular-Level Understanding of the Processes that Underpin the Earth's Biogeochemical Cycles
2. What Genetics Offers Geobiology
3. Enzymology of Electron Transport: Energy Generation With Geochemical Consequences
4. Siderophores and the Dissolution of Iron-Bearing Minerals in Marine Systems
5. Geomicrobiological Cycling of Iron
6. Molecular-Scale Processes Involving Nanoparticulate Minerals in Biogeochemical Systems
7. The Organic-Mineral Interface in Biominerals
8. Catalysis and Prebiotic Synthesis
9. The Evolution of Biological Carbon and Nitrogen Cycling—a Genomic Perspective
10. Building the Biomarker Tree of Life
11. Population Dynamics Through the Lens of Extreme Environments
12. Metabolism and Genomics: Adventures Derived From Complete Genome Sequencing

Citation preview

REVIEWS IN MINERALOGY AND GEOCHEMISTRY V O L U M E 59

2005

MOLECULAR GEOMICROBIOLOGY EDITORS: Jillian F. Banfield

University of California, Berkeley Berkeley, California

Javiera C e r v i n i - S i l v a

University of California, Berkeley Berkeley, California

Kenneth H. Nealson

University of Southern California Los Angeles, California

FRONT COVER: Dinitrogen (N 2 ) bound at the molybdenum-iron-sulfur active site of the nitrogenase enzyme complex, where it is ultimately reduced to biologically-useful ammonia. Nitrogenase is the only enzyme known to catalyze such a transformation, and is found only in prokaryotes, representing a crucial shunt between the inorganic and organic worlds. Created by Jason Raymond and Jill Banfield.

Series Editor: Jodi J.

Rosso

M I N E K A L O G I C A L S O C I E T Y OF A M E R I C A GEOCHEMICAL SOCIETY

COPYRIGHT 2 0 0 5

MINERALOGICAL SOCIETY OF A M E R I C A The appearance of the code at the bottom of the first page of each chapter in this volume indicates the copyright owner's consent that copies of the article can be made for personal use or internal use or for the personal use or internal use of specific clients, provided the original publication is cited. The consent is given on the condition, however, that the copier pay the stated per-copy fee through the Copyright Clearance Center, Inc. for copying beyond that permitted by Sections 107 or 108 of the U.S. Copyright Law. This consent does not extend to other types of copying for general distribution, for advertising or promotional purposes, for creating new collective works, or for resale. For permission to reprint entire articles in these cases and the like, consult the Administrator of the Mineralogical Society of America as to the royalty due to the Society.

REVIEWS IN MINERALOGY AND GEOCHEMISTRY ( Formerly:

REVIEWS IN MINERALOGY )

ISSN 1529-6466

Volume 59

Molecular Geomicrobiology ISBN 093995071-5 Additional copies of this volume as well as others in this series may be obtained at moderate cost from: THE M I N E R A L O G I C A L

S O C I E T Y OF A M E R I C A

3 6 3 5 CONCORDE PARKWAY, SUITE 5 0 0 CHANTILLY, VIRGINIA, 2 0 1 5 1 - 1 1 2 5 , U . S . A . WWW.MINSOCAM.ORG

DEDICATION Dr. William C. Luth has had a long and distinguished career in research, education and in the government. He was a leader in experimental petrology and in training graduate students at Stanford University. His efforts at Sandia National Laboratory and at the Department of Energy's headquarters resulted in the initiation and long-term support of many of the cutting edge research projects whose results form the foundations of these short courses. Bill's broad interest in understanding fundamental geochemical processes and their applications to national problems is a continuous thread through both his university and government career. He retired in 1996, but his efforts to foster excellent basic research, and to promote the development of advanced analytical capabilities gave a unique focus to the basic research portfolio in Geosciences at the Department of Energy. He has been, and continues to be, a friend and mentor to many of us. It is appropriate to celebrate his career in education and government service with this series of courses in cutting-edge geochemistry that have particular focus on Department of Energy-related science, at a time when he can still enjoy the recognition of his contributions.

MOLECULAR GEOMICROBIOLOGY 59

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FROM THE SERIES EDITOR This volume was prepared in advance of a short course entitled "Molecular Geomicrobiology." The short course, sponsored by the Mineralogical Society of America, the Geochemical Society, the US Department of Energy, and NASA Astrobiology Institute, was held at the University of California, Berkeley, December 3-4, 2005 prior to the fall AGU meeting in San Francisco, California. Errata (if any) can be found at the MSA website www.minsocam.org. Todi T. P-osso, Series Editor West Richland, Washington October 2005

PREFACE As geomicrobiologists, we seek to understand how some of nature's most complex systems work, yet the very complexity we seek to understand has placed many of the insights out of reach. Recent advances in cultivation methodologies, the development of ultrahigh throughput DNA sequencing capabilities, and new methods to assay gene expression and protein function open the way for rapid progress. In the eight years since the first Geomicrobiology volume (Geomicrobiology: Interactions between microbes and minerals; volume 35 in this series) we have transformed into scientists working hand in hand with biochemists, molecular biologists, genome scientists, analytical chemists, and even physicists to reveal the most fundamental molecular-scale underpinnings of biogeochemical systems. Through synthesis achieved by integration of diverse perspectives, skills, and interests, we have begun to learn how organisms mediate chemical transformations, the ways in which the environment determines the architecture of microbial communities, and the interplay between evolution and selection that shapes the biodiversity of the planet. This volume presents chapters written by leaders in the rapidly maturing field we refer to as molecular geomicrobiology. Most of them are relatively young researchers who share their approaches and insights and provide pointers to exciting areas ripe for new advances. This volume ties together themes common to environmental microbiology, earth science, and astrobiology. The resesarch presented here, the associated short course, and the volume production were supported by funding from many sources, notably the Mineralogical Society of America, the Geochemical Society, the US Department of Energy Chemical Sciences Program and the NASA Astrobiology Institute. We thank Jodi Rosso for her editorial contributions. October 2005 Jillian F. Banfield Javiera Cervini-Silva Kenneth H. Nealson

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TABLE OF CONTENTS 1

The Search for a Molecular-Level Understanding of the Processes that Underpin the Earth's Biogeochemical Cycles Jillian F. Banfield, Gene U'. Tyson, Eric E. Allen, Rachel J. Whitaker

CHARACTERIZING BIOGEOCHEMICAL SYSTEMS MOLECULAR GEOMICROBIOLOGY: OPPORTUNITIES AND CHALLENGES CONCLUDING COMMENTS ACKNOWLEDGMENTS REFERENCES

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What Genetics Offers Geobiology Dianne K. Newman, Jeffrey A. Gralnick

INTRODUCTION DEFINITIONS What is genetics? How is genetics different from molecular biology and genomics? What is a mutant? What is mutagenesis? TYPES OF GEOBIOLOGICAL PROBLEMS THAT GENETICS CAN SOLVE PRACTICAL CONSIDERATIONS FOR CREATING GENETIC SYSTEMS Step 1: Isolation and growth Step 2: Methods of mutagenesis Genetic polarity in bacteria Step 3: Identifying mutants Step 4: Mutant verification A brief note on phage Step 5: Mutant analysis CONCLUSIONS ACKNOWLEDGMENTS REFERENCES

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Enzymology of Electron Transport: Energy Generation With Geochemical Consequences Thomas J. DiChristina, Jim K. Fredrickson, John M. Zachara INTRODUCTION ENZYMATIC BASIS OF IRON AND MANGANESE REDUCTION Direct enzymatic reduction at the outer membrane Electron shuttling pathways Fe(III) solubilization by exogenous or bacterially-produced organic ligands followed by reduction of soluble organic-Fe(III) ENZYMATIC BASIS OF URANIUM REDUCTION Involvement of c-type cytochromes in enzymatic U(VI) reduction Effect of U(VI) chemical speciation on enzymatic U(VI) reduction activity Electron donors and competing electron acceptors Subcellular location of enzymatic U(VI) reduction activity ENZYMATIC MECHANISM OF TECHNETIUM REDUCTION Involvement of hydrogenases in Tc(VII) reduction Subcellular location of enzymatic Tc(VII) reduction activity MICROBIAL REDUCTION-INDUCED CHANGES IN MI I AI. BIOGEOCHEMISTRY Direct enzymatic effects of dissimilatory metal-reducing bacteria (DMRB) on metal solubility Indirect effects of DMRB on metal solubility REDUCTIVE TRANSFORMATION OF Fe- AND Mn-CONTAINING MINERALS Laboratory studies Field studies ROLE OF MICROBIAL METAL REDUCTION IN REDOX CYCLING Redox cycling in chemically stratified environments Microscale redox cycling SUMMARY ACKNOWLEDGMENTS REFERENCES

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Siderophores and the Dissolution of Iron-Bearing Minerals in Marine Systems Stephan M. Kraemer, Alison Butler, Paul Borer, Javiera Cervini-Silva INTRODUCTION 53 Scope of this review 53 The iron limitation hypothesis 54 BIOLOGICAL IRON ACQUISITION STRATEGIES 54 Iron acquisition by bacteria 54 Iron acquisition by eukaryotic phytoplankton 55 Role of protozoan grazers in the cycling of iron 56 SOURCES OF IRON IN HNLC OCEAN REGIONS 56 Atmospheric dust as a source of iron 57 Iron mineralogy of atmospheric dust 57 Transformation of iron-bearing minerals during atmospheric transport 57 CONCENTRATIONS, SPECIATION AND SOLUBILITY OF IRON IN SEAWATER ...58 Iron concentrations as a function of depth in HNLC regions 58 Inorganic iron species 58 Solubility of iron in the presence of iron oxides 59 Colloidal iron in marine systems 62 Photochemistry and redox speciation of iron 62 ORGANIC LIGANDS AND IRON SOLUBILITY AND SPECIATION 63 Speciation of soluble iron in the presence of organic ligands 63 Marine siderophores 64 Photo reduction of iron and redox cycling in the presence of siderophores 65 Effect of organic ligands on the solubility of iron oxides 67 DISSOLUTION OF AEROSOLS AND DEFINED IRON OXIDES IN SEAWATER 70 Dissolution mechanisms 70 Experimentally observed dissolution rates of aerosol and defined minerals 72 Photo-reductive dissolution in seawater 72 ORGANIC LIGANDS AND IRON OXIDE DISSOLUTION IN SEAWATER 73 Siderophore-promoted dissolution mechanisms 73 Photo-reductive dissolution mechanisms in the presence of siderophores 75 Amphiphilic siderophores 75 CONCLUSIONS 76 REFERENCES 76

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Geomicrobiological Cycling of Iron Andreas Kappler, Kristina L. Straub

INTRODUCTION General aspects of the iron cycle Solubility and chemical transformation of Fe(II) and Fe(III) minerals Surface area and reactivity of ferric iron oxides Ferrihydrite Forms of iron present in the environment Role of iron for microbial energy metabolism MICROBIAL OXIDATION OF Fe(II) Competition between chemical and microbial oxidation of Fe(II) Aerobic acidophilic Fe(II)-oxidizing microorganisms Aerobic neutrophilic Fe(II)-oxidizing microorganisms Anaerobic Fe(II)-oxidizing phototrophic bacteria Anaerobic Fe(II)-oxidizing nitrate-reducing bacteria Mechanisms of microbial Fe(II) oxidation Formation of Fe(III) minerals by microbial Fe(II) oxidation MICROBIAL DISSIMILATORY REDUCTION OF Fe(III) Acidophilic Fe(III)-reducing microorganisms Microbial reduction of Fe(III) at neutral pH Methods to study mechanisms of microbial Fe(III) reduction Microbial mechanisms of Fe(III) reduction at neutral pH MICROBIAL IRON CYCLING Microbial iron cycling under acidic conditions Microbial iron cycling at neutral pH Prerequisites for microbial iron cycling at neutral pH Oxygen-dependent microbial cycling of iron Oxygen-independent microbial cycling of iron ENVIRONMENTAL IMPLICATIONS Degradation of organic compounds coupled to dissimilatory Fe(III) reduction Iron minerals as adsorbents Immobilization of toxic metal ions by microbial Fe(II) oxidation and Fe(III) reduction Formation of reactive iron minerals SOME TASKS FOR FUTURE INVESTIGATIONS ACKNOWLEDGMENTS REFERENCES

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Molecular-Scale Processes Involving Nanoparticulate Minerals in Biogeochemical Systems Benjamin Gilbert, Jillian F. Banfield

INTRODUCTION Sources of nanoparticles in the environment Impacts of nanoparticles on their surroundings Nanoparticles—special properties and implications Overview of small size effects in minerals PHYSICAL STRUCTURE AND COMPOSITION OF NANOSCALE MINERALS Thermodynamic constraints on the structure of nanoparticles The nature of the initial precipitates and subsequent aging Size dependence of mineral solubility Characterization studies of biogenic nanoparticles The effects of water and other surface-bound molecules on nanoparticle structure Incorporation of impurity atoms The surfaces of nanoscale minerals ELECTRONIC STRUCTURE OF NANOSCALE MINERALS Introduction to electronic structure of solids Energy levels in semiconductor minerals Electronic structure of nanoparticles REDOX BEHAVIOR OF NANOPARTICLES Size effects on nanoparticle redox behavior Examples of nanoparticle redox behavior PHOTOCHEMISTRY Size effects on nanoparticle photochemistry Nanoparticle interactions with biomolecules Examples of nanoparticle photochemistry The stability of nanoparticles during redox chemistry and photochemistry Nanoparticle interactions with microorganisms Nanoparticle aggregation and its consequences CONCLUSIONS ACKNOWLEDGMENTS REFERENCES

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The Organic-Mineral Interface in Biominerals P. U. P. A. Gilbert, Mike Abrecht Bradley H. Frazer

BIOMINERALS: TOUGH STRUCTURES OF LIFE Introduction to biominerals Why biominerals The organic-mineral interface Zooming in on the organic-mineral interface SPECTROMICROSCOPY OF BIOMINERALS XANES spectroscopy of biominerals XANES microscopy of biominerals Overcoming charging effects THE ORGANIC-MINERAL INTERFACE IN MICROBIAL BIOMINERALS Prokaryotic biominerals Bacterial cell walls Capsules S-layers Sheaths Filaments THE ORGANIC-MINERAL INTERFACE IN EUKARYOTIC BIOMINERALS Eukaryotic biominerals The nano-structure of nacre Start and stop signals in nacre growth Synergy of mechanisms for nacre growth Bl( (MINERAL GLUE: THE CARBOXYL GROUP. CONCLUSION ACKNOWLEDGMENTS REFERENCES

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Catalysis and Prebiotic Synthesis James P. Ferris

INTRODUCTION 1 ORM.VI ION OF I III! SOLAR SYSTEM i i n : i:\Ri.Y I ARI II Atmosphere Primary sources of simple organics PREBIOTIC ROUTES TO BIOPOLYMER PRECURSORS RNA world The structure of and prebiotic synthesis of RNA monomers Vesicles CHIRALITY PREBIOTIC POLYMERIZATION OF RNA MONOMERS NON-ENZYMATIC TEMPLATE-DIRECTED SYNTHESIS OF RNA ALTERNATIVE GENETIC SYSTEMS EXAMPLES OF MINERAL AND METAL ION CATALYSIS IN PREBIOTIC CHEMISTRY Non-catalytic formation of biopolymers; polypeptides Montmorillonite catalysis of RNA synthesis Metal ion catalysis of template-directed synthesis POSSIBLE CATALYTIC REACTION PATHWAYS Metal ions Metal ion catalysis of template-directed synthesis of RNA oligomers A postulate for montmorillonite catalysis POTENTIAL STEPS TO THE ORIGIN OF LIFE FROM OLIGOMERS PROPOSED EXPERIMENTS Selection of oligomers that bind to other biomolecules Catalysis of template-directed synthesis Catalysis of RNA ligation ACKNOWLEDGMENTS REFERENCES

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The Evolution of Biological Carbon and Nitrogen Cycling—a Genomic Perspective Jason Raymond

INTRODUCTION USING GENOMICS TO UNDERSTAND THE PRESENT (AND INFER THE PAST) BIOLOGICAL NITROGEN CYCLING AND DIAZOTROPHY GEOLOGICAL CLUES TO THE EARLY NITROGEN CYCLE BIOLOGICAL CARBON CYCLING AND AUTOTROPHY WOOD-LJUNGDAHL (REDUCTIVE ACETYL-COA) PATHWAY THE rTCA CYCLE THE CALVIN-BENSON-BASSHAM CYCLE 3-HYDROXYPROPIONATE CYCLE AUTOTROPHY, HETEROTROPHY, AND THE ORIGIN OF METABOLISM REFERENCES

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Building the Biomarker Tree of Life Jochen J. Brocks, Ann Pearson

INTRODUCTION The biomarker principle The carbon isotopic composition of biomarkers BIOMARKERS IN GEOMICROBIOLOGY Biomarkers as indicators of metabolism Biomarkers as indicators of the evolution of life and the environment Orphan biomarkers and unknown pathways BUILDING THE BIOMARKER TREE OF LIFE A phylogenetic approach to the origin and distribution of biomarkers ACKNOWLEDGMENTS REFERENCES

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Population Dynamics Through the Lens of Extreme Environments Rachel J. Whitaker, Jillian F. Banfield

INTRODUCTION DEFINING A POPULATION - THE LENS OF EXTREME ENVIRONMENTS SOURCES OF G I N O M k VARIATION METHODS FOR IDENTIFYING GENOMIC VARIATION BASIC POPULATION PARAMETERS: SELECTION, RECOMBINATION AND GENETIC DRI1 I SHAPING POPULATION STRUCTURE THROUGH SELECTION AND RECOMBINATION IDENTIFYING ADAPTIVE TRAITS Recognizing genes under selection in recombining populations Recognizing genes under selection in clonal populations CONCLUSION: INTEGRATING GENETIC AND GEOCHEMICAL MOLECULAR TOOLS ACKNOWLEDGMENTS REFERENCES

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Metabolism and Genomics: Adventures Derived From Complete Genome Sequencing Karen E. Nelson, Barbara Methe

INTRODUCTION GENOME SEQUENCING AND ASSEMBLY SIMULTANEOUS COMPARISON OF MULTIPLE GENOMES FUNCTIONAL GENOMICS - A SYSTEMS-LEVEL APPROACH EXAMPLES OF WHOLE GENOME RECONSTRUCTIONS AND DERIVED INFORMATION GEOBACTER SULFURREDUCENS THERMOTOGA MARITIMA METABOLISM BASED ON GENOMICS AND COMPARATIVE GENOME HYBRIDIZATION COMPARATIVE GENOMICS AND PROTEOMICS, COLWELLIA PSYCHRERYTHRAEA 34H COMPARISONS OF MULTIPLE GENOMES, THE VIBRIOS AS AN EXAMPLE METAGENOMICS AND MICROBIAL DIVERSITY IN NATURAL ENVIRONMENTS OTHER TOOLS TO UNDERSTAND GENE FUNCTION SUMMARY REFERENCES xiv

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 1-7, 2005 Copyright © Mineralogical Society of America

The Search for a Molecular-Level Understanding of the Processes that Underpin the Earth's Biogeochemical Cycles Jillian F. Banfield, Gene W. Tyson, Eric E. Allen, Rachel J. Whitaker Department of Earth and Planetary Sciences and Department of Environmental Science, Policy, and Management, University of California Berkeley Berkeley California, 94720-4767, U.S.A. jill @ eps. berkeley. edu

CHARACTERIZING BIOGEOCHEMICAL SYSTEMS Evidence of connections between microbial activity and the Earth's biogeochemical cycles is all around us, and motivates our interest in the mechanisms of microbial transformations, their rates, and the distribution of microbial activities across environment types and over Earth history. In general, the approach to investigating a geomicrobiological process begins with biological and geochemical characterization of the environment of interest. Geochemical characteristics constrain available metabolisms (e.g., McCollom and Shock 1997) and patterns can reveal processes not recognized initially to be microbially mediated. The membership of microbial communities can be assayed through cultivation and cultivation-independent methods. However, this task is not without its challenges. There is little consensus about the ways in which organisms should be grouped into relevant ecological units such as species (Gevers et al. 2005). Even using standard classification techniques, the extent of microbial diversity appears vast, and recent analyses suggest that current estimates may tremendously under predict the amount of genetic diversity in the biosphere. In addition, a single organism type may contain far more genes than expected based on genomic sequencing of an isolate of that species because species populations can exhibit internal heterogeneity. Thus, it seems that comprehensive characterization of the microbial membership of an environment over space and time is a problem of almost incomprehensible magnitude. Furthermore, microbial census taking is only the first step. Beyond documenting the assemblage of organisms present, we need to know how they are distributed, what are they doing, how they are doing it, and the ways that their activities impact the physical and chemical characteristics of their surroundings. In the near future, the only systems in which it will be plausible to tackle the level of characterization required for relatively comprehensive analyses are the simplest ones. For example, in samples of relatively low geochemical and biological complexity, it is now possible to reconstruct the genomes of the dominant organism types using environmental genomic approaches. These data can be used to classify the individual members of a community into groups based on their genome structure and gene content and to infer some aspects of their metabolism (Tyson et al. 2004). In more complex environments, analyses are likely to be restricted to studies of a subset of biogeochemical processes or organism types. In very complex environments, genomic characterization of a community may be restricted to functional profiling (Tringe et al. 2005). Other profiling using methods such as multi-locus sequence analysis (e.g., Whitaker et al. 2003) may be useful to sample specific genes from 1529-6466/05/0059-0001 $05.00

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a much larger number of individuals in a population and to resolve microbial distribution patterns as a function of geochemical conditions and over time. Information about community structure and metabolic potential must be interpreted in the context of fine-scale measurements of temperature, pH, metal and oxygen concentrations, redox potential, etc. A current challenge in uniting geochemical parameters with community structure observations is to document community variation over scales comparable to those over which geochemical gradients occur. The discrepancies in sampling volumes for biological and geochemical characterization may be resolved when new methods such as single cell genomic analysis from environmental samples are combined with micron-scale methods such as microelectrode chemical analyses. Through such approaches it may be possible to decipher the extent to which geochemical gradients structure microbial populations and possibly identify important selective pressures. One of the most severe limitations in our understanding of biogeochemical systems arises from lack of information about the genetic basis for metabolic pathways involved in tasks such as iron oxidation and biomineral formation. Such gaps in our knowledge also restrict derivation of functional inferences from newly acquired genome sequences. A key strategy for deciphering how metabolic tasks are conducted and how these pathways are regulated begins with the development of genetically tractable model organisms (see Newman and Gralnick 2005). Once the sequences of genes involved in processes of interest are known, comparative analyses may provide clues to the evolutionary processes that gave rise to the function (see Raymond 2005). Purified gene products can be assayed to determine substrate specificity, intermediate products, and reaction kinetics, and this information can be incorporated into models for natural systems. Through reconstructions of complex pathways such as those involved in electron transport it is possible to learn how organisms derive energy and shape their surroundings (see DiChristina et al. 2005). For example, the electron transport chain is central to the catalysis of redox reactions involving geochemically abundant chemical species such as nitrate and iron, and can profoundly change the forms of nitrogen and iron in the environment(see Kappler and Straub 2005). Another example involves the microbial production and excretion of specifically tailored iron-binding molecules referred to as siderophores in order address the challenge of iron limitation (see Kraemer et al. 2005). In cases such as this, genetic, genomic, and biochemical approaches can be complemented by high-resolution data for minerals that can now be acquired using spectroscopic methods to reveal the ways in which organic ligands bind to, and interact with, minerals at the molecular level. Spectroscopic methods that provide molecular-scale insights include nano-scale secondary ion mass spectrometry (Guerquin-Kern et al. 2005), micro-scale infrared spectroscopy, nuclear magnetic resonance spectroscopy, and other X-ray-based analytical and imaging methods (see Gilbert et al. 2005). These approaches enable identification of tiny quantities of organic compounds contained in biomineral structures (e.g., Chan et al. 2004) and can reveal surface coordination geometries and reaction mechanisms. Spectroscopic approaches may also provide insights in a wide variety of other systems, including those involving organic molecules and mineral surfaces that may have had special relevance to prebiotic synthesis early in Earth history (see Ferris 2005). Spectroscopic methods also yield isotopic information and can be used to constrain reaction dynamics. The integration of high-resolution, spatially and chemically resolved data from natural inorganic and biological materials is only in a relatively early stage. Such syntheses will certainly generate fundamental new insights into how microorganisms shape their surroundings. Molecularly resolved spectroscopic approaches are also essential tools in efforts to define the structure and constrain mechanisms of reactions involving the mineral products of microbial metabolism. Mineral byproducts of anaerobic respiration (e.g., uranium oxide,

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zinc sulfide) are frequently no more than a few nanometers in diameter (e.g., Moreau et al. 2004). As a consequence of their ultra-small size, these particles may exhibit structures and properties (possibly including redox potential) that depend on the particle diameter (see Gilbert and Banfield 2005). Furthermore, the particle size and size and organization of colloidal aggregates of these particles may depend on the microbial metabolic rate, which itself depends upon solution chemistry (Jin and Bethke 2005). Recent advances in methods for study of nanoparticle structure and properties and for analysis of metabolism make it possible to analyze such connections and predict outcomes in biogeochemical systems.

MOLECULAR GEOMICROBIOLOGY: OPPORTUNITIES AND CHALLENGES One of the goals of molecular geomicrobiology is to understand how microorganisms function in, respond to, and shape their environments. Complete microbial genomes reveal an organism's metabolic potential and provide information about genome structure and gene content (see Nelson and Methe 2005). Thus, they provide an important starting point for biogeochemical analyses. However, it should be noted that the complete genomes derive from cultivated strains, so each analysis represents only a snapshot of the genome of a single representative of a population. More importantly, only a small subset of organisms can be cultivated. Despite many successful predictions of new functional capabilities from genomic data (Ramesh et al. 2005), there are innumerable cases where the function of predicted genes cannot be inferred because the gene bears no significant similarity to one for which a function can be assigned. This is not a small problem (Roberts et al. 2005). Typically 30-50% of genes in sequenced genomes are annotated as either hypothetical (a predicted gene with no similarity to any other gene in the databases) or conserved hypothetical (a predicted gene that bears significant sequence similarity to genes in the database, but for which no function has been determined). Given that no more than a few tens of novel genes are ascribed functions per year as the result of typical biochemical and genetic experiments (M. Thelen, pers. comm.), complete functional analysis based on genomic information is a long way off, even for the best studied microbes (e.g., E. coli). This may be one of the largest roadblocks facing geomicrobiologists. Genomic data from isolates have been used extensively in comparative studies for functional and evolutionary analyses (see Nelson and Methe 2005; Raymond 2005). These studies have provided a wealth of evidence that indicates that lateral gene transfer is an important force in genome evolution. It is apparent that genes are moved between organisms that are distantly related, at least occasionally, and that the frequency of transfer increases with decreasing evolutionary distance (e.g., between different species of the same genera; Gogarten and Townsend 2005). Remaining questions relate to the mode and frequency of genetic exchange within populations of very closely related individuals. Are genes taken up from naked DNA or acquired from phage or other organisms with high frequency, only to be discarded in subsequent generations because they rarely, if ever, confer an adaptive advantage? Or are such events still quite rare but their consequences often profound? Genomic data from coexisting members of natural populations may throw light on this question. Genomic analyses can reveal how metabolic traits distribute across lineages and environment types, the rates and mechanisms by which this movement occurs, and the roles that lateral gene transfer can play in biogeochemical cycling. For example, a recent important discovery is that photosystem II genes are found in phage genomes (Lindell et al. 2005). These genes impact levels of a protein involved in photosynthesis, implying that phage can influence

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or even control one of the key steps in the ocean carbon cycle. Other laterally transferred genes with biogeochemical significance include those that are spread on plasmids to confer the ability to degrade specific hydrocarbon contaminants (Wilson et al. 2003; Springail and Top 2004) or resistance to antibiotics or heavy metals (Coombs and Barkay 2004; Nielsen and Townsend 2004). The mobility of genes between lineages has presented a serious challenge to the species concept because the extent to which members of the same "species" share a common evolutionary history is unclear. It is our view that both the genetic characteristics that unite groups and the processes that subdivide them to yield divergent phenotypes are best evaluated through analysis of population genetic heterogeneity. With such information in hand, we may be better positioned to meaningfully delineate organism groups ("species") with likely ecological relevance. In addition to having the potential to tell us about evolutionary processes that occur over small times scales, environmental genomic data can reveal metabolic traits of organisms that have previously defied cultivation. This information may itself lead to growth of the organism in the laboratory, opening the way for more comprehensive physiological characterization. For example, recently Tyson et al. (2005) designed a cultivation approach based on the recognition that only a single organism type in a community was capable of nitrogen fixation. Population genomic data also reveal differences in metabolic potential that may be responsible for adaptation of otherwise closely related organisms to subtly different environment types. Whitaker and Banfield (2005) describe how methods developed for comparative analysis of (clonal) isolate genomes can be used to identify differences in gene content and sequence amongst closely related individuals and the ways in which population genetic methods may be adapted from macroscopic biology to reveal patterns of selection genome wide. With genomic information for the dominant organisms in a community in hand (whether obtained from isolates or natural populations) it is possible to monitor in situ microbial activity levels in multi-species consortia. For example, gene sequence information can be used to design microarrays to detect mRNA transcripts (see Nelson and Methe 2005) or to identify peptides via mass-based measurements (e.g., mass spectrometry). Functional analyses may reveal the relative contributions of specific organisms or strains to geochemical transformations such as carbon fixation, nitrogen fixation, and metal reduction at a given time, and to deduce how this changes over time. An important limitation for use of genomic data in functional analyses arises if these data do not accurately or fully capture the genetic potential of the community. For example, Ram et al. (2005) used genomic data from one sample to identify proteins in a closely related (but not identical) biofilm sample. Although over 2,000 proteins derived from all of the dominant organism types were detected, it is certain that an important subset were under-detected or missed because the predicted peptides differed from the observed peptides in their amino acid sequence. Thus, full analyses of function in microbial consortia will benefit from comprehensive genomic datasets that capture the full range of sequence types present in a community. Even if complete genomic data are available for one environment type, it is unclear whether they will enable functional analyses in a similar environment due to site-to-site genetic variability. With the exception of studies of organisms that cause plant and animal disease (Bhattacharyya et al. 2002; Holden et al. 2004), population-level differences in the same environment type in geographically separated locations have been little investigated (Whitaker et al. 2003; Escobar-Paramo et al. 2005). Consequently, it is difficult to predict whether the challenges associated with functional analyses of natural communities will be best addressed via better genomic databases, mass spectrometry method development, or both.

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Environmental genomic studies have the potential to constrain the rates of inter-site microbial dispersal and to reveal the relative importance of dispersal vs. in situ diversification in adaptation as environmental conditions change. Clearly, the relative importance of dispersal vs. in situ evolution will vary with environment type, organism type, and the rate and magnitude of the perturbation. However, this balance will impact the level of global-scale biodiversity for each species. Understanding the timescales of microbial evolutionary processes is a tremendous challenge that is perhaps be addressed via studies of geologic systems. In the past, this has been undertaken through direct examination of the fossil record, including analysis of organic biomolecules preserved in ancient rocks. The opportunities and obstacles associated with attempts to tie together biological and geochemical evolution over Earth history are discussed by Brocks and Pearson (2005). Future studies may focus on modern systems for which both a recent geological and biological history can be reconstructed.

CONCLUDING COMMENTS The knowledge sought through molecular geomicrobiological studies will find application in a variety of basic and applied fields such as astrobiology and environmental bioremediation. For example, understanding of the range of conditions in which life can persist, and the biochemical bases for the limitations, will constrain the variety of habitat types that may be targeted in the search for life signs on extraterrestrial planets. Molecular-level understanding of biogeochemical processes may be central to an assessment of the biogenicity of mineral biosignatures found there. Furthermore, information about the metabolic pathways for synthesis of organic compounds will assist in evaluation of the sources of organic biosignatures that persist in the geologic record. There has been great deal of interest in the possibility that the enormous problem of contamination of the environment by organic compounds, metals, and radionuclides may be tackled by harnessing the ability of microorganisms to change the chemical speciation of pollutants. Much research has been devoted to exploring this possibility (Madsen 2001; Lovley 2003; Nevin et al. 2003). In addition, understanding of the biogeochemical reactions that occur during stimulated bioremediation can be used to design methods to follow the progress of the treatment and identify key reaction products. For example, recently developed geophysical approaches can sense changes in subsurface transport properties, allowing progress of bioremediation to be evaluated and post treatment changes monitored (Williams et al. 2005). The merging of fields as disparate as molecular microbiology and geophysics is becoming routine, but the results are as yet mostly unknown. We can look forward with optimism to the product of the next decade of research in molecular geomicrobiology.

ACKNOWLEDGMENTS Funding for research and development of ideas described here derived from the National Science Foundation Biocomplexity Program, the Department of Energy Genomics: Genomes to Life Program and Basic Energy Sciences Chemical Sciences Program, and the NASA Astrobiology Institute. The contributions of our colleagues and collaborators to this work are gratefully acknowledged.

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REFERENCES Bhattacharyya A, Stilwagen S, Ivanova N, D'Souza M, Bernal A, Lykidis A, Kapatral V, Anderson I, Larsen N, Los T, et al. (2002) Whole-genome comparative analysis of three phytopathogenic Xylella fastidiosa strains. Proc Natl Acad Sci USA 99:12403-12408 Brocks JJ, Pearson A (2005) Building the biomarker tree of life. Rev Mineral Geochem 59:233-258 Chan CS, De Stasio G, Nesterova M, Welch SA, Girasole M, Frazer B, Banfield JF (2004) The role of microbial polymers in templated mineral growth. Science 303:1656-2658 Coombs JM, Barkay T (2004) Molecular evidence for the evolution of metal homeostasis genes by the lateral gene transfer in bacteria from the deep terrestrial subsurface. Appl Environ Microbiol 70:1698-1707 DiChristina TJ, Fredrickson JK, Zachara JM (2005) Enzymology of electron transport: energy generation with geochemical consequences. Rev Mineral Geochem 59:27-52 Escobar-Paramo P, Ghosh S, DiRuggiero J (2005) Evidence for genetic drift in the diversification of a geographically isolated population of the hyperthermophilic archaeon Pyrococcus. Molec Bio Evol 22: 2297-2303 Ferris JP (2005) Catalysis and prebiotic synthesis. Rev Mineral Geochem 59:187-210 Gevers D, Cohan FM, Lawrence JG, Spratt BG, Coenye T, Feil J, Stackenbrandt E, Van de Peer Y, Vandamme P, Thompson FL, Swings J (2005) Opinion: Re-evaluating prokaryotic species. Nat Rev Microbiol 3: 733-739 Gilbert B, Banfield JF (2005) Molecular-scale processes involving nanoparticulate minerals in biogeochemical systems. Rev Mineral Geochem 59:109-155 Gilbert PUPA, Abrecht M, Frazer BH (2005) The organic-mineral interface in biominerals. Rev Mineral Geochem 59:157-185 Gogarten JP, Townsend JP (2005) Horizontal gene transfer, genome innovation and evolution. Nat Rev Microbiol 3:679-687 Guerquin-Kern JL, Wu TD, Quintana C, Croisy A (2005) Progress in analytical imaging of the cell by dynamic secondary ion mass spectroscopy (SIMS microscopy). Biochim Biophys Acta 1724: 228-238 Holden MT, Titball RW, Peacock SJ, Cerdeno-Tarraga AM, Atkins T, Crossman LC, Pitt T, Churcher C, Mungall K, Bentley SD, et al. (2004) Genomic plasticity of the causative agent of melioidosis, Burkholderia pseudomallei. Proc Natl Acad Sci U S A 101:14240-14245 Jin Q, Bethke CM (2005) Predicting the rate of microbial respiration in geochemical environments. Geochim Cosmochim Acta 69:1133-1143 Kappler A, Straub KL (2005) Geomicrobiological cycling of iron. Rev Mineral Geochem 59:85-108 Kraemer SM, Butler A, Borer P. Cervini-Silva J (2005) Siderophores and the dissolution of iron-bearing minerals in marine systems. Rev Mineral Geochem 59:53-84 Lindell D, Jaffe JD, Johnson ZI, Church GM, Chisholm SW (2005) Photosynthesis genes in marine viruses yield proteins during host infection. Nature, doi:10.1038/nature04111 Lovley DR (2003) Cleaning up with genomics: applying molecular biology to bioremediation. Nat Rev Microbiol 1:35-44 Madsen EL (2001) Intrinsic bioremediation of organic subsurface contaminants. In: Subsurface Microbiology and Biogeochemistry. Fredrickson JK, Fletcher M (eds) Wiley-Liss Inc., New York, p. 249-278 McCollom TM, Shock E L (1997) Geochemical constrains on chemolithautotrophic metabolism by microorganisms in seafloor hydrothermal systems. Geochim Cosmochim Acta 61:4375-4391 Moreau JW, Webb RI, Banfield JF (2004) Ultrastructure, aggregation-state, and crystal growth of biogenic nanocrystalline sphalerite and wurtzite. Am Mineral 89:950-960 Nelson KE, Methe B (2005) Metabolism and genomics: adventures derived from complete genome sequencing. Rev Mineral Geochem 59:279-294 Nevin KP, Finneran KT, Lovley DR (2003) Microorganisms associated with uranium bioremediation in a highsalinity subsurface sediment. Appl Environ Microbiol 69:3672-3675 Newman DK, Gralnick JA (2005) What genetics offers geobiology. Rev Mineral Geochem 59:9-26 Nielsen KM, Townsend JP (2004) Monitoring and modeling horizontal gene transfer. Nat Rev Biotechnol 22: 1110-1114 Ram RJ, Verberkmoes NC, Thelen MP, Tyson GW, Baker BJ, Blake RC II, Shah M, Hettich RL, Banfield JF (2005) Community proteomics of a natural microbial biofilm. Science 308:1915-1920 Ramesh M A et al. (2005) A phylogenomic inventory of meiotic genes: evidence for sex in Giardia and an early eukaryotic origin of meiosis. Current Biology 15:185-191 Raymond J (2005) The evolution of biological carbon and nitrogen cycling—a genomic perspective. Rev Mineral Geochem 59:211-231 Roberts RJ, Karp P. Kasif S, Linn S, Buckley M R (2005) A» Experimental Approach to Genome Annotation. Critical Issues Colloquia Report, Washington D.C. USA: American Academy of Microbiology Springail D, Top EM (2004) Horizontal gene transfer and microbial adaptation to xenobiotics: new types of mobile genetic elements and lessons from ecological studies. Trends Microbiol 12:53-58

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Tringe SG, von Mering C, Kobayashi A, Salamov AA, Chen K, Chang HW, Podar M, Short JM, MathurEJ, Detter JC, Bork P, Hugenholtz P, Rubin EM (2005) Comparative metagenomics of microbial communities. Science 308:554-557 Tyson GW, Chapman J, Hugenholtz P, Allen EE, Ram RJ, Richardson PM, Solovyev VV, Rokhsar DS, Banfield JF (2004) Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428: 37-43 Tyson GW, Lo I, Baker BJ, Allen EE, Hugenholtz P, Banfield JF (2005) Genome-directed isolation of the key nitrogen fixer Leptospirillum ferrodiazotrophum sp. nov. from an acidophilic microbial community. Appl Environ Microbiol 71:6319-6324 Whitaker RJ, Grogan DW, Taylor JW (2003) Geographic barriers isolate endemic populations of hyperthermophilic archaea. Science 301:976-978 Whitaker RJ, Banfield JF (2005) Population dynamics through the lens of extreme environments. Rev Mineral Geochem 59:259-277 Williams KH, Ntarlagiannis D, Slater LD, Dohnalkova A, Hubbard SS, Banfield JF (2005) Geophysical imaging of stimulated microbial biomineralization. Environ Sci Technol 39:7592-7600 Wilson MS, Herrick JB, Jeon CO, Hinman DE, Madsen E L (2003) Horizontal transfer of phn-Ac dioxygenase genes within one of two phenotypically and genotypically distinctive naphthalene-degrading guilds from adjacent soil environments. Appl Environ Microbiol 69:2172-2181

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 9-26, 2005 Copyright © Mineralogical Society of America

What Genetics Offers Geobiology Dianne K. Newman Division of Geological and Planetary Sciences California Institute of Technology and the Howard Hughes Medical Pasadena, California, 91125, U.S.A.

Institute

dkn @gps. caltech. edu

Jeffrey A. Gralnick Department of Microbiology and The BioTechnology University of Minnesota St. Paul, Minnesota, 55108, U.S.A.

Institute

gralnick@ umn. edu

INTRODUCTION For over 50 years, the Parker Brothers' board game "Clue" has maintained its position as the classic family detective game. A murder has been committed in the mansion, but we don't know where, by whom, or how. Was it Professor Plum in the study with a knife, or Miss Scarlett in the ballroom with a candlestick? Through rolls of the dice, fragments of information patiently accumulated piece-by-piece, and the application of logic, players construct a case to figure out "whodunit". Because there are several potential solutions to the problem, the key challenge is to figure out what happened by understanding how it happened. As for the players of "Clue," scientists seeking to understand the co-evolution of life and Earth are often confronted with the dilemma of having to parse multiple solutions to an ancient biogeochemical event. For example, in trying to explain the genesis of Archean Banded Iron Formations, we must ask whether it was cyanobacteria in the near shore-environment producing 0 2 , or anoxygenic phototrophs in the oceans directly oxidizing iron (Kappler et al. 2005)? Again, in parallel to "Clue," typically all we have to work with are isolated scraps of evidence—metamorphosed pieces of rock collected from remote locales on Earth, that contain morphological and/or chemical fossils whose origin and/or meaning is enigmatic. Nevertheless, the legacies of billions of years of evolution—genetic rolls of the dice, subject to natural selection—provide us with a means to interpret these putative biosignatures. By applying the principle of uniformitarianism, we assume that the study of modern organisms can provide us with insights into the composition and behavior of their ancient relatives, thereby allowing us to reconstruct ancient events. This, of course, is a necessary assumption that may not be true, so in the end, all we can really claim is to construct satisfying stories that fit the available data. So how does one go about solving the mysteries of geobiology? Multiple approaches are covered in this book, but our focus in this chapter will be on how the logic of bacterial genetics can be applied to geobiological problems. Because genetics is not often a discipline that geologists are familiar with, we begin our discussion with some definitions. From there, we go on to discuss how genetics can help us understand the past, both generally and through specific examples; we do not discuss how genetics can help us understand modern biogeochemical processes, because we have recently reviewed this elsewhere (Croal et al. 2004a). Finally, 1529-6466/05/0059-0002$05.00

DOI: 10.2138/rmg.2005.59.2

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we close with practical information about how to develop genetic systems in newly-isolated strains of geobiological interest, to guide those seeking to incorporate genetic analysis into their own research.

DEFINITIONS What is genetics? Classical bacterial and phage genetics was pioneered in the 1940s and 50s by Max Delbrück, Salvador Luria, Oswald Avery, Maclyn McCarty, Alfred Hershey, Martha Chase, Joshua Lederberg, Sydney Brenner, Seymour Benzer, Arthur Pardee, François Jacob, and Jacques Monod to name only a few of the key players. The extraordinary history of the development of this discipline (and molecular biology more generally) has been told well by Horace Judson in the book The Eighth Day of Creation (Judson 1996). Thanks to these scientists, genetics became a powerful tool for understanding how basic biological phenomenon worked (e.g., the nature of the gene (Avery et al. 1944), recombination (Lederberg 1946), the regulation of gene expression (Pardee et al. 1959), the nature of the genetic code (Crick et al. 1961), and mutations (Benzer and Champe 1962)). In each of these cases, genetic analysis lead to insights into how things happened, and was predicated upon the construction and analysis of mutants (Beckwith and Silhavy 1992). Accordingly, when we talk about applying genetics to geobiology, we mean performing experiments to understand geomicrobiological processes in mechanistic detail, either by mutagenizing model organisms (e.g., strains that can catalyze a particular geochemical transformation of interest, such as manganese oxidation (van Waasbergen et al. 1996), iron reduction (Coppi et al. 2001 ; DiChristina et al. 2002; Myers and Myers 2002), arsenate reduction (Saltikov and Newman 2003), methanogenesis (Pritchett and Metcalf 2005)) or by cloning DNA from the environment and expressing it in a foreign host (this is sometimes called "metagenomics" (Beja et al. 2000; Riesenfeld et al. 2004)). For the remainder of this chapter, we will focus our discussion on bacterial genetics to illustrate the more general theory and practice of genetics, whose logic is the same, regardless of the organism in which it is applied. In the context of geobiology, however, it is important to also recognize the recent contributions several labs have made in advancing archaeal genetics (Metcalf et al. 1997; Peck et al. 2000); because archaea catalyze a variety of geochemically significant reactions, that representatives from this group now can be manipulated genetically bodes well for future studies aimed at understanding their impact on the environment. How is genetics different from molecular biology and genomics? Although modern bacterial genetics is molecular (e.g., gene composition can be readily determined by automated sequence analysis), originally it was not. The key to classical bacterial genetics was the use of deductive reasoning to understand the order and behavior of genetic elements in a genome, accomplished often through elegant assays that required little more than "toothpicks and logic" (Shuman 2003). While sequence information greatly facilitates genetic analysis today, the cornerstone of modern bacterial genetics is essentially the same as it was a half century ago: genetics deconstructs how a system works by making mutants that either eliminate/attenuate the ability of a strain to perform a certain function, or that confer a new property upon it. The challenge and satisfaction of this approach lies in being able to design simple experiments whose results will provide an explanation for a process. With a collection of different mutants, for example, complex biosynthetic processes can be broken down into components, each of which can be reconstructed and understood in detail. Genetic analysis goes hand in hand with physiological, cell biological and/or biochemical approaches that enable the phenotypes (i.e., physical characteristics or behavior) of mutants to be explored in depth.

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In contrast, molecular biology is the science of understanding the chemical composition of important biomolecules such as DNA and protein, and being able to manipulate them. Molecular biology commonly finds application in geobiology through microbial ecology surveys where the 16S gene for ribosomal RNA is cloned and sequenced to determine what types of organisms are present in a given environment (Pace 1997); another application is the use of molecular probes to identify organisms in natural samples through fluorescent in situ hybridization (FISH) (Schrenk et al. 1998; Orphan et al. 2001; Michaelis et al. 2002). In effect, molecular biology permits geobiologists to apply genetics to the environment—to search for the presence and/or expression of particular genes once their function is known (KarkhoffSchweizer et al. 1995; Malasarn et al. 2004). Finally, genomics is the study of genomes with respect to their gene content and organization (also see in this volume Nelson and Methe 2005 and Whitaker and Banfield 2005). It relies heavily upon computational analyses to compare different sequences (from one or more organisms) to each other and to identify motifs in the genes or their translated protein products that are predicted to have a specific function. For example, hypotheses can be generated about what types of reactions a given protein might catalyze, or the conditions under which the gene that encodes it might be expressed; sometimes, genomic analysis can even be used to make predictions about the behavior of entire microbial communities (Tyson et al. 2004). The special advantage of environmental genomic data is that it allows gene expression in communities to be monitored in situ (Ram et al. 2005). It should be emphasized, however, that although much can be learned from genomics, ultimately, predictions about an organism's (or a community's) potential to perform a certain function must be tested through classical genetic and/or biochemical analyses to prove that the connection between the presence of a particular gene and a given geochemical state is actually causal as opposed to correlative.

What is a mutant? A mutant is a bacterial strain that differs genetically in some way from the parent strain of the species. While the genotype (e.g., DNA) of the mutant must, by definition, be different from the parent, this is not necessarily the case phenotypically. A single base pair change in the genome could have no effect on the phenotype of the strain, however, genotypically, this strain is now different from the parent and is therefore a mutant.

What is mutagenesis? The capacity to alter the activities of single, or many proteins, from an organism by eliminating the gene(s) that encode them is critical for identifying proteins involved in a process of interest. Mutagenesis is the process of altering the genotype of a strain to make it different from the parent strain (i.e., a mutant). Traditional biochemical methods of identifying an activity in a cell extract can be a complementary method to genetics, but cannot unambiguously identify proteins required for an activity in vivo. If a protein is required for the activity of interest catalyzed by an organism, then removing the capacity of the strain to produce the protein will eliminate the activity. Several methods are used today to mutagenize bacteria, each with different strengths and weaknesses. These will be discussed in detail below.

TYPES OF GEOBIOLOGICAL PROBLEMS THAT GENETICS CAN SOLVE How can genetics help us learn about the geobiology of the past? To answer this question, we must first define what "geobiology of the past" means. Although a wide array of subjects— ranging from dinosaurs to ediacara—could fit this description, we will limit our discussion to microorganisms and how their evolution affected Earth's near surface environment (i.e.,

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subsurface down to a few kilometers). This choice is justified if one seeks to understand what life was like on this planet for the majority of its history because microorganisms have been in existence much longer than macroscopic organisms. Microorganisms (especially bacteria and archaea) are distinguished by their metabolic diversity rather than their morphological diversity, thus studying the geobiology of the past essentially is an exercise in understanding the evolution of metabolism as recorded in ancient rocks. Because our knowledge of the metabolic diversity of microbial eukaryotes is very limited, we will not consider them here, although we note that this is an area of opportunity for future students of geobiology. Modern microorganisms appear to be capable of generating metabolic energy from any redox reaction that is thermodynamically favorable so long as the constituents involved in the reaction are available in a habitable environment. Their metabolic diversity is based upon their ability to harvest energy from oxidation and reduction reactions, where the oxidant and/or the reductant may be organic or inorganic compounds. In some cases, the substrates and/or products of microbial metabolism are minerals, whereas in others, they are gases. Regardless of what form they come in, microbial substrate consumption or product formation can have a dramatic affect on the geochemistry of the environment. A classic example of this is the evolution of photosystem II, which enabled cells to produce molecular oxygen from water and thereby oxidize the Earth. Prior to this event, however, microbial life had to subsist anaerobically for millions and perhaps billions of years. How did cells cope? What electron acceptors and electron donors did microorganisms use for energy generation? And can we decipher a record of these primitive metabolisms in ancient rocks? These are hard questions, and at first blush, it is not obvious whether genetics can provide the answers. Genetics is an experimental discipline, requiring geobiologists to work with modern microorganisms that we assume behave in much the same way as their ancient relatives. How reasonable is this assumption? One argument in its favor is that the forces of natural selection are conservative: once a particular metabolism is "invented" and is successful, only a limited set of mutations in the genes that confer this metabolism are possible in order for it to be preserved. While evolutionary history records myriad instances in which genetic changes led to the development of novel proteins and hence novel metabolisms, if we focus on a particular metabolism, and the biochemistry of its catalytic core, it is reasonable to infer that biology has only a finite number of solutions to make it work (Kauffman 1993). Moreover, as the complexity or difficulty of a metabolic process increases, we might expect the repertoire of solutions to become even more limited. This conclusion appears to be robust, albeit facilitated through horizontal gene transfer, given the conservation of metabolic genes in the genomes of phylogenetically distant organisms (Doolittle 1999; Friedrich 2002; Nixon et al. 2002; Malasarn et al. 2004; Simonson et al. 2005). Interestingly, microbiologists of the Delft school anticipated these findings nearly a century ago, noting the "manifest unity" in the biochemistry that forms the basis for the ecological relationships of microorganisms in nature (Kluyver 1924). If biochemistry is essentially conservative with respect to metabolism, then using genetics to understand how modern metabolisms work can help us develop a basis for deciphering their origins and how organisms that utilized them may have altered the chemical and physical features of our planet. So what does this mean in practice? If understanding the evolution of metabolism is the goal, there are only two ancient records to work with: one that is recorded in rocks, and one that is recorded in genomes. Let us first consider the former. Rocks preserve two different types of fossils: morphological and chemical. Morphological fossils are the more familiar, as features that stand out from the parent rock are relatively straightforward to identify, and are becoming ever more so given recent innovations in imaging technologies (Watters and Grotzinger 2001; Corsetti and Storrie-Lombardi 2003; Kemner et al. 2004). Once identified, however, whether these features are truly biogenic can be the subject of intense debate, be it at the scale of

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nanoparticles such as magnetite (McKay et al. 1996), micron-sized putative cellular structures (Schopf 1993; Brasier et al. 2002), or centimeter-scale stromatolites (Grotzinger and Knoll 1999). To develop criteria whereby to evaluate the biogenicity of particular structures in ancient rocks, it is helpful to understand how these structures form. This is where genetics can help. For example, if certain conditions prove to be required for the biological formation of a particular structure in modern organisms, and traces of these conditions are absent in an ancient sample, this would argue against its biogenicity. Such an argument was recently made with respect to the magnetite in the Martian meteorite ALH84001, which did not contain a magnetic signature that supported a biogenic origin (i.e., alignment of magnetite in chains) (Weiss et al. 2004). The key assumption in Weiss et al.'s paper was that bacteria organize magnetite into chains by direct molecular control—an assumption that was based on phenomenological observations (Gorby et al. 1988). Recently, genetic analysis has begun to reveal the specific molecular components responsible for this organization (Komeili et al. 2005). The power of bacterial genetics lies is its ability to provide clear and definitive proof that a particular protein is involved in a given function. The case of magnetite is only one example of where genetic analysis can guide our interpretation of the biogenicity of ancient samples. As stated above, in addition to morphological fossils, rocks preserve chemical fossils. These, in turn, come in two varieties: organic and inorganic. It is fair to assume that all organic fossils are of biological origin (the likelihood that prebiotic organic synthesis left preservable traces is extremely small), but it is much harder to know what they mean when we find them, as discussed in the chapter by Brocks and Pearson (2005). Here too, genetics can help. For example, hydrocarbon molecules known as 2-methylhopanes in the sedimentary record can unambiguously be recognized as the molecular fossils of 2-methyl bacteriohopanepolyols (2MeBHPs) that are found in selected modern bacteria. Because cyanobacteria—the only bacteria that engage in oxygenic photosynthesis—are the only known, quantitatively important, source of 2-MeBHPs in the modern environment, it has been inferred that 2-methylhopanes can be used as biomarkers for oxygenic photosynthesis itself (Summons et al. 1999). Thus, Brocks et al. (1999, 2003) interpreted the presence of 2-methylhopanes in sediments of the Archaean Fortescue Group as evidence that photosynthetically-derived 0 2 first appeared on Earth at least 2.7 billion years ago. However, there is presently no evidence that 2-MeBHPs and oxygenic photosynthesis are functionally related. Our confidence in this critical assumption, as well as in the use of 2-methylhopanes as biomarkers for cyanobacteria (or any other organism in which they exist), would be significantly improved by an understanding of the biochemical function of 2-MeBHPs. Keeping to the theme of 0 2 evolution, the second class of chemical fossils—inorganic biosignatures—also can be used to shed light on when this critical event occurred. Recently, through the work of Farquhar et al. (2000), mass independent sulfur isotopic signatures from sulfide and sulfate in Precambrian rocks were used to date a major change in the change in the sulfur cycle between 2090 and 2450 million years ago, likely attributable to the rise of 0 2 . Canfield and colleagues have provided additional support for this conclusion, through their work on sulfur isotopic fractionation by archaea and bacteria (Canfield et al. 2000; Shen et al. 2001; Habicht et al. 2002). Central to these studies is the knowledge that sulfur isotope fractionation responds to metabolism—for example, uptake and reduction of sulfate involves kinetic isotope effects that result in the lighter isotope of sulfur being enriched in the sulfide product. The extent of enrichment depends on the growth rate of the organism, which can be controlled by temperature, the nature of the electron donor, and the concentration of sulfate among other factors (Jones and Starkey 1962; Kemp and Thode 1968; Shen et al. 2001)). While great strides have been made in this area without the involvement of genetics, knowledge of the biochemical pathway responsible for sulfate reduction has greatly facilitated interpretations of microbial sulfur isotopic fractionation by bacteria. It is thought that the majority of isotopic

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fractionation occurs when S-O bonds are broken, such as during reduction of adenosine 5'phosphatosulfate (APS) to sulfite by the enzyme APS reductase, with subsequent enzymatic reduction of sulfite to sulfide (Canfield et al. 2005). Genetics affords a means to identify such pathways for more recently discovered geomicrobial organisms that might leave an imprint in the rock record, where the mechanism(s) of isotope effects are not yet fully understood. For example, iron-oxidizing anoxygenic phototrophs have been implicated in the direct deposition of Banded Iron Formations, but at present is it difficult to distinguish their activities from those of cyanobacteria on the basis of iron isotopic fractionation alone (Croal et al. 2004b). Knowledge of what enzymes or molecular components catalyze iron oxidation, where they are localized, and other details of how anoxygenic phototrophs traffic in iron, will position us to better interpret the mechanism of iron isotope fractionation by these bacteria, and thereby develop criteria with which to identify the products of their metabolism in ancient rocks. Even if iron isotopes prove not to provide a unique signature for a particular microbial metabolism, genetic analysis can still be very useful in pointing to potentially novel biosignatures. For example, recent genetic and biochemical results from our laboratory indicate that the enzymes that catalyze iron oxidation are soluble proteins that are localized inside the cell (Croal et al. unpub. data). If true, this implies that the cell has a mechanism for preventing the intracellular precipitation of iron oxide, possibly by chelating ferric iron with an organic molecule that helps release it to the outside where it then precipitates. In the event such a molecule were to exist, and it were shown to be preservable over geologic time scales, this would be an example of a metabolically-specific biomarker discovered through genetics. Whether or not genetic analysis will ultimately lead to the discovery of physiologicallyspecific biomarkers, identification of the genes involved in geobiological processes will provide insight into their evolutionary origin. In this respect, DNA itself is a fossil, as phylogenetic relationships between sequences can provide information about their evolution. A good example of this is the interpretation of the antiquity of anoxygenic photosynthesis based on phylogenies of proteins involved in bacteriochlorophyll biosynthesis (Xiong et al. 2000). Although it is very difficult to date the divergence of groups of proteins, it is reasonable to use phylogeny in tandem with the rock record to infer the relative temporal evolution of different metabolisms (House et al. 2003; Kirschvink et al. 2000). Again, the role genetics plays in this process is to provide the proof that specific genes encode proteins that perform specific functions. Only after this is understood can phylogenetic comparisons be meaningful. As stated above, we caution against the danger of inferring function on the basis of phylogeny alone. Evolution is rife with instances where small sequence changes in an active site of a protein change its substrate specificity (such as in the case of the directed evolution of a fucosidase from a galactosidase; Zhang et al. 1997), thus we cannot be certain that a putative protein actually performs the function we think it does until we do an experiment to prove it. Moreover, there are cases where different proteins have independently evolved that catalyze a similar reaction, yet on the basis of their sequence, they appear to have little in common. A good example of this are the serine proteases, subtilisin and trypsin (Kelly et al. 2005). Thus the absence of a particular gene in the genome of an organism should not be taken as evidence that it cannot perform a certain function. Even for organisms such as Escherichia coli and Salmonella, upon whose DNA the science of bacterial genetics was built, there remain a large number of genes of unknown function. Finally, genetic analysis can provide insights into the conditions that regulate a particular process. As described below, it is straightforward to use molecular reporters to assay for the expression of a gene of interest by exposing the bacteria that harbor the gene to different chemicals, temperatures, or pressures. This has the potential to be useful in making inferences about the paleoenvironment. For example, if evidence were found in the rock record that a particular biomolecule was present that was known only to be produced under conditions

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when oxidized molybdenum [Mo(VI)] was available, this would suggest that the pH of that environment must have been greater than five and the redox potential greater than zero because these are the conditions where Mo(VI) exists in significant quantities (Anbar 2004).

PRACTICAL CONSIDERATIONS FOR CREATING GENETIC SYSTEMS As explained in the previous section, genetics has the potential to be a powerful tool for geobiology, offering insights into: i.) what structures to look for in the rock record, ii.) what they mean when we find them, iii.) what enzymes catalyze their production, and iv.) what conditions regulate their expression. To be able to convert this theory into practice, it is helpful to know where to begin in the laboratory. In this section, we outline the key steps that would need to taken to make an organism genetically tractable. To briefly summarize, the first step is to isolate an organism that will be amenable to genetic analysis; this strain will serve as the standard (or "wild-type") to which all subsequent mutants will be compared. This of course imposes a limitation on what genetics can offer geobiology, as not all strains can easily be coaxed into growing in the laboratory, much less be straightforward to mutagenize once isolated. Nevertheless, with perseverance and creativity, these difficulties can usually be overcome, leading to the second step: mutagenesis of the strain. Various methods for mutagenesis exist, offering the potential to eliminate/delete genes entirely, introduce pointmutations into specific genes, or introduce genes into an organism. The effects of these different types of mutations can be far ranging, from altering the amino acid composition of a protein and thereby affecting its substrate specificity, to eliminating the ability to make a set of proteins, to changing the regulation of an entire network of genes. After mutagenesis is performed, the third step is to identify the mutants either through a selection or a screen. A selection permits only those mutants that have the desired properties to grow, whereas a screen requires characterizing the behavior of thousands of mutants to identify only rare ones that have the properties/behavior of interest. Depending on the manner in which one has identified candidate mutants, secondary screens may be required to narrow the pool of candidates down to only those that are interesting. For example, if one performs a screen to find genes that control various steps in a biochemical reaction, if the assay for mutant identification involves looking at the rate at which a reaction proceeds, "false" mutants could be identified by the screen that are simply slow to grow but which do not have a specific defect in the reaction of interest. These mutants could be sorted out by measuring the growth rate of all candidates and only continuing to study those whose growth is normal with respect to the parent strain. Once interesting mutants are identified, the fourth step is to determine the nature of the mutation through sequencing and genetic verification. Sequence analysis can help generate hypotheses to explain why the mutant behaves the way it does, and thus infer what affects the process of interest. To test these hypotheses, however, the final step requires physiological, biochemical, or cell biological experiments to be performed in order to study the phenotype of the mutant in detail.

Step 1: Isolation and growth Developing a genetic system in an organism can be a tedious, albeit rewarding process. Development can be greatly enhanced when the organism of interest is a close relative to a microbe with an established genetic system. This was the case for the arsenic-respiring Gramnegative bacterium Shewanella sp. strain ANA-3, which resulted from a targeted-isolation of a strain that could grow strictly anaerobically on arsenate in minimal medium and also make single colonies overnight on Luria-Broth (LB) plates on the bench top. LB is a widely used rich medium in bacterial genetics, as it supports rapid growth and is easy to make. Because this enrichment strategy imposed a strong selection for bacteria that had respiratory versatility, it was not surprising that it resulted in the isolation of a new strain of Shewanella, a genus

16

Newman

&

Gralnick

renowned for this property (Nealson and Scott 2004). Since this organism is closely related to other strains of Shewanella that have established genetic systems, Saltikov et al. adapted strategies that had been successfully used in S. oneidensis strain MR-1 to their new isolate (Saltikov et al. 2003; Saltikov and Newman 2003). Several years prior to this, one of the authors had isolated a bacterial strain (Desulfotoniaculuni sp. strain OREX-4) that could also respire arsenate (Newman et al. 1998; Newman et al. 1997). However, because attempts to grow this strain on plates failed, a genetic system could never be established. Two main lessons regarding the development of a genetic system are illustrated by this example: 1.) Enrich for an organism in a targeted fashion so that a strain can be isolated that exhibits the desired properties and 2.) The ability to readily form colonies on plates is a highly desirable trait, for reasons that will be discussed below. One major benefit of growth on agar plates is facilitating strain isolation. Bacterial colonies on an agar plate typically form from a single cell, meaning that every cell that comprises the colony is identical at the genetic level, or of the same genotype. If a single colony is picked from a solid-surface medium, streaked across a new plate with the purpose of dispersing cells so that individual cells are isolated from their neighbors, and allowed to incubate, all subsequent colonies arising should be both morphologically and genetically identical to the original colony (Fig. 1). This process is typically called 'colony purification' and can yield pure cultures of the bacterial strain of interest. Using solid surfaces to culture bacteria is, for all practical purposes, essential for the isolation of mutant strains after they are generated. Solid or liquid medium then can be used to perform basic physiological studies, such as determining optimal growth temperature, nutritional requirements and sensitivity to antibiotics or some other selectable marker. Characterizing the susceptibility of a strain to a selectable marker, such as a heavy metal (e.g., tellurium) or an antibiotic (e.g., kanamycin) is important for many genetic techniques. These techniques require the ability to isolate individuals within a population that carry a genetic difference from the overall population. Often, transposons (or "jumping genes") that carry resistance determinants for a particular toxic compound are used to make mutants by disrupting

Figure 1. Streak plate. Example of a strain of S. oneidensis streaked for single colonies on solid medium.

What Genetics Offers Geobiology

17

the chromosome at random, but mutants in specific loci can also be generated by replacing the wild-type gene with a resistance determinant. Regardless of the method of mutagenesis, when these resistance determinants are inserted into the chromosome, they confer upon the resulting mutant strain resistance to the toxic compound. With the appropriate solid medium containing this compound, these mutants can be spatially separated and selected from a population that also contains the wild-type (the wild-type, lacking the resistance determinant, will die, so only the mutants will grow). When possible, it is helpful to make low endogenous resistance to several antibiotics a requirement in the isolation of an organism for genetic analysis. If the isolate is naturally resistant to many of the typical antibiotics (e.g., ampicilin, gentamycin, kanamycin, chloramphenicol and tetracycline), however, other strategies can be devised to make mutants— such as employing resistance to heavy metals (Gupta et al. 2002). Two additional properties are also beneficial to establishing genetics in an organism. First is the ability to introduce foreign DNA into the strain, which can be accomplished through transformation, transduction, or conjugation (Madigan et al. 2003). Transformation is when the cell takes up DNA directly—this can be facilitated by electroporation (using electric current to transform DNA into bacteria) or by generating chemically-competent cells (using high concentrations of salt, typically calcium chloride, and inducing the transformation via heat-shock). Transduction is the process whereby phage (i.e., viruses) infect bacterial cells and inject DNA into them which is then incorporated into the chromosome. Finally, conjugation if the process of transferring DNA from one bacterium to another by means of matings that involve the transfer of mobilizable plasmids. Introduction of foreign DNA is important for many targeted and random methods of mutagenesis, and critical for verifying the causality of the phenotype. The second beneficial property is speed of growth. When choosing a new strain for genetic work, the faster the organism grows, the faster its secrets will be unraveled (assuming the creativity of the scientist is not the limiting factor)! Step 2: Methods of mutagenesis There are three types of mutagenesis that are common in bacterial genetics: chemical, transposon, and targeted. Chemical and transposon mutagenesis typically generate random mutations that are useful when one has no preconceptions about how a system works and seeks to cast a wide net to identify all possible genes involved in a process. In contrast, targeted gene "knockouts" are made when one has an idea of what gene(s) might be involved in a process and wants to test them specifically. We briefly review these methods here, discussing their strengths and weaknesses. I. Chemical and UV mutagenesis. This method of generating mutants is rapid, inexpensive and fairly easy. Cells are treated with a mutagenic agent (e.g., ethyl or methyl methanesulfonate, nitrosoguanidine or ultraviolet light (Madigan et al. 2003)), grown briefly, and then plated for isolated colonies. A balance must be struck in how much to mutagenize the cells: too little treatment results in few mutants in the population and makes it difficult to find them among the remaining wild-type cells, while too much treatment frequently results in multiple mutations in a single cell which complications determinating causality later. Critical parameters to consider are mutagen concentration, mutagen type (some mutagens are stronger than others) and exposure time to the mutagen. In the case of UV mutagenesis, significant killing typically occurs, but this is a necessary side effect of achieving a sufficiently high frequency of mutation in the remaining viable population. The major downside to this type of mutagenesis is the difficulty in identifying the gene, or genes, disrupted by the mutation. This means that more cells must be screened for the defect of interest because a large proportion will be both phenotypically and genotypically wild-type. On the positive side, however, this method of mutagenesis enables subtle phenotypes (such as residues on proteins that affect their substrate specificity, or interactions with other proteins), as well as conditional

18

Newman & Gralnick

phenotypes (e.g., temperature sensitive mutations) or partial defects to be identified. This is particularly useful in the identification of essential genes, as they mutants can be generated under a condition that permits them to grow, and then shifted to a different condition that renders the mutation lethal. Another benefit of chemical/UV mutagenesis is that it does not depend on introducing foreign DNA into the strain, as the other techniques do (although later, this will be necessary to verify the nature of the mutation—see below). II. Transposon mutagenesis. Transposons are genetic elements that can move in either random, or non-random fashion into and out of chromosomes (Madigan et al. 2003). Facilitating this movement is an enzyme called transposase. These elements are believed to play a role in influencing evolution and can be found in all forms of life. Researchers have modified these elements to be used as tools to generate random mutations. Often times these modifications streamline the element to one or two genes, with one typically encoding resistance to an antibiotic. Plasmids used for transposon mutagenesis will contain both the transposon sequence, and a separate gene encoding the specific transposase. When the plasmid is transformed into a strain, the transposase can be made, which will then facilitate integration of the transposon on the plasmid into the chromosome in a random fashion. The optimal plasmids used for such a procedure are unable to replicate without specific genes, therefore subsequent selection of the population for strains resistant to the antibiotic will eliminate the parent strain. This leaves only mutant strains that have successfully integrated the transposon into their genome. A downside of transposon mutagensis is that genes that are essential for a process under the conditions where the transposon insertion is selected will be missed. This either requires the growth conditions for the selection of the transposon insertion to be different from those where the mutants will be identified, or the use of chemical or UV mutagenesis that permits the study of conditional/partial phenotypes. When a transposon mutant with the desired phenotype is identified, several methods exist to determine the disrupted gene. One way is by cloning the transposon from purified, digested (or sheared) genomic DNA using the antibiotic resistance property. This method will yield genomic DNA flanking the transposon. Primers designed to the transposon can then be used to generate sequence into the flanking region. Alternatively, a process called arbitrary PCR can identify a small portion of sequence adjacent to the transposon directly from genomic DNA without cloning (Caetano-Anolles 1993). If working with a fully sequenced strain, as little as 20 base pairs of sequence is sufficient to identify the location of the transposon. The process of identifying the transposon-mutated gene in an unsequenced strain is more cumbersome, but still straightforward. Two approaches are possible. One can make a genomic library from the mutant strain (a library comprises either plasmids or cosmids or fosmids, the latter holding significantly more DNA than plasmids), introduce this library into an appropriate host, and select for growth of cells that carry the transposon. Alternatively, the sequence identified through arbitrary PCR can be used to probe a genomic library of the wild-type. Using hybridization techniques, a probe consisting of DNA flanking the transposon can identify plasmids in the genomic library containing homologous sequence. Once these have been identified, the plasmids themselves can be sequenced, open reading frames (genes) identified, and the genomic region surrounding the transposon reconstructed. III. Targeted gene knockout. In situations where a particular gene is suspected of being involved in a process (for example, when the genome of an organism of interest has been sequenced, and one can perform genomic analysis on it), it is often helpful to mutagenize that gene to test its involvement. This is called making a targeted gene "knockout." Several methods exist to specifically eliminate a gene of interest. However, to take advantage of this technique, the sequence of the both the gene, and its surrounding region must be known (Fig. 2A). Simple inactivation of a gene can occur by inserting an antibiotic resistance gene into the gene targeted for knockout. This can be accomplished by cloning the gene, and some flanking sequence, if

What Genetics Offers

Geobiology

19

Gene of Interest

- 2

1.

C

=

>

^

E

-

>

Figure 2. Diagram of targeted gene knockout using a suicide vector. Refer to text for description of figure.

required, into a plasmid that will only replicate in a specific genetic background (Fig. 2B). Good examples of this class of plasmids are those that require the n protein (encoded by the pir gene, derived from the R6K plasmid (Kolter 1981) to replicate. By engineering the plasmid in an E. coli strain that contains the pir gene, one can construct such a vector. The idea is to clone the gene of interest, then modify the gene by inserting an antibiotic resistance cassette into the gene (which can be accomplished either by cloning or by fusion PCR, Fig. 2C). Ideally, this antibiotic resistance cassette will have at least 1,000 base pairs of sequence from the host strain on either side. This is important to facilitate homologous recombination into the genome of the strain of interest. Once the plasmid is constructed that contains the disrupted gene, the next step is to transform the strain with the newly constructed plasmid using a method described above. Strains that become resistant to both of the antibiotics encoded by the antibiotic resistance genes in the plasmid (antiA and antiB) have undergone a single crossover event (Fig. 2C), resulting in the integration of the plasmid into the genome (Fig. 2D). The strain cannot maintain the plasmid itself because it does not produce the n protein. By growing the strain without selecting for the endogenous plasmid resistance (antiA, Fig. 2), a second recombination

20

Newman & Gralnick

event can occur in some individuals within the population, resulting in the elimination of the plasmid DNA from the genome, along with the wild-type gene of interest (Fig. 2D, result 1). If selection for resistance to antibiotic B is maintained, the second recombination event (Fig. 2D, result 2) that reverts the strain back to wild-type, cannot occur. Variations on this technique can yield mutations such as total gene replacements, or even in-frame (non-polar) deletions of the gene of interest. Genetic polarity in bacteria Bacteria typically contain a single, circular chromosome. Genes can be arranged in either direction in the genome and are typically clustered into operons. Genes organized in operons tend to be involved in the same process, although this is not always the case (Salgado et al. 2000). An operon is defined as multiple genes sharing the same genetic regulatory elements. A mutation that alters the capacity of the regulatory element to express downstream genes is called a "polar mutation." This mutation can be any of the types discussed above, but is most often associated with transposon mutagenesis. Because of polarity, a gene disrupted by a transposon may not cause the identified phenotype itself, but a gene (or genes) downstream may be responsible. To attribute a specific process to a specific gene, the problem of polarity must be taken into account, and complementation experiments must be done to demonstrate that a defect can be restored by provision of a particular gene. Step 3: Identifying mutants Identification of mutants defective in the process of interest is usually limited only by the robustness of the selection/screen, meaning that careful planning and thought should go into its design. We briefly illustrate this with four examples from our laboratory. I. Screen for mutants defective in reducing anthraquinone-2,6-disulfonate (AQDS) in S. oneidensis strain MR-1 (Newman and Kolter 2000). The first screen we performed involved the identification of S. oneidensis mutants that were defective in reducing the soluble humic acid analog AQDS. Because reduced AQDS is orange in color, wells containing mutants defective in this process remained clear whereas other wells turned orange. Mutants were grown overnight, then inoculated into minimal medium containing AQDS in 96-well microtiter plates (96 independent mutant strains per plate) and covered with mineral oil to limit oxygen diffusion into the wells. Two classes of mutants were isolated from this screen: mutants that were completely unable to reduce AQDS, and mutants that reduced AQDS slowly. A screen that can be visually monitored over time can facilitate identification of several classes of mutants with varying degrees of defectiveness. An example of this screen is shown in Figure 3. Note the lighter wells around the outside of the plate are likely due to re-oxidation of AQDS by oxygen diffusing into the plate. These effects could have been avoided by incubating the plates in an anaerobic chamber, which illustrates the importance of screen design for maximal efficiency in identifying potential mutants. II. Screen for iron hydr(oxide) reduction mutants in Shewanella oneidensis strain MR-1 (Gralnick and Newman, unpublished). To identify mutant strains of S. oneidensis defective in the ability to reduce insoluble iron hydr(oxide), we grew mutant strains overnight aerobically in 96-well microtiter plates in LB. These cultures were then transferred to minimal medium that contained iron hydr(oxide) as the sole electron acceptor for growth. Plates were incubated without shaking overnight, then a compound (ferrozine) was used to detect the presence of ferrous iron [Fe(II)], the product of iron hydr(oxide) reduction. Because this is a colormetric assay (when ferrozine binds to Fe(II), a purple color is formed), putative mutants were easily identified by eye as wells that did not significantly change color. These mutants were retested by restreaking from the initial overnight culture, then checked again for their capacity to reduce iron hydr(oxide) to confirm the phenotype. Retesting is very important in this process, as it

What Genetics Offers

1

2

m

m t>

n

21

Geobiology

•

X

Wk iM

m

It

' I

0

i B & l i * > f

H o H r + j H *

3+

3+

{Fe }{H 2 0}

[Fe ]

W

h

h

Y Fe {H 2 0}

(5)

where [Fe3+] and [Fe(OH)n(3~'l)+] are the concentrations of the iron hexaquo species and the hydrolysis species respectively, expressed in units of mole/kg. y are activity coefficients. [H+] is defined on the free hydrogen ion molality scale (Byrne and Kester 1976). Equation (5) requires the calculation of activity coefficients in order to correct for non-ideality effects arising from the high ionic strength of seawater. Alternatively, conditional stability constants P*„ can be defined, that are only valid for the ionic strength and composition of seawater: Fe(OH)';-'*][H-J p:= K ] so that n = n* YFe(OH)n 7H+ Pn Pn Ttt /-»I IF„ {H 2 Oj

^ *

The use of conditional stability constants is convenient and appropriate for speciation in open ocean water where small variations of salinity have only a minor effect on activities. Iron hydrolysis has been under investigation for several decades (Baes and Mesmer 1976; Byrne and Kester 1976; Millero et al. 1995; Liu and Millero 1999). However, the determination of conditional hydrolysis constants in seawater has been problematic and considerable uncertainty remains. The principal problems include the analysis of total iron or iron species at trace concentrations dictated by the low solubility of iron in seawater (sub-nanomolar at pH 8!); and by the difficulty to distinguish the mononuclear hydrolysis species from polymeric and colloidal iron (Byrne et al. 2000). For the model calculations presented in this paper, hydrolysis constants by Liu and Millero (1999) have been used (see Table 1). Using these constants it can be predicted that the dominant inorganic iron species in seawater (pH of 8.1) are Fe(OH) 2 + , Fe(OH)3°, and Fe(OH)4~ at thermodynamic equilibrium and under aerobic conditions. If the iron speciation is dominated by hydrolysis species, the total dissolved iron concentration [Fe(III) r ] equals the sum of all inorganic species [Fe'] and is related to the iron hexaquo complex by the following relationship (Byrne and Kester 1976): [Fe(III) r ] = [Fe'] = [Fe 3 + ]

+ ft [ h + f

+ p; [ h + f

+ £ [ h + ]~3 + p; [ h + ] ~ 4 j

[Fe(III) r ] = [Fe'] = [ F e 3 + } a F e .

(8)

(9)

where a F e ' is the inorganic side reaction coefficient. Solubility of iron in the presence of iron oxides Some of the most important Fe(III) oxide phases in aerobic systems are ferrihydrite, lepidocrocite (y-FeOOH), goethite (a-FeOOH), and hematite (a-Fe 2 0 3 ). Ferrihydrite is a poorly ordered phase with variable composition (Cornell and Schwertmann 2003). We report dissolution reactions and corresponding solubility constants based on the simplifying assumption of aFe(OH) 3 stoichiometry. The dissolution reactions are:

60

Kraemer, Butler, Borer,

Cervini-Silva

Ferrihydrite:

Fe(OH) 3 + 3H +

Goethite and lepidocrocite:

FeOOH + 3 H + ^ F e 3 + + 2 H 2 0

(11)

0.5(oc-Fe 2 0 3 ) +3H + ^ F e 3 + + 1.5H 2 0

(12)

Hematite:

Fe 3+ + 3 H 2 0

(10)

With the conditional solubility constants K*oxide in seawater defined as:

{Fe3+}{H2Q}3 Fe(OH) 3 ~~

r

I

3

K FeOOH

.3

,

K K

{Fe 3 + }{H 2 0} 1 5 _L ^ — r

~

F

M

2 {Fe 3+ }{H 2 0} ^ —

K

,3

|H+|

3 Yf.{H2Q}

[Fe-] yE£{H2oT 3

~1

3

3

— A

Fe(OH)3

*

[Lp e 3 + ]J YFJH.O} 2 _ J R 3

+ 3

[H ]

'

3

rè

K L ] J Y • FeF eL{ H2 2~oJr ~~ | -

-,3

[H+]

FeOOH '

3

_R*

_ i V

TH

a-Fe203'

3 H

TFE{H2Q} 3 7H

^

'

TF^HZO}1'5 3

RH

where [...] and {...} are species concentrations and activities respectively, y are activity coefficients and Koxide are the solubility constants at infinite dilution. The activity of ocean water (with a total mass of dissolved salts per kg seawater of 35 parts per thousand at 2CM-0 °C) is 0.9813 mole/kg (Millero and Leung 1976). The total dissolved iron concentration in equilibrium with the solid can be calculated combining Equations (13) to (15) with Equation (8): Ferrihydrite: [FE(IN)R ] = < ( O H ) 3 [ H + ] 3 • ( I + P ; [ H + ] _ 1 + P ; [ H + P 2 + P ; [ H + P 3 + P ; [ H + Y )

A 6)

[Fe(III) R ] = 4 e ( O H ) 3 [ H + ] • a Fe -

(17)

Goethite:

[Fe(III)R ] = 4 e O O H [H + ] 3 • a Fe -

(18)

Hematite:

[Fe(III) R ] =

[ H + ] ' • a Fe -

(19)

The determination of conditional solubility constants are subject to the same difficulties as the determination of conditional hydrolysis constants. Indeed, both types of conditional constants are often derived from measurements of the total iron concentrations in seawater (or analogous synthetic media) in equilibrium with the corresponding solid phase. The uncertainties in the prediction of mineral solubilities do not only arise from experimental difficulties. Solubility constants are functions of the mineral properties. Solubilities increase with decreasing particle sizes (also see chapter by Gilbert and Banfield, which discusses other size-dependent phenomena in nanoparticles) and increasing bulk lattice energies of iron oxides. Size and lattice energy are influenced by ageing and isomorphous substitution by metal ions such as Al(III). The solubility of ferrihydrite is usually orders of magnitude larger than the solubility of goethite and hematite. However, with decreasing crystal sizes the solubilities of goethite and hematite increase and approach the solubility of ferrihydrite at particle sizes below 10 nm (Langmuir 1969; Trolard and Tardy 1987). Particle diameters of soil goethite and hematites are in the nanometer range (10-150 nm; Cornell and Schwertmann 2003). Hematite particles in aerosols

Siderophores

& Dissolution

of Iron

Bearing

Minerals

61

collected at a mountain p e a k in rural Poland had a size range of 5.5 to 8.5 n m (Kopcewicz and Kopcewicz 1991). In these size ranges, the solubilities of crystalline iron oxides are orders of magnitude larger than predicted f r o m bulk mineral solubilities (see Table 2). It is therefore important to note that the solubility constants used in this paper (Table 2) are provisional, a fact that needs to b e considered in the interpretation of solubility calculations.

Table 1. Conditional iron hydrolysis constants used for speciation calculations in this publication. log P*„ w

Reaction Fe 3+ + H 2 0 « Fe(OH) 2 + + H +

P*i

-2.52

Fe 3+ + 2H 2 0 « Fe(OH)^ + 2H +

P*2

-6.5

Fe 3+ + 3H 2 0 « Fe(OH)° + 3H +

P*3

-15

Fe 3+ + 4H 2 0 « Fe(OH)^ + 4H +

P*4

-22.8

HO-N>

HI 9 •OH R-N H O I « ê L H ê ^ H fi

Aquachelin

Amphibactin

Figure 1. Examples of siderophores including amphiphilic marine siderophores structures (Martinez et al. 2000, 2003).

66

Kraemer,

Butler,

Borer,

Cervini-Silva

Table 3. A selection of siderophores by marine and terrestrial organisms. Ligand

Ligating Groups

log7TFe3+L \ogK¥eL

Organism

Siderophores

Originating

from Marine

Ref.

Bacteria

Alterobactin A

catecholate hydro xycarbo xy late

Alteromonas luteoviolacea

23.9(a)

49-53

(1)

Alterobactin B

catecholate carboxylate

Alteromonas luteoviolacea

>24(a)

43.6

(1)

Anguibactin

catecholate hydro xamate

Vibrio anguillarum

(2)

Aquachelin

hydro xamate a-hydro xycarbo xy late

Halomonas aquamarina

(3)

Bisucaberin

hydro xamate

Alteromonas haloplanktis

(4)

Marinob actin

hydro xamate

Marinobacter sp.

(3)

Petrob actin

catecholate

Marinobacter hydro carbono clastic us

(5)

Vibrio sp.

(6)

a-hydro xycarbo xylate Amphibactin Vulnibactin

hydro xamate

Vibrio vulnificus

catecholate catecholate Siderophores

(7)

Synechococcus sp. Originating

from Marine and Terrestrial

Aerobactin

hydro xamate a-hydro xycarbo xylate

Vibrio sp.

Desferoxamine B

hydro xamate

Streptomyces pylosus

Desferoxamine G

hydro xamate carboxylate

Vibrio sp.

Strong Iron Binding Ligands

Originating

38.1 - 4 2 . 3

(7)

22.93,c)

(8)

30.6

(9)(10)

Bacteria

21.6(a)

(10)(11)

from

Algae

n.n.

Emiliana huxleyi

Prorocentrin

Prorocentrum minimum

(13)

n.n.

Scenedesmus incrassatulus

(14)

Siderophores

from Terrestrial Bacteria and

(12)

20.7—21.5

Fungi

Enterob actin

catecholate

Pseudomonas aeruginosa

20.8(d)

49

(15)

Ferrichrome

hydro xamate

Ustilago spaerò gena

21.6 W

29.1

(16)

ferrihydrite > lepidocrocite > goethite (Kuma and Matsunaga 1995). Iron dissolution from aerosol samples in seawater shows more complex dissolution behaviour than pure mineral phases for several reasons. Aerosols can consist of more than one iron-bearing mineral phase with corresponding variations in solubilities and dissolution rates. Moreover, minerals are undergoing extensive transformations due to the harsh conditions during atmospheric transport, leading to the labilization of some fraction of iron from primary minerals including dissolved Fe(II) and Fe(III) as discussed above. Zhuang et al. (1990) have observed fast dissolution of up to 50% of the total iron from aerosol samples immersed into seawater at ambient pH (see corrected value in Yhu et al. 1993). A labile Fe(II) pool of between 0.3-2.2% of the total aerosol iron was quantified by extraction in acidic solutions (Zhu et al. 1993; Zhu et al. 1997; Siefert et al. 1999; Johansen et al. 2000). Photo-reductive dissolution in seawater Typically, iron oxide photolysis in the laboratory has been investigated by measuring the photo-production of Fe(II). Quantification of iron oxide photolysis in seawater by this methodological approach is constrained by fast reoxidation of photo-produced surface Fe(II) as well as fast reoxidation of Fe(II) that has eventually been released to the solution. Thus, the formation of Fe(II) may not be used as a reliable quantitative measure of photo-reductive iron oxide dissolution in seawater. In recent years other approaches have been taken to quantify iron oxide photolysis in seawater samples. Barbeau and Moffett (2000) have used a novel inert tracer technique to investigate the photo-dissolution of a model iron oxide. Colloidal ferrihydrite uniformly impregnated with an inert tracer (133Ba) was spiked to seawater and the release and accumulation of this tracer in solution was measured under irradiated conditions (natural sunlight). According to these authors, iron oxide photo-dissolution was directly related to the release and accumulation of 133Ba, regardless of the fate of iron. During irradiation of 133 Ba and 59Fe impregnated ferrihydrite, only release and accumulation of 133Ba was observed (Barbeau and Moffett 2000) while iron was most likely re-oxidized. Wells and Mayer (1991) investigated the photo-dissolution of colloidal ferrihydrite and goethite in spiked seawater of pH 8 by measuring the labile portion of total iron as determined by extraction with the complexing agent 8-hydroxyquinoline. The lability of these colloidal iron oxides was found to increase upon irradiation with artificial and natural sunlight, and this was assigned to the rapid cycling of photo-reductive dissolution, rapid reoxidation in solution and precipitation in the presence of unknown chromophores. Pre-irradiation of the

Siderophores & Dissolution of Iron Bearing Minerals

73

seawater prior to addition of colloidal Fe(III) eliminated the photoreaction, confirming the role of natural organic chromophores in photo-dissolution of iron oxides. The labile portion of iron in seawater was further shown to correlate positively with its availability to marine algae (Wells and Goldberg 1991). Thus it seems that photo-reductive dissolution of colloidal iron may generate an iron pool that is bioavailable to marine algae, either by generating dissolved Fe(II) of highly labile colloidal Fe(III).

ORGANIC LIGANDS AND IRON OXIDE DISSOLUTION IN SEAWATER Siderophore-promoted dissolution mechanisms Siderophores can influence iron oxide dissolution by acceleration of the dissolution reaction via ligand-controlled and light induced dissolution mechanisms (Kraemer et al. 1999; Borer et al. 2005) and by modifying the solution saturation state of the seawater with respect to the iron oxide (Cheah et al. 2003; Kraemer 2004). A model calculation was performed to illustrate the effect of the concentration of a strong marine siderophore (alterobactin A) on the solution saturation state in the presence of various model iron oxides and a total concentration of 0.1 nM dissolved iron in seawater (Fig. 4). Under these conditions, a small concentration of the siderophore is required to maintain solubility equilibrium (AG = 0 kJ/mole). Obviously the equilibrium siderophore concentration increases with increasing thermodynamic stability of the iron oxide. A further increase of the siderophore concentration leads to under-saturation (AG < 0 kJ/mole). A quantitative treatment of the effect of the solution saturation state on dissolution rates as derived from the activated complex theory (Lasaga 1981; Aagaard and Helgeson 1982) has been applied to ligand-controlled dissolution (Kraemer and Hering 1997) resulting in an empirical rate law: Rnet = kL[L]adsf(AG)

= kL[L]a

1-exp

AG 2 RT

(41)

where kL is the rate constant of ligand-controlled dissolution, [L]ods is the adsorbed ligand concentration; AG is the Gibbs free energy of reaction (kJ mole -1 ); R is the gas constant, and Tis the absolute temperature (K). Figure 5 illustrates the effect of the solution saturation state expressed as Gibbs free energy change on the net dissolution rate represented as/(AG) = [1 - exp(AG/(2i?7))]. At a AG < - 3 kJ/mole,/(AG) > 0.5, i.e., net dissolution rates are more than half of the maximum dissolution rates. In the model calculation presented in Figure 4, AG « - 3 kJ/mole at a total siderophore concentration between 0.25 nM (ferrihydrite) and 1 nM (hematite) which is in the range of observed strong ligand concentrations in marine surface water. Based on these considerations, it seems likely that the maintenance of small free siderophore concentrations by marine bacterial exudation may provide the driving force for dissolution mechanisms including ligand-controlled dissolution. Adsorbed siderophores can also accelerate iron oxide dissolution by a ligand-controlled dissolution mechanism (Holmen and Casey 1998; Kraemer et al. 1999; Kalinowski et al. 2000; Maurice et al. 2000, 2001; Cervini-Silva and Sposito 2002; Cocozza et al. 2002; Cheah et al. 2003; Kraemer 2004). As indicated in the rate law for ligand-controlled dissolution (Eqn. 41) the effect of adsorbed siderophores on dissolution rates is linearly related to their adsorbed concentrations. Adsorbed concentrations are non-linearly related to soluble siderophore concentrations via adsorption isotherms (Kraemer et al. 1999, 2002; Cocozza et al. 2002; Neubauer et al. 2002; Cheah et al. 2003). At extremely low dissolved siderophore

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F i g u r e 4. C a l c u l a t e d s o l u t i o n s a t u r a t i o n state of v a r i o u s i r o n o x i d e s as a f u n c t i o n of the a l t e r o b a c t i n - A c o n c e n t r a t i o n , a s s u m i n g a total s o l u b l e i r o n c o n c e n t r a t i o n s [Fe(III) f o J = 0 . 1 n M in s e a w a t e r . T h e s o l u t i o n s a t u r a t i o n state is e x p r e s s e d as G i b b s f r e e e n e r g y c h a n g e A G as c a l c u l a t e d b y E q u a t i o n (34) u s i n g c o n d i t i o n a l h y d r o l y s i s c o n s t a n t s as listed in Table 1. Positive A G i n d i c a t e s s u p e r - s a t u r a t i o n , n e g a t i v e A G u n d e r - s a t u r a t i o n . A t e q u i l i b r i u m A G = 0. p H = 8.1; l o g i f F e i = 2 3 . 9 .

-15

-10

-5

0

AG [kJ/mole] F i g u r e 5. T h e e f f e c t of the s o l u t i o n s a t u r a t i o n state e x p r e s s e d as G i b b s f r e e e n e r g y c h a n g e A G o n net d i s s o l u t i o n r a t e s w h e r e / ( A G ) = [ l - e x p ( A G / ( 2 S r ) ) ] . A t e q u i l i b r i u m , / ( A G ) = 0, i.e., the net d i s s o l u t i o n rate Rnet = 0. W i t h d e c r e a s i n g G i b b s f r e e e n e r g y c h a n g e s , / ( A G ) a p p r o a c h e s unity, i.e., the net d i s s o l u t i o n r a t e s a p p r o a c h a c o n s t a n t m a x i m u m value.

concentrations reported in literature, adsorbed siderophore concentrations are also expected to be low. Based on this consideration Kraemer (2004) has suggested that direct siderophorecontrolled dissolution mechanisms are insignificant at low siderophore concentrations typically found in natural environments compared to other dissolution mechanisms including proton-promoted dissolution, alkaline dissolution or ligand-promoted dissolution mechanisms driven by other adsorbed ligands. In this context, the more important function of siderophores in oligotrophic natural environments may be to increase the solubility of iron oxides and to drive other dissolution mechanisms by lowering the solution saturation state. This hypothesis is supported by observations of siderophore-promoted dissolution rates of iron oxides in artificial seawater by Yoshida et al. (2002). They have demonstrated that

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micro molar concentrations of a siderophore produced by a marine bacterium Alteromonas haloplanktis accelerate the dissolution rates of goethite and a poorly crystalline iron hydroxide. The dissolution rates increased with increasing siderophore concentrations in a roughly linear relationship at pH 4. Interpolating these results toward nanomolar concentrations suggests that the effect of the siderophores on dissolution rates is negligible at natural concentration levels. Photo-reductive dissolution mechanisms in the presence of siderophores Photo-reductive dissolution of iron oxides or other particulate iron forms is expected to be slow at seawater pH due to low adsorption of possible photo-reductive ligands (e.g., carboxylic and a-hydroxycarboxylic acids) to iron oxide surfaces, slow release of photoproduced surface Fe(II) to the solution and fast reoxidation of surface Fe(II). Waite et al. (1995) studied diel variations in iron speciation in northern Australian shelf waters and found no correlation between measured particulate iron concentrations and ferrozine active iron (Fe(II)). Therefore, they proposed that particulate iron does not appear to be the dominant source of Fe(II) in seawater. However, for seawater that is characterized by the presence of strong iron complexes (e.g., HNLC waters), dissolution of iron oxides by photo-reductive mechanisms may be enhanced considerably. Recently, Borer et al. (2005) have studied the photo-reduction of goethite and lepidocrocite in the presence of a typical organic photoreductant (oxalate) and two model siderophores, desferrioxamine B (DFO-B) and aerobactin. They have observed that under irradiated and aerated conditions at pH 6, surface Fe(III) is reduced by oxalate, but only a minor part of surface Fe(II) is detached from the surface before reoxidation takes place. Due to the slow detachment of Fe(II) from iron oxide surfaces, in particular for higher crystalline and less soluble iron oxide phases, reoxidation of surface Fe(II) has been shown to limit the overall dissolution rate at circumneutral pH (Sulzberger and Laubscher 1995; Voelker et al. 1997). However, in the presence of siderophores, Fe(II) is efficiently detached from the surface and significant photo-reductive dissolution rates are observed (Borer et al. 2005). Due to the fact that Fe-siderophore complexes have very negative redox potentials at neutral pH, oxidation of dissolved Fe(II)-siderophore complexes is assumed to be very fast (Boukhalfa and Crumbliss 2002), and the trivalent iron state is stabilized against reduction by many ligands. For the reported case of DFOB, oxidation of Fe(II)-DFOB complexes is instantaneous (Welch et al. 2002). These combined observations indicate that siderophores potentially enhance photo-reductive dissolution without contributing to the formation of measurable Fe(II). Amphiphilic siderophores In addition to the preponderance of a-hydroxycarboxylic-acid-containing siderophores characterized to date from open ocean bacterial isolates, amphiphilic siderophores are also prevalent and many also contain both an a-hydroxycarboxylic-acid, in the form of (3hydroxyaspartic acid, as well as a fatty acid that confers the amphiphilicity (e.g., marinobactins and aquachelins, see Fig. 1). The wide diversity of marine bacteria from which amphiphilic siderophores have been isolated suggests this property evolved as a common iron acquisition strategy for marine bacteria (Martinez et al. 2003). Not only could the amphiphilic character of the siderophores function to keep siderophores in close contact with the bacteria (Xu et al. 2002), but importantly this amphiphilicity will increase surface reactivity. The enhanced surface reactivity of photo-reactive siderophores on iron-containing particles may well further promote dissolution of iron minerals; these investigations are in progress. The aquachelins, marinobactin and amphibactins are all produced as suites of siderophores. The amphiphilic siderophores with shorter fatty acids (e.g., C12) partition into vesicle membranes far less than the longer chained fatty acids (C18). The decreased partitioning however increases the availability of particle interactions.

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CONCLUSIONS U n d e r s t a n d i n g the cycling of iron in m a r i n e s y s t e m s and h o w it relates to biological nutrient acquisition p r o c e s s e s r e m a i n s a c h a l l e n g e for b i o g e o c h e m i c a l research. T h i s c h a l l e n g e h a s b e e n m e t w i t h impressive v i g o r and success, c o n s i d e r i n g the difficulty to m e a s u r e iron concentrations, solubilities, and speciation at s u b - n a n o m o l a r levels. H o w e v e r , s o m e i m p o r t a n t i n f o r m a t i o n is missing. F o r e x a m p l e , w h i l e it is w e l l k n o w n that iron in m a r i n e s u r f a c e w a t e r s is b o u n d to strongly c o m p l e x i n g ligands, their characterization and identification is difficult. However, indirect e v i d e n c e suggests that b i o g e n i c ligands including m i c r o b i a l s i d e r o p h o r e s play an i m p o r t a n t role in m a r i n e iron speciation. A f u r t h e r c h a l l e n g e will b e the u n d e r s t a n d i n g of trace nutrient cycling and the indications of trace nutrient limitation in the geological record, c o n s i d e r i n g the potential i m p o r t a n c e of iron and other trace nutrients for the global climate and f o r b i o l o g i c a l evolution in the past. In this c h a p t e r w e r e v i e w e d the c o o r d i n a t i o n c h e m i s t r y and r e d o x - / p h o t o r e d o x c h e m i s t r y of soluble s i d e r o p h o r e iron c o m p l e x e s as well as the e f f e c t of s i d e r o p h o r e s o n the solubility of iron-bearing minerals, and their dissolution m e c h a n i s m s and rates. W e h o p e that the d i s c u s s i o n of these p r o c e s s e s m a y h e l p to appreciate the c o m p l e x i t y of b i o l o g i c a l influences o n m a r i n e iron cycling.

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Trick CG (1989) Hydroxamate-siderophore production and utilization by marine eubacteria. Curr Microbio 18:375-378 Trick CG, Andersen RJ, Gillam A, Harrison PJ (1983) Prorocentrin - an extracellular siderophore produced by the marine dinoflagellate prorocentrum-minimum. Science 219:306-308 Trolard F, Tardy Y (1987) The stabilities of gibbsite, boehmite, aluminous goethites and aluminous hematites in bauxites, ferricretes and laterites as a function of water activity, temperature and particle-size. Geochim Cosmochim Acta 51:945-957 Tsuda A, TakedaS, Saito H, Nishioka J, Nojiri Y, Kudo I, KiyosawaH, Shiomoto A, Imai K, OnoT, Shimamoto A, Tsumune D, Yoshimura T, Aono T, Hinuma A, Kinugasa M, Suzuki K, Sohrin Y, Noiri Y, Tani H, Deguchi Y, Tsurushima N, Ogawa H, Fukami K, Kuma K, Saino T (2003) A mesoscale iron enrichment in the western Subarctic Pacific induces a large centric diatom bloom. Science 300:958-961 van den Berg CMG (1995) Evidence for Organic Complexation of Iron in Seawater. Mar Chem 50:139-157 Voelker BM, Morel FMM, Sulzberger B (1997) Iron redox cycling in surface waters: effects of humic substances and light. Environ Sci Technol 31:1004-1011 Voelker BM, Sedlak DL (1995) Iron reduction by photoproduced superoxide in seawater. Mar Chem 50:93102 Voelker BM, Sulzberger B (1996) Effects of fulvic acid on Fe(II) oxidation by hydrogen peroxide. Environ Sci Technol 30:1106-1114 Volker C, Wolf-Gladrow DA (1999) Physical limits on iron uptake mediated by siderophores or surface reductases. Mar Chem 65:227-244 Waite TD, Szymczak R, Espey QI, Furnas MJ (1995) Diel variations in iron speciation in Northern Australian shelf waters. Mar Chem 50:79-91 Weger HG (1999) Ferric and cupric reductase activities in the green alga Chlamydomonas reinhardtii: experiments using iron-limited chemostats. Planta 207:377-384 Welch KD, Davis TZ, Aust SD (2002) Iron autoxidation and free radical generation: Effects of buffers, ligands, and chelators. Arch Biochem Biophys 397:360-369 Wells ML (1999) Manipulating iron availability in nearshore waters. Limnol Oceanogr 44:1002-1008 Wells ML, Goldberg ED (1991) Occurrence of small colloids in sea-water. Nature 353:342-344 Wells ML, Goldberg ED (1993) Colloid aggregation in seawater. Mar Chem 41:353-358 Wells ML, Mayer LM (1991) The photoconversion of colloidal iron oxyhydroxides in seawater. Deep-Sea Res 38:1379- 1395 Wells ML, Trick CG (2004) Controlling iron availability to phytoplankton in iron-replete coastal waters. Mar Chem 86:1-13 Whisenhunt J, D.W., Neu MP, Hou ZG, Xu J, Hoffmann DC, Raymond KN (1996) Specific sequestering agents for the actinides. 29. Stability of the Thorium(IV) complexes of desferrioxamine B (DFO) and three octadentate catecholate or hydroxypyridinonate DFO derivatives: DFOMTA, DFOCAMC, and DFO-l,2-HOPO. Comparative stability of the Plutonium(IV) DFOMTA complex. Inorg Chem 35:41284136 Wilhelm SW (1995) Ecology of iron-limited cyanobacteria: A review of physiological responses and implications for aquatic systems. Aquat Microb Ecol 9:295-303 Wilhelm SW, Trick CG (1994) Iron-limited growth of cyanobacteria - multiple siderophore production is a common response. Limnol Oceanogr 39:1979-1984 Winkelmann G (1992) Structures and functions of fungal siderophores containing hydroxamate and complexone type iron-binding ligands. Mycol Res 96:529-534 Witter AE, Hutchins DA, Butler A, Luther GW (2000) Determination of conditional stability constants and kinetic constants for strong model Fe-binding ligands in seawater. Mar Chem 69:1-17 Witter AE, Luther GW (1998) Variation in Fe-organic complexation with depth in the Northwestern Atlantic Ocean as determined using a kinetic approach. Mar Chem 62:241-258 Wong GB, KappelMJ, Raymond KN, Matzanke B, Winkelmann G (1983) Coordination chemistry of microbial iron transport compounds. 24. Characterization of coprogen and ferricrocin, 2 Ferric hydroxamate siderophores. J Am Chem Soc 105:810-815 Wu JF, Luther GW (1994) Size-fractionated iron concentrations in the water column of the Western North Atlantic Ocean. Limnol Oceanogr 39:1119-1129 Wu JF, Luther GW (1995) Complexation of Fe(III) by natural organic-ligands in the northwest Atlantic-ocean by a competitive ligand equilibration method and a kinetic approach. Mar Chem 50:159-177 Wu JF, Luther GW (1996) Spatial and temporal distribution of iron in the surface water of the northwestern Atlantic Ocean. Geochim Cosmochim Acta 60:2729-2741 Xu G, Martinez JS, Groves JT, Butler A (2002) Membrane affinity of the amphiphilic marinobactin siderophores. J Am Chem Soc 124:13408-13415 Yoshida T, Hayashi K, Ohmoto H (2002) Dissolution of iron hydroxides by marine bacterial siderophore. Chem Geol 184:1-9

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 85-108, 2005 Copyright © Mineralogical Society of America

Geomicrobiological Cycling of Iron Andreas Kappler and Kristina L. Straub Geomicrobiology Group Center for Applied Geosciences University of Tubingen D-72074 Tubingen, Germany [email protected] kristina. straub @ uni-tuebingen.de

INTRODUCTION Iron is the most abundant element on Earth and the most frequently utilized transition metal in the biosphere. It is a component of many cellular compounds and is involved in numerous physiological functions. Hence, iron is an essential micronutrient for all eukaryotes and the majority of prokaryotes. Prokaryotes that need iron for biosynthesis require micromolar concentrations, levels that are often not available in neutral pH oxic environments. Therefore, prokaryotes have evolved specific acquisition molecules, called siderophores, to increase iron bioavailability. Acquisition of iron by siderophores is a complex process and is discussed in detail by Kraemer et al. (2005). Here we focus on prokaryotes that generate energy for growth by oxidation or reduction of iron. In both processes single electron transfers are involved. Hence, for a significant extent of energy generation, turnover of iron in the millimolar rather than the micromolar range is necessary. Iron metabolizing organisms have therefore a strong influence on iron cycling in the environment. Microbial iron oxidation and reduction will be discussed, with emphasis on circumneutral pH environments that prevail on Earth. The active metabolic processes outlined above have to be distinguished from indirect biologically induced iron mineral formation in which prokaryotic cell surfaces simply act as passive templates ("passive iron biomineralization") (e.g., Konhauser 1997). General aspects of the iron cycle On our planet, iron is ubiquitous in the hydrosphere, lithosphere, biosphere and atmosphere, either as particulate ferric [Fe(III)] or ferrous [Fe(II)] iron-bearing minerals or as dissolved ions. Redox transformations of iron, as well as dissolution and precipitation and thus mobilization and redistribution, are caused by chemical and to a significant extent by microbial processes (Fig. 1). Microorganisms catalyze the oxidation of Fe(II) under oxic or anoxic conditions as well as the reduction of Fe(III) in anoxic habitats. Microbially influenced transformations of iron are often much faster than the respective chemical reactions. They take place in most soils and sediments, both in freshwater and marine environments, and play an important role in other (bio)geochemical cycles, in particular in the carbon cycle. Microbial iron cycling impacts the fate of both organic and inorganic pollutants, including those released from industrial and mining areas (Thamdrup 2000; Straub et al. 2001; Cornell and Schwertmann 2003). Solubility and chemical transformation of Fe(II) and Fe(III) minerals Different Fe(II), Fe(III) and mixed Fe(II)-Fe(III) minerals are found in the environment and many are used, produced or transformed by microbial activities (Table 1). Fe(III) minerals are characterized by low solubility at circumneutral pH and usually only very low, hardly 1529-6466/05/0059-005$05.00

DOI: 10.2138/rmg.2005.59.5

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Chemical or microbial Fe(ll) oxidation with O2 and microbial Fe(II) oxidation with CO2 in the light or with NO3" at neutral pH

Fe(ll) minerals

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* Fe 3 + i

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Chemical or microbial Fe(lll) reduction at acidic pH

Fe(lll) minerals

Dissolution (pH decrease)

Chemical or microbial Fe(lll) reduction at neutral pH Figure 1. Microbial and chemical iron cycle.

detectable concentrations in the range of 10~9 M of Fe(III) are present in solution (Fig. 2). However, colloid formation or complexation by organic compounds can lead to elevated concentrations of dissolved Fe(III), even at neutral pH (Cornell and Schwertmann 2003; Kraemer 2004). At strongly alkaline or strongly acidic pH, ferric iron oxides can be dissolved because of their amphoteric character. Ferric iron oxides can be reduced chemically by a range of organic and inorganic reductants. However, the environmentally most important reducing agent for Fe(III) is hydrogen sulfide, which is a common end product of microbial sulfur and sulfate reduction (Thamdrup 2000; Cornell and Schwertmann 2003). In contrast to Fe(III) minerals, some ferrous iron minerals, e.g., siderite or ferrous monosulfides, are considerably more soluble at neutral pH. This leads to concentrations of

Table 1. N a m e s a n d f o r m u l a s of s o m e i m p o r t a n t iron minerals.

Fe(III) oxides

Fe(III) oxyhydroxides and hydroxides1

Hematite a - F e 2 0 3

Goethite a - F e O O H

Maghemite y-Fe 2 0 3

Lepidocrocite y-FeOOH Ferrihydrite 2 Fe 5 H08-4H 2 0

Fe(II) minerals Ferrous monosulfides 'FeS'

Mixed Fe(II)-Fe(III) minerals 3

Magnetite F e 3 0 4

Pyrite FeS 2

Green rusts F e ^ F e / ^ O H ^ + ^ A - ) , ; A" = CI"; l /i S 0 4 2 -

Siderite F e C 0 3

Greigite Fe 3 S 4

Vivianite Fe 3 (P0 4 ) 2 For simplicity also commonly referred to as iron oxides. Ferrihydrite frequently is inadequately assigned as Fe(OH) 3 . However, if the identity of a poorly crystalline iron hydroxide is unknown, this formula can b e used as approximation. This term embraces a variety of minerals with slightly varying stoichiometrics, i.e.. 1'c.S. . Only troilite contains iron and sulfur in an exact 1:1 stoichiometry. Troilite rarely occurs on Earth, but is found in iron meteorites and lunar rocks (Lennie and Vaughan 1996).

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o Ferrihydrite Fe 5 HO'8 g • 4H20

Figure 2. Dominance diagram showing the concentrations of different dissolved Fe(III) species in the presence of ferrihydrite at pH 6-8.

-25 6

6.4

6.8

7.2

7.6

8

PH dissolved Fe(II) that can reach the pM range, even in the presence of bicarbonate or sulfide. However, Fe(II) is stable at neutral or alkaline pH only in anoxic environments and is oxidized to Fe(III) minerals by molecular oxygen. At acidic pH, Fe(II) can persist, even in oxic habitats (Stumm and Morgan 1996; Cornell and Schwertmann 2003). Under anoxic conditions, Mn(IV), nitrate, nitrite and nitrous oxide were shown in laboratory studies to oxidize Fe(II) chemically. In anoxic natural habitats, however, Mn(IV) is the only relevant oxidant of Fe(II) (Buresh and Moraghan 1976; Moraghan and Buresh 1977; Myers and Nealson 1988). Surface area and reactivity of ferric iron oxides The rates of chemical and microbial transformations of iron minerals depend on the number of available reactive surface sites, e.g., on the number of reactive surface-OH functional groups in case of ferric hydroxides (Roden 2003). The mineral surface area in turn inversely depends on the crystal size of the ferric iron oxides. Different iron minerals and samples of the same iron mineral with different crystal sizes vary significantly in surface area and therefore in stability and reactivity. This influences dissolution kinetics, transformation reactions and adsorption of organic and inorganic compounds. Values for surface areas can be determined experimentally by different methods, although these may produce slightly varying results. Surface areas determined by the Brunauer-Emmett-Teller method (BET) as extent of No-adsorption to an outgassed sample of the respective mineral span from a few m2/g (e.g., 8-16 m2/g for highly crystalline goethite) to a few hundreds of nr/g (e.g., 100^-00 m2/g for poorly crystalline ferrihydrite) (Cornell and Schwertmann 2003). Ferrihydrite Ferrihydrite is widespread in many natural environments. It is frequently used in laboratory studies with Fe(III)-reducing microorganisms and was observed as a product in cultures of Fe(II) oxidizers (Fig. 3). Ferrihydrite is a high-surface area iron oxide that consists of nanometer-sized crystals. Although it has been reported to be hexagonal, its structure remains a matter of debate (Mancaeu and Drits 1993; Jambor and Dutriziac 1998; Janney et al. 2000, 2001). It is a material that exhibits considerable disorder, but it is not amorphous (for more details see Gilbert and Banfield 2005). The crystallinity of the different ferrihydrite species depends on the conditions

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j

500 n m

Figure 3. Scanning (A) and transmission (B) electron micrographs of ferrihydrite produced by the anoxygenic phototrophic Fe(II)-oxidizing bacterium 'Rhodobacterferrooxidans'strain SW2. Note that particles of the biologically produced ferrihydrite are of nm-size and thus much smaller than microbial cells of typical size.

during synthesis, e.g., formation rate and the presence of organic and inorganic compounds (Cornell and Schwertmann 2003). The small, nanometer-sized crystals of ferrihydrite often aggregate to form colloids with sizes in the pm-range (Fig. 3). Forms of iron present in the environment In the environment, iron is rarely present as pure, well crystalline mineral phase but rather is found: •

in association with or covered by natural organic matter (e.g., humic substances, biofilm exopolysaccharides)

•

in particles to which anions such as phosphate (P0 4 3 - ) and arsenate (As0 4 3 ~) or positively charged metal ions (e.g., Fe2+, Cu2+, Mir4") have adsorbed

•

as minerals that are mixed or co-precipitated with other minerals (e.g., clays)

•

in minerals in which other cations, e.g., Al, Cr, Mn, partially substitute for iron

•

as nano-sized mineral particles or as aggregates of nano-sized particles (colloids)

•

complexed (e.g., by organic acids) and thus dissolved.

Such complex natural systems provide a huge variety of microenvironments, and thus microniches, for microorganisms with different physico-chemical requirements. In fact, it is hard, if not impossible, to simulate this complexity in the laboratory. This difficulty might be one explanation for the poor growth of many iron-metabolizing bacteria in the laboratory. Role of iron for microbial energy metabolism Different physiological groups of prokaryotes can use iron as a substrate for energy generation (Fig. 1, Table 2). In the following two sections we will discuss such Fe(II)-oxidizing and Fe(III)-reducing microorganisms in more detail, focusing on electron transfer between cells and iron minerals. Intracellular electron transfer in Fe(III)-reducing bacteria via redox active proteins such as cytochromes was recently reviewed by Lovley et al. (2004). The rapid growth in availability of genomic information will significantly improve our understanding of the electron transport chains of iron cycling microorganisms (e.g., Nelson and Methe 2005). The third section focuses on microbial iron cycling catalyzed by the cooperation of these two

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Table 2. Physiological groups of prokaryotes that catalyze iron redox transformations. Habitat

Electron donor

Electron acceptor

pH

Microbial metabolism

Representative

Oxic

Fe(II)

o2

acidic

Fe(II) oxidation

Thiobacillus ferrooxidans Sulfobacillus acidophilus

Fe(II)

o2

neutral

Fe(II) oxidation

Gallionella ferruginea Leptothrix ochracea

Fe(II)

NO 3 -

neutral

N03~-dependent Fe(II) oxidation

Acidovorax sp. strain BrGl Azospira oryzae strain PS

Fe(II)

co2

neutral

Phototrophic Fe(II) oxidation

'Rhodobacterferrooxidans' Rhodovulum iodosum

Organic or inorganic compounds

Fe(III)

acidic

Fe(III) reduction

Acidiphilium cryptum sp. JF-5 Thiobacillus thiooxidans

Organic or inorganic compounds

Fe(III)

neutral

Fe(III) reduction

Geobacter metallireducens Shewanella oneidensis

Anoxic

strains

strain SW2

physiological groups. Finally, some environmental implications are described and tasks for future investigations defined.

MICROBIAL OXIDATION OF Fe(II) Competition between chemical and microbial oxidation of Fe(II) The chemical oxidation of Fe(II) with oxygen depends mainly on the pH and the concentration of oxygen (Fig. 4). At pH values above 5, the Fe(II) oxidation rate has a firstorder dependence on Fe(II) and 0 2 concentrations and a second-order dependence on the OH~ concentration. Thus, an increase of one pH unit increases the rate of Fe(II) oxidation 100-fold. Therefore in 0 2 -saturated water at neutral pH, Fe(II) is readily oxidized to Fe(III) with a halflife in the order of several minutes (Stumm and Morgan 1996). Aerobic, neutrophilic Fe(II)oxidizing microorganisms compete successfully with this fast chemical process. However, some of them thrive only in microoxic niches with low oxygen concentrations and hence a slower chemical oxidation of Fe(II) by oxygen (Emerson 2000). In contrast, under acidic conditions Fe(II) persists for long periods of time, even in the presence of atmospheric 0 2 levels. Under anoxic conditions, only manganese oxides and nitrite have been shown to oxidize freely dissolved Fe(II) chemically (Myers and Nealson 1988; Moraghan and Buresh 1977). However, neither nitrate nor sulfate react chemically with Fe(II) at appreciable rates at low temperature. Therefore, anaerobic Fe(II)-oxidizing bacteria are the most important catalysts/ oxidants for the generation of Fe(III) in anoxic habitats. Aerobic acidophilic Fe(II)-oxidizing microorganisms Due to the stability of ferrous iron at acidic pH even in the presence of 0 2 , aerobic acidophilic Fe(II)-oxidizing microorganisms can readily compete with chemical oxidation. However, at acidic pH the redox couple Fe 3+ /Fe 2+ relevant for the redox reaction catalyzed by these bacteria has a redox potential of +770 mV. Therefore, at pH 2 only ~33 kJ/mol iron is produced during the oxidation with 0 2 , since the relevant redox potential of the redox couple 0 2 / H 2 0 is +1106 mV. This difference is just big enough for the synthesis of 1 mol ATP. Under

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0.5

LU 0

-0.5

-1

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

PH Figure 4. Eh-pH diagram for Fe(II), Fe(III), 0 2 and H 2 calculated with a Fe 2+ concentration of 10 |jM. For simplicity Fe(OH) 3 is used as approximation for the Fe(III) precipitates that are formed.

such conditions, ~90 mol Fe(II) has to be oxidized to fix 1 mol of C 0 2 as biomass (Ehrlich 2002). This relationship explains the huge amount of iron that is oxidized by aerobic acidophilic microorganisms, for instance in acid mine drainage (Baker and Banfield 2003; Druschel et al. 2004). Note that at pH values above 2, Fe(III) starts to precipitate and the oxidized product is removed, leading to a lowering of the redox potential of the Fe(III)/Fe(II) couple to less positive values. Since the redox potential of the 0 2 / H 2 0 couple is less pH-dependent (59 mV change per pH unit) than the Fe(III)/Fe(II) couple (177 mV change per pH unit), growth at less acidic pH values is more favorable for aerobic acidophilic Fe(II) oxidizers. A number of lineages of acidophilic iron-oxidizing organisms have been described to date. These were reviewed comprehensively by Nordstrom and Southam (1997) and more recently by Blake and Johnson (2000) and Baker and Banfield (2003). Furthermore, aspects of the population biology of acidophilic microbial communities sustained by iron oxidation are reviewed by Whitaker and Banfield (2005). Aerobic neutrophilic Fe(II)-oxidizing microorganisms This physiological group of microorganisms uses 0 2 as electron acceptor for enzymatic oxidation of Fe(II) at neutral pH. To gain energy for growth they have to compete with the chemical oxidation of Fe(II) by 0 2 . Initially, research on oxygen-dependent, neutrophilic Fe(II) oxidizers focused on species of the genera Gallionella and Leptothrix. Organisms of these two groups were already recognized in the 19th century to grow in oxic iron-rich environments. Gallionella ferruginea, a bean-shaped autotrophic bacterium, typically produces twisted stalks that are encrusted with ferric iron minerals (Hanert 1981). Gallionella spp. are very good examples of gradient organisms: growth is observed only under conditions that are neither strongly reducing nor highly oxidizing. The heterotrophic bacterium Leptothrix ochracea forms tubular sheaths which are also covered with ferric iron minerals (Emerson and Revsbech 1994). It has been suggested that the deposition of iron oxide minerals on the stalks or sheaths avoids encrustation of Fe(II)-metabolizing cells. Encrustation of living cells might impair both substrate uptake and metabolite release, and may even cause cell death (Hanert 1981; Hallberg and Ferris 2004).

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A range of novel microaerophilic Fe(II)-oxidizing bacteria were isolated with gradient culture techniques using gradients of Fe(II) and 0 2 to mimic natural environments. Representatives of the a-, (3- and y-subgroup of Proteobacteria were isolated from groundwater, deep sea sediments and freshwater wetland samples (Emerson and Moyer 1997; Edwards et al. 2003; Sobolev and Roden 2004). More details on aerobic bacterial Fe(II) oxidation at neutral pH are given by Emerson (2000). Anaerobic Fe(II)-oxidizing phototrophic bacteria About a decade ago anoxygenic phototrophic bacteria were discovered which grow in the light with ferrous iron as sole electron donor (Widdel et al. 1993). Experimental results were in good agreement with the following equation, assuming as the approximate formula of cell mass: 4FeC0 3 + 7H 2 0 h> + 4Fe(OH) 3 + 3C0 2 In the meantime, seven cultures of anoxygenic Fe(II)-oxidizing phototrophic bacteria have been established (Table 3). They include representatives of the three major phylogenetic lineages of anoxygenic phototrophs, and furthermore include freshwater and marine species. All known anoxygenic phototrophs oxidized Fe(II) optimally only within the narrow pH-range of 6.5 to 7. This allows them to use Fe(II) as electron donor since the standard redox potential for Fe 2+ /Fe 3+ (+770 mV at pH 1) is shifted at neutral pH to less positive values (around 0 mV) due to the low solubility of Fe(III) (Fig. 4; Widdel et al. 1993; Stumm and Morgan 1996). Therefore, Fe(II) can donate electrons to the photosystems of purple or green bacteria, with midpoint potentials around +450 mV or +300 mV, respectively (Clayton and Sistrom 1978). Fe(II)-oxidizing phototrophic bacteria can oxidize dissolved Fe(II). In addition, they grow with relatively soluble Fe(II) minerals such as siderite or ferrous monosulfide (Kappler and Newman 2004). In contrast, they were unable to utilize less soluble Fe(II) minerals, e.g., pyrite (FeS2) or magnetite (Fe 3 0 4 ). These results indicate that the phototrophs studied so far may depend on the supply of dissolved Fe(II). Geological records indicate that oceans contained considerable amounts of dissolved ferrous iron and hardly any molecular oxygen in the beginning of the Precambrian. It is therefore intriguing how massive iron mineral deposits, known as banded iron formations (BIFs), were generated at that time. This is even more puzzling, given doubt that the

Table 3. Ferrous iron-oxidizing phototrophic bacteria from different phylogenetic groups. Phylogenetic

group

Purple sulfur bacteria Purple non-sulfur bacteria

Green bacteria

Species Thiodictyon sp.

a

Strain

Source

Ref.

F4

Freshwater marsh

(1)

'Rhodobacter ferrooxidans'

SW2

Freshwater ditch

(2)

Rhodomicrobium vannielii

BS-1

Freshwater

(3)

Rhodopseudomonas palustris

TIE-1

Iron-rich freshwater mat

(4)

Rhodovulum iodosum

N1

Marine sediment

(5)

Rhodovulum robiginosum

N2

Marine sediment

(5)

KoFox

Freshwater ditch

(6)

b

Chlorobium ferrooxidans

a

Mixed culture, highly enriched in Thiodictyon

b

Defined co-culture with chemoheterotrophic 'Geospirillum' sp.

sp.

References: (1) Croal et al. 2004; (2) Ehrenreich and Widdel 1994; (3) Widdel et al. 1993; (4) Jiao et al. 2005; (5) Straub et al. 1999; (6) Heising et al. 1999

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photochemical oxidation of Fe(II) by UV light (Cairns-Smith 1978; Francois 1986; Anbar and Holland 1992) plays a major role in complex environments such as seawater. Until recently, BIFs were mainly considered the product of chemical or microbial oxidation of dissolved Fe(II) with 02 that was released by cyanobacteria during early oxygenic photosynthesis (Fig. 5)(e.g., Konhauser et al. 2002). Today, the anaerobic oxidation of Fe(II) by anoxygenic phototrophs is regarded as an alternative or additional explanation for the generation of BIFs (Fig. 5) (Widdel et al. 1993; Konhauser et al. 2002). Interestingly enough, in the literature it was speculated that anoxygenic Fe(II)-oxidizing phototrophs participated in the generation of BIFs even before such organisms had been isolated (Hartman 1984). A recent study considering rates of anoxygenic phototrophic Fe(II) oxidation under light regimes representative of ocean water at depths of a few hundred meters suggest that, even in the presence of cyanobacteria, anoxygenic phototrophs living beneath a wind-mixed surface layer provide the most likely explanation for BIF deposition in a stratified ancient ocean (Kappler et al. 2005).

Figure 5. Proposed mechanisms for the deposition of Precambrian banded iron formations in the presence or absence of molecular oxygen: oxidation of Fe(II) either indirectly by cyanobacterially produced 0 2 or directly by anoxygenic photosynthetic Fe(II)-oxidizing microorganisms.

Anaerobic Fe(II)-oxidizing nitrate-reducing bacteria Furthermore, it was discovered that microorganisms are capable of coupling oxidation of ferrous iron to dissimilatory reduction of nitrate (Hafenbradl et al. 1996; Straub et al. 1996). At pH 7, all redox pairs of the nitrate reduction pathway can accept electrons from ferrous iron because their redox potentials are more positive than that of the redox couple Fe(III)/ Fe(II) (Tables 4 and 5). The first observations of this metabolism were made with a lithotrophic enrichment culture that was transferred successively several times in medium that contained ferrous iron as sole electron donor (Straub et al. 1996). In this culture, ferrous iron oxidation coupled to nitrate reduction definitely supported cell growth; no oxidation of Fe(II) occurred in the presence of heat-inactivated cells or when nitrate was omitted. This type of metabolism is likely to be more abundant than ferrous iron oxidation by anoxygenic phototrophs since it is not restricted to habitats that are exposed to light. Furthermore, most-probable-number studies combined with molecular techniques indicated that the ability to oxidize ferrous iron with nitrate as electron acceptor is widespread among bacteria: members of the a-, (3-, y- and 5- subgroup of the Proteobacteria as well as gram-positive bacteria are probably able to oxidize ferrous iron (Straub and Buchholz-Cleven 1998; Straub et al. 2004). For these reasons, it was not surprising that enrichments of ferrous iron-oxidizing nitrate reducers were successfully established with a variety of marine, brackish or freshwater sediment samples. However, continuous cultivation

Geomicrobiological with ferrous iron as sole electron donor turned out to be impossible for most of these enrichments. After a few transfers, ferrous iron was oxidized only in the presence (of low concentrations) of an organic substrate, e.g., 0.5 m M acetate. Accordingly, most Fe(II)-oxidizing nitrate reducers isolated so far need an organic co-substrate for growth, i.e. grow only mixotrophically with ferrous iron (Straub et al. 1996; Benz et al. 1998; Straub and Buchholz-Cleven 1998; Lack et al. 2002; Straub et al. 2004). For many of these strains that need an additional organic substrate, it is questioned whether ferrous iron oxidation is beneficial and supports cell growth or whether iron is just oxidized in a rather unspecific side reaction. Experiments with Azospira oryzae strain PS (formerly known as Dechlorosoma suillum) undoubtedly showed that oxidation of ferrous iron initiated only after the organic (co) substrate was completely oxidized (Chaudhuri et al. 2001). However, at least for some mixotrophically ferrous iron-oxidizing strains, i.e. Acidovorax sp. strain B r G l , Aquabacterium sp. strain BrG2 and Thermomonas sp. strain BrG3, the situation was more complex

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Table 4. Redox potentials of redox pairs relevant for microbial nitrate reduction at pH 7.0 and 25 °C (Thaueretal. 1977). Redox pair

E0' [MV]

NO3-/NO2-

+430

NO2-/NO

+350

NO/N2O

+1180

N2O/N2

+1350

Table 5. Redox potentials1 of some redox pairs relevant for microbial reduction of iron oxides at pH 7.0 and 25 °C (Thamdrup 2000). Redox pair

E0' [mV]

Fe5H08-4H20 (ferrihydrite)/Fe2+ 2+

y-FeOOH (lepidocrocite)/Fe 2+

+2 -88

a-FeOOH (goethite)/Fe

-274

a-Fe 2 0 3 (hematite)/Fe2+

-287

2+

Fe 3 0 4 (magnetite)/Fe

-314

1

Slightly varying data can b e found in the literature because redox potentials strongly depend on pH, temperature, concentrations of reactants, crystal size of the iron oxide and thermodynamic data chosen for calculations.

because the oxidation of ferrous iron seemed to be regulated. Only if electrons from the organic substrate exceeded those from ferrous iron by a factor of ten or if the concentration of nitrate was limited, ferrous iron oxidation ceased completely (Straub et al. 2004). Recently, some strains were isolated from the deep sea that oxidized Fe(II) with nitrate in the absence of an additional organic substrate. Unfortunately, it is not clear whether these strains can actually grow with ferrous iron as the sole electron donor for several successive generations (Edwards et al. 2003). Mechanisms of microbial Fe(II) oxidation The mechanism of microbial Fe(II) oxidation has been studied best with the acidophilic Fe(II) oxidizer Thiobacillus ferrooxidans. According to a present model, Fe(II) is oxidized to Fe(III) at the outer membrane of the cell (Blake and Johnson 2000). The electron is then transferred to a copper-containing protein (rusticyanin) which in turn transfers it to a periplasmic c-type cytochrome. From such cytochromes, electrons are finally passed on to 0 2 via cytochrome oxidase to form water. The exact pathway of the electron transfer from ferrous iron to oxygen is still not completely understood, and slightly varying models are described in the literature. However, there is general agreement that the initial step, i.e. the oxidation of ferrous iron, occurs outside the cell (Blake and Johnson 2000). In addition, it was shown for neutrophilic aerobic Fe(II)-oxidizing Leptothrix spp. that the oxidation of Fe(II) is catalyzed by Fe(II)-oxidizing compounds that are actively secreted by

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the cell (De Vrind-de Jong et al. 1990); an Fe(II)-oxidizing protein with a molecular weight of 150 kDa was identified from spent culture medium of strain Leptothrix discophora (Corstjens et al. 1992). For anaerobic Fe(II) oxidation, it is unknown where in the cell or at the cell surface Fe(II) is oxidized, and it is not understood how the bacteria deal with the poor solubility of the product. In particular, it is unclear how Fe(II)-oxidizing microorganisms either avoid encrustation with ferric iron minerals (such as the phototrophic Fe(II)-oxidizer 'Rhodobacter ferrooxidans' strain SW2) or overcome encrustation such as the nitrate-reducing Fe(II)oxidizing strain BoFeNl (Fig. 6). A microenvironment of lowered pH values in vicinity of the cells was observed around colonies of phototrophic Fe(II) oxidizers ('Rhodobacter ferrooxidans' strain SW2) fixed in semi-solid agarose (Kappler and Newman 2004). Such an acidification could explain why these microorganisms do not become encrusted with ferric iron minerals during oxidation of Fe(II) (Fig. 6). With the aerobic Fe(II)-oxidizing strain TW2, deposition of Fe(III) minerals was observed not at the cell surface but at a certain distance from the cells. It was suggested that Fe(III) was released in a ligand-bound dissolved form. The dissolved Fe(III)-ligand complex is thought to

Figure 6. Scanning electron micrographs showing (A) cells of the nitrate-reducing Fe(II)-oxidizing strain B o F e N l highly encrusted with Fe(III) minerals and (B) anoxygenic photosynthetic Fe(II)-oxidizing m i c r o o r g a n i s m s that are associated but not encrusted with Fe(III) minerals.

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diffuse away from the cells. Destabilization of the Fe(III)-ligand complex would finally lead to hydrolysis and precipitation of Fe(III) minerals distant from the metabolically active cells (Roden et al. 2004). The nature of the Fe(III)-ligand and the trigger necessary for destabilizing the dissolved Fe(III)-ligand complex are unknown so far. However, this hypothesis is supported by energetic calculations. The estimated biomass yield for growth was 0.15 mol cell-C per mol oxidized Fe(II), and hence approximately 7.5x more than experimentally observed in gradient cultures. This suggests that a substantial amount of energy is available for synthesis of other cellular components, including Fe(III)-binding ligands. Formation of Fe(III) minerals by microbial Fe(II) oxidation Microbial oxidation of Fe(II) and precipitation of Fe(III) minerals might be better understood by comparing observations from microbial cultures to results from chemical Fe(II) oxidation experiments (e.g., Cornell et al. 1989). Mono- and dinuclear dissolved species of ferrous iron such as [FeOH]2+ and [Fe2(OH2)]4+ are formed initially during abiotic oxidation of Fe(II). Subsequently, these dissolved species transform into polymeric Fe(III) colloids before they precipitate as poorly crystalline ferrihydrite particles with a size of ~2-5 nm in diameter. Depending on the reaction conditions, the initial precipitation might be followed by further transformations of ferrihydrite. Either "solid-state conversion" to hematite (Fe 2 0 3 ) by internal rearrangement of iron and oxygen atoms is induced or dissolution to low-molecular weight polynuclear iron species occurs which then transform to better crystalline iron oxides such as goethite ("dissolution-reprecipitation mechanism") (Hansel et al. 2003; Schwertmann and Cornell 2003). Transformation of ferrihydrite to goethite via dissolution-reprecipitation could be facilitated in particular by enhanced proton activities close to cell surfaces. Lowered pH values and transformation of ferrihydrite to goethite were indeed observed in the vicinity of anoxygenic phototrophic Fe(II)-oxidizing bacteria (Kappler and Newman 2004). The formation of crystalline iron oxides during microbial Fe(II) oxidation might accelerate the speed of Fe(II) oxidation by an autocatalytic mechanism. Excess dissolved Fe(II) has a high affinity for surface-OH groups of iron oxides. These surface OH-groups are electron-donor ligands that increase the electron density of the adsorbed ferrous iron. An increased electron density stabilizes +3 charged iron better than +2 charged iron. Therefore, adsorption of Fe(II) on iron oxide surfaces increases the rate of Fe(II) oxidation (Wehrli et al. 1989; Eisner et al. 2003). An electron transfer from surface-adsorbed Fe(II) through the underlying iron oxide to the cell (where electrons could be accepted by outer membrane compounds) would abolish the need for the Fe(II)-oxidizing microbe to be in direct contact with the dissolved Fe(II). The first evidence for such an electron transfer between adsorbed Fe(II) and Fe(III) from the underlying ferric iron oxide was recently reported by Williams and Scherer (2004). Formation of a variety of different iron minerals by different Fe(II)-oxidizing microorganisms indicates that, apart from medium composition, concentration of possible co-substrates and incubation conditions, the mechanism of Fe(II) oxidation, metabolic rates and the presence of nucleation sites influence (and maybe even control) the mineralogy of the Fe(III) minerals produced. As an example, in a recent report polysaccharide strands were suggested to be extruded to act as a template for formation of akaganeite pseudo-single crystals (Chan et al. 2003)

MICROBIAL DISSIMILATORY REDUCTION OF Fe(III) Microbial reduction of ferric iron was known as a phenomenon for many decades before its (bio)geochemical relevance was recognized. It was presumed that microorganisms cause reduction of Fe(III) only indirectly, e.g., by lowering the redox potential or the pH. In addition,

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only few bacteria were known that transferred just few electrons to Fe(III) during fermentative growth (for details see Lovley 1991). This perspective changed notedly with the discovery of bacteria that respire ferric iron and thereby reduce substantial amounts of it (Balashova and Zavarzin 1979; Lovley and Phillips 1988; Myers and Nealson 1988). Today, it is generally accepted that dissimilatory ferric iron-reducing prokaryotes, i.e. organisms that gain energy by coupling the oxidation of organic or inorganic electron donors to the reduction of ferric iron, have a strong influence on the geochemistry of many environments (e.g., Lovley 1997; Thamdrup 2000). Acidophilic Fe(III)-reducing microorganisms The ability to reduce Fe(III) to Fe(II) under acidophilic conditions seems to be widespread among acidophilic microorganisms, but the degree of Fe(III) reduction varies significantly (Johnson and McGinness 1991). Chemolithotrophic and heterotrophic prokaryotes (bacteria and archaea) are able to couple the reduction of Fe(III) to the conservation of energy. Interestingly enough, acidophilic iron reduction does not require strict anoxia in some strains and proceeds most rapidly even under microoxic conditions (Johnson et al. 1993). Studies with Acidiphilium sp. strain SJH showed that this bacterium is able to reduce a variety of different Fe(III) forms, with the highest reduction rates observed for dissolved Fe(III) (Bridge and Johnson 2000). Barely soluble poorly crystalline iron oxides (e.g., ferrihydrite) were reduced faster than better crystalline iron oxides (e.g., goethite). Apparently, Acidiphilium sp. strain SJH causes dissolution of ferric iron indirectly since direct contact between bacterial cells and solid ferric iron was not necessary for ferric iron reduction to occur. The strain appears to produce an extracellular compound that accelerates Fe(III) dissolution but not reduction. The nature of this extracellular compound and further details of the dissolution process are still unknown (Bridge and Johnson 2000). Microbial reduction of Fe(III) at neutral pH In the past decade, numerous strains of dissimilatory ferric iron-reducing bacteria and archaea have been isolated from a vast range of habitats. A comprehensive list of Fe(III)reducing microorganisms was recently published by Lovley et al. (2004). The widespread occurrence of Fe(III)-reducing prokaryotes correlates with the ubiquitous presence of ferric iron. Many sediments and soils may contain ferric iron minerals in the range of 50-200 mmol per kg dry matter. Ferric iron is therefore often the dominant electron acceptor although it is barely soluble at neutral pH. According to experimental observations, Fe(III)-reducing microorganisms developed three different strategies to cope with the difficulty of transferring electrons from the cell to the surface of a barely soluble electron acceptor (Fig. 7) (reviewed by Hernandez and Newman 2001; Lovley et al. 2004): A.

Physical contact between cell surface/cell surface compounds and ferric iron allows direct delivery of electrons.

B.

Iron chelators increase the solubility of Fe(III) and hence alleviate Fe(III)reduction.

C.

Electron-shuttling compounds transfer electrons from the cell to Fe(III) without the necessity of physical contact between cells and ferric iron.

Considering the complexity of natural environments and the wealth of microbial capabilities, it is not surprising that different organisms as well as single organisms developed different strategies in order to reduce diverse Fe(III) compounds under varying conditions. For example, some evidence indicates that Shewanella algae and Geothrix fermentans produce and release both Fe(III)-chelators and electron shuttles (Nevin and Lovley 2002a; Lovley et al. 2004). Furthermore, evidence in Geobacter spp. indicates that different cellular compounds are involved in reduction of dissolved Fe(III)-citrate and barely soluble ferrihydrite (Straub

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Fe(lll)-mineral crust on soil particle

B

Figure 7. Schematic illustration of different microbial strategies to transfer electrons to ferric iron: (A) Physical contact between cell surface and ferric iron allows direct delivery of electrons; (B) Iron chelators increase solubility of ferric iron; (C) Electron-shuttling molecules transfer electrons to ferric iron. Note: single crystals of ferric iron oxides might be smaller than bacteria (see Fig. 3). However, in nature iron oxides may form crusts on soil particles as depicted here.

and Schink 2004a, Leang et al. 2005). As the methods to study microbial mechanisms of Fe(III) reduction are pivotal, they will be discussed in the next section. Methods to study mechanisms of microbial Fe(III) reduction Physiological studies of microbial ferric iron reduction at neutral pH are rather difficult. Low solubility of ferric iron is the most prominent obstacle. It impedes the monitoring of cell growth by means of optical density and the separation of cells from iron minerals by simple centrifugation. To circumvent this difficulty, iron chelators (e.g., citrate, EDTA) were applied in many studies to keep iron in solution. However, chelators change the redox potential of ferric iron, may enter the periplasm and can react unspecifically with electron-releasing cellular compounds (reviewed by Straub et al. 2001). In addition, there is growing awareness that culturing microorganisms in rich medium (in particular with other electron acceptors than ferric iron) may cause production of cell compounds which will not be produced under iron-reducing conditions in natural habitats (Glasauer et al. 2003). Caution in the interpretation of results is also necessary when supernatants were prepared either by filtration or centrifugation. Cells of Geobacter spp. were shown to artificially release compounds (e.g., cytochromes) by filtration with 0.2 fim filters as well as by centrifugation (Straub and Schink 2003). In other studies, semi-permeable membranes were used to separate cells and iron oxides physically in order to determine whether prokaryotic cells produce Fe(III)-chelators or electron-shuttling molecules. However, it was recently shown that Fe(III)-chelators and electron-shuttling molecules were unable to diffuse freely through dialysis membranes with the largest pore size available (Nevin and Lovley 2000). Therefore, results from studies with semi-permeable membranes need critical assessment, in particular when positive controls with known electron-shuttling molecules are lacking. To minimize artifacts that might be induced by centrifugation or filtration, further methods were developed to study production of Fe(III)-chelators or electron-shuttling

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molecules in vivo. In a simple one, ferric iron is entrapped in medium solidified with 1% agar (Straub and Schink 2003). Technically more elaborate is the use of iron containing microporous alginate (Nevin and Lovley 2000) or iron-containing glass beads (Lies et al. 2005). Microbial mechanisms of Fe(III) reduction at neutral pH For Fe(III) reduction, species of the genus Geobacter appear to require physical contact to ferric iron oxides (Nevin and Lovley 2000; Lovley et al. 2004). The latest study with Geobacter sulfurreducens showed that pili (a special type of cell appendages) were produced during growth with poorly soluble Fe(III), but not with dissolved Fe(III)-citrate as electron acceptor. In addition, experiments with a pilus-deficient mutant implied that those pili were not just required for attachment of cells to ferric iron, and conducting-probe atomic force microscopy indicated that the pili were highly conductive. Together these results suggest that Geobacter sulfurreducens attaches and delivers electrons to the surface of ferric iron oxides via pili (Reguera et al. 2005). Initially it was thought that such a physical contact between Fe(III)-reducing prokaryotes and ferric iron minerals is mandatory for the delivery of electrons from the cells to the minerals. Today, it is generally accepted that Fe(III)-reducing microorganisms also use Fe(III)-chelators or electron-shuttling molecules to reduce barely soluble ferric iron oxides (e.g., Hernandez and Newman 2001; Rosso et al. 2003; Lovley et al. 2004). Diffusible chelators and shuttling molecules help to bridge spatial distance between cells and ferric iron oxides (Fig. 7). This is of particular importance since microorganisms and ferric iron oxides are not evenly distributed in natural environments. Plant root exudates and plant debris can release organic acids which are known to chelate Fe(III), e.g., oxalate or citrate. Accordingly, highly elevated levels of dissolved Fe(III) in the range of 20 to 50 pM were reported for soils in laboratory incubations with rice (Ratering and Schnell 2000). In comparison to the nM range of dissolved Fe(III) at neutral pH (Fig. 2), significantly elevated levels of dissolved, presumably chelated Fe(III) in the range of 4 to 16 pM were reported furthermore for freshwater sediment and groundwater samples (Nevin and Lovley 2002b). Plant debris is also the source for phenolic compounds and humic substances which can act as electron-shuttling molecules (e.g., Lovley et al. 1996, 1998). The oxidized form of an electron-shuttling molecule is used as the electron acceptor by the metabolically active cell. The electrons are then transferred from the reduced shuttling molecule in a chemical reaction to ferric iron. It is important that this chemical reaction regenerates the oxidized form of the shuttling molecule (Fig. 7). Prokaryotes that reduce ferric iron oxides only via electronshuttling molecules are not ferric iron-reducing bacteria in a strict sense as their electron acceptor is the shuttling molecule rather than ferric iron. In that respect it is worth mentioning that sulfur-reducing bacteria also can benefit from indirect reduction of ferric iron oxides via sulfur cycling, with sulfide as reductant of ferric iron (Straub and Schink 2004b). The impact of prokaryotes that reduce ferric iron oxides only indirectly with the help of naturally occurring electron shuttles on the total Fe(III) reduction in anoxic environments has not yet been evaluated. Finally, it is useful to discuss what advantages, if any are available to iron-reducing microorganisms that specifically produce and excrete Fe(III)-chelating or electron-shuttling molecules. For a single bacterium, production and release of such specialized molecules might be too expensive, in particular if such molecules are lost or degraded before the costs of biosynthesis have been compensated. However, in bacterial communities (e.g., biofilms, cell aggregates) such expenses might be balanced: each cell contributes just few chelator or shuttle molecules and the whole community benefits from the accessibility of ferric iron as electron

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acceptor. To date, no Fe(III)-chelating or electron-shuttling O compound that was specifically produced and excreted in ferric iron-reducing cultures in vivo has been identified. However, some evidence indicates that Shewanella algae and Geothrix fermentans produce and release both Fe(III)-chelators and electron shuttles (Nevin and Lovley 2002a; Lovley et al. 2004). Furthermore, it was recently N demonstrated that some antibiotics, e.g., phenazine-1Figure 8. Chemical structure of carboxamide (PCN), bleo-mycin and pyocyanine, function phenazine-l-carboxamide, PCN, as electron shuttles between bacteria and Fe(III) minerals a redox-active antibiotic produced (Hernandez et al. 2004). These redox-active antibiotics, by Pseudomonas chlororaphis exemplified in Figure 8 by PCN, structurally resemble that functions as electron shuttle between different microorganhumic substances with regard to aromaticity and redoxisms and ferrihydrite. active functional groups. Pseudomonas chlororaphis can transfer electrons to ferric iron oxides only due to the production and reduction of PCN. In addition to the PCN-producing strain, Shewanella oneidensis, Escherichia coli, Pseudomonas fluorescens, Pseudomonas aeruginosa and Vibrio cholerae were able to reduce PCN and thus indirectly reduce Fe(III) minerals (Hernandez et al. 2004). So far it is unknown whether the antibiotic-producing and/or antibiotic-reducing strains actually gain energy through this indirect Fe(III) reduction. It might just as well be a new microbial mechanism to acquire iron for assimilatory processes (compare to Kraemer et al. 2005). Interestingly enough, appreciable concentrations of phenazines in the range of 27 to 43 ng per g root (with soil) were found in the rhizosphere of wheat plants (Thomashow et al. 1990).

MICROBIAL IRON CYCLING Many reactions relevant to geochemistry are driven and/or accelerated by the activity of prokaryotes. Examples are manifold and include carbon mineralization, nitrogen fixation and sulfate reduction as well as iron transformations. In particular, prokaryotes that gain energy through oxidation of Fe(II) or reduction of Fe(III) have a strong influence on the global iron cycle (for details see Kraemer et al. 2005). For example, in most acidic aerobic environments, Fe(II) would persist if not oxidized by acidophilic Fe(II) oxidizers. Microbial iron cycling under acidic conditions Understanding microbial cycling of iron at acidic pH has implications for the leaching of ores and the development of (bio)remediation techniques for acid mine drainage. Evidence for in vivo iron cycling was obtained from mining sites and was investigated in more detail in the laboratory (Johnson et al. 1993). Mixed cultures of acidophilic Fe(II)-oxidizing and Fe(III)reducing microorganisms cycled iron between the oxidation states +11 and +III when the concentration of dissolved oxygen fluctuated and sufficient electron donor for Fe(III) reducers was supplied. Similarly, iron cycling could also be demonstrated in pure cultures since some acidophiles, e.g., Thiobacillus ferrooxidans and Sulfobacillus acidophilus catalyze both Fe(II) oxidation and Fe(III) reduction under appropriate conditions (reviewed by Johnson et al. 1993; Blake and Johnson 2000). Microbial iron cycling at neutral pH Ferric iron is the dominant electron acceptor for the mineralization of carbon particularly in anoxic freshwater habitats (Thamdrup 2000). Therefore, processes that regenerate Fe(III) minerals that are again available for Fe(III)-reducing prokaryotes have become of significant interest. Since microbial Fe(III) reduction and Fe(II) oxidation were recognized, microbial

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cycling of iron seemed plausible and is hypothesized for many environments. For example, it was estimated that in marine coastal sediments each iron atom cycled approximately 100 to 300 times before being buried in the sediment (Canfield et al. 1993). However, the natural complexity of habitats aggravates direct measurements of microbial iron transformation reactions and thus microbial iron cycling in vivo has not yet been clearly demonstrated. Prerequisites for microbial iron cycling at neutral pH Microbial iron cycling needs iron plus appropriate supplementary substrates, i.e., electron donors for Fe(III) reduction and electron acceptors for Fe(II) oxidation (Fig. 9). Furthermore, the nature of the iron minerals formed is crucial for an efficient cycling since not all iron minerals are equally good substrates. For instance, the redox potential of an iron redox couple determines whether it is available as electron donor or acceptor in terms of energetics (Table 5). At pH 7, molecular oxygen and all redox pairs of the nitrate reduction pathway (Fig. 4) can accept electrons from ferrous iron, independently from the Fe(III) mineral produced. The situation is more complex with ferric iron oxides as electron acceptor. The oxidation of acetate (C0 2 /acetate, E0' = -290 mV) is energetically favorable just with iron oxides such as lepidocrocite or ferrihydrite. On the other hand, for the reduction of goethite, hematite or magnetite, electron donors with a lower redox potential are necessary, e.g., molecular hydrogen (2H7H 2 , E0' = -414 mV) or formate (C0 2 /formate, E0' = -432 mV). Hence, theoretically acetate can fuel microbial cycling of iron only if ferrihydrite or lepidocrocite is the product of microbial Fe(II) oxidation. Furthermore, it is essential that supplementary electron donors and acceptors can diffuse since ferric iron is barely soluble and thus rather immobile in natural environments. The solubility of Fe(III) in equilibrium with ferrihydrite is in the range of 10~9 M (Fig. 2). The solubilities of goethite and hematite are even lower and the Fe(III) concentrations in the presence of these minerals is in the range from 10~10 M to 10~13 M (Kraemer 2004). In natural environments, the concentration of dissolved Fe(II) is controlled by adsorption or precipitation and is therefore insignificant in comparison to solid Fe(II). Dissolved Fe(II) adsorbs to soil particles, cell surfaces and also to the surface of ferric iron oxides (e.g., Liu et al. 2001; Cornell and Schwertmann 2003); in model calculations for a coastal sediment, adsorbed Fe(II) exceeded the concentration of freely dissolved Fe(II) 30fold (Van Cappellen and Wang 1996; Thamdrup 2000). Oxygen-dependent microbial cycling of iron The product of microbial aerobic Fe(II) oxidation is often identified as poorly crystalline ferrihydrite, a ferric iron oxide that is a favorable electron acceptor for ferric iron-reducing prokaryotes. However, traces of oxygen may repress iron respiration in facultatively anaerobic Fe(III) reducers and can even inhibit the activity of strictly anaerobic ferric iron-reducing

Electron donor,

e.g. N2

e.g. benzoate

e.g. C0 2 , H 2 0

^

^

hOI 11 1

i-eii'J

Electron acceptor, e.g. nitrate

Figure 9. Schematic illustration of microbial iron cycling.

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microorganisms, as shown e.g., for Geobacter spp. (Straub and Schink 2004a). Hence, oxygen-dependent microbial cycling of iron (most likely) always depends on a transition between oxic and anoxic conditions. In natural environments, such transitions are supported by temporary oxygen release by roots, bioturbation by burrowing and boring animals and mixing of sediments by waves or storm events. Of particular interest for oxygen-dependent iron cycling are microaerophilic Fe(II) oxidizers since they thrive in oxic-anoxic transition zones, allowing for microscale microbial redox cycling. Such oxic-anoxic transition zones are characterized by the simultaneous presence of ferrous iron which was produced during anaerobic Fe(III) reduction and of low concentrations of oxygen which reached this zone via diffusion from overlying oxic zones (Sobolev and Roden 2002). Oxygen-independent microbial cycling of iron The identification of ferrihydrite as the primary product of anaerobic Fe(II) oxidation by phototrophs (Straub et al. 1999; Kappler and Newman 2004) or nitrate-reducing bacteria (Straub et al. 1996, 1998) indicated the possibility of anaerobic iron cycling. Biologically produced ferrihydrite has been shown to be an excellent electron acceptor for Fe(III)-reducing bacteria, which reduced it completely to the ferrous state (Straub et al. 1998,2004). Similar to ferric iron, nitrate is used as electron acceptor only in anoxic zones after oxygen is depleted. In contrast to iron, nitrate is soluble at pH 7. Finally, it was feasible to show an anaerobic iron cycling in laboratory co-culture experiments (Straub et al. 2004). For these experiments, Fe(II)-oxidizing nitrate reducers were chosen that were unable to oxidize benzoate. As a counterpart, an Fe(III) reducer was selected that utilized benzoate with Fe(III) but not with nitrate as the electron acceptor. Only in experiments that were inoculated with Fe(II) oxidizers plus Fe(III) reducers was benzoate completely oxidized with nitrate in the presence of iron (Fig. 9). Although the transient iron phases in such co-cultures were not analyzed, stoichiometric considerations suggest that iron cycled 6 times between the oxidation states +11 and +III in these experiments (Straub et al. 2004). Clearly, the relevance of anaerobic nitrate-dependent iron cycling for the complex flow of electrons in anoxic environments still needs to be determined. Microbial anaerobic iron cycling is possible with the participation of anoxygenic Fe(II)oxidizing phototrophs. Light-dependent, anaerobic cycling of iron may occur in top layers of shallow sediments that are reached by light or in (iron rich) microbial mats.

ENVIRONMENTAL IMPLICATIONS Microbial reduction of Fe(III) and oxidation of Fe(II) may have left geological imprints during Earth's history, and continues to significantly affect modern environments. Due to the considerable amount of iron in soils and sediments, Fe(III) usually represents the most abundant electron acceptor in anoxic soils and freshwater sediments; only in marine sediments is this dominance counterbalanced by the high sulfate concentration of seawater (Thamdrup 2000). Carbon cycling, mobility of micronutrients and in particular the degradation, transformation and (im)mobilization of organic and inorganic pollutants are closely linked in many environments to the microbial iron cycle. Degradation of organic compounds coupled to dissimilatory Fe(III) reduction In pristine environments, Fe(III)-reducing microorganisms typically couple the reduction of Fe(III) to the oxidation of H 2 or other fermentation products such as simple fatty acids or ethanol. Some ferric iron-reducing strains have in addition the ability to oxidize aromatic, organic pollutants such as benzene, toluene, ethylbenzene, phenol, p-cresol and o-xylene (e.g., Lovley et al. 1989; Lovley and Lonergan 1990; Lovley and Anderson 2000; Jahn et al.

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2005). If at contaminated sites ferric iron oxides are available for dissimilatory iron-reducing bacteria and other essential nutrients for microbial growth (e.g., nitrogen, phosphorous, sulfur) are present, microbial Fe(III) reduction has the potential to significantly contribute to the degradation of aromatic pollutants in a process termed 'natural attenuation'. Iron minerals as adsorbents Many ferric iron mineral surfaces are positively charged at neutral pH due to their high points of net zero charge (ZPC). The pH ZPCs are ~7.9 for ferrihydrite, ~8.5 for hematite and ~9.0-9.4 for goethite (Cornell und Schwertmann 2003). Such iron oxides therefore constitute good adsorbents for negatively charged compounds like phosphate (P0 4 3 - ), bicarbonate (HC0 3 ~) and oxyanions of toxic metal ions such as arsenate (As0 4 3 ~), arsenite (As0 3 3 ~) or chromate (Cr0 4 2 - ). Furthermore, negatively charged natural organic matter (humic substances) also binds strongly to ferric iron mineral surfaces (Stumm and Morgan 1996; Cornell and Schwertmann 2003). Anions were shown to adsorb to ferrihydrite surfaces via replacement of surface hydroxyl groups, leading to tight bonds of almost covalent character. For weak organic acids also an outer-sphere adsorption via weak electrostatic interactions was observed. Cations usually adsorb to iron oxides via hydroxyl-bridged inner-sphere complexes at the oxide surface. A comprehensive overview on adsorption processes on iron oxides is given by Cornell and Schwertmann (2003). Transformation of iron minerals and pH changes in the environment both influence the adsorption of cations and anions to ferric iron oxides. In some cases this has dramatic consequences, as in the well-documented example of arsenic: Arsenite and arsenate both strongly bind to ferric iron oxides (Dixit and Hering 2003). There is evidence from extended X-ray absorption fine structure (EXAFS) studies for inner sphere complexation but the nature of the surface complexes is still controversial (e.g., Waychunas et al. 1993; Shermann and Randall 2003) The microbially induced reductive dissolution of arsenic-loaded iron oxides is thought to play a key role in As-release into the groundwater, which leads to enormous drinking water contaminations observed in countries such as Bangladesh and India (Cummings et al. 1999; Smedley and Kinniburgh 2002; Islam et al. 2004; Harvey et al. 2005). In addition, arsenate can be released into the groundwater when high-surface area ferrihydrite transforms into hematite or goethite with significantly lower surface areas (Ford 2002). Immobilization of toxic metal ions by microbial Fe(II) oxidation and Fe(III) reduction Reductive dissolution of metal-loaded iron oxides releases adsorbed metal ions into the environment. In contrast, Fe(II) oxidation can lead to the immobilization of toxic metal ions. Either co-precipitation during Fe(II) oxidation (Gunkel 1986; Richmond et al. 2004) or adsorption to synthetic or natural iron oxides potentially provides an applicable biotechnological method to remove toxic metal ions such as arsenic efficiently from drinking water. Natural removal of arsenic by iron oxides was observed when ferrihydrite was precipitated together with arsenic from arsenic- and iron-rich hydrothermal fluids (Pichler and Veizer 1999). In addition to mobilization of adsorbed compounds by dissolution of Fe(III) minerals or immobilization of pollutants by adsorption to or co-precipitation with biogenic iron minerals, iron-metabolizing microorganisms can also have a more direct effect on the fate of pollutants. For example, Fe(III)-reducing microorganisms were shown to convert toxic metal ions from more soluble forms (e.g., Cr(VI) and U(VI)) to less soluble forms that are likely to be immobilized in the subsurface (e.g., Cr(III) and U(IV)) (e.g., Lovley 1993; Lovley and Phillips 1992). Formation of reactive iron minerals During microbial Fe(III) reduction, different minerals are formed depending on the chemical composition of the medium, on the substrate concentrations and on the incubation

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conditions (e.g., Roden and Zachara 1996; Lovley 1997; Fredrickson et al. 1998; Urrutia et al. 1999; Benner et al. 2002; Zachara et al. 2002; Hansel et al. 2003; Kukkadapu et al. 2004). In particular, the presence of different counter ions leads to the precipitation of different Fe(II) minerals, e.g., iron mono- or disulfides ('FeS' or FeS 2 ), ferrous iron phosphate (vivianite), carbonate (siderite) or magnetite (Cornell and Schwertmann 2003). Also transformation of ferrihydrite to the more crystalline iron oxides hematite and goethite was observed during Fe(III) reduction (Hansel et al. 2003). Knowing the products of microbial Fe(III) reduction is quite important since the Fe(II)-species formed as the result of microbial Fe(III) reduction (either Fe(II) minerals or mineral-adsorbed and thus activated Fe(II)-species) can be efficient reductants in contrast to free aqueous Fe(II). They were shown to reduce organic contaminants such as nitroaromatic and chlorinated organic compounds (Hofstetter 1999) but also to reduce inorganic compounds such as U(VI) and Cr(VI) (Buerge and Hug 1999; Liger et al. 1999; Lovley and Anderson 2000; Jeon et al. 2005). Because different Fe(II)-species show different reactivities with respect to reductive pollutant transformation, understanding the mechanisms and conditions leading to different Fe(II)-species is necessary (Haderlein and Pecher 1999; Pecher et al. 2002; Eisner et al. 2003).

SOME TASKS FOR FUTURE INVESTIGATIONS Prokaryotes that gain energy from iron redox transformations have a strong influence on the geochemistry of pristine or polluted environments. This was recognized only in the recent past and still needs to be studied in more detail. In particular the influence of the microbial cycle of iron on the global cycles of other elements, such as carbon, nitrogen or sulfur is not completely understood. The majority of ferrous iron-oxidizing and ferric ironreducing prokaryotes were isolated during the last decade. Therefore, it is not surprising that our knowledge of these prokaryotes and their iron metabolism is still in its infancy. One major task in microbial physiology is to explain how prokaryotes transfer electrons from or to iron minerals. In this context, the combination of physiology with molecular genetics to track the activity of certain proteins is very promising as recently summarized by Croal et al. (2004) and reviewed by Newman and Gralnick (2005). Anticipated genomic data from isolates (as described by Nelson and Methe 2005) and natural communities (as discussed by Whitaker and Banfield 2005) will assist in the identification of targets. Furthermore, the identification of Fe(III)-chelating and electron-shuttling molecules intentionally produced and released by prokaryotes is key to understand the biological and ecological importance of these postulated mechanisms. The advancement of different microscopic methods, e.g., cryo transmission electron or environmental scanning electron microscopy, will help to describe intimate interactions between microorganisms and iron minerals. Finally, consequences of microbial iron transformations for the fate of organic and inorganic pollutants have to be explored in more detail to better understand the process of natural attenuation and to foster remediation of polluted sites. An interdisciplinary approach as pursued in the emerging field of geomicrobiology which comprises such diverse fields as microbial physiology, molecular genetics, geochemistry and mineralogy will certainly help to answer many open questions.

ACKNOWLEDGMENTS Parts of the work for this chapter were done by AK in Dianne Newman's lab at the California Institute of Technology (Caltech) and by KLS in Bernhard Schink's lab at the University of Konstanz (Germany). The electron micrographs were taken by AK at Caltech/JPL with the help of M. Chi and R.E. Mielke. We would like to thank B. Schink for reviewing the manuscript. AK is supported by an Emmy-Noether fellowship from the German Research Foundation (DFG).

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Kappler A, Pasquero C, Konhauser KO, Newman DK (2005) Deposition of banded iron formations by photoautotrophic Fe(II)-oxidizing bacteria. Geology. In press. Konhauser KO (1997) Bacterial iron biomineralization in nature. FEMS Microbiol Rev 20:315-326 Konhauser KO, Hamade T, Raiswell R, Morris RC, Ferris FG, Southam G, Canfield DE (2002) Could bacteria have formed the Precambrian banded iron formations? Geology 30:1079-1082 Kraemer SM (2004) Iron oxide dissolution and solubility in the presence of siderophores. Aquat Sci 66:3-18 Kraemer SM, Butler A, Borer P, Cervini-Silva J (2005) Siderophores and the dissolution of iron-bearing minerals in marine systems. Rev Mineral Geochem 59:53-84 Kukkadapu RK, Zachara JM, Fredrickson JK, Kennedy DW (2004) Biotransformation of two-line silicaferrihydrite by a dissimilatory Fe(III)-reducing bacterium: formation of carbonate green rust in the presence of phosphate. Geochim Cosmochim Acta 68:2799-2814 Lack JG, Chaudhuri SK, Chakraborty R, Achenbach LA, Coates JD (2002) Anaerobic biooxidation of Fe(II) by Dechlorosoma suillum. Microb Ecol 43:424-431 Leang C, Adams LA, Chin KJ, Nevin KP, Methe BA, Webster J, Sharma ML, Lovley DR (2005) Adaptation to disruption of the electron transfer pathway for Fe(III) reduction in Geobacter sulfurreducens. J Bacteriol 187: 5918-5926 Lennie AR, Vaughan DJ (1996) Spectroscopic studies of iron sulfide formation and phase relations at low temperatures. In: Mineral Spectroscopy: A Tribute to Roger G. Burns. Dyar MD, McCammon C, Schaefer MW (eds) The Geochemical Society, St. Louis, p 117-131 Lies DP, Hernandez ME, Kappler A, Mielke RE, Gralnick JA, Newman DK (2005) Shewanella oneidensis strain MR-1 uses overlapping pathways for iron reduction at a distance and by direct contact under conditions relevant for biofilms. Appl Environ Microbiol 71:4414-4426 Liger E, Charlet L, Van Capellen P (1999) Surface catalysis of uranium(VI) reduction by iron(II). Geochim Cosmochim Acta 63:2939-2955 Liu CX, Kota S, Zachara JM, Fredrickson JK, Brinkman CK (2001) Kinetic analysis of the bacterial reduction of goethite. Environ Sci Technol 35:2482-2490 Lovley DR, Phillips EJP (1988) Novel mode of microbial energy metabolism: organic carbon oxidation coupled to dissimilatory reduction of iron or manganese. Appl Environ Microbiol 54:1472-1480 Lovely DR, Baedecker MJ, Lonergan DJ, Cozzarelli JM, Phillips EJP, Siegel DJ (1989) Oxidation of aromatic contaminants coupled to microbial iron reduction. Nature 339:297-300 Lovley DR, Lonergan DJ (1990) Anaerobic oxidation of toluene, phenol, and p-cresol by the dissimilatory ironreducing organism, GS-15. Appl Environ Microbiol 56:1856-1864 Lovley DR (1991) Dissimilatory Fe(III) and Mn(IV) reduction. Microbiol Rev 55:259-287 Lovley DR, Phillips EJP (1992) Reduction of uranium by Desulfovibrio desulfuricans Appl Environ Microbiol 58:850-856 Lovley DR (1993) Dissimilatory metal reduction. Annu Rev Microbiol 47:263-290 Lovley DR, Coates JD, Blunt-Harris EL, Phillips EJP, Woodward JC (1996) Humic substances as electron acceptors for microbial respiration. Nature 382:445-448 Lovley DR (1997) Microbial Fe(III) reduction in subsurface environments. FEMS Microbiol Rev 20:305-315 Lovley DR, Fraga JL, Blunt-Harris EL, Hayes, LA, Phillips EJP, Coates JD (1998) Humic substances as a mediator for microbially catalyzed metal reduction. Acta Hydrochim Hydrobiol 26:152-157 Lovley DR, Anderson RT (2000) The influence of dissimilatory metal reduction on the fate of organic and metal contaminants in the subsurface. J Hydrol 238:77-88 Lovley DR, Holmes DE, Nevin KP (2004) Dissimilatory Fe(III) and Mn(IV) reduction. Adv Microb Phys 49: 219-286 Manceau A, Drits VA (1993) Local structure of ferrihydrite and feroxyhite by EXAFS spectroscopy. Clay Minerals 28:165-184 Moraghan JT, Buresh RJ (1977) Chemical reduction of nitrite and nitrous oxide by ferrous iron. Soil Sci Soc Am J 41:47-50 Myers CR, Nealson KH (1988) Microbial reduction of manganese oxides: interactions with iron and sulfur. Geochim Cosmochim Acta 52:2727-2732 Nelson KE, Methe B (2005) Metabolism and genomics: adventures derived from complete genome sequencing. Rev Mineral Geochem 59:279-294 Newman DK, Gralnick JA (2005) What genetics offers geobiology. Rev Mineral Geochem 59:9-26 Nevin KP, Lovley DR (2000) Lack of production of electron-shuttling compounds or solubilizaiton of Fe(III) during reduction of insoluble Fe(III) oxide by Geobacter metallireducens. Appl Environ Microbiol 66: 2248-2251 Nevin KP, Lovley DR (2002a) Mechanisms for accessing insoluble Fe(III) oxide during dissimilatory Fe(III) reduction by Geothrixfermentans. Appl Environ Microbiol 68:2294-2299 Nevin KP, Lovley DR (2002b) Mechanisms for Fe(III) oxide reduction in sedimentary environments. Geomicrobiol J 19:141-159

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Nordstrom DK, Southam G (1997) Geomicrobiology of sulfide mineral oxidation. Rev Mineral 35:361-390 Pecher K, Haderlein SB, Schwarzenbach RP (2002) Reduction of polyhalogenated methanes by surface bound Fe(II) in aqueous suspensions of iron oxides. Environ Sei Technol 36:1734-1741 Pichler T, Veizer J (1999) Precipitation ofFe(III) oxyhydroxide deposits from shallow-water hydrothermal fluids in Tutum Bay, Ambitle Island, Papua New Guinea. Chem Geol 162:15-31 Ratering S, Schnell S (2000) Localization of iron-reducing activity in paddy soil by profile studies. Biogeochemistry 48:341-365 Reguera G, McCarthy KD, Mehta T, Nicoll JS, Tuominen MT, Lovley DR (2005) Extracellular electron transfer via microbial nanowires. Nature 435:1098-1101 Richmond WR, Loan M, Morton J, Parkinson GM (2004) Arsenic removal from aqueous solution via ferrihydrite crystallization control. Environ Sei Technol 38:2368-2372 Roden EE, Zachara JM (1996) Microbial reduction of crystalline iron(III) oxides: influence of oxide surface area and potential for cell growth. Environ Sei Technol 30:1618-1628 Roden EE (2003) Fe(III) oxide reactivity toward biological versus chemical reduction. Environ Sei Technol 37: 1319-1324 Roden EE, Sobolev D, Glazer B, Luther GW III (2004) Potential for microscale bacterial Fe redox cycling at the aerobic-anaerobic interface. Geomicrobiol J 21:379-391 Rosso KM, Zachara JM, Fredrickson JK, Gorby YA, Smith SC (2003) Nonlocal bacterial electron transfer to hematite surfaces. Geochim Cosmochim Acta 67:1081-1087 Shermann DM, Randall SR (2003) Surface complexation of arsenic(V) to iron(III) (hydr)oxides: structural mechanism from ab initio molecular geometries and EXAFS spectroscopy. Geochim Cosmochim Acta 67:4223-4230 Sobolev D, Roden EE (2002) Evidence for rapid microscale bacterial redox cycling of iron in circumneutral environments. Anton van Leeuw 181:587-597 Sobolev D, Roden EE (2004) Characterization of a neutrophilic, chemolithoautotrophic Fe(II)-oxidizing ßProteobacterium from freshwater wetland sediments. Geomicrobiol J 21:1-10 Smedley PL, Kinniburgh DG (2002) A review of the source, behaviour and distribution of arsenic in natural waters. Appl Geochem 17:517-568 Straub KL, Benz M, Schink B, Widdel F (1996) Anaerobic, nitrate-dependent microbial oxidation of ferrous iron. Appl Environ Microbiol 62:1458-1460 Straub KL, Buchholz-Cleven BEE (1998) Enumeration and detection of anaerobic ferrous iron-oxidizing, nitrate-reducing bacteria from diverse European sediments. Appl Environ Microbiol 64:4846-4856 Straub KL, Hanzlik M, Buchholz-Cleven BEE (1998) The use of biologically produced ferrihydrite for the isolation of novel iron-reducing bacteria. System Appl Microbiol 21:442-449 Straub KL, Rainey FA, Widdel F (1999) Rhodovulum iodosum sp. nov. and Rhodovulum robiginosum sp. nov., two new marine phototrophic ferrous-iron-oxidizing purple bacteria. Int J Syst Bacteriol 49:729-735 Straub KL, Benz M, Schink B (2001). Iron metabolism in anoxic environments at near neutral pH. FEMS Microbiol Ecol 34:181-186 Straub KL, Schink B (2003) Evaluation of electron-shuttling compounds in microbial ferric iron reduction. FEMS Microbiol Lett 220:229-233 Straub KL, Schink B (2004a) Ferrihydrite reduction by Geobacter species is stimulated by secondary bacteria. Arch Microbiol 182:175-181 Straub KL, Schink B (2004b) Ferrihydrite-dependent growth of Sulfurospirillum deleyianum by electron transfer via sulfur cycling. Appl Environ Microbiol 70:5744-5749 Straub KL, Schönhuber WA, Buchholz-Cleven BEE, Schink B (2004) Diversity of ferrous iron-oxidizing, nitrate-reducing bacteria and their involvement in oxygen-independent iron cycling. Geomicrobiol J 21: 371-378 Stumm W, Morgan JJ (1996) Aquatic Chemistry: Chemical Equilibria and Rates in Natural Waters. John Wiley & Sons, New York Thamdrup B (2000) Bacterial manganese and iron reduction in aquatic sediments. In: Advances in microbial ecology. Schink B (ed) Kluwer Academic/Plenum Publishers, New York, p 41-84 Thauer RK, Jungermann K, Decker K (1977) Energy conservation in chemotrophic anaerobic bacteria. Bacteriol Rev 41:100-180 Thomashow LS, Weller DM, Bonsall RF, Pierson LS (1990) Production of the antibiotic phenazine-1carboxylic acid by fluorescent Pseudomonas species in the rhizosphere of wheat. Appl Environ Microbiol 56:908-912 Urrutia MM, Roden EE, Zachara JM (1999) Influence of aqueous and solid-phase Fe(II) complexants on microbial reduction of crystalline iron(III) oxides. Environ Sei Technol 33:4022-4028 Van Cappellen P, Wang YF (1996) Cycling of iron and manganese in surface sediments - A general theory for the coupled transport and reaction of carbon, oxygen, nitrogen, sulfur, iron, and manganese. Am J Sei 296:197-243

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Waychunas GA, Rea BA, Fuller CC, Davis JA (1993) Surface chemistry of ferrihydrite: part 1. EXAFS studies of the geometry of coprecipitated and adsorbed arsenate. Geochim Cosmochim Acta 57:2251-2269 Wehrli B, Sulzberger B, Stumm W (1989) Redox processes catalyzed by hydrous oxide surfaces. Chem Geol 78:167-179 Whitaker RJ, Banfield J F (2005) Population dynamics through the lens of extreme environments. Rev Mineral Geochem 59:259-277 Widdel F, Schnell S, Heising S, Ehrenreich A, Assmus B, Schink B (1993) Ferrous iron oxidation by anoxygenic phototrophic bacteria. Nature 362:834-835 Williams AGB, Scherer MM (2004) Spectroscopic evidence for Fe(II)-Fe(III) electron transfer at the iron oxide-water interface. Environ Sci Technol 38:4782-4790 Zachara JM, Kukkadapu RK, Fredrickson JK, Gorby YA, Smith SC (2002) Biomineralization of poorly crystalline Fe(III) oxides by dissimilatory metal reducing bacteria (DMRB). Geomicrobiol J 19:179-207

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 109-155, 2005 Copyright © Mineralogical Society of America

Molecular-Scale Processes Involving Nanoparticulate Minerals in Biogeochemical Systems Benjamin Gilbert Earth Sciences Division Lawrence Berkeley National Laboratory 1 Cyclotron Road MS 90R1116 Berkeley, California, 94720, U.S.A. [email protected]

Jillian F. Banfield Earth and Planetary Sciences University of California Berkeley Berkeley, California, 94720-4767, U.S.A. jill @ eps. berkeley. edu

INTRODUCTION Mineral particles with diameters on the scale of nanometers (nanoparticles) are important constituents of natural environments. The small size of such particles has a host of consequences for biogeochemical systems, which we will review in this chapter. We begin by briefly reviewing what is known about how and when nanoparticles form and the ways in which nanoparticles impact natural processes. Nanoparticles form via a variety of inorganic and biological pathways and may be introduced into the environment as a consequence of human activity. They are widespread in the environment (Banfield and Navrotsky 2001; Penn et al. 2001; Kennedy et al. 2003a,b; van der Zee et al. 2003), although few quantitative studies of their abundance are available. While all crystals begin as very small particles, an important subset retain small size at the Earth's surface over relatively long time scales, because the combination of low temperature and low solubility inhibits growth. As a consequence, nanoparticles have the potential for a long lifetime in the environment, and widespread transport under certain circumstances. Processes that result in the removal of nanoparticles from an environment include dissolution, settling from air, transport in solution, and crystal growth. Particle aggregation may be an important component of these processes because it will promote settling, limit dispersal via solution transport, and can lead to aggregation-based crystal growth. The presence of nanoparticles can profoundly influence biological systems. Because they are frequently formed in environments that are populated by microorganisms, nanoparticles often adhere to cell surfaces or cell-associated polymers (see Fig. 1 for examples). These coatings can have important consequences for metabolic activity, for example, by restricting communication between the cell and its surroundings. They may also provide protection from predators, inhibit desiccation, screen cells from ultraviolet radiation, and alter the cell buoyancy (e.g., Tebo et al. 1997; Phoenix et al. 2001). The controlled precipitation of nanoscale minerals can lead to formation of integrated organic-inorganic structures with diverse morphologies. In some cases, the shapes provide a record of past microbial activity (i.e., serve as biosignatures, possibly by preserving cell 1529-6466/05/0059-0006505.00

DOI: 10.2138/rmg.2005.59.6

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Figure 1. Microorganisms can produce copious quantities of nanoparticles. a). Field-emission scanning electron microscopy (SEM) micrograph of spherical aggregates of ZnS nanoparticles (with trace amounts of Fe, As, and Se) in a sulfate-reducing bacteria dominated biofilm growing on wood in neutralized acidmine drainage (Moreau et al. 2003). Draped over the aggregates is a dehydrated filamentous microbial cell of a morphology commonly observed in ZnS-dense regions within the biofilm. Image courtesy of John Moreau. b). High-resolution SEM image of a fractured sulfate reducing bacterium encrusted in aggregates of compositionally mixed ZnS and FeS nanoparticles (Williams et al. 2005). Inset: Higher magnification view of biomineral coating around a fracture cell. Images courtesy of Ken Williams, c). SEM micrograph of iron oxyhydroxide nanoparticle coatings on microbial structures from biofilms from the Piquette Mine, Tennyson, WI. The twisted stalks and cylindrical sheaths are characteristic products of GaUioneUa ferruginea (an iron oxidizer) and Leptothrix spp. (a putative iron oxidizer), respectively. Image courtesy of Susan Welch and Clara Chan. d). Transmission electron micrograph of aggregated U 0 2 nanoparticles adhering to the surfaces of sulfate reducing bacteria taken from the Midnite Mine, Washington, U S A (Suzuki et al. 2002). Image courtesy ofYohey Suzuki.

morphology, as seen in the iron oxyhydroxide nanoparticle coatings on extracellular sheaths of Leptothrix, Fig. 1). Biominerals constructed from nanoparticles can be generated through deliberate action of the organism in order to create cell architecture (Mann 2000), and magnetic nanoparticles can serve a role in navigation (Bazylinski and Frankel 2004). However, in many cases the function is unclear or the particles may serve no function, and their existence is purely a byproduct of microbial metabolism (e.g., ZnS and U 0 2 nanoparticles, Fig. 1, and Mn(IV) oxides). Binding of nanoparticles to cell surfaces can also affect the fate and distribution of nanoparticles in the environment, by restricting or facilitating their transport, aggregationbased growth, and mineral transformation pathways. The interactions between nanoparticles, individual cells, and extracellular biomolecules can also act to bind biofilms together (Mayers and Beveridge 1989).

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Sources of nanoparticles in the environment A major pathway for nanoparticle formation in aqueous environments is the precipitation of sparingly soluble dissolved ions derived from both inorganic and biological processes. Precipitation is possible when the concentrations of ions in solution exceed the solubility of a mineral (e.g., see De Yoreo and Vekilov 2003). However, formation of a crystal nucleus is inhibited by an energy penalty associated with creation of a solid-liquid interface. Consequently, ion concentrations must generally exceed the saturation state of the solution for precipitation to occur. The relative energy cost associated with this interface is reduced as the particles grow, providing a driving force for coarsening. Materials that form ultra-small particles are frequently very insoluble with low energy barriers for nucleation. Examples include U0 2 , with a solubility product for bulk material l o g i ^ « - 6 0 , which forms 1-3 nm diameter particles (Suzuki et al. 2002; O'Loughlin et al. 2003); and ZnS, with a solubility product of logiTsp « -24, which typically forms 2 - 3 nm diameter particles (Labrenz et al. 2001; Moreau et al. 2004). In fact, a wide range of both natural and synthetic nanoparticles initially forms in this size range. Inorganic sources of environmental nanoparticles. A variety of inorganic pathways can lead to nanoparticle formation. Chemical weathering reactions that occur when minerals in rocks are exposed to water and air at the Earth's surface liberate ions that can reprecipitate as nanometer-scale silicate clay minerals, oxides, oxyhydroxides, and phosphates. Common examples include smectite (e.g., montmorillonite (Na,Ca)(Al,Mg)6(Si4O10)3(OH)6-«H2O), anatase (Ti0 2 ), hematite (a-Fe 2 0 3 ), and rhabdophane (CeP0 4 H 2 0). Aqueous clusters of metal sulfides and aluminum oxide are found in some lake and marine environments (Rozan et al. 2000; Casey and Swaddle 2003). Nanoparticulate minerals may nucleate at sites on another mineral surface (Stack et al. 2004). Additional inorganic sources of nanoparticles include impacts, combustion, vaporization (e.g., breakdown of meteorites as they enter the atmosphere), evaporation of sea spray, erosion, faulting, and other mechanical processes. Biological sources of environmental nanoparticles. Microbial activity is a major source of nanoparticles in the environment, and a summary of biogenic minerals is given by Frankel and Bazylinksi (2003). Central to microbial metabolism is the process of energy generation, which harnesses the free energy liberated as the result of coupled oxidation and reduction reactions. Reactions used for energy generation must be thermodynamically favorable, but are often kinetically inhibited. Organisms utilize enzymes to overcome these barriers and may speed up geochemical reactions by several orders of magnitude. In many cases, minerals can serve as either reductant or oxidant in microbial metabolism. In the presence of reduced organic carbon, oxygen or nitrate often serve as the electron acceptor for microbial carbon respiration. However, electrons can be passed to ferric iron, Mn(III)/IV, or sulfate when oxygen and nitrate are not available (Banfield and Nealson 1997; Konhauser 1998; Edwards et al. 2000; Ehrlich 2002). Uranium ions can also be biologically reduced. In either metabolic or co-metabolic processes (Lovely et al. 1991; Abdelouas et al. 2000; Fredrickson et al. 2000), electrons are passed from organic carbon to aqueous uranyl (U0 2 2+ ) ions, resulting in the formation of insoluble uraninite (U0 2 ) nanoparticles. Ferric iron and manganese minerals that act as electron acceptors are typically fine grained oxides that can dissolve upon reduction (Roden and Zachara 1996; Lovely 1997; Bratina et al. 1998; Quantin et al. 2001). In contrast, for sulfate reduction, aqueous sulfate ions are converted to HS~, which- in the presence of a suitable counter-ion, will precipitate as sulfide nanoparticles. Because reduction of sulfate is quantitatively linked to the oxidation of carbon, these metabolic pathways can generate copious quantities of nanoparticulate sulfides over short time periods (see Fig. la,b).

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In the absence of organic carbon for respiration and light for photosynthesis, both carbon fixation and energy generation can be driven by energy harvested from inorganic chemical reactions alone (Lovely 1993). In such chemoautotrophically based ecosystems, bacteria such as Thiobacillus ferrooxidans oxidize sulfide and/or ferrous iron that is present in pyrite (FeS2) (Fowler et al. 1999). The resulting ferric iron and sulfate ultimately precipitate, often as nanoparticulate iron oxyhydroxide (ferrihydrite or goethite, a-FeOOH) or iron sulfate compounds (schwertmannite, Fe 16 0 16 (0H) ) ,(S04) z -wH20, and others). Anthropogenic nanoparticles. Industrial manufacturing and combustion processes can lead to nanoparticle emission into the air or into wastewater effluent. For example, numerous groups are seeking to manufacture stable water-soluble magnetic iron oxide nanoparticles as an injectable diagnostic agent for enhancing contrast in magnetic resonance imaging (Tartaj et al. 2003). Cerium dioxide nanoparticles are of interest as catalysts during combustion processes (e.g., in automotive engines), because of the capacity of the Ce0 2 lattice to buffer changes in oxygen partial pressures and oxidize carbon monoxide (Bekyarova et al. 1998). These nanoparticles may be released during manufacturing, use, or as the result of product disposal, and could ultimately accumulate in the environment in high enough concentrations to have important ecosystem impacts, such as accumulation in and toxicity for aquatic organisms (Oberdorster et al. 2005). Impacts of nanoparticles on their surroundings The formation of nanoparticles can influence the local chemical environment in which organisms live. Nanoparticles sequester ions when they precipitate, and can decrease or increase the porosity and permeability of sediments. For example, formation of sulfide nanoparticles removes both metal ions (e.g., Cu, Zn, As, Cd, Fe) and toxic sulfide ions from solution, improving habitability of the environment. Nanoparticle precipitation and dissolution reactions can be sources or sinks for protons, and thus can influence environmental mineralogy through the impact of pH on mineral solubility (Langmuir 1996). For example, the precipitation of iron oxyhydroxide nanoparticles and dissolution of sulfide nanoparticles both lead to environmental acidification, promoting dissolution of surrounding minerals. The solubilization of manganese oxides may liberate adsorbed trace metals that provide nutrients in oligotrophic environments (Bratina et al. 1998). Nanoparticles, with their high surface areas, can play especially important roles in adsorption. For example, nanoparticles of iron oxyhydroxide formed during the neutralization of acidic, ferrous iron-rich solutions can sorb phosphate ions, possibly limiting biological productivity in some environments. Nanoparticle surfaces can also sequester protons or toxic ions such as arsenate (Waychunas et al. 2005). Nanoparticles—special properties and implications Recently, a great deal of research has shown that nanoscale inorganic solids may exhibit substantially modified properties relative to their bulk counterparts (Alivisatos 1996; Murray et al. 2000; Trindade et al. 2001), with consequences for the inorganic and biological interactions of nanoparticles in the environment. As a foundation for studies of coupled geochemical processes involving nanoparticles, we examine some principles describing how size influences nanoparticle properties and reactivity. The present chapter introduces the physical and chemical consequences of small particle size in minerals, and discusses the effect small particle size has on redox and photochemical reactions. The concepts introduced here can be used for understanding the environmental impact and fate of both natural and engineered nanoscale materials.

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Overview of small size effects in minerals While molecular geochemistry has always been a "nano-science," the science of nanoscale clusters and nanoparticles is distinct in an important way. The motivating tenet of contemporary nanoscience is that the chemical and physical properties of a solid inorganic material may vary as a function of particle dimensions below a critical size. The definition of the critical size depends both upon the material under consideration and the property of interest. It may refer to the start of a size dependent trend, such the onset of electronic confinement, or to an abrupt change, such as a switch in the thermodynamically stable structure of a mineral. We stress that, in almost all cases, the description of the unmodified (i.e., bulk) material provides an excellent guide to the properties of a nanosized material (even below a critical size). Thus, knowledge of the relevant solid state physics and chemistry for a given mineral is an indispensable foundation for understanding small-size effects. We emphasize, however, that important small size effects are not limited to modifications of nanoparticle structure and properties alone, which we denote as static effects. Static small-size effects in mineral particles include the stabilization of structural phases that are metastable for bulk materials, and the presence elevated strain and disorder, particularly at nanoparticle surfaces. Electrons within solids respond to shifts in the equilibrium positions of atoms, surface-solvent interactions, and the presence of a confining surface itself. The latter effect—quantum confinement—is striking in some materials, but (when present) is neither the only, nor always the dominant, size effect in mineral nanoparticles. A large number of surface effects (e.g., confinement, surface charge, solvent interactions, and surface reconstruction) modulate electronic structure. The kinetics of charge, energy, and material transfer also change at the nanoscale. Geochemical processes are dynamic, and significant size-dependent changes in reaction kinetics may affect processes in natural systems. The impact of nanoparticles on biogeochemical processes can depend on the kinetics of competing pathways. For example, the ability of photoexcited electrons in nanoparticles to reduce biomolecules is governed by the rates of several size-dependent processes that may enhance reactivity or dissipate energy without reaction. Furthermore, the products of various (photo)reduction experiments can be different for nano- versus micron-sized particles, indicating a size effect on reaction pathways (Müller et al. 1997). We start by discussing small-size effects in individual particles. However, nanoparticles are frequently observed to be intimately aggregated, with significant consequences for their behavior in biogeochemical systems.

PHYSICAL STRUCTURE AND COMPOSITION OF NANOSCALE MINERALS Thermodynamic constraints on the structure of nanoparticles One of the better-understood ways that size can influence the structure of nanomaterials is through interfacial energy effects on phase stability. This topic was reviewed in detail by Banfield and Zhang (2002) and Navrotsky (2002). In brief, when a compound can exist in more than one structural form (polymorph), a change in the relative stabilities of the structural variants may occur as the consequence of differences in their surface energies. This effect is only likely at small particle sizes, for which surface areas are large. For example, sizedependent phase stability may explain the precipitation of the hexagonal polymorph of ZnS (wurtzite) in place of the cubic form (sphalerite) in sediments or aqueous solutions, despite the

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higher stability of sphalerite compared to wurtzite in bulk materials up to temperatures over 1000 °C (Scott and Barnes 1972; Qadri et al. 1999; Zhang 2003). However, it should be noted that kinetic effects may also lead to the production of metastable phases (amorphous or highly disordered materials), especially in low-temperature systems where precipitation rates are fast (Schwertmann et al. 1999; Wolthers et al. 2003). It can be difficult to assess whether an observed nanophase is thermodynamically stable or metastable. It can also be difficult to evaluate the structure and natural abundance of amorphous or highly disordered materials. The nature of the initial precipitates and subsequent aging For many minerals formed at low temperature or by biological processes, the initial precipitates are reported to be amorphous or highly disordered, possibly hydrated nanoparticles. Examples include amorphous iron sulfides, hydrous ferric oxide (HFO), and layered Mn(IV) oxides. These initial materials themselves do not grow beyond the nanoscale, and instead undergo crystallization, dehydration, or other transformations to mineral phases that may subsequently grow. It is widely thought that extracellular bacterial surfaces provide sites for heterogeneous nucleation that lower the free energy barrier for precipitation (Fortin et al. 1997; Warren and Ferris 1998). This model is widely used to describe the precipitation of ferric iron as a result of the activity of iron oxidizing bacteria (Douglas and Beveridge 1998; Ferris 2005). The model is challenged, however, by a recent study of Rancourt et al. (2005), on the precipitation of HFO in the presence of nonmetabolizing bacteria. They showed that while Fe(III) ions adsorb onto functional groups on bacterial surfaces, they remain external to the structure of HFO particles that subsequently form. Rancourt et al. argue convincingly that both inorganic and biological HFO formation always occurs via fast homogeneous precipitation. There is also uncertainty as to the role of biological factors in affecting transformations that occur in nanoparticles after precipitation. While aqueous conditions (solution chemistry, pH, temperature), rather than their inorganic or biological origins, should govern the evolution of mineral precipitates (Konhauser 1998), comparative studies of the structure and reactivity of biominerals versus synthetic analogs frequently reveal differences. The presence of organic matter is thought to be a crucial factor (Ferris 2005). Furthermore, microbial metabolism frequently generates aqueous ions (e.g., Fe(II), or small organic molecules) that can interact with and stabilize or destabilize mineral surfaces during growth, phase transformation, and dissolution (Cornell and Schwertmann 1979; Urrutia et al. 1999; Davis et al. 2000; Thomas et al. 2004). One interesting biological effect is the observation that the association of 2-line ferrihydrite nanoparticles with bacterial cell walls confers significant stability to the mineral against hydrothermal coarsening and transformation into hematite (Kennedy et al. 2004). The stabilization effect is observed with both biogenic and abiotic ferrihydrite in the presence of bacteria. It is inferred that the nanoparticles principally grow by an aggregation-based pathway that is hindered when the particles are immobilized on cell walls. Orientated aggregation (OA) is a significant pathway for nanoparticle growth in which individual particles achieve a common crystallographic orientation (Penn and Banfield 1998). Subsequent elimination of the interfaces between oriented particles can generate larger single crystals, some of which may have unusual morphologies and properties (Banfield et al. 2000). An example of joined U 0 2 nanoparticles is given in Figure 4. Size dependence of mineral solubility From the point of view of biogeochemical systems, one of the most important sizedependent materials properties is solubility. As can be seen from the following equation

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(Stumm and Morgan 1996), solubility increases as particle size decreases because the interfacial energy, y, in J m~2, is a positive contribution to the total energy. iog
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'C J5 "6 • , and Faraday's constant, F. The relation between the chemical potential, and the activity of ion i is given in many textbooks (Lyklema 2001). The electrochemical potential for the electron in Equation (9) is defined as the difference in the values for the oxidized and reduced species, ixeredox = JxRed - p 0 t . (Memming 2001). The electrolyte Fermi energy, EKredox (in eV), is then related to jJc ^ (in J mol -1 ), by e ^F,redox ¡ < ^ r.rtrUr. For the solid phase and aqueous phase Fermi level concepts to be directly comparable, they must be expressed in the same units on the same energy scale, typically in eV on the absolute vacuum scale (AVS). The redox potential associated with a half reaction such as

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Equation (9) is usually expressed in V relative to the normal hydrogen electrode (NHE) or other electrode. As discussed by Xu and Schoonen (2000), the energy of an electron in an energy band can be converted to the associated redox potential by the relation £ ( N H E , V) = -E(AVS, eV) - 4.5

(12)

At equilibrium, EF = EKredox, which requires charge redistribution. Electrons flow into the solution from the material and change the concentration of redox species if EF > EKredox, and vice versa. This changes the potential at the interface, lowering the free-energy difference due to the term ZjFfy in Equation (10) until equilibrium is attained. The VB and CB states at the interface are affected by the local potential, a phenomenon called band bending, as depicted in Figure 10. Energy levels further from the interface than the Debye length, LD, are shielded from the effect of the interfacial potential because of the dielectric properties of the solid. LD is typically greater than 100 A, depending on the density of charge carriers. Thus, surface charges are not well screened in particles of dimensions smaller than this, and the electronic bands are flat (but shifted) throughout a nanoparticle, as illustrated in Figure 10. This depiction assumes that the kinetics of the redox couple are fast, but it is well known that many environmental systems are far from thermodynamic equilibrium (Schilling et al. 2000). Electric double layer. The distribution of aqueous ions near the surface of a mineral in water is affected by the presence of an electrostatic potential at this interface. Such surface

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•^F.redox

J

Figure 10. Semiconductor particles immersed in water reach equilibrium by donating or accepting electrons from solution until the electronic electrochemical potential (the Fermi level) is constant throughout. The Fermi level in the solution is determined by the redox couple(s) in solution. In micrometerscale particles, the change in local charge carrier density causes shifts in VB and CB energy levels (band bending) over a space charge region, dsc. The direction of band bending depends on whether holes (p-type) or electrons (n-type) are the dominant charge carriers (the results for an n-type semiconductor are shown). For nanometer-scale particles of diameter d < d s c the electronic bands inside the entire particle are shifted. The positions of the nanoparticle CB and VB are shown shifted both due to surface charging (which lifts the CB and VB energy positions) and by quantum confinement (which increases the CB-VB separation). After Memming 2001.

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potentials can be created by equalization of the Fermi levels in the solid and the electrolyte (as described above) and by the chemisorption of charged solution species to the mineral surface. For a given mineral surface, strongly interacting charged species are called potential determining ions (PDI) (Lyklema 2001). For example, H + and OH~ are PDI for metal oxides, while HS~ can be a PDI for sulfide minerals (Bebie et al. 1998). The pH driven shifts in oxide band energies are quantitatively described by the Nernstian relation that predicts a shift of 0.059 V/pH at 25 °C and 1 atmosphere pressure. However, there are apparently no experimental tests of this relation for nanoscale particles. Similarly, although nanoparticles (and colloids in general) act as ready sorbents for inorganic and organic ions and molecules, the effects of different sorbates on band positions are generally not known. The adsorption of redox active solution species seldom affects the energy band positions.

REDOX BEHAVIOR OF NANOPARTICLES Having completed a brief review of the factors that affect the energies of electronic bands in solids, we are now able to apply this knowledge to the (photo)chemical reactions of nanoparticles. The fundamental reactions in which nanoparticles can participate are depicted in Figure 11. Size effects on nanoparticle redox behavior The modification of the absolute valence and conduction-band energy levels is a predominant effect on redox behavior when it occurs. As discussed above, doping of a semiconductor, sorption of potential determining ions, and finite particle size may all contribute to such effects. Examples of size effects on redox potential. As shown by Bras (1984), and reproduced in Figure 8a, finite size effects can have a large impact on the redox potentials of semiconductors (see also Franschetti et al. 2000). However, the extent to which valence electrons are delocalized and hence susceptible to finite size effects is unclear for several environmentally

RFDOX REACTIONS

^ ^ Oxidation of a donor

PHOTOCHEMICAL REACTIONS

C)

Photocxcitalion of a ianoparticte

V

PhnldiL'iJuHLin (ifan acceptor A A

•

[ Reduction Of an acceptor d ) Pholooxidaiion of a donor

CHARGE & ENERGY TRANSFER

g)

••

• A

Photorcduciion of an acceptor ' / by a sensitized nanoparltcSe ¿.J*

Electron transfer between nanoparticles

s

h)

Non-resonant cxciton transfer between nanoparticles

.

¿i • •A

• « A —K-.

t A-

• •

• •

Figure 11. Scheme of the possible redox, photochemical and charge or energy transfer reactions that can take place at the surfaces of semiconductor mineral nanoparticles. D = electron donor (or reductant); A = acceptor (or oxidant); S = surface adsorbed sensitizing ligand; V B = valence band; C B = conduction band; Eg = band gap. ( • + ) represents a negatively (positively) charged nanoparticle; • * represents a nanoparticle containing a photoexcited electron-hole pair.

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relevant materials. For example, sphalerite (ZnS) and pyrite (FeS2) are, respectively, direct and indirect delocalized electron semiconductors in which quantum confinement effects will occur. Figure 8b plots the size-dependent shifts in the VB and CB levels for these materials predicted by the EMA. It is presently difficult to anticipate quantum confinement effects in environmental iron and manganese compounds for which electron and hole effective masses have not been tabulated. Nevertheless, a recent X-ray spectroscopic study identified an increase in the band gap of hematite nanorods ~ 4 nm in diameter by approximately 0.3 eV (Guo 2005). UV-vis spectroscopy of encapsulated iron oxide nanoparticles also indicated size-dependent bandgap opening (Iwamato et al. 2000). In common with most iron (III) and manganese (IV) (oxyhydr)oxide minerals, the conduction and upper valence bands have the character of cation ¿-states, while the lower valence band is principally composed of oxygen p-like orbitals, although covalency in the metal-oxygen bond causes mixing in the valence band states (Cox 1992; Sherman 1984,1985,2005). In Figure 8b, we predict the size dependence of the hematite band gap using an estimate for the effective masses of charge carriers (assuming m* = mh*) consistent with the observations of Guo (2005). Band-gap opening, as depicted in Figure 8, will significantly affect mineral reactivity (Rodriguez et al. 1998). The predictions of Figure 8 require further experimental testing, particularly the use of combined X-ray absorption and emission spectroscopic measurements of nanoparticle band gaps (Liming et al. 1999; Sherman 2005), and more sophisticated theoretical treatments (O'Connor and Sposito 2005). A complementary approach for understanding the electronic properties of mineral nanoparticles will be studies of the kinetics of surface reactions. Kinetics studies have been used to determine the relative reactivities of different iron minerals to surface redox or complexation reactions (Hering and Stumm 1990; Eisner et al. 2004; Poulton et al. 2004; Peak 2005). Such studies provide a method for determining size-dependent changes in surface reactivity (see below; Madden and Hochella 2005). The roles of surface states. Atoms at the surface of a material are not generally able to attain the same coordination environment that is present within the interior. Thus, atomic sites at a surface may exhibit modified local electronic structure that in some cases can introduce energy levels within the band gap of a semiconductor or insulator (Morrison 1980). Surface states can therefore have the same effect as interior impurity atoms, either facilitating the creation of mobile electron or hole charge carriers or acting as traps for them. For example, underbonded surface anions can donate electrons into the CB of the mineral (cf. Fig. 16). Surface states can also mediate the transfer of charge between an adsorbate and states within a mineral or between two aqueous or adsorbed reagents. In addition, the trapping of electrons at surface states can affect the lifetime of photoexcited electrons and holes, and can determine the rate of electron transfer between neighboring particles (see below). The above phenomena occur at the surfaces of both bulk minerals and nanoparticles. The surfaces of nanoparticles are structurally more diverse, and molecular simulations indicate that inhomogeneous charge distributions can occur at nanoparticle surface and edge sites, modifying the surface Lewis acid or base characteristics relative to large particles (Lucas et al. 2001; Noguera et al. 2002; Rustad and Felmy 2005). Scanning tunneling spectroscopy (Preisinger et al. 2005) and optical luminescence spectroscopy (Chen et al. 1997) are approaches for detecting surface states that lie in the electronic band gap. However, environmental nanoparticles and their synthetic analogs are poorly studied. Undercoordinated surface sites tend to be more reactive and hence are frequently the sites at which molecules bind to nanoparticle surfaces. In place of the initial surface states, new

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surface-ligand molecular orbitals are formed, with discrete energy levels that may no longer reside within the band gap. While ligand binding has been extensively studied for the removal of mid-gap states in engineered nanoparticles (e.g., Green and O'Brien, 1999), ligand binding can also create (photo)redox active mid-gap energy states (e.g., Rajh et al. 2002) Examples of nanoparticle redox behavior Nanoparticles as molecular-tike redox active solution species. Nanoparticles can accept or donate electronic charge, and in this sense can be considered redox active species. Figure 12 shows that CdS nanoparticles can diffuse to, and react with an electrode in an electrochemical cell in a manner similar to an aqueous ion (Kukur et al. 2003). The potential at which the nanoparticles can be reduced (i.e., charged by a single electron) varies with particle size in agreement with confinement effects. However, even for nonaggregated nanoparticles, diffusion rates are considerably slower than dissolved ions or molecules (Scholz and Meyer 1998). The Brownian diffusion rate for nanoparticle transport is given by the Stokes-Einstein equation: D=

k T

6nr\r

(13)

where r| is the solution viscosity, and r is the particle radius. The implication of the results of Figure 12 is that nanoparticles are available to participate in molecular redox reactions with aqueous ions and biomolecules. Below, we discuss the important issue of the stability of individual nanoparticles during (photo)redox reactions. The example above is one of a number of experimental investigations of the charging of nanoparticles that was conducted at electrochemical electrode (Haram et al. 2001; Kukur et al. 2003; McKenzie and Marken 2001). In nature, redox active solution species can inject electrons into the conduction band of a mineral, provided that the redox potential of the aqueous redox reaction is more negative than the position of the CB minimum. For example, Cd(II) and Co(II) can be oxidized on the surface of ZnO and manganese (IV) oxides, respectively (Murray and Dillard 1979; Manceau et al. 1997). In the opposite direction, electrons may transfer from the mineral VB to a strongly oxidizing organic species such as ascorbic acid, which can cause the direct oxidation of manganese oxide minerals (Stone and Morgan 1984; Stumm and Morgan 1996). A negatively charged nanoparticle is free to act as a reductant with a suitable acceptor species. If further charge transfer to the nanoparticle carries an energy penalty (see below),

•e IS

0L5

1.0

Evs. AgjAgN03(V)

Figure 12. Semiconductor nanoparticles exhibit molecular-like redox behavior with size-dependent redox potentials. Electrochemical oxidation of a solution of CdSe nanoparticles in acetonitrile at a gold electrode shows a clear trend with increasing particle size (a to d). The position of the oxidation peak (Ep) indicates the valence band maximum and the trend is in quantitative agreement with an effective mass approximation calculation of electronic confinement energies, a = 3.23 nm diameter; è = 3.48nm; c = 3.73nm; D+A"

(14)

where X > D represents donor species D adsorbed onto a nanoparticle. Alternatively: D < X H> D + (aq) + [X]

(15a)

[X]" + A(aq) —> X > A"

(15b)

For electron transfer reactions, the donor (or acceptor) species and the nanoparticle must (1) have a redox potential that coincides with electron energy bands in the minerals, and (2) attain sufficient wavefunction overlap with these bands (Huber et al. 2000). Many singleelectron transfer reactions can occur via electron tunneling to or from species bound to the surface by outer-shell adsorption. However, ligand-particle electron transfer rates are greatly enhanced by surface complexation (Moser et al. 1991); and certain charge transfer reactions, particularly involving Fe ¿-electron states, require inner-sphere surface coordination to proceed at all (e.g., Ennaoui and Tributsch 1986). The possibility of multiple oxidation states of nanoparticles. The energy required to singly charge a solvated nanoparticle (Fig. 11a) is sensitive to both the nanoparticle size and the dielectric constant of the solvent (Franceschetti et al. 2000). The addition of subsequent electrons to an already charged nanoparticle is possible, but additional energy may be required to compensate for Coulomb repulsion if there is electronic overlap between CB electrons (Brus 1984). In this case, nanoparticles can behave more like atoms with variable redox states (Banin et al. 1999), than bulk minerals within which excess charges may diffuse apart. Atomic-like redox behavior would lead to a quenching of bioreductive processes involving nanoparticles, because the successive charging energies would eventually exceed the reducing power of extracellular electron shuttle molecules. However, this is not observed for the biological reduction of ferric iron minerals, since phases with higher surface areas (i.e., smaller particle size) are more completely reduced (Roden and Zachara 1996; Hansel et al. 2004). For minerals composed of atoms susceptible to valence changes, mineral dissolution is an effective pathway for shedding excess charge. Furthermore, in the small polaron model of charge transport in localized carrier materials, an additional electron at an iron site is spatially localized within a radius less than the near-neighbor bond length (Cox 1992). This implies that interactions between multiple ferrous iron sites will be weak, and that the energy required to add an electron to a ferric iron nanoparticle will not depend on the number of excess electrons already hosted, in contrast to the behavior of delocalized band semiconductors. Reductive transformation of halogenated organic contaminants. Many relevant investigations have been motivated by the desire to identify natural pathways for immobilizing or transforming organic or inorganic contaminants. For example, Fe(II) adsorbed to the surface of ferric iron and non-iron-containing minerals can be a powerful reductant, one that can transform hazardous chlorinated hydrocarbons such as carbon tetrachloride (CT) (Pecher et al. 2002; Eisner et al. 2004) and chromate (Wielinga et al. 2001). Mineral surfaces that stabilize the Fe(III) product of the oxidation of surface-bound Fe(II) can lower the Fe(II)Fe(III) redox potential (Stumm and Morgan 1996; Amonette et al. 2000; Pecher et al. 2002). Structural Fe(II) in mixed-valence iron oxide compounds such as magnetite, particularly biogenic magnetite nanoparticles, can also transform CT. As shown by Figure 13, numerous electron shuttle molecules used by anaerobic DFeRB also possess reduction potentials that can degrade CT, and co-metabolic pathways

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Gilbert & Banfield Microblal

«•donors

Respiration components

Iron respiration (m&tabolism) E0' (mV)

Chlorinated methanes

I CCI, / CMC I] (>673) CHClj/CHjCI, (•»©) . CH,CI, / C HjCl (+494) CH3CII CM4 (+-457)

F^OH),/ F«*p (4*) B lotie (co-maiabodism)

C:

c _ t

HCOj' f CHjCOO' (-300) e- M mi>crot>l*l r carrier» HCOj / CHjCHOHCOO' (-3«0> H-/H,(-414) I Figure 13. Structural Fe(II) in biogenic magnetite nanoparticles (shown in TEM image, left) is a potent reductant of halogenated organic solvents. Although the redox potentials of common biological electron shuttle molecules are also sufficient to drive the reduction of carbon tetrachloride (right), the mineral nanoparticle driven process is almost 100 times more effective. [Used by permission of the American Chemical Society, from McCormick et al. (2002), Environmental Science and Technology, Vol. 36, Figs. 1 & 4, p. 403-410.]

do contribute to the natural attenuation of this compound. However, in laboratory studies, biogenic magnetite is approximately two orders of magnitude more effective than biomolecular pathways (McCormick et al. 2002; McCormick and Adriaens 2004). Nanoscale magnetite also reduces U(VI) to U(IV) under anaerobic conditions (following surface adsorption) much more rapidly than occurs in solution under reducing conditions (Missana et al. 2003). Surface-promoted redox reactions. Bulk mineral surfaces can mediate charge transfer between solution species that otherwise interact too weakly for effective redox pathways. For example, sulfide minerals—including pyrite, galena, and several doped sphalerite minerals— catalyze the oxidation of thiosulfate to tetrathionate by dissolved molecular oxygen (Xu and Schoonen 1995). A significant nanosize effect was recently observed for hematite-promoted Mn oxidation (Madden and Hochella 2005). While the oxidation of aqueous Mn(II) by oxygen is very slow at pH < ~8.5, it may be promoted following adsorption to mineral surfaces. Surface hydroxyl groups (denoted >OH) mediate electron transfer from molecular oxygen to adsorbed manganese, facilitating the reaction: Mn 2 + +

+ ^H20

>oh

)Mn(III)OOH + 2H +

(16)

As shown in Figure 14, the kinetics of this reaction, normalized to surface area, exhibit an increase of more than one order of magnitude for 7 nm diameter hematite nanoparticles compared with 37 nm particles. Madden and Hochella (2005) discuss the possible origins of this striking enhancement of reactivity. Hematite energy bands do not play a direct role in this process; hence, electronic confinement effects are unlikely to be responsible. Possible explanations of the rate enhancement may be understood from Marcus's original description of the rate of electron transfer (Marcus 1993). By setting AG* = (AG° + X)2/4X in Equation (5),

ket = kv exp

4

UbT

(17)

where AG° is the standard free energy of the reaction (positive or negative) and X is the reorganization energy (always positive). Size-dependent changes in either AG° or X are plausible and would modify the reaction kinetics, provided that electron transfer is the rate-limiting step.

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137

28.5 28.0 c - 27.5 27.0

26.D 25.5 7.0

7.2

7.4

7.6

7.8

8,0

pH Figure 14. The rate of heterogeneous oxidation of Mn(II) promoted by 7 nm and 37 nm diameter hematite nanoparticles. The smaller hematite nanoparticles promote oxidation at a rate that is almost two orders of magnitude larger than the larger particles. [Reprinted with permission of Elsevier, from Madden and Hochella (2005) Geochimica et Cosmochimica Acta, Vol. 69. Fig. 5, p. 389-398.]

For example, it is likely that the redox potential of Mn(II) adsorbed to the smaller particles is shifted because of a size-dependent modification in the Lewis base character of oxygen atoms on the surface of the hematite to which Mn adsorbs (Noguera et al. 2002, Lewis et al. 2001). If this drives the AG° of Reaction (16) more negative, Mn oxidation would not only be more favorable, but ket would increase. Alternatively, small particles may exhibit a higher density of surface sites at which the coordination geometry of adsorbed ions is distorted from the perfectly octahedral configuration preferred by Mn(II). However, Mn(III) complexes tend to prefer a distorted octahedral coordination. Therefore, if the smaller nanoparticles possess greater surface disorder, less structural reorganization may be necessary for the reaction to proceed. This effect would reduce X, thereby increasing ket The results of Madden and Hochella (2005) demonstrate that the redistribution of both charge and atoms at the surfaces of nanoparticles may strongly influence their reactivity. EXAFS investigations into changes in the coordination environment of Mn(II) bound to hematite nanoparticles in the absence of oxygen may help evaluate these two models.

PHOTOCHEMISTRY A photon of energy greater than the band gap can excite a valence electron to the CB, which leaves a vacant orbital (hole) in the VB. The excited electron (hole) has the ability to reduce (oxidize) chemical species at the surface of the nanoparticle. As with redox chemistry, the ability to do this depends on the absolute electron or hole energy, and hence can be affected by particle size (and pH), as described above. Size effects on nanoparticle photochemistry Kinetics of recombination and reaction. Following photoexcitation of a nanoparticle, several processes can occur that facilitate or prevent reaction, and these processes may exhibit distinct small-size effects (Gratzel and Frank 1982; Gerischer 1993). Diffusion of an excited electron or hole to the surface and transfer to surface species competes with the recombination of the electron-hole pair and trapping at surface states (Zhang 2000). The transit time to the surface varies as the square of the particle radius, and is generally less than 1 ps for few-nm

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diameter particles (Gratzel and Frank 1982; Huber et al. 2000). The recombination time is principally material dependent, with a weak size dependence caused by enhanced electronhole overlap. Since the recombination time is generally in the range 0.1-1 ns, exited electrons have a far greater probability of reaching the surface of nanoparticles than larger colloidal particles, such as >100 nm diameter iron oxide colloids, in which most electron-hole pairs recombine before reaching the surface (Leland and Bard 1987). Nanoparticle surface states can act as traps for excited electrons with lifetimes that may vary by many orders of magnitude for different nanoparticles. If a photoexcited electron or hole is scavenged by a solution or surface species, recombination within the nanoparticle is no longer possible, and the nanoparticle can remain excited for a considerable time (e.g., minutes) (Leland and Bard 1987). Because both a hole and electron are created following light absorption, both cathodic (i.e., reduction) and anodic (i.e., oxidation) reactions are possible at a nanoparticle surface and may proceed in very close proximity. The kinetics of these reactions are seldom equivalent, providing an opportunity for reaction intermediates to interact. Several studies have concluded that competition between the above processes, plus variation in surface area:volume ratio, leads to an optimum particle size for the maximum efficiency of a given photoreaction that is frequently in the 5-20 nm diameter range (Wang et al. 1997; Almquist and Biswas 2002). Reactions requiring multiphoton absorption. The probability of a photoexcited nanoparticle absorbing a second photon declines with particle size for statistical reasons (Wang et al. 2003), and hence reactions requiring rapid multielectron transfer are highly unlikely for nanoscale particles under environmentally relevant illumination conditions. For example, the products of the photooxidation of ethanol are different for micron-sized versus nanometer-sized ZnS colloids (Miiller et al. 1997). Under constant illumination, transfer of two photoexcited holes to adsorbed ethanol can occur readily within 200 ns on the surface of the larger particles. By contrast, the mean time to create two holes in a nanoparticle reaches several seconds, permitting partially oxidized ethanol radicals to diffuse into solution and form more complex organic species. Shifts in electronic band energy positions. The effect of particle size on the photoredox activity of nanoparticles can be illustrated through analogy, with the effect of pH on the photoreduction of methylviologen ions (MV2+) at the surface of colloidal Ti0 2 particles (Duongdong et al. 1982). The half-reaction, MV + MV 2+ + e~, has the redox potential E0 = -440 mV versus NHE that is independent of pH. By contrast, the electrochemical potential of the Ti0 2 CB varies with pH as ECB (Ti0 2 ) = ECB (Ti0 2 , pH 0) - 0.059(pH) V (vs. NHE)

(18)

As shown in Figure 15, photoexcited electrons in the CB are sufficiently reducing only above pH around 4-5. Photoreduction of MV 2+ is thermodynamically forbidden below this pH threshold. As shown below, for materials that exhibit size-dependent shifts in CB position, thresholds in particle size can exist below which photoredox reactions are enabled. For completeness, it should be recalled that changes in pH can strongly affect the affinity of ionic sorbates to surface binding sites, particularly around the point of zero surface charge (pHzpc) for a material (Kormann et al. 1991). Such effects can complement or compete with shifts of the nominal redox potentials of CB electrons and VB holes. Nanoparticle interactions with biomolecules It is clear from the study of environmental colloids that mineral surfaces can exhibit high affinities for organic molecules (Yariv and Cross 1979; Amal et al. 1992; Tiller and O'Melia 1993), and many groups have demonstrated effective surface binding of molecules to sulfide

Molecular-Scale a)'

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r^V

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630 635 640 645 650 655 660 665 670

700

705

710

715

720

725

730

photon energy (eV)

photon energy (eV)

Figure 5. (A) Manganese L-edge X-ray absorption near edge structure (XANES) spectra of manganese oxides. The formal M n oxidation states are given on the right. (Data f r o m Gilbert et al. 2003a). (B) Iron L-edge X A N E S spectra f r o m ferric (III), ferrous (II) and metallic iron (0), in the minerals and metal indicated. (Data f r o m Frazer et al. 2005)

B Ca L edge

S L edge

eo «c CI T3 CJ N

15 E

342

344

346

348

350

photon energy (eV)

352

354

150 155 160 165 170 175 180 185 190 photon energy (eV)

Figure 6. (A) C a L-edge X A N E S spectra f r o m calcite and aragonite, trigonal-rhombohedral and orthorhombic polymorphs of CaCO,, respectively. The two main peaks, c o m m o n to both spectra are the L , and L 2 edges, respectively. Two additional peaks at ~346 and ~350 eV (arrows), due to the crystal field, are prominent in calcite but have lower intensity and different line shape in aragonite. (B) X A N E S sulfur L-edge spectra f r o m sphalerite and wurtzite, cubic and hexagonal polymorphs of ZnS, respectively. Notice the difference in line shape between 165 and 170 eV. Used with permission of the American Chemical Society, f r o m Gilbert et al. (2003), J. Phys. Client. A, Vol. 107, Fig. 1, p. 2839-2847.

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Interface in

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materials (Bozek et al. 1990), elemental speciation in soils and sediments (Myneni et al. 1997; Beauchemin et al. 2003; Zawislanski et al. 2003) and other environmentally relevant samples (Myneni 2002a,b; Myneni et al. 1999). Many other experiments on the microlocalization of trace elements in eukaryotic cells (De Stasio et al. 1993, 1996, 2001; Gilbert et al. 2000) and the identification of prokaryotic biomineral products (Labrenz et al. 2000; Lawrence et al. 2003; Lopez-Garcia 2003; Chan et al. 2004), also attest to the power and breadth of XANES spectroscopy and spectromicroscopy. As mentioned, the lineshape of XANES spectra gives information on the molecular and/ or crystal structures surrounding the element under analysis. The interpretation of spectral lineshape and peak assignment, however, can be complicated. When the molecular or crystal structure is known, and relatively simple, ab initio calculations can be used to simulate the XANES spectrum. A comparison of experimental and calculated spectra enables peak assignment to specific molecular structures. Specific peaks can be considered "spectral signatures" of specific molecular features. XANES is extremely sensitive to carbon chemistry: examples of molecular features that generate well-established spectral signatures are C=C, C=C, C-O, C=0, C-O, as well as C - C - C bond angles, conjugation of adjacent bonds, etc. A material that contains several of these molecular features exhibits a XANES spectrum resulting from the combination of their corresponding spectral signatures: the "building blocks" (Stohr 1992). For other edges, e.g., Si or S at the L-edge, simulations of XANES spectra are not currently adequate because the electronic structure is too complex to be calculated. In these cases, the spectral signatures do exist and are measurable, but they are not univocally assigned to specific bonds or molecular structures. Unknown minerals, however, such as sub-micron silicate inclusions, can still be identified by empirical comparison with spectra from known, macroscopic, reference silicate minerals (De Stasio et al. 2003; Gilbert et al. 2003b). XANES microscopy of biominerals XANES spectroscopy has been used to study the same kind of molecular interactions discussed hereafter, but without spatial resolution. Examples include organic-mineral interaction at the binding sites in metalloproteins (Benfatto et al. 2003) or between metal ion and humic macromolecules (Myneni et al. 1999; 2002a). There are practical reasons that, until recently, completely precluded the spectromicroscopy of biomineralized structures, as described below first from a spectroscopy, then from a microscopy point of view. XANES spectroscopy can be performed in two ways: by detecting either fluorescence photons or photoemission electrons (photoelectrons) from a solid sample surface. Fluorescence XANES signal is most intense for high Z elements (Z > 30). These elements have their core shell electrons at binding energies much greater than 1000 eV, therefore the corresponding absorption edges detectable by XANES spectroscopy can only be detected in the "hard-X-ray" regime. On the contrary, low Z elements, which include all the organic elements C, N and O, have their absorption edges below 1000 eV: the C K-edge is at 285 eV, the N K-edge at 400 eV, and the O K-edge at 531 eV. Since none of these edges is easily accessible to the hard-Xray fluorescence range, the organic components of biominerals have never before been studied with fluorescence XANES. Photoelectron XANES, also known as total electron yield or TEY-XANES, is much more intense than fluorescence below 1 keV, where the Si, P, S, and Ca L-edges, and the C, N and O K-edges are located. In this spectral region, a strongly space-averaged TEY spectroscopy

166

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has always been possible on an insulating biomineral. This is, however, not particularly informative, given the highly organized microscopic structure of biominerals. Spectromicroscopy with X-ray PhotoElectron Emission Spectromicroscope (X-PEEM) adds spatial resolution to the TEY-XANES experiment, down to the 10 nm level (Frazer et al. 2004). Until recently, however, X-PEEM could only image and analyze the chemistry of conductive sample surfaces. Insulating samples such as minerals and biominerals could not be analyzed without major charging problems. Transmission X-ray microscopy experiments (e.g., scanning transmission X-ray microscopy, STXM (Kilcoyne 2003; Tyliszczak 2004), which do not suffer from charging, are limited to very thin solid samples (few atomic monolayers) or dilute liquid samples. Most biominerals, therefore, are excluded from this powerful analysis. Overcoming charging effects We recently optimized a differential-thickness coating method (De Stasio et al. 2003) that enabled us to extensively study mineral and biominerals surface with X-PEEM and do highresolution imaging and XANES analysis on them (35 nm or better) (Gilbert et al. 2003-2). The coating approach is shown in Figure 7. We have used this coating approach on a variety of insulators, including wood, quartz, zircons, glass slides, tribological polyphosphate and nano-diamond films, cells in culture, mollusk shells and bone. In all these cases the coating completely removed charging and enabled micro- and nano-XANES spectroscopy of insulators. Figure 8 shows a representative example of the results enabled by differential-thickness coating. As aforementioned, the combination of

embed

shell epoxy shell epoxy

shell

:

.

.. ,

:

:

.

polish

500 A Pt

cpoxv

shell epoxy Figure 7. Schematic diagram showing the preparation steps (top to bottom) for the differential thickness coating. First the biomineral (e.g., a mollusk shell) is embedded in epoxy, then the surface is polished with grit, down to 50 nm if high-resolution imaging is desired, then a thick coating (500 A ) of platinum is deposited by magnetron sputtering on the sample, while masking and not coating the central area, typically 3 mm in diameter, which will then be analyzed by X-PEEM. Finally, a thin coating (10 A ) is deposited on the whole sample surface. The photoelectron escape depth is on the order of 30 A at the C K-edge, therefore photoelectrons from the shell can be collected through the 10 A coating at the center. The thicker coating layer around the central region ensures perfect conductivity and a good electrical contact with the sample holder, therefore the sample can be kept at a reliable and stable voltage, it does not charge when electrons are extracted by X-ray illumination, and XANES analysis can be performed (De Stasio et al. 2003).

Organic-Mineral

Interface in

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Figure 8. Distribution map of Ca in the nacreous layer of pinctada margaritifera, the Tahitian black pearl oyster. Dark indicates higher Ca concentration. The Ca-poor regions between nacre tablets are thicker organic matrix strata that could be due to seasonal changes, as suggested by other researchers of abalone nacre (Lin and Meyers 2005), although the thickness and spacing are different in pinctada. This map was acquired using the spectromicroscope for photoelectron imaging of nanostructures with X-ray s (SPHINX) instrument, which is an XPEEM (Frazer et al. 2004), on a fragment of nacreous layer from pinctada embedded in epoxy and polished.

XANES spectroscopy and X-PEEM microscopy is called spectromicroscopy. From an image such as the one in Figure 8, specific regions of interest can be selected (with the computer mouse), and spectra (e.g., C K-edge XANES spectra) can be extracted, showing different spectroscopic signatures characteristic of the crystals and the organic matrix. This powerful technique can investigate both the organic and the inorganic components of biominerals. Real-time, full-field imaging can be done with a maximum field of view of 180 pm in diameter. At this low magnification the area of interest in a biomineral can easily be identified, then zooming in to higher magnification down to a field of view of 1.7 pm allows highresolution imaging and spectroscopic analysis of biomineral nanostructures. The usual mode of data acquisition consists of acquiring stacks of images while scanning the photon energy, therefore obtaining "movies" that can then be played independent of the synchrotron source. In these movies the third coordinate is energy rather than time, and each pixel (typically 512x512 pixels in each image) contains the full XANES spectrum. The number of spectra simultaneously acquired is therefore 2 x l 0 5 . The resulting complexity in data analysis and interpretation initiated a considerable effort in software design, which is in constant evolution. From each one of these movies, all the elemental composition, oxidation state, coordination number, molecular or crystal structure information is available, and can be retrieved after data acquisition. Once carbon XANES spectra from the bound mineral-templating and unbound organic matrices of biominerals are obtained, the difference between those spectra reveals the organic-mineral interaction. Interpretation of the data is then done by comparison with the extensive literature on carbon XANES spectroscopy in individual amino acids and organic compounds (Stohr 1992; Kaznacheyev et al. 2002; Carravetta et al. 1998; Myneni 2002b; Lawrence et al. 2003), or by comparison with reference molecules prepared and analyzed separately for a specific interaction. Two main limitations remain for XANES spectromicroscopy with the X-PEEM approach: the samples must be compatible with ultra-high vacuum, and must be flat. The vacuum compatibility requirement arises from the necessity to collect photoelectrons, which would recombine with gas molecules if these were present in the experimental chamber. The flatness requirement arises from the necessity to keep the sample at high voltage (typically - 2 0 keV) to accelerate electrons away from the sample surface and towards the electron optics column. If the samples have high surface corrugation, greater than ~1 pm, severe distortions of the electric field provoke imaging artifacts and distortions, and in extreme cases even arching and

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sparking which preclude analysis. Surface corrugations lower than 0.5 jim in height, however, are very easy to obtain on solid samples such as minerals and biominerals by conventional surface polishing. Another complication in the XANES X-PEEM approach is the difficulty in separating co-localized mixed phases. In the presence of multiple proteins in a biomineral (for example bone), carbon K-edge spectra may be too complicated to interpret. In that case it is necessary to acquire spectra from separate single-components and deconvolve individual contributions to XANES spectra of the mixture. Separation and/or purification of single components may not be possible. Furthermore, the components may not be spectroscopically distinguishable. If the individual organic components contributing to XANES spectra are known and spectroscopically distinct, singular value decomposition or cluster analysis methods can be used to deconvolve and quantify their contributions (Pickering et al. 2000; Lerotic et al. 2004).

THE ORGANIC-MINERAL INTERFACE IN MICROBIAL BIOMINERALS Prokaryotic biominerals Microbes or prokaryotic cells, which include Bacteria and Archea, are single-celled organisms. They are small, ranging in size from 200 nm to 7 |im, and lack the tissue differentiation and sophisticated external structures immediately apparent in single- and multicelled eukaryotes. They also lack nuclei and membrane-bound internal organelles, with the notable exception of magnetosomes, surrounded by a phospholipid bilayer, in magnetotactic bacteria. Another exception are Gemmatata obscuriglobus, recently discovered bacteria with a double membrane surrounding their nucleoid, making them appear very similar to eukaryotes (Fuerst and Webb 1991; Lindsay et al. 2001). Prokaryotes, however, are among the most abundant organisms on Earth and can be found in virtually every known environment. In the driest location on Earth, the Atacama desert in Chile, 103 bacteria per gram of soil, can be found in the immediate underground (Maier et al. 2004). That number increases dramatically in more hospitable locations, up to 109 bacteria/g of soil in the rolling hills of Tuscany or the rain forests. Bacteria have also been found as deep under the Earth's crust as man has drilled: over 6000 m underground in a South African mine (Takai et al. 2001; Newman and Banfield 2002). Prokaryotes not only inhabit all natural waters, soils and sediments, they are also capable of surviving in extremes of temperature, pH, or salinity. Additionally, unlike eukaryotes, which depend on glycolysis and require glucose as an energy source and oxygen as an oxidant, prokaryotes adapt to extract energy from diverse and often even multiple chemical reactions (Nealson and Stahl 1997). Sources of metabolic energy include redox reactions of minerals and ions in solution, as well as other inorganic molecules. One of the most eclectic of bacteria, Shewanella putrefaciens, can extract energy from reducing iron and manganese oxides, or sulfur, or fumarate or nitrate or many other compounds, in anaerobic conditions, depending on their availability. If oxygen is available instead, Shewanella becomes an aerobic organism using molecular oxygen to oxidize its energy source (organic carbon or hydrogen) (Myers and Nealson 1990). Returning to the definitions of the different biomineralizations, microbes mostly perform biologically induced mineralization (Lowenstam 1981; Frankel and Bazylinski 2003). Magnetotactic bacteria are an exception, and are, together with coccoliths, the most studied microbes to exhibit biologically controlled mineralization (Bazylinski and Frankel 2003). Biologically induced mineralization is especially significant for bacteria in anaerobic habitats, because in these conditions bacteria respire with sulfate and/or various metals as terminal electron acceptors in electron transport (Frankel and Bazylinski 2003).

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Bacterial communities and biofilms thrive in environments rich in metal ions in solution and play an important role in mineral and/or rock dissolution, formation and deposition. From a materials science point of view, prokaryotes can be considered rock-catalysts: they enact or induce chemical transformations that lead to geochemical cycling and biomineral formation. Minerals formed by biologically induced mineralization are generally nucleated and grown extracellularly as a result of metabolic activity of the organism and subsequent chemical reactions involving metabolic byproducts. Microbes secrete one or more organic macromolecules that react with ions or compounds in the environment, resulting in the subsequent deposition of mineral particles. This biomineralization may be unintended (Frankel and Bazylinski 2003) or advantageous for the organism (Chan et al. 2004). The minerals formed are often nanoparticles with considerable particle-size distributions (Frankel and Bazylinski 2003). A more thorough review of the general characteristics of prokaryotic nanoparticulate biominerals is given elsewhere in this volume (Gilbert and Banfield 2005). As catalysts of biomineralization, however, prokaryotes are ideally configured. The larger the volume of an organism, the smaller the surface/volume ratio. Therefore the smallest organisms, microbes, are the most efficient in rapidly exchanging nutrients and waste byproducts with the surrounding environment. This metabolic advantage also implies that every bacterium can produce many times its body weight in biominerals. This efficiency has a price: bacteria, more likely than other larger organisms, are prone to become encrusted in their biomineral products. Furthermore, the microbial cell walls have a strong negative charge, with multiple sites available for metal binding. Metal ions in solution interact with the charged surface of the cell wall and initiate the formation of minerals. In other microbes, additional structures such as sheaths, capsules, S-layers and filaments provide binding and nucleation sites for mineralization. In addition, bacteria can induce mineralization by secreting extracellular polysaccharides and enzymes that, when released into the surrounding environment, transform minerals already present or induce the precipitation of new minerals and metastable mineral precursors. In the first case, the organic-mineral interface of Figure 3D is located on the surface of bacteria or on extruded but still connected structures, whereas in the second case the biomineralization occurs entirely extracellularly and away from the cell bodies. In both cases, the organic macromolecules induce nucleation and growth of the minerals, and are formed first. In prokaryotic biomineralization, however, a combination of the cell physiology and the chemistry of the surrounding environment determine the mineralization process and the final mineral product. No general statements, therefore, can confidently be made, and the paradigm of Figure 3A is certainly not widely applicable to prokaryotic biomineralization. The only general conclusion, perhaps, is that as a result of prokaryotic biomineralization the mineral changes redox state and the microbe gains energy, while in eukaryotic mineralization there is seldom a redox change, and the organism expends energy to form the biomineral. The structure and dynamics of the microbe-mineral interface can be studied with atomic force microscopy (Lower et al 2001a). The interactions at that interface were also reviewed by Juniper and Tebo (1995). Several groups did spectroscopic analysis of the minerals formed by microbes. Among these, several studies used extended X-ray absorption fine structure (EXAFS) spectroscopy, which explores the structure of the 2-3 nearest neighboring shells of atoms in minerals of biogenic origin. These studies include Suzuki et al. (2002), Tebo et al. (2004), and Villalobos et al. (2005). Another article analyzed the changes in elemental concentrations between adhering and suspended bacteria using hard X-ray fluorescence spectromicroscopy (Kemner et al. 2004). Other studies used XANES or STXM-XANES spectromicroscopy, to analyze the oxidation states of biomineral products (Grush et al. 1996; Tonner et al. 1999; Toner et al. 2005). The latter studies, being all in the soft-X-ray region have the potential of analyzing both the mineral and the organic components of biominerals. This is, again, due to the location in energy of the absorption thresholds of organic elements, C, N, O, etc. However, to

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the best of our knowledge all those studies have focused on the mineral components of bacterial biomineralization. We will later describe the first two cases in which the organic and mineral components, and the interface between them was analyzed using XANES spectromicroscopy (Chan et al 2004; Lawrence et al. 2003). Biomineralization on various prokaryotic structures is reviewed hereafter, including cell walls, capsules, S-layers, sheaths, and filaments. Bacterial cell walls Bacterial cell walls can be classified into one of two groups based on their reaction to Gram's stain, a stain used for visible light microscopy. The cell walls of both Gram-positive and Gram-negative bacteria are negatively charged and may induce biomineral formation. However, Gram-negative cells have been shown to precipitate only a fraction of the quantity of minerals produced by Gram-positive cells (Beveridge and Fyfe 1985). The cell wall for Gram-positive bacteria is made up of a layer of peptidoglycans and is separated from the interior of the cell by the plasma membrane. Peptidoglycans are composed of repeating dimers of N-acetylglucosamine and N-acetylmuramic acid. Each N-acetylmuramic acid molecule exhibits a side stem, which is a peptide with four or five amino acids. These stems covalently bond with other stems on neighboring peptidoglycan strands to form a strong and enduring 3-dimensional macromolecular structure that surrounds the bacterium. This cell wall is 15-25 nm thick (Fortin and Beveridge 2000). Both the glycan strands and peptide stems of peptidoglycans are rich in carboxyl groups and give the cell wall a net negative charge. Secondary polymers like teichoic or teichuronic acids, which contain negatively charged phosphoryl groups, are also bound in the peptidoglycan structure and increase the negativity of the cell surface. The large number of anionic reactive sites provided by the peptidoglycan layer is the main source of surface catalysis or mineralization in Gram-positive bacteria. The cell walls of Gram-negative bacteria are more complex, both structurally and chemically. The peptidoglycan layer is much thinner than in Gram-positive cells (3 nm), contains no secondary polymers and is bound on both sides by membranes composed of lipid-protein bilayers. The outer membrane of Gram-negative bacteria is unique and asymmetric: the inner layer is composed of phospholipids but the outer layer contains an unusual lipopolysaccharide (LPS) layer, which is found uniquely in prokaryotes. LPS is a large complex molecule with three components: a lipid core, a core polysaccharide and a short polysaccharide chain that contains unique and species-specific sugar sidechains. The core polysaccharide is rich in anionic phosphate and carboxyl groups and gives the cell wall a net negative charge. The sugar sidechains can extend up to 40 nm from core polysaccharides and may also contain negatively charged carboxyl groups (Langley and Beveridge 1999). In contrast to Gram-positive bacteria, the peptidoglycan layer is not only considerably thinner, but also shielded by the outer membrane in Gram-negative bacteria. Metal ions in the environment, therefore, cannot reach the peptidoglycans, presumably by the same mechanism excluding the Gram stain, and the biomineralization site is constituted of the numerous phosphate and carboxyl groups in the LPS layer (Fig. 9). Active cell metabolism can slow down biomineral formation on the cell wall. A clear example of this behavior is given by Bacillus subtilis cells. During metabolism, a membraneinduced proton motive force continuously pumps protons into the cell wall. Therefore metal ions must compete with protons for anionic cell wall sites, and the result is that these bacteria bind more minerals dead than alive (Urrutia et al. 1992). Capsules Both Gram-positive and Gram-negative cells can possess additional outer layers that also

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Figure 9. Transmission electron micrograph of ShewaneUa putrefaciens, a Gram-negative bacterium, exposed to nanocrystalline hematite. The crystals adhere to the cell wall due to its negative charge. This example illustrates that the bacterial cell wall not only binds ions f r o m solution, but also alreadyformed mineral crystals. Reproduced with permission of the American Society of Microbiology, f r o m Glasauer et al. (2001), Applied and Environmental Microbiology, Vol. 67, Fig. 5, p. 5544-5550.

induce biomineralization. Among these, capsules are highly hydrated amorphous matrices of exopolysaccharides or polypeptides, and strongly attached to the cell wall (see Fig. 10A). Capsules extend up to 1 pm away from the cell, and serve as protective shields for bacteria and, as cell walls, contain numerous carboxyl groups (see Fig. 10B). They contain 99 % water and allow for efficient transport of nutrients and waste products (Schultze-Lam et al. 1993). The negatively charged polysaccharides filter and capture the positive cations from solution and induce precipitation away from the cell, thereby protecting the organism from becoming encrusted with minerals.

•400 rim Figure 10. (A) T E M micrograph of bacteria, surrounded by exopolysaccharide (EPS) capsules, to which clay nanoparticles adhere. Reproduced with permission f r o m \v\v\v.n\vri.ca/envirozine/images/bacteria_ e.gif. (B) SEM image of another bacterium exhibiting the remains of a capsule. Bacteria in this ground water sample were not fixed, nor treated in any way, therefore the morphology of the 99% water-containing capsule is altered by dehydration. Sample courtesy of Clara S. Chan.

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Capsules also stabilize the metal ion concentration around the cell wall. This is particularly advantageous when the metal ion concentration in the surrounding environment, which naturally fluctuates, reaches toxic levels. Experiments have shown that mutated forms of Klebsiella aerogenes, which do not produce capsules, were unable to survive in concentrations of metals in which the capsule-forming wild-type strains thrived (Bitton and Freihofer 1978). S-layers S-layers are paracrystalline surface layers 5 to 25 nm thick, containing many ordered repeats of a single protein or glycoprotein. Both Archea and Bacteria may form S-layers. These self-assemble into a well-ordered two-dimensional shell around the bacterium (Sleytr 1997). S-layer proteins or glycoproteins assemble into regular patterns in which the unit cell has 2-, 3- 4- or 6-fold rotational symmetry. The well ordered lattice contains pores that are identical in size and morphology. Since the S-layer becomes the outermost layer for the bacterium, it can serve several functions. In addition to determining the external morphology and shape of the cell, S-layers can be extremely resistant to external chemical challenges such as salts, detergents and even enzymes, and thus provide a protective armor for the cell (Schultze-Lam and Beveridge 1994). An S-layer with well-defined pore size is a barrier for compounds with a large molecular weight and therefore acts as a molecular sieve. S-layers may promote cell adhesion to crystalline surfaces and can also provide a method of surface recognition. Before S-layer formation, the proteins and glycoproteins forming this layer have negative charges, while after formation, as the proteins self-assemble into the ordered structure, the charged amino acids are embedded within the layer, and in most cases the final S-layer presents a net neutral charge at the cell surface. However, some S-layer proteins retain exposed anionic residues and are capable of inducing biomineralization (Schultze-Lam et al. 1993). The cyanobacteria Synechococcus spp, have a 6-fold symmetry S-layer as their outermost surface. This strain showed that strontium and calcium carbonates and other minerals can form on the S-layer (Fortin and Beveridge 2000). Sheaths Sheaths are well-defined biomineralized structures, such as hollow cylinders, that often surround chains of filamentous cells, and can be sites of biomineralization. Once biomineralized, the sheaths can remain long after the bacteria have died and decomposed. Leptothrix spp oxidizes ferrous iron in solution by secreting a complex matrix of heteropolysaccharides that catalyzes Fe oxidation and precipitation as iron oxyhydroxide (FeOOH) nanoparticles (Banfield et al. 2000). This bacterium thrives in high concentration of Fe and Mn, and leaves behind long sheaths as shown in Figure 11. Filaments Other bacteria induce the formation of biomineral filaments. The microbial mineral filaments of Figure 12 are formed by iron-oxidizing bacteria that have not yet been isolated nor phylogenetically identified. All these filaments show an unprecedented ~ 2 nm wide, up to 10 |im-long, curved pseudo-single crystals of akaganeite (P-FeOOH) in their cores (Chan et al. 2004), as presented in Figure 12B. The filaments are 20-200 nm wide, tangled, and composed of 2-line ferrihydrite ( F e 0 0 H « H 2 0 ) , surrounding the akaganeite cores (Fig. 12B). Formation of akaganeite in solution requires the presence of chloride, and is unexpected in fresh water. Chan et al. (2004) therefore suggested that akaganeite formation is catalyzed by organic polymers extruded by the bacteria. In this model, chemical bonds are formed between an organic molecule and ions in solution or amorphous nanoparticles, which are precursors of the crystal cores. As in other biominerals, the organic molecule acts as a template for a particular mineral polymorph, in this case, akaganeite. The paradigm of Figure 3A therefore

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applies to this biomineral formation, although akaganeite crystal cores are formed upon aging

Figure 11. SEM micrograph of the FeOOH sheaths formed by Leptothrix spp in the Piquette mine, Tennyson, WI. Sample courtesy of Clara S. Chan.

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Figure 12. (A) SEM image of mineralized filaments produced by Fe-oxidizing bacteria in the Piquette abandoned and flooded mine in Tennyson WI. The filaments, approximately 100 nm in diameter are mineralized by FeOOH adhesion to the polysaccharide chains immediately after being extruded by the bacterium. On the right hand-side of the image a thinner, faint, strand is visible, possibly a non-mineralized polysaccharide fibril. Image used with permission of the American Journal of Science from De Stasio et al. (2005), American Journal of Science, Vol. 305, Fig. 4. Sample courtesy of Clara S. Chan. (B) TEM micrograph of a mineralized filament similar to the one in (A). The outer structure is formed by 1-2 nm wide 2-line ferrihydrite nanoparticles, while the central core of each filament exhibits a ~2 nmwide crystalline core of akaganeite (p-FeOOH). This crystal core is only 2-3 unit cells wide, and can be identified as akaganeite by its distinctive crystal spacing (0.75 nm). Image courtesy of Jillian F. Banfield.

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of the mineral filaments, not as FeOOH nanoparticles are nucleated and grown. Bacterially extruded polymer fibrils were analyzed using the SPHINX spectromicroscope, and identified as polysaccharides by comparison of their carbon K-edge XANES spectra with those from representative reference compounds (Fig. 13). Mineralized filaments also revealed a polysaccharide spectrum at the carbon K-edge. FeOOH nanoparticles form a ~50 11111 thick coating around the polysaccharide fibrils, hence the carbon signal is much lower, relative to the uncoated filaments. Most interestingly, carbon spectroscopy from mineralized filaments revealed a new peak, which was absent from spectra of non-mineralized polysaccharide fibrils. This spectral signature was interpreted as a a* resonance of a C-O single bond involved in FeOOH binding. It is likely that the C-O groups that interact with FeOOH originate from the carboxyl groups (0=C-0~) of acidic polysaccharides (e.g., alginate). Acidic polysaccharides have an excess of COO" groups that have high affinity for binding positive ions. Chan et al. (2004) concluded that carboxyl groups in the unidentified biofilm polysaccharide chains must be the sites at which FeOOH amorphous nano-precipitates form chemical bonds, templating for the formation of akaganeite crystal cores upon aging (Fig. 13). This is a relatively simple biomineral, in which the biomineral composite has only three components: an unidentified COO~-rich polysaccharide, akaganeite crystal fibers and ferrihydrite nanoparticles. Because of its simplicity, its analysis (still incomplete) suggested a possible templation mechanism, which could be inferred at the molecular level (Chan et al. 2004). Biomineralization of these bacterial filaments has common features with many other biominerals. As a careful reader may have already noticed in all the biominerals reviewed thus far, it is always negatively charged groups along the organic macromolecules that direct the interaction with positively charged mineral ions, such as Fe 3+ or Ca2+. In the case of the

M filament

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Figure 13. SPHINX image and spectra of the filaments produced by iron-oxidizing bacteria. (A) mineralized filaments from the biofilm-contain the akaganeite crystal core described in the text. (B) Carbon K-edge XANES spectra from non-mineralized (NM) fibrils and the mineralized (M) filament in (B), and reference organic molecules: alginate, albumin, lipid and DNA. Notice the similarity of the spectra from the N M fibrils and M filaments with the polysaccharide spectrum, and the additional structure in the one from the M filament: the peak at 292.4 eV was assigned to the C-O bond in carboxyl groups. Data from Chan et al. 2004.

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microbial acidic polysaccharides, negatively charged COO" groups are responsible. In cell walls, capsules, S-layers and sheaths, either acidic polysaccharides (rich in COO" groups) or peptide sequences rich in negatively charged amino acids (also exhibiting carboxyl groups) enact the nucleation and biomineral growth. The paradigm of Figure 3, therefore, has one more identified component: at the interface of the inorganic and mineral components is most frequently, perhaps always, a carboxyl group. We will now discuss the biomineralization paradigm in eukaryotes, and highlight the similarities of the core mechanisms.

THE ORGANIC-MINERAL INTERFACE IN EUKARYOTIC BIOMINERALS Eukaryotic biominerals The majority of animals mineralize at least part of their bodies, usually as internal skeletons or external armors, using a variety of proteins and minerals with calcium carbonates, calcium phosphates, and silica being the most common (Currey 2005). Other eukaryotic biominerals contain a variety of elements, including barium, strontium, iron, manganese, magnesium, copper, zinc, and sulphur. These complex composites, often hierarchically organized, include bone, teeth, eggshell, mollusk shells, crustacean shells, corals, sponge skeletons, the statoliths through which trees sense gravity and grow vertically even on the steepest mountain slopes, the otoliths in the inner ear of most animals, from humans to zebra fish (Sollner et al. 2003), warm jaws (Lichtenegger et al. 2002), and many more composites, in excess of 70 biominerals known nowadays. See Weiner and Dove (2003) and Mann (2001) for the most recent complete lists of biominerals. Eukaryotic biominerals can be distinguished from their abiotic counterparts because of their uniform crystal size and habit and the regular nanostructures that result from biologically controlled mineralization (Weiner and Dove 2003). The control, again, is enacted by the organic matrix and its macro molecules: proteins, glycoproteins, and carbohydrates. Mollusk shells, and in particular that of red abalone (Haliotis rufescens), have been widely studied for their very regular repeating crystalline domains and astounding properties. The nacre layer, or mother of pearl, at the inner surface of the abalone shell has a fracture resistance 3000 times greater than that of aragonite, the pure mineral of which it is composed. The toughening effect is due to well-defined nanolayers of organics at the interfaces between micro-tiles of aragonite (Kamat et al. 2000; Currey 2005). In nacre and many other eukaryotic biomineral structures, the stiff mineral tiles absorb the bulk of the externally applied loads. The alternating organic layers, in turn, provide toughness, prevent the spread of the cracks into the interior of the structure, and even confer a remarkable capacity for recovery after deformation (Smith et al. 1999). Two other structural characteristics of eukaryotic biominerals contribute to the superior mechanical properties of skeletons made from them. First, at the lowest level, they are often made of tiny crystals that are smaller than the "Griffith length" necessary for cracks to spread (Gao et al. 2003). Second, the precision with which they can be laid down (changing their main orientation over a few micrometers, for instance) allows exquisite adaptations to the loads to which the skeletons are subjected (Currey 2005). Nacre is composed of approximately 95 mass percent aragonite and 5 mass percent organic macromolecules. We note that various groups have studied other systems of marine biominerals. For instance, in studies on marine sponges such as Tethya aurantia that form silica needles, research has focused on the role of the proteins and their possible use in organosilicon chemistry. The ultimate goal there is to manufacture silicon based polymeric materials in milder conditions than those used in today's industry. The proteins responsible for biological silica

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synthesis have received a lot of attention recently, including their very own name, "silicateins" (Shimizu et al. 1998; Shimizu and Morse 2000; Weaver and Morse 2003; Pozzolini et al. 2004). In this section, we will focus on nacre and promote our opinion that the key to nacre formation lies at the organic-mineral interface. Understanding the role of that interface is thus pivotal to the development of biomimetics, that is, the field that imports biologically inspired concepts and mechanisms into the design and fabrication of new materials. The nano-structure of nacre Mollusk shell and pearl nacre presents a highly regular brick and mortar arrangement in which aragonite tiles, 500 urn thick along the c-axis, 10-20 pm wide along the a and b axes (Mann 2001), and polygonal in shape, form extremely flat layers (Fig. 14). Subsequent layers of aragonite tiles and organic matrix, composed of silk-like proteins and glycoproteins, keep alternating across the entire thickness of the nacreous layer (Currey 1977; Jackson et al. 1988; Schafferet al. 1997). The regularly repeating layering of nacre, the semi-transparency of aragonite and the pitch of this periodic structure (500 nm), which falls in the middle of the visible light wavelength range (400-700 nm), all combine to generate the iridescence typical of mother of pearl. As the observation angle varies, the color perceived changes due to the variation in apparent spacing between the semi-transparent layers of crystals. Furthermore, there is considerable crystallographic alignment, with the c-axes of most tiles lying in the direction perpendicular to the tiled planes. Aragonite is an orthorhombic polymorph of CaC0 3 , whereas the outer prismatic layer of all mollusk shells is formed by columns of the trigonal-rhombohedral calcite polymorph. In the prismatic layer the c-axes are along the long axis of each prismatic column, perpendicular to the shell surface and parallel to the nacreous layer c-axes. Epithelial cells form a layer along the inner surface of the shell, called mantle, and secrete all the macromolecules of the organic matrix (see Figs. 15 and 16). Mechanically nacre is stiff and resistant to fracture; it therefore combines the behavior of flexible materials that can absorb energy by rearranging their molecular conformation (distortion and deformation), and that of hard and stiff materials. On the other hand, it does not suffer from the limitations of its components, as it is neither compliant (as most soft materials) nor brittle (as most hard materials). Jackson et al. (1988) reported the Young's modulus of

Figure 14. SEM micrograph of red abalone nacre tiles seen at a fractured edge.

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abalone shell and mantle mantle

growth surface nacreous aragonite spherulitic calcite (5-25 pm) green organic (5-15 |jm) blocklike calcite (10-15 pm) nacreous aragonite

secretory epithelium

growth surface nacreous aragonite reen organic-calcite leterolayer nacreous aragonite periostracum prismatic calcite

prismatic calcite (0.5-3 mm) periostracum (100-200 nm) Figure 15. Schematic, not to scale, of a vertical cross-section of the outer edge of the shell and mantle of red abalone (Haliotis rufescens) with an enlargement indicating the thickness of each shell structure. The size of the extrapallial space is exaggerated for clarity. Used by permission of the American Chemical Society, f r o m Z a r e m b a et al. (1996) Chemistry of Materials, Vol. 8, Fig. la, p. 680.

p-Ghilin

Asp-rich glycoprotein?

Occluded Asp-rich glycoproteins

Silk fibroin gel

Figure 16. A proposed model for the organic matrix structure in nacre of the bivavlve shell Atrina serrata, observed in the hydrated state by cryo-TEM. Note that silk was found to be present in both phases, the water-soluble and water-insoluble matrices. Reproduced with permission of Elsevier, f r o m Levi-Kalisman et al. (2001), J. Structural Biology, Vol. 135, Fig. 1, p. 8-17.

nacre in the bivalve Pinctada umbricata to be approximately 70 GPa and 60 GPa for dry and wet samples, respectively, whereas the tensile strength is a corresponding 170 MPa and 140 MPa. The work of fracture varies between 350 and 1240 J/m 2 (up to 3000x higher than that of CaC0 3 ) (Jackson et al. 1988). Interestingly, the organic layers are thick along the c-axis, very thin and hard to detect,

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or non-existent on the lateral surfaces of tiles (see Fig. 16). The thick organic layers between tile layers are consistent with the model in which sliding of the tiles give nacre its resistance to fracture (Lin and Meyers 2005). It is conceivable that upon sliding, the chains of looped organic macromolecules stretch and break loops without breaking the main molecular chain, thus conferring nacre with its elastic behavior (Smith et al. 1999). Start and stop signals in nacre growth Several groups studied the growth of abalone nacre and other mollusks (Addadi and Weiner 1985; Lowenstam and Weiner 1989; Belcher et al. 1996; Zaremba et al. 1996; Lin and Meyers 2005). In nacre the organic matrix is a true matrix: its continuous sheets are formed first (Fig. 3A) and they provide the many nucleation sites, which initiate crystal growth to fill the voids in the three-dimensional organic matrix. This the "start" signal. The position and nature of the nucleation points determines the crystal species and polymorph (Falini et al. 1996), while the structure of the voids in the matrix, presumably, determines crystal habit and size. Laterally, along the a and b axes, crystal growth is stopped by crystal-crystal contacts. At the surface of nacre, which is the growth front, tiles are piled up as stacks of coins, or cones, or Christmas trees, as many authors have called them (see Fig. 15). Lateral growth along the a and b (in plane) directions occurs in these cones until adjoining terraces come in contact. This is one of the "stop" signals, and explains the polygonal appearance of nacre tiles. Vertically, however, the reproducibly perfect thickness of 500 nm must be controlled by another extremely accurate "stop" signal, transduced by the preformed matrix macromolecules. Such signals, and the matrix molecules involved in the growth cessation, are still unknown (Lowenstam and Weiner 1989). Since the aragonite tiles have a relatively small thickness in the c direction (the pure mineral aragonite crystals are much more elongated along that direction, and are much longer than 500 nm), there must be a signal stopping this growth. This signal may be linked to stereochemical adsorption of proteins in the growth of calcite crystals demonstrated by Addadi and Weiner (1985) and Addadi et al. (1987). It can be speculated that the host animal produces the proteins that stop growth in a periodic manner (Lin and Meyers 2005). Another relevant observation is that the size of the aragonite tiles does not depend on the size of the animal. The growth of nacre in space and time has been analyzed in vivo and in vitro using the flat pearl system (Fritz et al. 1994). They found that nacre growth begins with the secretion of proteins that mediate the precipitation of calcite. Other proteins then induce a phase transition from calcite to aragonite (Zaremba 1996; Belcher and Gooch 2000; Lin and Meyers 2005). Some of the matrix macromolecules involved in nacre formation have been identified. Among the known molecules are the insoluble P-chitin central sheet in each organic matrix layer (Addadi and Weiner 1985), insoluble silk fibroin protein layers above and below this sheet, and unidentified soluble acidic macromolecules. Even without identification, however, these macromolecules can be extracted from nacre, exposed to non-shell P-chitin and silk fibroin in a saturated solution of CaC0 3 and induce nucleation and growth of aragonite, not calcite (Falini 1996). Aragonite formation is induced by the macromolecules even when seeding calcite crystals! (Thompson et al. 2000). This is particularly clear proof of the role of these unknown acidic macromolecules in polymorph selection, since aragonite is much less stable than calcite. The Thompson et al. (2000) experiment proves that nucleation and polymorph selection are independent in nacre formation. The recent discovery and sequence of Asprich proteins contributes to the clarification of the nature of these acidic macromolecules (Gotliv et al. 2005). Again, as already noted in microbial biominerals, it is the negatively charged amino acids aspartate and glutamate in acidic glycoproteins in mollusk shell that are

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believed to initiate biomineral formation (Mann 1988, 2001; Mann et al. 2000; Weiss et al. 2000; Weiner and Dove 2003; Gotliv et al. 2005). Stereochemical recognition determines the specific interactions between aspartic acidrich proteins and certain faces of various calcium dicarboxylate crystals, which are used as model systems. The specific faces have carboxylate groups oriented perpendicular to the face and can therefore optimally complete the coordination polyhedron around the protein bound calcium ions (Addadi and Weiner 1985). A more recent study, which explored the subtle links between atomic scale dynamics and macroscopic crystal faces, clarifies further this issue and reconciles the stereochemical recognition model with the simple mechanistic model of crystal growth by step propagation across crystallographic faces, the terrace-ledge-kink model (De Yoreo and Dove 2004). A possible stereochemical recognition model for abalone nacre is reported in Figure 17. Synergy of mechanisms for nacre growth Several mechanisms likely conjoin in the formation of nacre. These are: •

Heteroepitaxial nucleation: in this case nucleation and growth of each aragonite tile are detrmined by the organic matrix sheet beneath it (Schaffer et al. 1997).

•

Epitaxial crystal growth of the /th crystal layer, connected to the (/ - l) ,h crystal layer

(ÌSheet

(b) Figure 17. Unit cell of aragonite: (a) perspective view (b) normal view showing schematic position of (Asp-Y) n and p-pleated organic matrix sheet. Notice protruding Ca ions on (001) face: black atoms are Ca, small black are C and gray are oxygen. This model is in perfect agreement with the paradigm of Figure 3. Reproduced with permission of Elsevier, from Lin and Meyers (2005), Materials Science & Engineering, Vol.390, Fig. 5, p. 27-41.

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After nucleation on the organic matrix sheet, the growth of aragonite may be mediated or catalyzed by proteins in solution (Falini et al. 1996).

All of these mechanisms, and possibly others not yet discovered, are likely to control in synergy the growth and architecture of nacre.

BIOMINERAL GLUE: THE CARBOXYL GROUP. We have already highlighted the similarity of all organic-mineral interface in prokaryotic biominerals. In the few biominerals thus far analyzed at the molecular level, including prokaryotic and eukaryotic, it is often negatively charged carboxyl groups (COO") that attract positive ions from solution, and these nucleate for biomineral crystal growth. The carboxyl groups are located either along polysaccharide chains or in acidic amino acids, along the sequences of protein and glycoprotein rich in aspartate or glutamate (Mann 1988, 2001; Mann et al. 2000; Weiss et al. 2000; Weiner and Dove 2003; Gotliv et al. 2005). The very reason the latter are commonly called aspartate and glutamate, and not aspartic and glutamic acid, highlights the fact that they are nearly always deprotonated, and therefore their carboxyl group terminations are negatively charged at physiological pH (the typical pK for both is 4.4; Stryer 1995). Carboxyl-group-rich proteins and/or polysaccharides are the most common and most effective cation-binding macromolecules that any organism can assemble to bind mineral precursors and either control or induce biomineralization. We hypothesize that this is why this molecular functional group was selected in many biominerals as the organic-mineral interface of Figure 3D. In this hypothesis, the carboxyl group is a molecular "glue" of choice for biominerals. Interestingly, even when this hypothesis is not confirmed in specific biominerals, by analyzing with XANES an intact and pristine biomineral from both the mineral and the macromolecule perspective, it is always possible to identify spectral signatures, even if the bond sites and functional groups involved are not those expected.

CONCLUSION Frequently in biology a gene or a protein is identified but its function is unknown for decades. Even now, in the most intensely studied genomes, 25% or more of the genes are yet to be associated with a function. In biomineralization it is quite the contrary: most often the function, namely, the formation of a specific biomineral structure is identified, but the molecule or molecules responsible for it are unknown. We know, however, that composite biominerals form as a result of complex chemical interactions between organic and inorganic matrices, and that the former acts as a template for the latter, according to a paradigm presented in Figure 3. Few approaches enable the simultaneous analysis of both the organic and mineral components in biominerals and their interface. XANES spectromicroscopy studies of that interface might reveal some of the molecular details of templation mechanisms (e.g., Figs. 13 and 17). We note that at this interface, in diverse eukaryotic and prokaryotic biomineralization, there is frequently a carboxyl group. Acidic amino acids or polysaccharides with excess carboxyl groups are the most common and most effective cation-binding chemical species that any organism can assemble to bind mineral precursors and initiate templation. In this sense COO" is a biomineral preferred "glue".

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Ultimately, once the molecular-scale chemistry of the interface is elucidated in more biominerals, it may be possible to harness it and synthesize novel biomimetic composite materials that self-assemble and, as natural biominerals, outperform the sum of their components. Two conceivable avenues towards bio-inspired synthetic materials are: (i) templation by structured organic surfaces, such as self-assembled monolayers or Langmuir-Blodgett films and functionalized polymers; and (ii) precipitation from solution with growth modifiers, such as ions, proteins, and synthetic polymers (Han and Aizenberg 2003). The first biomineral-inspired man-made material synthetically reproduced the nacre assembly with alternating organic and inorganic matrices, using synthetic organic molecules and clay crystals. Remarkably, the tensile strength of the prepared multilayers was similar to that of nacre, and the Young's modulus approached that of lamellar bone (Tang et al. 2004). We envision a future with many more of these synthetic materials, assembling and structuring themselves at different scales as biominerals have done for well over 500 million years. Impact resistant cars, trains and spacecrafts, in which cracks do not propagate might one day have an attractive mother of pearl luster. In the meantime, the best we can do is to analyze and understand at the molecular level the formation mechanisms of biominerals. The paradigm introduced here includes some prokaryotic and many eukaryotic biomineralization mechanisms. In prokaryotic biominerals, however, the organic components are fewer and simpler to analyze, while the mineral diversity is enormous. This is a distinct advantage offered by prokaryotes for understanding biomineral formation. Following that paradigm as an incomplete but useful starting point, and analyzing as many prokaryotic biominerals as possible, we anticipate that the mechanisms of biomineral formation will be further elucidated. The general rules, the exceptions and the anomalies that are characteristic of the living world will eventually be clear for the biomineral world.

ACKNOWLEDGMENTS We thank Jill Banfield and Clara Chan for their expert, friendly and continued collaboration, and most importantly for bringing GDS into the exciting adventure of discovering templation of akaganeite crystal fibers. That experiment sparked her interest in biomineralization mechanisms, a field now impossible to abandon! We thank Ben Gilbert and Ronke Olabisi for critically reviewing this manuscript. GDS acknowledges the support of the UW-Graduate School, the Department of Physics, the Synchrotron Radiation Center, Air Force grant FA9550-05-1-0204 and NSF grant PHY-0523905. X-PEEM experiments were performed at the UW-Synchrotron Radiation Center, supported by NSF-DMR 0084402.

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 187-210, 2005 Copyright © Mineralogical Society of America

Catalysis and Prebiotic Synthesis James P. Ferris NY Center for Studies on the Origins of Life and Department of Chemistry Rensselaer Polytechnic Institute Troy, New York, 12180-3590, U.S.A. [email protected]

INTRODUCTION Little is know about the origins of life on Earth. Most scientists believe this event occurred some time within a billion years after the Earth formed 4.6 billion years ago (Ga). It is also possible that the Earth was "seeded" by life transported here by another body like a meteorite or by extra-terrestrials. Most scientists in this field assume that life originated on Earth or in our solar system because there would be little data on which to base a proposal for the origin of life at a location outside our solar system. As it is we have a very rudimentary knowledge of the environments on the primitive Earth in the first billion years on our planet. Some relevant books and reviews include Brack (1998), Fry (2000), Zubay (2000), Orgel (2004), and Ferris (2005). Ten years ago it appeared that we had made good progress on understanding about when life arose and what the environmental conditions on the Earth were at that time. Carbon isotope studies on rocks present on the Earth 3.8 Ga suggested life arose in or slightly after that time period (Mojizsis et al. 1996). In addition, microfossils found in rocks dated to be 3.5 Ga suggested were consistent with the presence of life 3.5 Ga (Schopf 1993). These data have been challenged recently (Brasier et al. 2002) so it is not certain the proposed microfossils were originally living organisms. Also the carbon isotope studies have been challenged (Moorbath 2005). But new and entirely different findings suggest that that the Earth had liquid water and an environment suitable for life 4.3 Ga. (Watson and Harrison 2005). In addition it has been proposed that the early Earth had an atmosphere with a mixing ratio of hydrogen of 0.3 (Tian et al. 2005). This suggests the possibility of an atmosphere compatible with reduced organic compounds. So the good news is that this is an active area of research and there is a chance that enough data will accumulated so that a more accurate picture of the conditions on the early Earth will arise from the current confusion. One of the first problems to consider in studies on origin of life is what is life? How would the first, very primitive life form be recognized? This life form would have just barely transited from the non-living to the living so may be lost in the large excess of inanimate material from which it arose. The first life was probably expending all its energy just staying alive so would be hard to recognize. Another problem is the only models of life we have are the highly evolved forms that surround us on the Earth today. Was the biochemistry of the first life just a simpler form of our protein - DNA world or was it entirely different? We don't know. Many scientists have proposed a definition of life. The definitions proposed often describe a model of the first life that the individual is investigating. Those postulating an RNA world propose the need for RNA or structures that were precursors to RNA. Those investigating the need for cell membranes propose the need for the origin of life in a contained like a vesicle to 1529-6466/05/0059-0008505.00

DOI: 10.2138/rmg.2005.59.8

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protect it from losing the essential molecules to maintain this first life. My favored definition is a system of biomolecules that it capable of replication and mutation. This definition does not require that the assemblage of molecules be confined within a membrane nor does it specify the nature of the replicating system present. It has the advantage of being applicable to a variety of different replicating systems that may live in a variety of different environments.

FORMATION OF THE SOLAR SYSTEM The Big Bang, the starting point for the formation of the universe occurred 13.7 Ga. This event has been described as the simultaneous appearance of plasmas of primary particles everywhere at the same time in the Universe. The next stage in the evolution in the Universe was the spontaneous formation of the lighter elements (hydrogen, helium, lithium and beryllium) from the primary particles by the spontaneous combination of neutrons and protons. Star formation occurred next where there was a greater density of particles and elements in the Universe. This process was the result of a greater density of elements and particles in a region of the Universe that condensed to form stars. Once star formation took place there was a sufficiently high concentration of particles and elements to form carbon in a three-body reaction. The next stage in the evolution of the universe was star formation where the primary particles were concentrated in a star with the initial elements where the close proximity resulted in the formation of carbon via a three-body reaction. Once carbon formed the elements up to and including iron-58 formed spontaneously. Additional energy was required to form the elements with atomic masses greater that iron. This additional energy was provided when the star's fusion reactor shut down because the nuclear fuel, hydrogen and helium, were consumed. The star then collapsed and then exploded violently and the energy released powered the formation of the elements with masses greater than that of iron-58. The energy released during the supernova blew the elements that formed by the nuclear fusion reactions into the interstellar medium. Some stars containing high levels of carbon distributed large amounts of carbon into the interstellar medium. These violent explosions distributed clouds of dust in the interstellar medium that contained carbon, silicates and an array of other elements. The action of cosmic rays and other energy sources on the carbon initiated reactions with the abundant interstellar hydrogen to generate simple hydrocarbons. These dust clouds have a lifetime of about 10s years. They then collapse, possibly as a result of an external force like a supernova, and star formation together with the formation of the planets and other bodies in the solar system was repeated. When a dust cloud collapses to form a solar system the bulk if the material in the cloud forms the protostar and the remainder of the dust forms small bodies called planetismals that continue to accrete dust and smaller bodies to eventually form plants as they orbit the protostar. Comets form in the outer solar system where they accumulate gases, water, ice, silicates, and organic compounds. The material in comets has undergone the least change of all the orbiting material because it is far away from the radiation released by the protostar when it accumulated sufficient mass to initiate fusion reactions. Comets may have delivered organics and water to the surface of the primitive Earth. After the comets formed they orbited the Sun in the vicinity of the giant planets, Jupiter, Saturn and Uranus. The strong gravitational forces of these planets accelerated many of these comets out of the Solar System to the Oort cloud. This process probably resulted in the passage of comets near the inner solar system and some of the comets may have impacted with the Earth and brought organics and water to its surface. Asteroids orbit the Sun between Mars and Jupiter in our solar system. This collection of small bodies never coalesced to planets because the strong gravitational field emanating from

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Jupiter perturbs them. There are collisions between asteroids as they orbit the Sun. These collisions resulted in the formation of dust and smaller bodies (meteorites) that are ejected from the asteroid belt. Some of this material impacts on the Earth. It is postulated from spectral studies that that some of the asteroids contain organic compounds and the dust and meteorites may released from these asteroids may have brought the organic compounds and water to the primitive Earth that initiated the origin of life. This process of accumulating dust and meteorites on the Earth continues today but at a much slower rate than it occurred on the primitive Earth. It is estimated that about 30,000 tons of dust per year is accreted on the surface of the Earth today. This general model for the formation of our solar system suggests that there will be an abundance of solar systems around other stars in the universe. This appears to be the case since over 150 extrasolar planets have been discovered. Most of the extrasolar planets are equal to or greater than the size of Uranus while few even approach the size of Earth. Planets the size of Uranus or greater may be gas giants and would not be likely to have life, as we know it, on them. The failure to detect Earth-size planets is probably not due to their absence but rather to the detection method used. It is based on the gravitational perturbation of the motion of their star, which is very small for low mass, Earth-size planets. If Earth-size planets are discovered does this mean that the conditions on them are conducive to life? Not necessarily, but it does seem likely that some of these rocky bodies will at least have microbial life. It should be noted that some scientists believe that the Earth was formed under a very restricted set of favorable conditions that may not be present on comparable Earth-size bodies. They also feel that civilizations of the type present on Earth are unlikely to be present on these Earth-size planets (Ward and Brownlee 2000).

THE EARLY EARTH It is difficult to obtain data greater than 4 Ga about the primitive Earth's from the rock record. This is because plate tectonics has resulted in the subduction of most of the Earth's crust where it was subjected to high temperatures and pressures. This resulted in the destruction of much of the evidence in the rock record of earliest life on Earth. One thing that appears to be known from the rock record is that the oxidation level of the Earth's crust and mantle 3.8 Ga is the same as it is today (Delano 2001). The discovery of zircons that are 4.0^1.3 Ga old opened up a new window on the primitive Earth in the 4^1.5 Ga time period (Watson and Harrison 2005). This suggests that the impacts of larger bodies, such as comets or meteorites that would have heated the Earth to over 100 °C had decreased to a low level by 4.3 Ga. The high temperatures and pressures resulting from plate tectonics do not alter these refractory zircons. They also contain inclusions of other elements that may provide additional insight into the chemical processes on the primitive Earth prior to 4 Ga. There is evidence from lunar material of a sharp increase in the impacts with the Moon at 3.9 Ga. If it is assumed that the same heavy bombardment occurred on the Earth at 3.9 Ga it could have extinguished much of the life on Earth at that time. If this happened it might have required that the origin of life occurred again after these impact decreased in intensity. It is possible that some life survived the impacts in a niche, like the deep ocean, and this life was the ancestor of life on Earth today. Alternatively, the first life on Earth may have arisen after 3.9 Ga.

Atmosphere If the oxidation level of the Earth's crust and mantle was the same 3.9 Ga as today then it is unlikely that a reducing atmosphere was present on the primitive Earth (Delano 2001). If the recent claim that the Earth's atmosphere contained 30% hydrogen is correct (Tian et al. 2005)

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this hydrogen may have altered the overall oxidation state of the atmosphere but may not have changed the oxidation states of the other gases present in the atmosphere. The atmosphere of the Earth is believed to have formed as a result of outgasing the Earth's crust and mantle. It is unlikely that the gases emitted 3.8 Ga would differ from the carbon dioxide, water, sulfur dioxide and other oxidized gases emitted from volcanoes today. It is not clear whether the presence of 30% hydrogen in an atmosphere containing oxidized gases atmosphere could have been a precursor to the reduced organics that resulted in the protein and nucleic acids, central to life on the Earth today. The large deposits of limestone and other carbonates on Earth suggest that carbon dioxide was an important constituent of the primitive atmosphere. The oceans may have been slightly acidic as a consequence the dissolved carbon dioxide and the acidic oxides of sulfur emanating from volcanoes. The rate of precipitation carbonate minerals would have determined the length of time the oceans and other bodies of water were acidic and were probably not favorable for the origin of life. It is encouraging that there are an increasing number of new findings about the ancient Earth. The field of the origins of life suffers from the lack of definitive data about the environment on the primitive Earth. Consequently, there are a plethora of hypotheses but few facts the support or refute them. Primary sources of simple organics Earth's atmosphere. The Miller-Urey experiment was the first laboratory experiment designed to investigate routes to organic compounds on the primitive Earth. In this experiment Stanley Miller passed an electric discharge through a mixture of methane, ammonia, hydrogen and water vapor at 100 °C. After allowing the experiment to proceed for one week the water was analyzed and Miller detected the presence of amino acids. Later he also found hydroxy acids, carboxylic acids and other products. This experiment was carried out with reduced carbon and nitrogen compounds because Harold Urey believed that the atmosphere of the early Earth contained these gases. Up to the present time scientists did not think the primitive Earth had a reducing atmosphere and it was generally agreed that he Miller-Urey reaction conditions are not a valid model for the source of simple organics on the primitive Earth. The proposal that the atmosphere of the primitive Earth contained 30% hydrogen reopens the debate on whether reduced carbon and nitrogen compounds were formed by the Miller-Urey reaction. Even if reduced organics are formed, the rapid photolysis of carbon, nitrogen and sulfur compounds such as methane, ammonia and hydrogen sulfide by solar ultraviolet light suggests that they were present in very small amounts. Meteorites. Meteorites emanating from the asteroid belt may have been an important source of organics on the primitive Earth. It is estimated that greater than 1021 kg of the original asteroid belt reached the Earth's surface in the form of dust and meteorites (Vokrouhlicky and Farinella 2000). This would correspond to a layer of material weighing 5 x 106 kg/m 2 if spread evenly over the surface of the Earth. If the carbon content of that material is about ~1% this would have been equivalent to a layer of carbon 25 m thick over the surface of the Earth (Private communication from Michael Gaffey). Small meteorites are not destroyed when they hit the Earth's atmosphere or surface since they break into small chunks. Large meteorites also survive their impact with the atmosphere but they generate so much energy when they hit the Earth's surface that the organics present in them are destroyed. Dust particles from asteroids and comets float down through the atmosphere and make a soft landing on the Earth's surface. Meteorites are particularly important since they are a direct source of the extraterrestrial material delivered to the primitive Earth. The Murchison meteorite, which fell in the town of Murchison, Australia, was collected shortly after it fell and was therefore less likely to have been contaminated organic compounds indigenous to the Earth. It contains about 2% organic material

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with the bulk of it present as a polymeric organic matrix called kerogen and the remainder the material present as soluble small organic molecules. The latter is a complex mixture organic compounds including amino acids, purines, pyrimidines, and carboxylic acids (Table (Pizzarello et al. 2001). Other carbonaceous meteorites contain some of the same compounds it appears likely that these compounds were present on the primitive Earth.

of of 1) so

Comets. As noted previously comets formed in the outer regions of the solar system where the solar radiation is lower so the structures of the organics more closely reflect those in the dust cloud from which the solar was formed. It has been possible to determine the structures of some of the compounds by spectroscopic analysis of the coma and tails of comets (Table 2). The energetic particles and UV radiation of the Sun not only melts the ice in a comet to release the organics it also degrades high molecular weight organics and generates the lower molecular weight degradation products. Missions are in progress to directly collect cometary dust and return it to the Earth for structure analysis. For example, the Stardust mission sent a probe that arrived at comet Wild2 in January 2004. It collected dust emanating from the comet and is now returning to Earth where the captured dust will be parachuted to Earth on January 15, 2006. The European Space Agencies Rosetta Mission launched a probe to comet in March 2004. Upon arrival in 2014

Table 1. Soluble organics in the Murchison meteorite. 3

Concentration (ppm)

Compounds Identified

Aliphatic hydrocarbons

>35

140

Aromatic hydrocarbons Dicarboxylic acids Carboxylic acids Pyridine carboxylic acids

15-28 >30 >300 >7

87 17 20 7

Dicarboximides Sulfonic acids Amino acids Amines

>50 67 60 8

3 4 74 10

Amides Hydroxy acids

n.d. 15

4 7

Class

"Adapted from (Pizzarello 2001)

Table 2. Some organic compounds observed in comets.

Name

Formula

Name

Formula

Methanol

CH3OH

Formic acid

HCOOH

Formamide

HCONH2

Methyl formate

HCOOCH3

Methane

CH4

Acetylene

C2H2

Ethylene

C2H4

Ethane

C2H6

Methylacetylene

CH3C2H

Hydrogen cyanide

HCN

Acetonitrile

CH3CN

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it will launch a lander to the comet to analyze it's surface and subsurface. The probe will undertake extensive analysis of the comet and volatiles emanating from it. Hydrothermal systems. Hydrothermal systems provide an ecosystem where heat from the Earth's interior, rather than sun light, provides the energy to support life at the bottom of the sea. These "black" and "white smokers" occur at crustal spreading centers where heat driven circulation of water through crustal material brings dissolved compounds in proximity to iron-containing magma. Here the iron reduces oxidized substances in the water. For example, dissolved sulfate is converted to sulfides and the resultant smoker is a precipitate of metal sulfides formed in the neighborhood of the vents when they exit the 300 °C vent into the 4 °C ocean water. Laboratory studies have demonstrated the reduction of molecular nitrogen at temperatures of 500-700 °C and pressures of 0.1 GPa. Nitrogen oxides have also been reduced under high temperature and pressures of hydrothermal systems using iron sulfides and magnetite as reductants (Brandes et al. 1998). More complex organics that may have been destroyed by the high temperatures in a hydrothermal vent would have been stable if formed a short distance away from the vent. The heat flow from the vent also drives the circulation of ocean water through vent regions that is "off axis" or away from the area close to the magma. The combination of the reducing agents, e.g. metal sulfides that precipitated in the vicinity of the vent, the possible mineral catalysts in the crust and the lower temperatures could have served to generate complex structures that were stable under these reaction conditions. Some laboratory studies have been successful modeling the chemistry in hydrothermal systems. Laboratory findings have demonstrated the possibility of generating methane thiol (CH3SH) from carbon dioxide (Heinen and Lauwers 1996). Carbon dioxide is reduced to acetic acid in the presence of methane thiol (Huber and Wachtershauser 1997). Dipeptides are formed in the reaction of amino acids with carbon monoxide, an iron and nickel sulfide catalyst or methane thiol at 100 °C (Huber and Wachtershauser 1998). Reaction of carbon monoxide with iron sulfate at 250 °C generates the Krebs cycle compound pyruvate (Cody et al. 2000). So far it has not been possible to demonstrate the formation of more complex biomolecules in simulations of the reactions in hydrothermal systems but studies of this type are in progress. At the present time it appears that hydrothermal systems may have served as a source of simple organics that were converted to more complex structures in other environments on the primitive Earth.

PREBIOTIC ROUTES TO BIOPOLYMER PRECURSORS RNA world Biopolymers are essential structures in life today. Protein enzymes catalyze the synthesis and transformation of chemical processes that drive metabolic and other processes in the cell. DNA stores the genetic information in its sequences. DNA transfers this information to RNA, which in turn brings it to the ribosome, the site of protein synthesis. RNA brings genetic information to the ribosome and it also catalyzes a key step in protein synthesis in the ribosome. The observation that RNA could both store genetic information in its sequences and catalyze reactions, process that are carried our by the DNA and proteins in contemporary life, led to the proposal that the first life could have had one essential biopolymer, RNA. This was the genesis of the RNA world. A big advantage of this postulate was only one biopolymer would have to be formed by prebiotic processes rather than two. Perhaps some simple peptides may have served as catalysts in the RNA world. Eventually the RNA evolved the ability to catalyze the synthesis of proteins that in turn evolved to catalyze the synthesis of DNA.

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Since the emphasis in this review is a world where one type of biopolymer that can both store information and catalyze reactions the prebiotic synthesis of proteins or protein-like structures will not be emphasized. The structure of and prebiotic synthesis of RNA monomers RNA is a biopolymer composed of monomers linked together. The monomer is composed of three units, bases, ribose and phosphate (Fig. 1). Bases. Two purines, adenine and guanine and two pyrimidines, uracil and cytosine are the principal bases in RNA. Purines are present in small amounts in the Murchison and other carbonaceous meteorites. They are also formed from hydrogen cyanide (HCN) via two routes. The polymerization of HCN generates a black substance called the "HCN Polymer" from which adenine may be extracted in low yields after water hydrolysis. The second route is via the HCN tetramer, an intermediate in the polymerization process, that when photolyzed yields a substituted imidazole (Fig. 2). This imidazole may also be prepared by the reaction of the HCN tetramer with formamidine. Reaction of the substituted imidazole with HCN generates adenine. A variety of other purines can be prepared by the reaction of the imidazole formed by photolysis of the HCN tetramer with other simple molecules.

B a

( )

RNA Monomers

HO

O ii

B

OH

OH OH activated nucleotide

O-P-O • O" OH

OH

OH

nucleoside

(b)

B

nucleotide

Bases H

H cytosine

guanine

adenine

uracil

Pyrimidines

Purines NH 2 (c)

RNA Oligomer

3'-end Figure 1. R N A structural elements.

OH

OH

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4 HCN NH 2

CN

H C N Tetramer

NT H

NH2

GUANINE

H

H XANTHINE

Figure 2. The reaction pathway from HCN to some purine bases.

Pyrimidines may be synthesized by the reaction of cyanoacetylene or cyanoacetaldehyde, (the hydrolysis product of cyanoacetylene) with cyanate, guanidine or urea. Pyrimidines have also been isolated from the product mixture obtained by the hydrolysis of the HCN polymer (Ferris and Hagan 1984). Purines and pyrimidines have also been isolated by the hydrolysis of the products formed the polymerization of a mixture of HCN and ammonia that was kept at - 7 8 °C for 27 years (Miyakawa et al. 2002). Most of the products obtained in this study were comparable to those obtained in the reactions carried out for shorter times at room temperature (Ferris et al. 1978). The various sources observed for purines and pyrimidines described above suggest that it is likely that they were present on the primitive Earth. Ribose. The five-carbon sugar ribose is the backbone of nucleoside monomers. Initially it was proposed that the prebiotic synthesis of ribose proceeded by the Formose reaction, the self-condensation of formaldehyde catalyzed by divalent metal ions like calcium. This route dropped from favor because the yield was very low and about 35 other sugars that would have reactivity comparable to that of ribose were also formed so that it was not obvious why these didn't compete with ribose in subsequent reactions to form nucleosides. Recent investigations suggest that ribose could have been present on the primitive Earth. It may have been possible to selectively isolate the cyanamide (NH2C=N) adduct of ribose from other reaction products (Springsteen and Joyce 2004). The adduct forms 7-fold faster than the comparable adduct with arabinose and 30 times faster than the adduct with glucose. It crystallizes from water under conditions where none of the other adducts crystallize and this adduct is much more stable than free ribose. The only problem is that cyanamide reacts with formaldehyde, glycolaldehyde and glyceraldehydes, compounds present in the Formose reaction mixture to give adducts that do not react further to give the ribose adduct. So it is necessary to postulate that cyanamide appeared in these mixtures after these intermediates were consumed. Three other routes to ribose have been reported that suggest that ribose was present on the primitive Earth. In one approach the use of a magnesium ion - lead ion mixture as a catalyst for the Formose reaction. This catalytic cocktail reduced the number of products from 35 to the 4 possible pentoses (Zubay 1998). Also of interest was the observation that the catalyst also directs the conversion of any one of the 4 pentoses to a mixture of the all four of them. This lead-magnesium ion mixture also catalyzes the conversion of hexoses to the 4 pentoses. A second prebiotic approach to ribose is the reaction of formaldehyde with calcium hydroxide in the presence of borate. The borate forms a complex with the hydroxyl groups

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of ribose and ribose precursors so that the subsequent reaction with formaldehyde is to form hexoses and polymeric products are inhibited (Ricardo et al. 2004). A third route to ribose is a stepwise synthesis by first reacting glycolaldehyde phosphate with formaldehyde to generate glyceraldehydes phosphate. This in turn reacts with glycolaldehyde to give ribose 2,4- diphosphate. Unfortunately neither phosphate is in 5'-position where it may have functioned as a point for linking nucleotides together via the 5'-phosphate group (Miiller et al. 1990). Nucleosides. There is an early report of a prebiotic synthesis of purine nucleosides. It is a dry phase heating reaction of purine bases with ribose in the presence of sea salts or MgCl 2 to get 1-8% yields of purine nucleosides (Fuller et al. 1972). No nucleosides were observed when the same reaction procedure was performed using pyrimidine bases in place of the purine. The low yields of purine nucleosides and the absence of formation of pyrimidine nucleosides indicates that this is not a likely prebiotic pathway to nucleosides. Limited progress has been made in other approaches to the synthesis of nucleosides but so far none of the proposed prebiotic syntheses has generated nucleosides in sufficiently high yields to believe that these monomers would be present in amounts large enough to have been starting materials for RNA synthesis. This is an area that requires new ideas and experiments. Nucleotides. Nucleotides can be synthesized from nucleosides by heating them in the solid phase with acid phosphates like ammonium dihydrogen phosphate (NH 4 H 2 P0 4 ) (Osterberg and Orgel 1972; Osterberg et al. 1973). The reactions are catalyzed by amides like urea. The reaction probably proceeds by driving off the ammonia of the ammonium dihydrogen phosphate to give phosphoric acid that catalyzes the phosphorylation. When this dry heating reaction is carried out with uridine about a 70% yield of a mixtures of the phosphorylated adducts of uridine is obtained. Linear polyphosphates are formed by heating acid phosphates like sodium dihydrogen phosphate (NaH 2 P0 4 ) (Osterberg and Orgel 1972). The linear polyphosphates are converted to cyclic trimetaphosphate (Fig. 3), which reacts with nucleosides in basic solution to yield triphosphates or with 5'-nucleotides under less basic conditions to give triphosphates in a series of reaction steps (Fig. 3). The yields of phosphorylated products formed by dry heating suggest that these may have been abundant on the primitive Earth if there was a plausible prebiotic synthesis of nucleosides. Another concern is that the conditions under which ribose synthesis and phosphorylation n

o

5'-AMP

O o

o

HO

Trimetaphosphate

,0

9 O o

Figure 3. A reaction pathway from a 5'-AMP and trimetaphosphate to ATP.

OH

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reactions occur are very different. It is difficult to imagine how this series of steps required for nucleoside synthesis occurred on the primitive Earth. More experimental studies are required here.

Vesicles Vesicles, also called lipsomes, are small enclosed, compartments separated from their aqueous environments by a lipid bilayer. It is proposed that enclosed compartments similar to vesicles may have contained a suite of molecules that constituted the first life. It has been observed that an organic fraction obtained from the Murchison meteorite formed vesicles and other structures when mixed with water (Deamer and Pashley 1989). It is not likely that these vesicles are enclosed within a lipid bilayer. It is known that under the proper conditions vesicles form from linear carboxylic acids containing 9 or more carbon atoms when the pH of the solution is close to the pK a of the carboxylic acids. Since carboxylic acids are present in the Murchison meteorite this may be a possible explanation for the formation of vesicles. As discussed in detail below, montmorillonite clay, which enhances the rate of formation of vesicles from carboxylic acids, also catalyzes the formation of RNA oligomers (Hanczyc et al. 2003; see discussion in "Prebiotic Polymerization of RNA Oligomers." The prebiotic synthesis of linear carboxylic acids may have proceeded in hydrothermal systems where the high temperatures, pressures and the presence of iron may have produced them from carbon monoxide and carbon dioxide (McCollum et al. 1999; Rushdi and Simoneit 2001). The above discussion assumes that the first life required a container to maintain the integrity of the living system. Since this first replicater was extremely simple and probably was unable to catalyze the formation of the fatty acids needed to form vesicles it may have replicated while attached to a surface. In the simplest case the community of RNAs may have been attached to a mineral surface where it captured the necessary nutrients of life as they flowed past. There they could have also bound the metal ions that may have been required for the functioning of this extremely primitive system.

CHIRALITY Life on Earth is composed of a specific handedness of the molecules that it utilizes. For example the proteins are composed of L-amino acids and the RNA and DNA of D-nucleotides (Fig. 4). An L-amino acid is the mirror image of the corresponding D-amino acid and each mirror image molecule is called an enantiomer. It is not known why contemporary life has amino acids with the L-configuration and nucleotides with the D-conformation. One proposal is that it was a chance event that occurred during evolution when life based on D-amino acids and L-nucleotides was not able to compete with L-amino acids and D-nucleotides because of a favorable mutation in the latter. The latter life forms gradually took over the Earth and these configurations have been frozen in place ever since. Another theory is based on the observation of circularly polarized infrared light in the vicinity of interstellar dust clouds (Bailey et al. 1998). Circularly polarized light can be either left- or right-handed. It is proposed that if there is circularly polarized infrared radiation then there will also be circularly polarized UV radiation as well. It is known from laboratory studies that irradiation of a mixtures of enantiomers with one handed circularly polarized UV light results in the faster rate of loss of one of the enantiomers so that an excess of the other enantiomer is left behind (Flores et al. 1977). This postulate has some support by the observation of an excess of the L-enantiomer in some of the amino acids found in the Murchison meteorite (Pizzarello and Cronin 2000). If it is assumed that there is a correlation between the handedness of the circularly polarized light and the L-configurations of the interstellar amino acids reaching the Earth via meteorites then one could conclude that the

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Synthesis NH2

NH2

a.

Figure 4. Enantiomers. (a) the amino acid alanine, (b) the nucleoside adenosine.

NH2

NH2

b.

observed conformations resulted from the interstellar circularly polarized light. So far there has been no proof of this postulate.

PREBIOTIC POLYMERIZATION OF RNA MONOMERS The condensation of RNA monomers to oligomers in aqueous solution at pHs near neutrality is not favored energetically. The reactivity of the 5'-phosphate group must be activated for the reaction to proceed. In contemporary biochemistry the 5'-phosphate group is activated by the attachment of a diphosphate group to the 5'-nucleotide. The nucleotide triphosphate group is quite stable in aqueous solution and only generates RNA polymers in the presence of a polymerase enzyme. It was observed that some amine derivatives of the 5'phosphates (phosphoramidates) are effective activating groups for the monomeric nucleotides. Adducts of imidazole (Fig. 5a,b) and 1-methyladenine (Fig. 5c) have been observed to be effective activating agents (Weimann et al. 1968; Prabahar and Ferris 1997). Some montmorillonite clays have been shown to be effective catalysts of the oligomerization of both phosphorimidazolides and phosphoro-l-methyladenylides. It was possible to generate oligomers (short polymers) that contained 10 monomer units (10 mers) (Ferris and Ertem 1992). It was then observed that a synthetic 10 mer could be elongated to a 40-50 mer using "feeding reactions" where the activated monomer is added daily to the reaction mixture. The 40-50 mers were observed after feeding for 14 days (Ferris et al. 1996;

o

O

a. ImpB, R = H

HO

b. 2-MeImpB, R= CH3

OH

n

HO

CH 3 c. 1 -MeadpB

OH

d. a-activated nucleotide

Figure 5. Activated nucleotide monomers where B is a purine or pyrimidine base, (a) nucleoside 5'phosphorimidazolide (ImpB), (b) nucleoside 5'-phosphoro-2-methylimidazolide (2-MeImpB), (c) nucleoside 5'-phosphoro-l-methyladenium (1-MeadpB), (d) a - nucleoside 5'-phosphorimidazolide (a-ImpB).

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Ferris 2002). The previous studies were performed using imidazole as the activating group. It was recently observed that 40 mers were formed in 1 day when 1-methyladenine is used as the activating group (Huang and Ferris 2003). It is possible to form longer oligomers of RNA because the catalyst selectively directs the reaction pathway to the formation of a limited number of reaction products. If the catalyst were not selective then the formation of longer oligomers would not occur because all possible isomers would be formed and these side reactions would consume all the activated monomers before 40-50 mers are formed. It has been calculated that it would be required to form 1048 isomers weighting 1028 grams, an amount equal to the mass of the Earth, to prepare a mixture that contained two identical 40 mers (Joyce and Orgel 1999). Sequence selectivity was demonstrated in the montmorillonite-catalyzed reaction of a mixture of the four activated nucleotides. Here 80 % of the dimers formed were 8 of the 16 possible dimers (Ertem and Ferris 2000; Miyakawa and Ferris 2003). In the second study of the reaction of active ImpA with ImpC the pentamer fraction contained 4 main products in yields of 4.3-13 % while random synthesis would have generated 512 products with a 0.2% yield of each (Miyakawa and Ferris 2003). Selectivity was also observed in the formation of phosphodiester bonds. The montmorillonite-catalyzed reaction of ImpA generates oligomers in which about 67% of bonds formed were 3',5'-linked. In the absence of catalysis the percentage of 3',5'-phosphodiester bonds are about 20%. The outcome of the reaction of D,L- ImpA has been investigated to determine if oligomers form from a D,L-mixture. It was not expected that there would a selective reaction of only one of the enantiomers during montmorillonite catalysis because montmorillonite does not have D- and L-conformations. A preponderance of homochiral oligomers over what was expected was observed. That is there was an excess of both all D and all L-enantiomers over the expected yields of D,L- and L,D- dimers. Similar results were observed with the trimers formed. Heterochiral products predominate in the reaction of D,L-ImpU.

NON-ENZYMATIC TEMPLATE-DIRECTED SYNTHESIS OF RNA RNA is essential to early life because information is stored in its sequences of purines and pyrimidines. The process of template-directed synthesis preserves this information. Information is preserved in contemporary biological systems because the sequences in the RNA can be replicated in a two-step process from the complementary chain (Fig. 6a). The key to the replication process is the selective hydrogen bonded interactions with G and C (Fig. 6b) and those with A and U. In contemporary biology the monomers of the nucleotides that are activated

r r r r r r c c I I I I I I I I ! ! ! ! LJ

+

U

8-Mer of C

-, g

^

nnnnnnnn GGGG GGGG c c c c c c c c

-»-

t i i i i i r~ G G GG GG G c c c c c c c

G Monomers

—i r n

rn

rn

GGGG GGGG

+

c c c c c c c c

| I I Y I I I |

8-Mer of G m

f y-J

0---H-NH

y

M (/

\ / \

\ I G

q C

F i g u r e 6. Template-directed synthesis, (a) schematic replication of a template of the 8 mer of C and the formation of an 8 mer of G, (b) Watson-Crick hydrogen bonding between G and G.

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with the triphosphate group interact with their complementary bases in the RNA and then the monomers are coupled by a polymerase enzyme to form the complementary chain. The original chain and the complementary chains dissociate and the template directed synthesis takes place on the complementary chain to regenerate the original chain. The errors in this process provide a mechanism by which evolution occurs. Leslie Orgel and coworkers discovered that template-directed synthesis does occur to a limited extent in the absence of catalysis. The best example of this is the formation of oligomers of G by the reaction of 2-MeImpG (Fig. 5b) on a poly(C) template (Fig. 6a) (Inoue and Orgel 1981). Unfortunately the other possible template-directed syntheses are not as successful. The synthesis of oligo(A)s on a poly(U) template gives lower yields of shorter of oligo(A)s. The reactions of activated pyrimidine nucleotides on polypurine templates does not yield oligopyrimidines. Replication of an RNA chain is not possible in the G - C system because the formation of the complementary oligo(C)s on a poly(G) template was not successful. These observations suggest that the RNA world will need a catalyst (RNA?) or some changes in the reaction conditions or reagents to initiate the replication of RNA. It has been estimated that a library consisting of about 1020 sequences of 40 mers is likely to contain at least one self-replicating RNA molecule (Joyce and Orgel 1999). Mineral and/or metal ion catalysis may have generated the catalytic RNAs that catalyzed RNA replication but to date none been discovered.

ALTERNATIVE GENETIC SYSTEMS It was noted in "Nucleosides" that there are deficiencies with the currently proposed prebiotic syntheses of nucleosides and nucleotides. In addition, a plausible prebiotic formation of the activated monomers has not been accomplished. These deficiencies prompted the search for simpler monomers from which to form a replicating system with the expectation that this simpler system would in turn invent the RNA world. Carboxylic acid ester groups, polypeptides with interacting charged side chains, link some of the proposed polymers. In one instance it was proposed that a replicating clay mineral initiated the first life that catalyzed the formation of organic molecules that were more efficient than the clay as catalysts and they took over clay life to form life based on organic molecules (Cairns-Smith 1982). There are no experimental data to support the later hypothesis. A more complicated group of alternative biopolymers have incorporated some of the structural features of RNA, such as being II "O-P-O linked by phosphoester bonds and the utilization of the same bases and base pairings as RNA. Eschenmoser and coworkers initiated a research program to undertake a systematic investigation of structures that are similar to RNA and not the prebiotic synthesis of biopolymers (Eschenmoser 1999). Their first synthetic target was homo-DNA OH in which the five-membered ring of RNA was replaced with a sixmembered ring. Next they prepared pyranose-RNA (p-RNA), which Figure 7. Nucleotide also had a six-member ring in which the phosphodiester bond differed of threose. in location from that of homo-DNA. p-RNA also differed from homoDNA in that would form a double helix with a complementary strand. A recent addition to the RNA analogs is TNA, which is based on the four-carbon sugar threose (Fig. 7). This is especially interesting since it not only forms double helices with complementary TNA strands it also forms a double helix with a complementary RNA strand even though threose only contains one less carbon atom than ribose (Schoning et al. 2000). This structure has the advantage of a simple evolution of RNA from TNA by template-directed synthesis of RNA monomers on a TNA template. The TNA would have to have catalyzed the biosynthesis of the RNA monomers.

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A similar approach to preRNAs is peptide RNA (PNA), which was prepared as an analog of RNA, since it has about the same distances between the monomer units as RNA (Fig. 8). The other advantage of PNA is that it has no chiral centers. It forms double helices with itself and with RNA. Once it forms a double helix with RNA it assumes the chirality of the RNA to which it is bound. It can be used as a template for the formation of the complementary RNA (Bohler et al. 1995; Schmidt et al. 1997). One problem is that it has no charges on its backbone so longer oligomers are not likely to be soluble in water. There are no complete prebiotic synthesis of any of these pre-RNAs so it has not been demonstrated how they could have been formed on the primitive Earth (Miller 1997).

HpN

OH

H2N

a.

b.

Figure 8. PNA. (a) monomer, (b) oligomer.

EXAMPLES OF MINERAL AND METAL ION CATALYSIS IN PREBIOTIC CHEMISTRY Minerals and metal ions have been investigated as potential catalysts for prebiotic reactions. There are few general principles to guide the experimentalist in choosing a particular metal ion to catalyze a proposed prebiotic process. Their selection has been mainly based on (1) their ability to bind reactants (2) their utilization in contemporary biological systems to catalyze reactions similar to proposed prebiotic reactions (3) just try available metal ions. Examples of minerals and metal ions used to bring about prebiotic reactions and what is known about the source of their catalytic activity will be outlined here. It is my view that these catalysts were central to the formation of the biopolymers that were essential to the origin of life since it is unlikely that polymers could have formed without them.

Non-catalytic formation of biopolymers; polypeptides The simplest role that a mineral could play in the formation of biopolymer is to serve as a matrix on which polymers would bind and growth. These minerals are not catalysts so the key to the polymer growth is the increase in the strength of binding of the oligomer to the mineral as it increases in length. In addition, the rate of oligomer formation must be greater than its rate of hydrolysis. This procedure requires that the substrate binds to the mineral but does not require that the mineral catalyze the reaction (Ferris et al. 1996; Orgel 1998). Feeding reactions in which a condensing agent that is used to drive polypeptide formation from amino acids on mineral surfaces may generate polypeptides containing up to 50 monomer units. Hydroxyapatite, Ca 5 (P0 4 ) 3 (0H), binds the acidic amino acid glutamic acid via the Ca2+ of the mineral. After 50 feedings of the glutamic acid together with the condensing agent, l,l'-carbonyldiimidazole (CDI) (Fig. 9), in the presence of hydroxyapatite yields polypeptides containing up to 45 monomer units. Similar results were ob-

0

N ^ N ^ N ^ N \=/

\=I

Figure 9. The condensing agent 1,1 '-carbonyldiimidazole (CDI).

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tained using the clay mineral illite (Hill et al. 1998). Aspartic acid oligomers were formed on hydroxyapatite using l-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDAC) as the condensing agent but oligomer formation decreased when CDI was used as the condensing agent (Liu and Orgel 1998). The positively charged amino acid arginine was elongated on both illite and FeS 2 using CDI as the condensing agent. Variation of the structure of the amino acids used and the surface of the mineral indicates that the extent of oligomer formation depends on a number of factors (Hill and Orgel 1999). This procedure has not been successful with amino acids with not net charge, such as alanine, since they have weak binding interactions with the mineral surfaces. Montmorillonite catalysis of RNA synthesis Structure and properties of montmorillonite. Montmorillonite is a 2D sheet of corner linked Si0 4 tetrahedra bound to layers of edge-linked A10 6 octahedra (Fig. 10). The montmorillonite platelets associate with each other via interlayer cations and van der Waals forces. Montmorillonite is a clay mineral Key: formed by the weathering of volcanic O Oxygen ash. Its composition varies depending on the other elements present in the © Hydroxyl exchangeable cations environment where it is formed. Magwater layers o Aluminum nesium ion (Mg2+) ferrous ion (Fe2+) and ferric ion (Fe3+) are often incorporated • Silicon into the octahedral layer positions. In 3+ e Magnesium, Iron addition, Al may be substituted for tetravalent silicon (Si4+) in the tetrahedral silicate layer. While the theoretical formula is Al4Si802oOH)4, the actual formula for a Wyoming montmorillonite, with Fe3+ and Mg 2+ in the octahedral layer and Al in the tetrahedral layer and 0.67 monovalent exchangeable cations is (Al2.33Feo.6sMgo.47XSi7.71 Figure 10. The layer structure of montmorillonite. A1o.2902o(OH)4Xo.67. Since the number of oxygen atoms in the montmorillonite sheet is constant the lattice has a net negative charge that is balanced by the charge of 0.67 cations. The associated cations that neutralize this negative charge usually reside in the interlayers between the montmorillonite sheets. Dry montmorillonite expands when water is added due to the solvation of the interlayer cations. When organics bind in the interlayer the sheets come further apart if the binding energy between the sheets is less than the binding energy of the organic compound. Van der Waals interaction between organic molecules and the silicate layer is often the force that attracts organic compounds to bind in the clay interlayer. Montmorillonite found in deposits on Earth usually contains a mixture of cations in its interlayer that reflect those present in the environment where the montmorillonite is formed. Na+, Ca2+ usually predominate. It is possible to exchange this mixture of cations with a single cation in the laboratory to obtain a homoionic montmorillonite. This is usually done before investigating possible catalytic activity so as to avoid chemical processes due to the interlayer cations. Substances with multiple negative charges may bind at the acidic edges of the montmorillonite sheets. These include polyphosphates, dicarboxylic acids and polyanionic polymers. The edges have Al +3 with three oxygens bound to it. The fourth oxygen atom is not there because that is the bond where the sheet was broken. A water molecule will bind at Al +3 via the lone pair of electrons on the water molecule. This coordination enhances the acidity

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of the water molecules and generates an acidic site that can transfer a proton to a basic or a negatively charged molecule. RNA oligomer formation. In most of our studies on the montmorillonite-catalyzed formation of RNA oligomers homoionic Na + -montmorillonite was used. It was observed that other alkali and alkaline earth cations also gave catalytically active montmorillonites with the exception of Mg 2+ . When other divalent cations like Ni 2+ and Cu 2+ serve as the exchangeable cations the montmorillonite does not catalyze RNA oligomer formation. It was also observed that the acid titration exchange procedure of (Banin 1973; Banin et al. 1985) was essential for the preparation of most of these catalytically active montmorillonite. In most instances an alternative procedure where the clay is treated with an excess of NaCl to give Na + montmorillonite does not generate a catalytic montmorillonite. Not all montmorillonites catalyze oligomer formation. There may be a correlation between the increase in the iron content of the clay lattice and the increase in catalytic activity (Ferris et al. 1990). This potential correlation breaks down for the nontronites where Fe 3+ replaces almost all the Al3+. Binding studies established that purine nucleotides bind more strongly to montmorillonite than do the pyrimidine nucleotides. This is consistent with the greater van der Waals interactions between the purine ring and the silicate surfaces of the montmorillonite than the smaller pyrimidine ring (Kawamura and Ferris 1999; Ertem and Ferris 2000). That the reaction of activated mononucleotides occurs in the clay interlayer was determined by first treating the montmorillonite with tetraalkyl ammonium salts (Ertem and Ferris 1998). Dodecyltrimethylammonium cations (Fig. 11a) inhibit oligomer formation while tetramethyl ammonium ions (Fig. l i b ) did not. The inhibition resulting from the substituted quarternary ammonium salts is due to the positively charged quarternary ammonium group binding to the negatively charged clay lattice and hydrophobic interactions between the long alkyl groups of the quarternary ammonium salts in the interlayer. These alkyl groups fill up the interlayer and bind so strongly that they are not replaced by the activated RNA monomers.

a.H

H2

3

H2

H2

H2

H2

+

C,c,C.c,C.c,acX.c,C.c.N(CH

H2

H2

H2

H2

H2

H2

3

)3

CH3 +

b

C H 3

_,[j_

C H 3

CH3

Figure 11. Quarternary ammonium salts, (a) dodecyltrimethylammonium, (b) tetramethylammonium.

It has also been observed that the deoxypyrophosphate derivative, dA 5 'ppdA, (Fig. 12) inhibits oligomer formation (Wang and Ferris 2001). It is proposed that the strong inhibition by dA 5 'ppdA is the result of the van der Waals interaction of both adenine rings to the silicate layers so that it is not possible for an RNA monomer, with only one adenine ring, to displace it from the interlayer. The chemical reactivity of the 3'-OH of deoxynucleotides O O is much less than that of the 2',3'-hydroxyl 11 11 O -- P pI -- O --PpI - O groups of ribonucleotides so that reaction at the 3'-hydroxyIs of dA 5 'ppdA does not occur O" O" (Ferris and Kamaluddin 1989). OH OH The possibility that the catalysis occurred at the edge sites of montmorillonite was also

Figure 12. Deoxyadenosine pyrophosphate (dA5'pp5'dA).

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investigated (Ertem and Ferris 1998). Trimethylsilyl groups bound to the edge silanol groups or fluoride ion bound to the trisubstituted edge aluminum groups (Fig. 10) resulted in some levels of inhibition as determined from the slightly shortened chain lengths of the oligomers formed. This finding suggests the absence of edge catalysis because the formation of oligomers was not strongly inhibited. As noted in "Prebiotic Polymerization of RNA Monomers," the preparation of oligomers containing 40-50 mers has been achieved by two experimental approaches. These are feeding reactions where activated monomers are added daily for 14 days to a decamer primer yielded 50 mers and reactions where 1-methyladenine is used instead of imidazole as an activating group generate 3 5 ^ 0 mers in a one day (Huang and Ferris 2003). It is not clear why it has not been possible to generate oligomers longer than 40-50 mers. One possibility is the binding of the oligomers to montmorillonite increases, as the oligomers grow longer. Since oligomers must be mobile on the clay surface for them to react with activated monomers to increase in length, very strong binding may decreases their mobility on the surface so they block the catalytic sites in the interlayer. Another possibility is that the oligomers formed fill up the interlayer so no more activated monomers can be accommodated there. Uranyl ion catalysis of RNA oligomer formation. Uranyl ion (U0 2 2 - ) catalyzes of the formation of oligo(C)s, oligo(A)s and oligo(U)s with chain lengths up to 10, 16 and 10 mers, respectively, from the corresponding phosphorimidazolides of nucleotides starting compounds (Sawai et al. 1989) (Sawai et al. 1992). There are some similarities between the reactions catalyzed by U 0 2 2 - and montmorillonite. The optimal pH for both catalysts is 8; cyclic dimers are formed in high yields from the activated pyrimidine nucleotides. Mainly 2',5'- phosphodiester bonds form in reactions of activated pyrimidine nucleotides catalyzed by either U 0 2 2 - or montmorillonite. There are some differences in the reaction of Imp A catalyzed by U 0 2 2 - or montmorillonite. Neither cyclic dimers nor high yields of 3',5'-linked oligomers are formed in the U 0 2 2 - catalyzed reactions of ImpA. Higher yields of oligomers are observed in the U 0 2 2 - catalyzed reactions because the extent of the hydrolysis reaction of the activated monomers is much lower than that observed with montmorillonite. Catalysis of RNA oligomer formation by lead and other metal ions. Lead (Pb2+), zinc (Zn ) and lanthanide metal ions have been observed to catalyze the formation of 5-10 mers from ImpA. Pb 2+ is second only to U 0 2 2 - as a catalyst. The ratio of the yields of oligomers formed from the lanthanide metal ions to the yield of hydrolyzed activated monomer increases with the atomic weight of the metal ion where the highest ratio is 49 with Lutitium (Lu3+) (Sawai 1988; Sawai and Yamamto 1996). Zn 2+ gave results similar to those of Pb2+ except the longest oligomers observed were only tetramers and the oligomers formed had mainly 2',5'links (Sawai and Orgel 1975). 2+

The Pb2+ catalysis is enhanced when the reaction is performed in the eutectic liquid phase of water at - 1 8 °C for 2 0 ^ 0 days when most of the water is present as ice crystals. Ice predominates reactants and the Pb2+ catalysts are concentrated in the small liquid phase. Here oligomers as long as 17 mers are formed with overall yields of 80-90% (Kanavarioti et al. 2001; Monnard et al. 2002, 2003). The higher yields and longer oligomers are due in part to the high concentrations of reactants and the slower rate of hydrolysis of the activated monomers. It is postulated that base stacking and ordered monomer assemblies on the ice surfaces enhances the chain lengths in the eutectic phase but there is no specific data that supports this claim. Metal ion catalysis of template-directed synthesis Zn 2+ and Pb2+ catalyze the template-directed synthesis of RNA oligomers from ImpG and ImpA (Fig. 6a) (Sleeper et al. 1979; Lohrmann et al. 1980). Pb2+ catalyzes the poly(C) template-directed synthesis of mainly 2',5'-linked oligo(G)s that containing up to 40 mers.

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Pb2+ also catalyzes the formation oligo(A)s on a poly(U) template but the maximum chain length is only 7 mers. Here 75% of the phosphodiester bonds are 3',5'-linked. Zn 2+ catalysis of the template-directed synthesis of oligo(G)s in the reaction of ImpG on a poly(C) template gives oligomers as long as 30 mers that are 75% 3',5'-linked. When the reaction is performed in the absence of Zn 2+ the oligomers formed are mainly 2',5'-linked. Zn 2+ does not catalyze the template-directed formation of oligo(A)s. In the investigation of the reaction pathway it was observed that 2 Zn 2+ per ImpG gave optimal oligomer yields. One of the zinc ions can be replaced with Mg 2+ . X-ray structure analysis of the Zn2+-nucleotides complexes show Zn 2+ binding at both N7 and the phosphate of the nucleotide. It is tentatively proposed that in this complex one Zn 2+ binds to N(7) and either Zn2+ or possibly Mg 2+ binds to the imidazole (Birdson and Orgel 1980). No postulates on the reaction pathway of the template-directed reactions catalyzed by Pb2+ have been proposed other than the coordination of the lead ion with the 2'-hydroxyl of the nucleotide. The main basis for this suggestion is the preferential formation of 2',5'-phosphodiester bonds (Sleeper et al. 1979). Other metal ions have been tested as catalysts for the template-directed synthesis of oligo(G)s from ImpG besides Pb2+ and Zn 2+ (van Rode and Orgel 1980). Of the 17 tested, 4 (Bi3+, Sn2+, Sb3+, and Mn 2+ ) exhibited catalytic activity. All of these generated lower yields of oligomers than were formed by Pb2+catalysis and all the oligomers were linked by 2',5'phosphodiester bonds. The divalent transition metal ions that would be expected to coordinate with imidazole (Co2+, Ni2+, Cu2+and Cd2+) protect ImpG from hydrolysis and also inhibited catalysis. It is proposed that these metal ions bind to the imidazole of the activating group where they protect ImpG from hydrolysis and at the same time they inhibit oligomer formation. The research on the metal ion catalysis of template-directed synthesis stopped when it was observed that when the imidazole activating group was replaced with 2-methylimidazole metal ions were not required to enhance the formation 30 mers of oligo (G) s on a poly(C) template (Inoue and Orgel 1981).

POSSIBLE CATALYTIC REACTION PATHWAYS Since metal ions, RNA templates and montmorillonite clay all catalyze the reactions of nucleotides activated with imidazole at the 5'-position it may be possible to gain insight into the reaction pathway on montmorillonite by reviewing the mechanisms proposed for the catalysis by metal ions and RNA templates.

Metal ions U 0 2 2 - and Pb 2+ are effective while Zn 2+ and lanthanides metal ions are much less effective catalysts of the reactions of ImpN where N is A, U, G, C and I. In most cases the products formed are mainly 2',5'-linked. It is proposed that U 0 2 2 - forms a complex with the activated monomers that binds them in the correct orientations for the 2'-hydroxyl group of one monomer to react with the activated phosphate of the other monomer (Shimazu et al. 1993). In studies where the nucleotide base is inverted in the nucleotide, a a-nucleotide, (Fig. 5d) the longest oligomers formed are half as long as those formed from the natural P-nucleotide and the bonds formed were linked mainly by 3',5'-phosphodiester bonds (Sawai et al. 1997). It was not noted whether the U 0 2 2 - complex, formed from U 0 2 2 - monomers, binds a-ImpA in the proper orientations for reaction and whether this complex can also bind oligomers in the correct orientation for elongation. Reactions catalyzed by soluble metal ions are probably initiated by complex formation between the metal ion and the activated nucleotide. If the metal ion binds two or more activated

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nucleotides then they may be held in the proper orientation for reaction in the complex. An alternative proposal is the metal ion binds the activated nucleotide in a way that activates the 2'-hydroxyl group of the activated nucleotide. This postulate is supported by the observation that the best catalyst among the lanthanide series of metal ions is Lu3+, in which the bound water has the greater acidity, and as such should be the most effective metal ion for activating the 2'-hydroxyl group of the nucleotide (Sawai and Yamamto 1996). Metal ion catalysis of template-directed synthesis of RNA oligomers Metal ion catalyzed template-directed synthesis enhances the length of the oligomers formed over that of the catalysis by either the metal ions or the templates alone. The most successful metal ion catalysts are Pb 2+ and Zn2+. Pb2+ catalyzes the poly(C) template-directed synthesis of mainly 2',5'- linked G oligomers and the synthesis of mainly 3',5'-linked an oligomers on a poly (U) template. Zn 2+ catalyzes the template-directed synthesis of a mainly 3',5'-linked G oligomers on a poly(C) template. The observation that metal ions were not responsible for catalysis when the mononucleotide is activated with 2-methy limidazole suggests that they may not have a direct role in the activation of the mononucleotide for reaction. Rather the metal ion may just change the geometry of the double helix of the poly(C) template with the growing G oligomers so that the activated nucleotides are lined up for reaction (Birdson and Orgel 1980). This favorable orientation does not require the activation of either the 2'- or 3'-hydroxyl groups by a metal ion. A postulate for montmorillonite catalysis If it is assumed that similar pathways are followed in oligomer formation for metal ion, template-directed and montmorillonite-catalyzed synthesis of RNA oligomers it may be possible propose a possible mechanism for the montmorillonite-catalyzed synthesis of RNA oligomers. The observation that a 2-methylimidazole activating group is all that is needed to generate long oligomers from activated nucleotides suggests that the optimal orientation of the activated monomers for reaction is the key factor in the montmorillonite-catalyzed reaction. The failure of certain montmorillonites to be catalysts may be due to differences in the geometry of their interlayer from those of the catalytic clays. The proper orientation of the activated bound nucleotides has also been proposed to be an important factor in U 0 2 2 - and Pb 2+ catalysis as well. While activation of the 2'-hydroxyl group may be a factor with some of the metal ions it appears not to be a factor in the montmorillonite catalysis. The selectivity observed for reaction at either the 2'- or 3'-hydroxyl groups may be due to factors specific for each catalyst. The difference in selectivity for montmorillonite may be due to a difference in the orientation of the activated nucleotide when bound to the clay interlayer. This difference in orientation may be responsible for the selectivity for the formation of the 3', 5'-link with purine nucleotides and 2', 5'- links with pyrimidine nucleotides.

POTENTIAL STEPS TO THE ORIGIN OF LIFE FROM OLIGOMERS Research on the formation of RNA oligomers is based on the assumption that the requisite activated RNA monomers formed spontaneously on the primitive Earth. Progress has been made in their formation but no plausible prebiotic synthesis of the activated RNA monomers or the monomers that would the basis of any other genetic polymer has been reported at the time of this writing (see discussion in "Alternative Genetic Systems"). In this Section we will assume that a catalyst was found that generated a mixture of informational biopolymers on the primitive Earth that were sufficiently long to store genetic information and to catalyze reactions.

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The next question is how far away are these biopolymers from the formation of the first life? Since these polymers were formed catalytically it is reasonable to assume that there was selectivity in the synthesis of these oligomers so a limited number of isomers were produced (see discussion in "Prebiotic Polymerization of RNA Monomers"). Because it is a catalytic process a continuous supply of these structurally related oligomers were formed continuously. If the first life was based on a self-replicating system capable of mutations then the key step was the origin of the replication of these oligomers. In one scenario it is assumed that the first life is an array of oligomers bound on the mineral that catalyzed their formation. This would require that a subgroup of these oligomers, or the mineral-oligomer-complex, had the ability to catalyze their own synthesis while bound to the mineral. This group of catalytic oligomers would rapidly take over the mineral surface if their rates of replication were greater than the catalytic formation of oligomers by the mineral. In this scenario the subgroup of oligomers would serve as the catalysts and the templates for the synthesis. It is assumed that the rate of catalysis by the biopolymer will increase as a consequence of the selection of the more rapidly forming oligomers. Another important catalyst was one that catalyzed the ligation of the oligomers formed by mineral catalysis. This generates longer biopolymers with greater capability of storing more genetic information. Greater information storage will be essential for the evolution of the more complex biochemical machinery needed for the formation of more sophisticated forms of life. At some point in the above process the biomolecules will have to become independent from the mineral catalyst to which they are bound. This is because the higher molecular weight oligomers will bind more strongly to the minerals surface and block the catalytic sites. This dissociation could be a stepwise process where the oligomer-catalyst complex is encapsulated within a vesicle and then the oligomers are released from the catalyst. The direct incorporation of the catalyst-oligomer complex into a vesicle is an alternative to life originating on the surface of a mineral catalyst. A possible scenario for such an event has been described (Hanczyc et al. 2003; also see discussion in "Vesicles"). Here montmorillonite catalyzes both the formation of RNA oligomers and the vesicle that encapsulated the oligomercatalyst complex. The one flaw with this particular scenario is that the conditions necessary for the formation of the biopolymer destroys the vesicle (Monnard et al. 2002). It seems likely that there may be an alternative approach that will be successful in the incorporation of the mineral-catalyst inside a vesicle without destroying it. One can imagine the ingestion of molecules in the vesicle that elute the oligomers from the catalyst. Of course these molecules should do this without inhibiting the catalyst. The stages leading to a self-replicating system after the initial trapping of the biopolymer inside a vesicle will be similar to the ones described above for life originating in a family of biopolymers bound to a catalytic mineral. The main difference will be the need for the fission of the vesicle into two or more vesicles once it has reached a critical size (Walde et al. 1994).

PROPOSED EXPERIMENTS Selection of oligomers that bind to other biomolecules The oligomers formed by montmorillonite catalysis are long enough to fold into threedimensional structure that can bind to other RNA oligomers or other biomolecules (Joyce and Orgel 1999). Studies should be performed to determine if this binding does indeed occur. The selectivity observed in the oligomers formed by montmorillonite catalysis suggests that it is likely, if binding is observed, that an appreciable fraction of these oligomers will bind. If

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this occurs it possible that a small fraction of these oligomers will catalyze reaction(s) of the biomolecules to which they are bound. Catalysis of template-directed synthesis One of the essential catalytic processes required for the first life if the replication of RNA by template-directed synthesis. This is essential for the reservation of genetic material as well as the preservation of catalytic RNA. As noted in "Non-enzymatic Template - Directed Synthesis," the non-enzymatic template-directed synthesis is only successful in the formation of G oligomers on a C-template or on a template that contains more cytidine nucleotides than guanosine nucleotides. Catalysis is needed to enhance the rates of formation of RNAs that contain A, U and C nucleotides. The potential catalysts include RNA oligomers and minerals. There are examples of the template-directed synthesis of G-oligomers on a polyC template bound to minerals (Schwartz and Orgel 1985; Holm et al. 1993). So far no minerals have been detected that enhance the rates of template-directed synthesis of activated nucleotides over that from RNA templates alone. Catalysis of RNA ligation Some of the oligomers formed by montmorillonite catalysis are long enough to be catalysts but the bulk of the oligomers are not. A ligation catalyst that would link these smaller oligomers would enhance the pool of longer oligomers. An RNA catalyst of this type would generate longer oligomers that have similar structures because it would have a template that would simultaneously bind two oligomers close enough so that they could form a phosphodiester bond between them. While it is likely that the ligation catalyst would be another RNA molecule it is also possible that a mineral would catalyze phosphodiester bond formation between two oligomers.

ACKNOWLEDGMENTS Research support was provided by NSF grant CHE-0413739 and NASA grant NAGS12750 that supports the NY Center for Studies on the Origins of Life.

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Miller SL (1997) Peptide nucleic acids and prebiotic chemistry. Nature Structural Biology 4:167-169 Miyakawa S, Cleaves HJ, Miller SL (2002) The cold origins of life: B. Implications based on pyrimidines and purines produced from frozen ammonium cyanide solutions. Origins Life Evol Biosphere 32:209-218 Miyakawa S, Ferris JP (2003) Sequence- and regioselectivity in the montmorillonite-catalyzed synthesis of RNA. J Am Chem Soc 125:8202-8208 Mojizsis SJ, Arrhenius G, McKeegan KD, Harrison TM, Nutman AP, Friend CRL (1996) Evidence for life on Earth before 3,800 million years ago. Nature 384:55-59 Monnard P-A, Apel CL, Kanavarioti A, Deamer DW (2002) Influence of ionic inorganic solutes on selfassembly and polymerization processes related to early forms of life: implications for a prebiotic aqueous medium. Astrobiology 2:139-152 Monnard P-A, Kanavarioti A, Deamer DW (2003) Eutectic phase polymerization of activated ribonucleotide mixtures yields quasi-equimolar incorporation of purine and pyrimidine nucleobases. J Am Chem Soc 125:13734-13740 Moorbath S (2005) Dating earliest life. Nature 434:155-155 Miiller D, Pitsch S, Kittaka A, Wagner E, Wintner CE, Eschenmoser A (1990) Chemie von a-Aminonitrilen. Aldomerisierung von Glycolaldehyd-phosphat zu racemischen Hexose-2,4,6-triphosphaten und (in Gegenwart von Formaldehyd) racemischen Pentose-2,4-diphosphaten: rac-Allose-2,4,6-triphosphat und rac-Ribose-2,4-diphosphat sind die Reaktionshauptprodukte. Helvetica Chimica Acta 73:1410-1468. Orgel LE (2004) Prebiotic chemistry and the origin of the RNA world. Critical Revs Biochem Mol Biol 39: 99-123 Orgel LE (1998) Polymerization on the rocks: theoretical introduction. Origins Life Evol Biosphere 28:227234 Osterberg R, Orgel LE (1972) Polyphosphate and trimetaphosphate formation under potentially prebiotic conditions. J Mol Evol 1:241-248 Osterberg R, Orgel LE, Lohrmann R (1973) Further studies of urea-catalyzed phosphorylation reactions. J Mol Evol 2:231-234 Pizzarello S, Cronin JR (2000) Non-racemic amino acids in the Murray and Murchison meteorites. Geochim Cosmochim Acta 64:329-338 Pizzarello S, Huang Y, Becker L, Poreda RJ, Nieman RE, Cooper G, Williams M (2001) The organic content of the Tagish Lake meteorite. Science 293:2236-2240 Prabahar KJ, Ferris JP (1997) Adenine derivatives as phosphate-activating groups for the regioselective formation of 3',5'-linked oligoadenylates on montmorillonite: possible phosphate-activating groups for the prebiotic synthesis of RNA. J Am Chem Soc 119:4330-4337 Ricardo A, Carrigan MA, Olcott AN, Benner S (2004) Borate minerals stabilize ribose. Science 303:196 Rushdi AI, Simoneit BRT (2001) Lipid formation by aqueous Fischer-Tropsch-type synthesis over a temperature range of 100-400 °C. Origins Life Evol Biosphere 31:103-118 Sawai H (1988) Oligonucleotide formation catalyzed by divalent metal ions. The uniqueness of the ribosyl system. J Mol Evol 27:181-186 Sawai H, Higa K, Kuroda K (1992) Synthesis of cyclic and acyclic oligocytidylates by uranyl ion catalyst in aqueous solution. J Chem Soc Perkin 1:505-508 Sawai H, Itoh T, Kokaji K, Shinozuka K (1997) An approach to prebiotic synthesis of a-oligoribonucleotides and description of their properties: selective advantage of p-RNA over a-RNA. J Mol Evol 45:209-215 Sawai H, Kuroda K, Hojo T (1989) Uranyl ion as a highly effective catalyst for internucleotide bond formation. Bull Chem Soc Jpn 62:2018-2023 Sawai H, Orgel LE (1975) Oligonucleotide synthesis catalyzed by the Zn 2+ ion. J Amer Chem Soc 97:35323533 Sawai H, Yamamto K (1996) Lanthanide ion as a catalyst for internucleotide bond formation. Bull Chem Soc Jpn 69:1701-1704 Schmidt JG, Nielson PE, Orgel LE (1997) Information transfer from peptide nucleic acids to RNA by templatedirected synthesis. Nucleic Acids Res 25:4797-4802 Schoning K-U, Scholz P, Guntha S, Wu X, Krishnamurthy R, Eschenmoser A (2000) Chemical etiology of nucleic acid structure: The a-threofuranosyl-(3 -2') oligonucleotide system. Science 290:1347-1351 SchopfWJ (1993) Microfossils of the early Archean Apex chert: new evidence of the antiquity of life. Science 260:640-646 Schwartz AW, Orgel LE (1985) Template-directed polynucleotide synthesis on mineral surfaces. Letter to the Editor. J Mol Evol 21:299-300 Shimazu M, Shinozuka K, Sawai H (1993) U0 2 2+ -catalyzed oligothioadenylate synthesis with high regio- and stereoselectivity. Angew Chem Int Ed Engl 32:870-872 Sleeper HL, Lohrmann R, Orgel LE (1979) Template-directed synthesis of oligoadenylates catalyzed by Pb2+ ions. J Mol Evol 13:203-214

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9

Reviews in Mineralogy & Geochemistry Vol. 59, pp. 211-231,2005 Copyright © Mineralogical Society of America

The Evolution of Biological Carbon and Nitrogen Cycling—a Genomic Perspective Jason Raymond Microbial Systems Division Biosciences Directorate Lawrence Livermore National Laboratory Livermore, California, 94550, U.S.A. jason. raymond@ llnl. gov

INTRODUCTION Carbon and nitrogen are essential to all living organisms, owing to their abundance and remarkable characteristics when participating in chemical bonds. Their essentiality dates back to the very origin of life, where current theories hypothesize either a prebiotic abundance of organic compounds rich in carbon and nitrogen, or an ability to assimilate them inorganically through abiotic reactions that might have been catalyzed on ancient mineral surfaces. This chapter details the core reactions essential to the assimilation of these elements in biologically useful forms—the so-called fixation of carbon and nitrogen—focusing on recent literature and insights from comparative genomics and phylogenetics. Though considerable debate continues on the antiquity of these pathways, especially whether or not they might have been present in the last common ancestor (LCA) of modern organisms, it is clear that carbon and nitrogen fixation pathways were of crucial importance to the primitive ancestors of extant life. Furthermore, the biological assimilation of inorganic carbon (autotrophy) and atmospheric nitrogen (diazotrophy) represent pivotal juxtapositions of biological and geological cycles. It is thought that atmospheric C 0 2 concentrations have decreased substantially since the proposed origin of life some 3.8 billion years ago, due in large part to either primary (fixation) or secondary (e.g., weathering) influence by biota (Hayes 1994; Rye et al. 1995; Des Marais 1997; Lowe and Tice 2004). Though the biosphere accounts for a relatively small fraction of the total carbon on Earth, the rate of carbon flux through the biosphere far exceeds that through any geological reservoirs (Des Marais 1997). Biological carbon fixation is closely balanced to carbon recycling through biological oxidation, and the future stability of this and other C 0 2 reservoirs (and our ability to influence or understand them) depends critically on these biological underpinnings (e.g., Falkowski et al. 2000). Conversely, nitrogen, especially the atmospheric N 2 reservoir, is remarkably stable, owing largely to the stability of the N-N triple bond and the relative inertness of the molecule. In fact, many environments are considered nitrogen limited, meaning that biologically available nitrogen is essentially locked up in biomass. Thus many ecosystems are dependent upon diazotrophs, prokaryotes that can convert atmospheric N 2 into ammonia by way of the enzyme nitrogenase. As is detailed below, this enzyme is thought to be ancient and is extremely sensitive to oxygen; nitrogen-fixing bacteria and archaea are either anaerobic or have evolved elaborate mechanisms for shielding nitrogenase from molecular oxygen. It is estimated that as nitrogenase fixes of the same order per year as all anthropogenic and abiotic processes combined, including the industrial Haber-Bosch process and the lightning-catalyzed production of nitrate that (prior to Haber's revolutionary invention) formed the basis for profitable mining industries, especially in arid areas such as Chile's Atacama. 1529-6466/05/0059-0009505.00

DOI: 10.2138/rmg.2005.59.9

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Raymond USING GENOMICS TO UNDERSTAND THE PRESENT (AND INFER THE PAST)

At present, 254 prokaryotic and 20 eukaryotic genomes have been completed, with over 400 and 200 more, respectively, progressing through various pipelines around the world. The term comparative genomics—once an applied discipline unto itself—is arguably redundant, as the wealth of sequence data now available obliges genomics to be inherently comparative. More specifically, given a single gene or chromosome sequence, ab initio prediction of a protein's structure, function, and interactions are still far beyond current capabilities, and simply predicting the position and arrangement of coding sites given a "universal" genetic code is imprecise even in the simplest prokaryotic genomes. The bootstraps upon which our vast repositories of genetic information are propped stem ultimately from the comparison of new sequences with previously characterized evolutionary "relatives"—homologous proteins that have been painstakingly expressed and characterized. Thus our understanding hinges on our knowledge of molecular evolution, how processes such as natural selection and horizontal gene transfer alter gene sequences and the function of an organism's proteins. Widely used function prediction front-ends, such as NCBI's BLAST sequence vs. database comparison tool, are essentially distilled algorithms for determining a protein's phylogeny, in particular for finding homologs with known functions. Fast database search tools are typically sufficient for assessing homology between sequences and annotating a newly sequenced genome, but a wealth of additional information can be obtained by looking not just at whether a group of sequences is related, but how they have changed through time. The textbook example is how natural selection has promulgated variability in the immunoglobulin antigen-recognition domain, thereby increasing the robustness of vertebrate immune systems (Tanaka and Nei 1989). Phylogenetic analysis of enzyme families, such as those presented in this chapter for proteins involved directly in carbon and nitrogen cycling, give insight into how metabolic capabilities and pathways have evolved. For example (as is discussed below), since diverging from its homologs in chlorophyll biosynthesis pathways, it is possible to elucidate how the enzyme nitrogenase has become progressively more specific for atmospheric dinitrogen as a substrate, even though the mechanism, structure, and cofactor complement of the enzyme has been largely retained in these functionally diverse pathways. Likewise, one can envisage how the reductive tricarboxylic acid cycle, used by diverse and deeply-branching organisms for "fixing" C 0 2 into biomass, likely evolved from a much simpler pathway by duplication of a few ancient genes followed by improved substrate specificity. Taken as a whole, the function of the expressed protein complement encoded within an organism's genome comprises its metabolome and, in essence, comprises its phenotype: how and under what conditions an organism can thrive. Connecting the dots between the genome-encoded genotype and the functional phenotype represents the next major frontier in biology, with two major hurdles that so-called functional genomics must overcome. The first is that, at a given time and under varying conditions, not all of the protein complement of a genome is translated into protein. High-throughput determination of this "business end" is presently being attacked both at the transcriptional level, using microarrays and gene chips to quantify mRNA levels, and also at the proteome level, in particular using high resolution mass spectrometers to identify fragments of proteins being expressed by an organism under varying conditions. Theoretical advances have also been made using metabolic network modeling methods such as flux balance analysis, which can correctly segregate important versus redundant metabolic pathways by optimizing flux through a metabolic network under a given set of (environmentally-imposed) boundary conditions. The second major hurdle in connecting genotype to phenotype is the remarkable paradox presented by so-called hypothetical proteins of unknown function, paradoxical because their

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presence and relative abundance has continued almost unabated since the first genomes became available a decade ago. Specifically, this means that every new genome sequenced will have on average of 1/3 of its putative proteins with no clear homologs in any protein database or in any other genome (Bork 2000)—a veritable Red Queen principle that appears only to be solvable by bench-top biochemical characterization. However, it is not difficult to envision how high-throughput proteomics and microarray analysis will give insight into the function of hypothetical proteins, giving insight into whether and when a particular protein is expressed (Ram et al. 2005). As we learn how to decode and interpret their genomes and proteomes, microorganisms present an unrivalled diagnostic tool for understanding the physical chemistry and dynamics of natural environments, highly-tuned to their surroundings and possessing a remarkable capacity to adjust their metabolic repertoire and/or community organization in response to changing conditions. This raises the attractive possibility that an understanding of microbial evolution can provide a glimpse into the past. While this appears to hold true for many cases, for example the near-concurrence in the geological and biological records of the evolution of oxygenic photosynthesis and mitochondrial-based respiration, the plasticity with which organisms, pathways, and individual genes have evolved and, in the latter case, been horizontally transferred stand as important caveats. In particular, relying on so-called "universal" phylogenies to infer characteristics of ancient organisms is fraught by the assumption that modern lineages have somehow remained metabolically "frozen," a difficult tenet to hold in light of the remarkable geological changes the Earth has undergone and given the proclivity and non-linearity through which evolution sometimes acts.

BIOLOGICAL NITROGEN CYCLING AND DIAZOTROPHY In modern organisms, assimilation of inorganic nitrogen is universally shunted through ammonia (as the ammonium cation), representing the central inorganic nitrogen source and further suggestive of a pivotal role in the early evolution of life. Though nitrate and nitrite are important inorganic nitrogen sources for extant organisms, these compounds were of fleeting abundance on the early Earth and probably played a minor role until their concentration increased following the oxidation of Earth's atmosphere (see discussion below). Numerous transmembrane permeases transport ammonium into cells, whereafter it is enzymatically incorporated into carbon skeletons of central metabolites. This juxtaposition of the carbon and nitrogen cycles is carried out by a highly conserved set of enzymes comprising the GS/GOGAT cycle, illustrated in Figure 1. The enzyme glutamine synthetase (GS) adds ammonium to glutamate to form glutamine, which then is used as a substrate in the amination of 2-oxoglutarate by glutamine:2-oxoglutarate aminotransferase (GOGAT or glutamate synthase). This results in the cyclic formation of two molecules of glutamate—regenerating the original glutamate substrate and freeing a second glutamate to be used in other metabolic reactions. The products of this central cycle, glutamate and glutamine, serve as the ultimate nitrogen donors for all additional nitrogen-containing metabolites through a cascade of aminotransferase reactions. Regulatory response to combined nitrogen availability is tightly queued to the intracellular ratio of glutamine to 2-oxoglutarate, further underscoring the centrality of this intersection between carbon and nitrogen assimilatory pathways. This overlap between pathways has also garnered substantial interest in the evolutionary history of the key enzymes, glutamine synthetase and glutamate synthase. Glutamine synthetase is a multisubunit enzyme (homododecameric in bacteria, homooctamer in many eukaryotes, including Homo sapiens) that catalyzes the ATP-dependent condensation of ammonium with glutamate. The wide distribution of this enzyme across all three domains of life argues that the enzyme is ancient, notably comprising two major classes

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Figure 1. GS/GOGAT cycle, as discussed in the text. Boxes over arrows indicate enzymes responsible for the biochemical reactions shown. Pathways are abbreviated for simplification.

(GSI and GSII) of enzymes whose duplication origin has been argued to predate the LCA. Early attempts to date major divergences on the tree of life used this early duplication as time zero, along with an argued "clock-like" evolution among GS proteins that remains controversial (Pesole et al. 1991; Brown et al. 1994). So far, the GSI family is exclusive to bacteria, whereas eukaryotes possess only GSII. Some bacteria, most notably the rhizobia, express both forms of GS (Turner and Young 2000). Archaea also contain GSI, with euryarchaeotes sharing a highly similar GSI (GSI-a) with Gram-positive bacteria and Thermotoga, with horizontal gene transfer as a very likely explanation for this distribution (see below). Sulfolobus and other crenarchaeotes, however, possess GSI's that are phylogenetically distinct from the GSI-a or GSI-P (bacterial) clades, with functional and phylogenetic features intermediate between the bacterial and euryarchaeal enzymes (Cabello et al. 2004). Within both classes of GS are examples of HGT, potentially confounding their evolutionary history. Some of the strongest early evidence for HGT came from analysis of the GSI family, where interdomain transfer between Gram-positive bacteria and euryarchaeotes is clear) which, intriguingly, is similar to the pattern of interdomain (bacteria archaea) transfer evident in analysis of nitrogenase genes (discussed below) (Pesole et al. 1995; Nesbo et al. 2001). It is not yet clear whether these similar patterns of gene transfer are in fact linked—for example, as an adaptation specific to biological nitrogen cycling—or the result of a more extensive, nonspecific exchange of genetic information (as is suggested by recent whole genome analysis of methanogens; e.g., Deppenmeier et al. 2002). HGT also obfuscates the phylogeny of the GSII family, noted originally among the rhizobia (Turner and Young 2000). The evolution of GOGAT/glutamate synthase, shown in Figure 2, is even more perplexing. The enzyme itself comes in several different flavors that vary by their obligatory (two) electron donor, which can be ferredoxin, NADH, or NADPH. Most bacteria possess NADH- or NADPH-dependent GOGAT's, with some specificity within taxa such as NADH dependence in many proteobacteria versus NADPH dependence in Gram-positive Bacillus subtilis (Suzuki and Knaff 2005). The GOGAT from cyanobacteria is ferredoxin-dependent, as is that found in the plastids of photosynthetic eukaryotes. Alternatively, non-photosynthetic eukaryotes and

Evolution of Biologic C & N Cycling—Genomic

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J T3 > , 0 O w • e ' M s CD w-5 a 3 a § I 5 2 -60 3 S 6 8 CD —< 1 CD CD• ? S3 c < 3 R §< S & .H m •s ™ £ CD Q u > C H 3 C O O H + 2 H 2 0 + n ATP with an overall change in free energy of dG° = - 9 5 kJ/mol (Muller 2003). This pathway is unique among known autotrophic assimilation pathways in allowing fixation concomitant with generation of ATP. Importantly, this dual role of energy generation and carbon fixation is not universal among microorganisms, many of which have components of the Wood-Ljungdahl pathway but are not autotrophs. Whereas methanogens, acetogens, and aerobic carboxydotrophs depend upon the pathway for chemoautotrophy and subsequent biosynthesis (and thereby actively take up C 0 2 f r o m the environment), many non-autotrophic anaerobic fermenters utilize this pathway to further reduce C 0 2 generated f r o m pyruvate decarboxylation to C O (Ragsdale 2004). The key enzyme for the reduction of C 0 2 to C O is carbon monoxide dehydrogenase (CODH), which catalyzes this reversible reaction using a variety of electron donors. The enzyme is one of a handful of enzymes that requires elemental nickel, though an oxygen-tolerant C O D H that apparently utilizes molybdenum rather than nickel has been characterized f r o m carboxydotrophs (Meyer et al. 1990). The other key enzyme in this pathway, acetyl-CoA synthase (ACS), has also been shown to contain two nickel atoms complexed to an ironsulfur cluster (despite their common nickel-containing metal clusters, ACS and C O D H are not thought to be homologous) (Hegg 2004). In autotrophs, the ACS enzyme forms a bifunctional complex with C O D H , where C O generated by C 0 2 reduction is passed through a protein "channel" f r o m C O D H to ACS, then combined with methane and coenzyme A (CoA) to form acetyl-CoA (Hegg 2004; Ragsdale 2004). Figure 4 shows the C O D H phylogeny, inferred f r o m sequences of completely sequenced genomes. As can be observed, gene duplication has been extensive, and there is a lack of overall taxonomic cohesion, as in the paraphyly of methanogens. Bootstrap support and conserved sequence signatures suggest that the phylogeny is robust overall, and that horizontal gene transfer is a good explanation for some of the topology. A number of more distant C O D H homologs are excluded f r o m this tree. These include the hydroxylamine reductase/hybrid cluster protein—to which C O D H is still closely related enough to be "converted" into by sitedirected mutagenesis (Heo et al. 2002)—along with very distantly related C O D H homologs f r o m other bacteria and archaea that may carry out unrelated functions.

THE rTCA CYCLE With the exception of aerobic carboxydotrophs briefly mentioned above, both the WoodLjungdahl pathway and reverse or reductive tricarboxylic acid (rTCA) cycle are typically the realm of anaerobic or microaerobic autotrophs, thanks in part to 0 2 -sensitivity of many of their key enzymes. The r T C A cycle, as its name implies, is the conceptual "reverse" of the familiar T C A (also Krebs or citric acid) cycle which, rather than oxidizing acetate (to two molecules of C 0 2 ) concomitant with the production of reducing equivalents, uses reducing equivalents to fix C 0 2 ultimately to acetyl-CoA. The net production of acetyl-CoA is also found in the Wood-Ljungdahl pathway, though the r T C A cycle differs in being endergonic and cyclic/network autocatalytic (cycle intermediates can serve as templates for their own synthesis and—as "carriers" of assimilated carbon—are not consumed as the cycle propagates). Three key enzymes of the r T C A cycle distinguish it f r o m the archetype Krebs cycle: fumarate reductase, ATP citrate lyase, and 2-oxoglutarate:ferredoxin oxidoreductase. 2-oxoglutarate:ferredoxin oxidoreductase catalyzes the carboxylation of succinyl-CoA,

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Figure 4. CODH protein phylogeny, constructed as described in the legend for Figure 2. Numbers indicate duplicate CODH copies in a single genome. Many organisms in fact have two or more CODH paralogs, and the interspersed bacterial-archaeal phyla indicate a highly nonvertical evolution likely beset by horizontal gene transfer. Methods as given in Figure 2.

forming 2-oxoglutarate. ATP citrate lyase catalyzes the citrate "cleavage" that closes the cycle, forming oxaloacetate and acetyl-CoA. 2-oxoglutarate:ferredoxin oxidoreductase is a member of the diverse thimine diphosphate-dependent 2-oxoacid oxidoreductases and, along with its homolog pyruvate:ferredoxin oxidoreductase (PFOR), is able to "reverse" the oxidative decarboxylations carried out by unrelated dehydrogenases of the Krebs cycle, incorporating C 0 2 into biomolecules. The evolutionary history of PFOR, key in synthesizing pyruvate from acetyl-CoA in Wood-Ljungdahl as well as rTCA autotrophs, is shown in Figure 5. The phylogeny is congruent in many respects with the 16S rRNA-based tree of life, but the enzymes are clearly overrepresented in organisms that have an obligately or facultatively anaerobic lifestyle (with notable exceptions to both of the previous points). As with the Wood-Ljungdahl pathway, the rTCA cycle is also found among diverse prokaryotes, many of which are early-branching lineages on the tree of life. The pathway was first described from the obligately anaerobic, non-oxygen producing phototroph Chlorobium tepidum, where the electrons generated during photosynthesis eventually enter into the rTCA cycle for carbon fixation (Evans et al. 1966). So-called Knallgas bacteria (metabolizing via 2H 2 + 0 2 —» 2H 2 0), such as members of phylum Aquificales, are microaerophiles that use the rTCA cycle. The pathway is also found in autotrophic Crenarchaeota, sulfate-reducing bacteria, and in some chemolithotrophic epsilon Proteobacteria (Shiba et al. 1985; Schafer et al. 1986; Schauder et al. 1987; Hugler et al. 2005). Remarkably, several of the key enzymes from the rTCA cycle are found among a broad range of aerobic heterotrophs. Citrate lyase, for example, has homologs in humans and other vertebrates that function in fatty acid metabolism

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A.variabili$1964 Nostoc sp\2284 C. watsonii\ 1367 Synechocystis 6803\2805 A. variabilis\4948 Nostoc sp\3176

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— S.elongatus\8SS

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— R.rubrum\2304 C.aurantiacus\1199 • M. capsulatum 13637 S.typhi\1244

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H.mobilis\1691

-

C.pertringens\2124 C.acetobutylicum\2199

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D.hafhiense\204 C.acetobutylicum\2466 -

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S.tokodaii\1662 S.tokodaii\1937 S.solfataricu$2501 A.fulgidus dsm4304\2021 -

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Euryarchaeotes

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.thermoautotrophicum\1700 M.kandleri\82 M.jannaschii\271 M.maripaludis\1505

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P.furiosu$966 P.abyssi\1344

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horikoshii\710

Figure 5. Pyruvate:ferredoxin oxidoreductase (PFOR) protein phylogeny. As discussed in the text, PFOR is a decarboxylating enzyme found in both heterotrophs and autotrophs and functions reversibly as a key carboxylating enzyme in therTCA and Wood-Ljungdahl pathways. There is a clear stratification of bacteria (top clade) and archaea (bottom clade), with distributions loosely consistent with phylum-level taxonomy (shown in boxes; asterisks indicate notable deviations). Methods as given in Figure 2.

and biosynthesis (Wahlund and Tabita 1997). Thus detection of the rTCA cycle as a suspected

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autotrophic pathway in new organisms must be based on multiple factors—phenotype and the presence of all key genes—rather than the presence of any single diagnostic gene. The rTCA cycle has been argued by some authors to have been a pivotal pathway not only in the evolution of life but in the origin of metabolism. The pathway occupies a unique position at the hub of most metabolic networks, with metabolites used as precursors in biosynthesis of all major classes of biochemical compounds. Several of the enzymatic steps have plausible prebiotic analogs, most notably discussed by Wachtershauser in his hypothesis for primitive sulfur-linked "thioanalogs" of modern rTCA cycle intermediates (Wachtershauser 1990). This had the argued advantage of overcoming the unfavorable kinetics of several reactions, e.g., beta-carboxylations, of the rTCA cycle as well as inevitably linking this early metabolism with a sulfur/pyrite-rich interface. Thermodynamically unfavorable reactions could thereby be coupled to pyrite oxidation, much as coupling to ATP hydrolysis provides the basis for difficult modern biochemical reactions (Bebie and Cody 2000). These arguments have also been carried forth by Smith and Morowitz (2004), who argue that such a network-autocatalytic (self-replicating), redox-intermediate cycle is exactly what natural selection might be expected to produce. However, in the absence of catalysis, detractors point out that several critical steps in the pathway are simply not expected as favored outcomes (Orgel 2000). Because many of these arguments focus on pre-LCA metabolism, they are simply beyond the resolution of comparative genomics and phylogenetics. While the centrality of the rTCA cycle in metabolic charts is striking, it could just as likely represent a favorable but relatively recent reorganization of pre-existing metabolic pathways.

THE CALVIN-BENSON-BASSHAM CYCLE The Calvin-Benson-Bassham (CBB) cycle represents the best known of the autotrophic pathways, most notably because it is the only one present in eukaryotes, making it amenable to now-infamous large scale preparations from e.g., spinach for biochemical and biophysical studies. The key enzyme of the pathway, ribulose-l,5-bisphosphate carboxylase/oxygenase (RuBisCO), is the key enzyme of the cycle. The enzyme itself falls somewhere between evolutionary enigma and embarrassment, having a turnover rate of only a few carboxylation reactions per second and also carrying an intrinsic, energetically wasteful proclivity for using molecular oxygen, rather than carbon dioxide, as a substrate. Photoautotrophs, plants in particular, attempt to compensate for RuBisCO's inefficiencies by overexpressing the enzyme, and as a result RuBisCO is by far the most abundant protein in perhaps the largest biomass group on the planet, making it arguably the most abundant enzyme on Earth. The CBB cycle is in essence split into three separate phases. The first stage, carboxylation or carbon fixation, takes place by the RuBisCO-catalyzed addition of C 0 2 to ribulose bisphosphate, a C 5 sugar that is synthesized from ribose-l,5-bisphosphate by the other key/ unique enzyme of the Calvin cycle, phosphoribulokinase (PRK). The carboxylation step is exergonic and essentially irreversible, though the overall cycle is net endergonic. The resultant C 6 sugar is subsequently cleaved to two C 3 3-phosphoglycerates, which are converted to glyceraldehydes 3-phosphates (G3P)—a highly utilized carbon "currency" in many cells— during the so-called reductive phase of the CBB cycle. The reductive phase requires a net input of ATP and NADPH. Because a 3C compound is output, the Cycle must turn three times per G3P generated, so that cycle intermediates are not depleted. The regeneration phase of the cycle then incorporates a number of ATP-dependent aldolase and isomerase steps to regenerate the 5C precursor to RuBisCO carboxylation. The competing oxygenase activity of RuBisCO results in aprocess termed photorespiration, whereby 0 2 rather than C 0 2 combines with ribulose-1,5-bisphosphate, yielding one molecule of 3-phosphoglycerate and another of 2-phosphoglycolate. This latter compound must be

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salvaged—reconverted into usable 3-phosphoglycerate in a series of reactions that require both ATP and NADH. As this salvage pathway does not result in fixed carbon and requires energy and reducing equivalents to amend, photorespiration may reduce the efficiency of the Calvin cycle by as much as 50%. To counter the effects of photorespiration, a suite of novel carbon concentrating mechanisms (CCM's) have evolved to ramp up the ratio of C 0 2 to 0 2 inside cells and chloroplasts (e.g., Badger et al. 2002), responsible for, among other adaptations, the carboxysome that is among the largest known enzyme aggregates. Notably, some recent evidence suggests that photorespiration may in fact be important in higher plants as an energy sink or source of metabolites (Wingler et al. 2000). The evolutionary history and diversity of the Calvin cycle has been studied in great detail, as evidenced by the enormous repository of RuBisCO gene sequences (~25,000) available in GenBank. A disproportionately large number of these sequences are from eukaryotes, so the focus here is constrained to the more diverse RuBisCO (large subunit) sequences available from completed prokaryotic genomes. As illustrated in Figure 6, several distinct clades are evident in the phylogenetic tree, and importantly some of these represent proteins not known to function within the Calvin cycle, as evident based on active site substitutions, absence of PRK, and experimental verification. True RuBisCO's fall into two groups, so-called form I and form II (with subgroups within each) that highlighted on the tree. Form III and IV homologs of RuBisCO, the so-called RuBisCO-like-proteins (RLP's), have become a recent focus of several investigations. A suite of recent experiments by Tabita and colleages has illustrated quite compellingly that the form III RuBisCO homologs are able to fix atmospheric C 0 2 , using a functional analog of PRK to generate a substrate for the enzyme (Finn and Tabita 2004). While it is not evident that these methanogens use this alternative pathway (most are Wood-Ljungdahl autotrophs) as a primary mode of carbon fixation (Sprott et al. 1993), this may serve an important anaplerotic role and provides an exciting window into RuBisCO evolution and possible engineering. Conversely, the distantly-related form IV RuBisCO homologs, found in a diverse range of organisms including several anoxygenic phototrophs (Ashida et al. 2003), is argued to be involved with methionine salvage pathways and is not able to fix C 0 2 . Importantly, with the exception of RuBisCO and PRK, all of the enzymes used in the Calvin cycle are found in functions known from other pathways. At least schematically, the Calvin cycle bears tantalizing similarities with the aforementioned ribulose monophosphate (RuMP) pathway found in many methanotrophs, functioning to incorporate Cj units in the form of formate rather than C 0 2 (analogously driving Cj + C 5 —> C 6 fixation in the process). Thus it can be argued that most of the enzymes of the Calvin cycle were already present in the ancestors of the first Calvin cycle autotrophs, and that "invention" of RuBisCO and PRK, combined with recruitment of enzymes from the RuMP pathway, could have resulted in a new, 0 2 -tolerant form of autotrophy. The timing of the appearance of the Calvin cycle appears to have been closely linked to the development of bacterial aerobic respiration and photosynthesis, events that were both tied to the progressive and irreversible oxidation of Earth's atmosphere. As the rTCA cycle and Wood-Ljungdahl pathways are both inhibited at high oxygen concentrations, it seems reasonable that RuBisCO came about in response to the challenge of an atmosphere that was increasingly oxic and with decreasing C 0 2 availability. The taxonomically-diverse RLP's, recently discovered to be involved with methionine salvage, present a plausible ancestral pathway from which RuBisCO was recruited and came to function as a carboxylase, and structure-function analyses are presently providing a testbed for this hypothesis (Ashida et al. 2005). The unique dual oxygenase/carboxylase role of the enzyme would have been much less of a disadvantage as the Precambrian C 0 2 : 0 2 ratio was still high, and feasibly could have served a useful additional role in ameliorating high levels of oxygen.

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10Q— C.watson ii I— Synechocystis 6803

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3-HYDROXYPROPIONATE CYCLE This pathway was first discovered only fairly recently in the filamentous anoxygenic phototroph Chloroflexus aurantiacus, of evolutionary interest because of its early-branching position on the tree of life. In fact many of the steps in this unique pathway are only now being fully resolved, particularly by the investigations of Fuchs and colleagues (Herter et al. 2002). However, it has also recently become clear that the cycle is more widespread than previously thought, apparently functioning in many aerobic autotrophic crenarchaeota (Hugler

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et al. 2003). Schematically, the pathway as presently elucidated incorporates a combination of novel reactions with enzymatic steps recruited from other metabolic pathways, including the rTCA cycle and propionyl-CoA pathway which carries out odd-chain fatty acid oxidation. Carbon fixation ultimately leading to pyruvate actually comprises a bicyclic pathway; in the first cycle, two carboxylations take place to give rise to a glyoxylate intermediate, which then condenses with an intermediate product from the first half of the first cycle (which accounts for the third carbon) (Herter et al. 2002). Several rearrangements, schematically similar to a reversed glyoxylate cycle but technically like a reversed citramalate pathway, eventually give rise to the cleaved pyruvate end-product. Though this remarkable pathway has now been solved in considerable detail, its evolution still remains enigmatic. Somewhat perplexing is that, despite its discovery in type strain C. aurantiacus, some close relatives of this organism (within phylum Chlorofiexi) apparently do not have a 3-hydroxypropionate cycle, instead apparently having a functioning CBB cycle (Ivanovsky et al. 1999). Furthermore, many of these organisms are content to grow (photo)heterotrophically and are often found in microbial mats with abundant biomass to facilitate such a lifestyle. As shown in Figure 7, this pathway is found only in a few different groups of aerobic prokaryotes, suggesting that it, as with the Calvin cycle, might have arisen as an ad hoc autotrophic solution to the oxidation of Earth's atmosphere, bypassing the oxygen-sensitive enzymes that catalyze critical roles in the rTCA cycle and Wood-Ljungdahl pathway. This speculation has some support from genomic data as it appears that, while homologs to several of the key enzymes that C. aurantiacus uses are present in crenarchaeotes, some enzymatic steps may be different in different crenarchaeota, suggesting evolutionary convergence or some plasticity in pathway operation (Menendez et al. 1999). The relatively recent discovery of this cycle and the apparently diverse means by which organisms carry it out suggest that there are pathways for autotrophic carbon fixation that have yet to be discovered, and resolving these as well as known pathways will no doubt shed additional light on the origin and evolution of microbial-environmental interactions.

AUTOTROPHY, HETEROTROPHY, AND THE ORIGIN OF METABOLISM For several decades, origin of life research focused on establishing a diverse synthetic library of prebiotic compounds upon which early life might have been built. A so-called heterotrophic origin assumes that a relatively complex milieu of chemical compounds would have been present on the early earth, supplied exogenously (e.g., during cometary accretion) or through abiotic reactions involving prevalent inorganic precursors such as N 2 , C0 2 , and H 2 (and typically involving a mineral catalyst and/or an energy source such as lightning to overcome energetic barriers). Plausible synthetic sources for many essential ingredients of prokaryotic cells have been illustrated, and it is thought that as early cells became more complex, enzymatic routes of synthesis eventually replaced their prebiotic counterparts as their prebiotic precursors became increasingly scarce. While impressively successful in the breadth of biologically-relevant metabolites that have been obtained, heterotrophic theories have not been without criticism. Opponents cite that reaction conditions often invoke conditions that are quite different than geochemical evidence suggests might have been available on the early Earth, as well as the fact that it is difficult to imagine a single environment where all of the necessary catalysts and conditions would allow precursors to accumulate. Thus about two decades ago, autotrophic origin of life theories proposed that prebiotic reactions might have involved only inorganic precursors, catalyzed for example on mineral surfaces or within FeS "membranes" (Russell et al. 1988; Wachtershauser 1988). Such schemes arguably allow for locally high concentrations of metabolites to accumulate and invoke a comparably simple set

Evolution

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227

Perspective

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Building

the Biomarker

Tree of Life

239

When inorganic carbon is fixed into biomass, these reactions necessarily are controlled by the activity of specific enzymes, each of which has an associated KIE. The biological transformation of substrate (A) to product (B) is accompanied by a fractionation factor that most commonly is written using the e notation, for the subsequent convenience of relating eA.B to 8,4 and 8 S when £ is a small number. Because 13C preferentially remains in A, eA.B always is a positive number and products are "lighter" than reactants. sA-B = ( 542 million years (Ma) ago), as body fossils of animals that give evidence about anoxic conditions in younger rocks do not exist in this period. Biomarkers as indicators of the evolution of life and the environment Phototrophic sulfur bacteria and a sulfidic ocean in the Proterozoic. Today, Earth's oceans are teeming with complex life, and even deep marine trenches contain enough oxygen to support macroscopic organisms. However, oceans in the distant past were fundamentally different. For the first two billion years of its existence, the ocean-atmosphere system was almost entirely anoxic (Fig. 2) (Holland 1994), but around 2450 to 2320 Ma ago, the disappearance of mass-independent fractionation of sulfur isotopes indicates that the concentration of atmospheric oxygen rose from previously trace levels to at least 10~5x the present level (Farquhar et al. 2000; Bekker et al. 2004; Holland 2004). Soon after this initial rise of oxygen, fossil soils (paleosols) begin to show typical oxic weathering patterns that suggest atmospheric 02 quickly may have reached 15% of its present value (Rye and Holland 1998). However, the deep oceans remained mostly or entirely anoxic until at least ~1,800 Ma ago, the point in geological history when the last Paleoproterozoic banded iron formations (BIFs; iron silicates and iron carbonates) disappeared (Fig. 2). Surprisingly, the state of the ocean in the following "mid-Proterozoic" interval (~1,800 to ~800 Ma) remains particularly mysterious. One model suggests that deposition of BIFs ceased ~ 1,800 Ma ago because Fe11 emitted from mid-oceanic ridges was precipitated immediately on the oxygenated sea-floor as Fe ln -hydroxides (Holland 1994). However, according to a competing model (Canfield 1998), Fe11 was not removed as oxidized rust but precipitated as Fe n -sulfides in sulfidic ocean waters. Evidence is accumulating from the isotopic composition and distribution of sulfides (Canfield 1998; Shen et al. 2003; Poulton et al. 2004), sulfates (Kah et al. 2001) and molybdenum (Arnold et al. 2004), that appears to support Canfield's model. It is also possible that a hybrid of both models existed, resembling a 'marble cake' ocean (A. H. Knoll, personal communication). If large areas of the world ocean were euxinic (anoxic and sulfidic) in the midProterozoic, then our understanding of more than one fifth of Earth history would change

'mid-Proterozoic 1 (e)

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Figure 2. Geological time chart beginning with (a) the formation of Earth ~4.6 billion years ago (Ga); (b) anoxic, non-sulfidic oceans; (c) onset of oxygenation of the atmosphere (Bekker et al. 2004; Holland 2004); (d) disappearance of banded iron formations as indicator of changing ocean chemistry (Holland 2004); (e) the informally defined "mid-Proterozoic" interval with possible widespread, anoxic and sulfidic marine conditions (Canfield 1998); (f) major radiation of eukaryotic algae (Knoll 1992); (g) first appearance and major radiation of multicellular organisms and animals. 0.54 Ga marks the PrecambrianCambrian boundary. P = Paleozoic, M = Mesozoic, C = Cenozoic.

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radically. Geochemical cycles would have been altered, and many bioessential elements, such as nitrogen, molybdenum, and copper would have been rare. Trace-metal limitation may explain why familiar forms of life, such as modern algae and animals, arose so late in Earth history (Anbar and Knoll 2002). In the euxinic ocean, organisms requiring oxygen would have been marginalized, restricted to surface waters and shorelines. The ocean would have promoted extensive growth of green and purple sulfur bacteria wherever sulfidic conditions rose into the photic zone. The earliest evidence for the existence of phototrophic sulfur bacteria comes from a biomarker study on the 1,640 Ma Barney Creek Formation in the McArthur Basin, northern Australia (Brocks et al. 2005). Well preserved, organic-rich dolostones of the Barney Creek Formation were deposited in deep waters of the rift basin. The lipids extracted from these sedimentary rocks contain some of the oldest, clearly indigenous biomarkers known to date (Summons et al. 1988b). Significantly, the samples contain relatively high concentrations of isorenieratane 2, chlorobactane 19, and okenane 10. This indicates that the basin was stratified, and euxinic conditions extended—at least episodically—into the photic zone of the water column. This ancient assemblage of biomarkers had two further characteristics which were radically different from any younger bitumen. Steroids alkylated at C-24 in the side chain and diagnostic for eukaryotic organisms were present at levels close to or below detection limits. In contrast, aromatic steroids without side chain alkylation but which were methylated at C-4 (see 8) were very abundant. These biomarkers, together with high relative concentrations of 3P-methyl-hopanes, suggest aerobic type-I methanotrophic bacteria were abundant members of the population. Aerobic methanotrophs are typically found in sulfate-starved environments (95% genomic coverage (Lander and Waterman 1988). Figure 3 relates species abundance, sequencing effort, and genome coverage for a community of microorganisms. As shown, a sequencing budget in the range of 100 Mbp should allow analysis of population dynamics for the more abundant species of any community or for the majority of species in relatively simple communities (i.e., those with few members). In highly diverse populations, population variability in target species may be assessed though directed approaches that screen for clones from certain organism types before sequencing (Stein et al. 1996; Handelsman et al. 1998; Henne et al. 1999; Beja et al. 2000; Rondon et al. 2000; DeLong 2002; Hallam et al. 2003; Brady et al. 2004; Handelsman 2004; Riesenfeld et al. 2004; Daniel 2005; DeLong 2005; Schleper et al. 2005). In addition, variation in specific genome regions of interest may be identified by combining environmental genomics with targeted PCR amplification and gene sequencing.

BASIC POPULATION PARAMETERS: SELECTION, RECOMBINATION AND GENETIC DRIFT We have described how to define microbial populations and recognize fine-scale patterns of variation within them. The patterns of individual-level variation observed in a population (through the methods described above) result from the dynamic interaction of evolutionary

Collect sample of microbial community

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Figure 2. Methods for environmental genomics. Microbial cells are sampled f r o m the environment. D N A extraction results in a mixture of genomes in proportion to their representation in the sample if there is no bias in D N A extraction between species. D N A is fragmented using restriction digests or by sheering in to fragments that are approximately the same size. Each fragment is inserted into a vector to make a clone library. Each species representation in the clone library should be proportional to their representation in the extracted D N A if there is no cloning bias. A random sample f r o m the clone library is then sequenced in two directions. Resulting paired-end sequences are then assembled using assembly software.

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Figure 3. A. Rank abundance curve showing the relative distribution of different species in a model community. Proportion of the library with sequence from each species relates to both its relative abundance in the community and its genome size relative to all other community members. B. The average depth of coverage for each species from the model community, assuming every species has same genome size of 2Mb and a total of 100 Mbp were sequenced from the library and that there is no bias in cloning from different species. Thick bars represent consensus sequence. Thin bars represent individual sequences. Connections between thin bars represent paired end sequences from the same clone. C. The proportion of the genome of each species that is sequenced estimated as l-(e~ c ) where C is the estimated coverage of each species genome and e~c is an estimate of the proportion of the genome that will not be sampled given a Poisson distribution for sampling each base in the genome.

forces, including selection, recombination and neutral genetic drift. We describe each of these forces, and then discuss how they interact to structure diversity in natural populations. One of the primary forces that shape populations is natural selection. There are many different types of natural selection which act to fix or preserve variation within a population. For example, when a mutation confers a selective advantage, that mutation will be selected for across generations and in time may become fixed (i.e., variation is removed) in the population through positive selection. Alternatively, when mutations are deleterious, purifying selection (i.e., selection against individuals with a harmful mutation) will generally remove it from the population. Natural selection may also preserve diversity within a population by favoring multiple variants in a process referred to as diversifying selection (Kreitman and Hudson 1991). The relative intensity of selection for different mutations or genome changes will vary. The relative importance of selection as an evolutionary force has been the subject of great debate in evolutionary literature (Nei 2005). Another important evolutionary force in natural populations is the redistribution of genetic variation among individuals. This occurs through transfer of DNA between cells and its incorporation into the recipient chromosome via recombination. In most microorganisms, these processes are not linked to reproduction as they are in sexually reproducing eukaryotes. Instead, genes are transferred between individuals though transduction (i.e., by viruses), transformation (i.e., direct uptake of DNA from the environment), or conjugation (i.e., unidirectional transfer of chromosomes between individuals). The processes of gene transfer and recombination lead to greater variation in individual fitness within a population, because

Population Dynamics in Extreme

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267

both beneficial and deleterious mutations are continually re-sorted into new combinations (Burt 2000; Goddard et al. 2005). Genetic drift is an evolutionary process in which gene frequencies change at random from one generation to the next (Fisher 1930; Kimura 1983). These random deviations generally have a greater effect on small populations than on large ones. Genetic drift may result in the fixation or removal of mutations from a population without any selection, and is therefore considered a neutral force. Variation introduced into a population may be fixed or removed by selection or random genetic drift and it can be redistributed between individuals through recombination. However, these forces do not act in isolation. Instead, the interaction among evolutionary forces influences the overall structure of diversity within a population. There is a substantial body of work in theoretical population biology and experimental evolutionary biology that predicts the characteristic footprints that each of these evolutionary processes leave in the patterns of sequence variation (Li 1997; Souza et al. 2002). Based on this work, it is possible to interpret historic evolutionary processes from the distribution of variation among individuals in a population.

SHAPING POPULATION STRUCTURE THROUGH SELECTION AND RECOMBINATION The structure of diversity within a population (e.g., the extent of genome-level heterogeneity, its distribution among individuals within the population, and the abundance distribution of the genotypes) represents the outcome of interactions among several evolutionary forces. Conversely, after identifying the structure of a microbial population, we can infer the combination of forces that created it. One of the primary interactions that defines microbial population structure is the balance between selection and recombination. We begin a discussion of the interaction between recombination and selection by considering extremes of population structure (also see Fig. 4): (i) a clonal structure, resulting from natural selection in populations where recombination events are rare, and (ii) a recombinant structure, in which recombination occurs fast enough to widely distribute genetic variation prior to selection events. (i) When all genes in the genome are physically linked to one another, natural selection that effects one position must affect the entire genome. As clonal populations evolve in natural environments, the linked fate (linkage) of genes across the genome results in a dynamic process known as periodic selection. This process begins when a single individual randomly acquires an adaptive mutation that increases its fitness (i.e., its survival and rate of asexual reproduction relative to other individuals in the population). The faster reproduction of this individual clone relative to other individuals within a population results in an increase in the overall frequency of its genotype (clonal expansion). Eventually, if the adaptive mutation confers a great enough advantage, this single adaptive genotype may outcompete all other types in the population and become fixed. Replacement of all individuals in a population by a single genotype periodically purges all variation from the population and is known a selective sweep. After a selective sweep, individuals in the population will diversify as they acquire random neutral genetic mutations until the next adaptive mutation is introduced, resulting in another genome-wide selection event. Population structures of some bacteria show evidence of periodic selection events that purge genetic diversity (Majewski and Cohan 1999; Palys et al. 2000; Feil et al. 2003). This process has also been documented in experimental populations of E. coli, at least during the initial period of adaptation (Levin 1981; Lenski and Travisano 1994). Cohan predicts

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A. Periodic selection purges diversity in a clonal population

C. Diversity overtime in clonal and recombining populations

> Time

B. Neutral g e n o m e diversity is resistant to purging in a recombining population

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Figure 4. Comparing clonal and recombining populations. A simplified model showing the difference in diversity (number of genome types) for two populations that differ only in recombination rate. A. Shows a clonal population structure which begins with a single clone represented here by a single black circle. Over time, this clone acquires random neutral mutations (solid arrows) at different positions shown by small white spots. When a selection event occurs (grey rectangle) only the individual with the mutation at approximately seven o'clock position in the genome can survive and the population is purged of diversity. This clone will begin the process of neutral divergence again at the beginning. B. Shows a recombining population structure. Between mutation events recombination distributes mutations among individuals to create new genotypes (dashed arrows). This processes results in an increases the total number of genotypes in the population. Here again there is a selection event (for the same adaptive mutation) however, because this mutation has been distributed between individuals through recombination three different genotypes survive. This shows that in recombining populations some of the diversity that has accumulated is preserved. In this model three clones are left after the selection event to diversify through mutation and recombination. C. Illustrates the difference in diversity estimated as number of different genotypes in a clonal (top) and recombining (bottom) population over time. As above all other population parameters; mutation rate, population size and the type and frequency of selection are the same between populations.

diversification between clonal populations will lead to the development of ecological species (ecotypes) in which each clonal population is specifically adapted to a unique environmental niche (Cohan 1994; Cohan 2002). In this model of ecological speciation, ecotypes are defined as populations that are genetically cohesive (cohesion is the result of periodic selection events that purge diversity) and ecologically distinct (Gevers et al. 2005). (ii) Recombination disrupts the physical linkage between regions of the genome, and thus reduces the ability of selection events to purge diversity from the population (see Fig. 4). This occurs because gene variants are distributed among individuals such that selection for a gene that confers an adaptive advantage increases the frequency of that gene in the population without affecting the frequency of unlinked regions of the genome. Recombination is a cohesive force because a beneficial adaptation can be spread throughout the population, restricting the divergence of the lineage in which the gene arose. Conversely, barriers to recombination allow species divergence. The rise of independent lineages as the result of barriers to recombination is analogous to the biological speciation in sexual eukaryotes.

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Evidence for recombination among members of archaeal populations was first observed through community genomic analysis of a single biofilm growing in extremely metal rich acid mine drainage (Tyson et al. 2004). Tyson et al. reconstructed partial and near complete composite genome sequences for the five dominant organism types in the biofilm community. Each genome sequence was a composite because it was derived from closely related but not identical sequence reads. Population level analyses were possible because sequencing reads can be arrayed against the composite sequence. The authors recognized evidence for recombination in transitions between two types of sequences observed within a single sequence read (see Fig. 5). One recombination event was detected on average every 3-5 Kbp across the entire genome of the archaeal species Ferroplasma type II. Ferroplasma type II is one of two discrete coexisting Ferroplasma lineages that would have been grouped as a single species based on 16S rRNA gene sequence analysis. Despite extensive evidence of recombination within Ferroplasma type I and Ferroplasma type II populations, there was evidence for only very limited recombination between them. The authors suggested that the decrease in recombination rates with increasing genetic divergence might represent a species boundary. It may be inferred that the level of sequence divergence between these populations (on average 77% nucleotide identity) prevents homologous recombination from initiating (Majewski and Cohan 1998). Genome rearrangements and differences in gene content may also create barriers to homologous recombination and lead to sympatric speciation (occurring within a contiguous population) (Vetsigian and Goldenfeld 2005). A second study of archaea cultured from extremely high salinity salterns environments used multilocus sequence analysis of 40 Haloarculum strains to identify evidence for recombination (Papke et al. 2004). This study suggests that the recombination occurs at 5x the rate of mutation in this species. Further analysis revealed that all but one of the recent recombination events observed in this population occurred between individual clones that were closely related (Whitaker et al. 2005). The decrease in extent of genetic exchange with increasing evolutionary distance is a phenomenon that can ultimately result in the formation of biological species, as described above. It should be possible to use genetic information to infer the relative rates of recombination and selection within populations. Figure 4 shows, for example, two cases where selection events occur with the same frequency for two organisms but the organisms differ in their recombination rates. In one population, recombination events are infrequent so that after a selection event genome diversity is purged (a single genome type is observed), where in the second the recombination events are frequent and their effects can accumulate, thus maintaining greater levels of genetic diversity after selection. Multilocus sequence studies of bacteria associated with human and plant disease have revealed a range of population structures from purely clonal to completely recombinant (Suerbaum et al. 1998; Feil et al. 2000; Falush et al. 2001; Feil and Spratt 2001; Suerbaum et al. 2001; Enright et al. 2002; Feil et al. 2003; Sarkar and Guttman 2004). Population structures between the two extremes have evidence for clonal expansion of one clonal type (possibly resulting from natural selection) and recombinant genomes. This is called an epidemic population structure, where a single clone is overrepresented but does not completely overtake the entire population (Smith et al. 1993; Fraser et al. 2005). Multilocus analysis of the thermoacidophilic crenarchaea Sulfolobus islandicus from a geothermal hot spring in Kamchatka, Russia represents the first in-depth analysis of the balance between recombination and selection within a single geographically isolated endemic population (Whitaker et al. 2005). The boundaries of this population were defined prior to this study, facilitating assessment of the interaction between selection and recombination and their relative effects on population structure. Whitaker et al. (2005) showed that recombination is

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three to six times as frequent as mutation within this single hot spring community. This study also identified evidence for natural selection in one of the six protein-encoding genes analyzed, indicating that recombination was rapid enough to allow genetic loci to evolve independently. In addition, this population was shown to have an epidemic population structure in which clonal expansions increased the frequency of a single clone but did not completely purge diversity. The Tyson et al. (2004) environmental genomics study demonstrated that environmental genomics analysis will allow simultaneous sampling of multiple populations within the same sample and comparison of population dynamics among them. Notably, significant differences in population dynamics were inferred for bacterial and archaeal groups in the biofilm through methods described in Figure 5 A. A very low incidence of nucleotide polymorphisms was seen in the Leptospirilhim group II population, suggesting a near clonal structure that may have resulted from a recent selective sweep or from a decrease in diversity following a founding event by a single clone (Tyson et al. 2004). By comparison, the genomic heterogeneity of the Ferroplasma type II population indicated that it had not recently experienced a genome-wide selective sweep. The higher diversity in this population may have resulted from frequent recombination limiting the purging effects of negative selection or from a rarity of adaptive mutations or selection events leading to dominance by a single genotype. Above we introduced two extremes of population structures that are clonal and recombinant. We discussed three extreme island-like environments in which population dynamics have been described (high salt, high temperature, high acidity) and in which the archaeal recombination rates are rapid compared to selection rates. However, in the case of the acid mine drainage biofilm, the bacteria exhibit an apparently clonal population structure,

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suggesting lower recombination rates relative to selection. It remains to be seen whether high relative recombination rates are a more common characteristic of archaeal than bacterial populations in extreme environments. Identifying the structure of a population is essential to understanding how diversity is shaped by environmental change. Below we will describe how defining a population also determines the methods that may be used to identify specific traits that are under natural selection in natural microbial systems.

IDENTIFYING ADAPTIVE TRAITS There are innumerable examples that illustrate how microbial communities are shaped by, and shape their environments (for example see Kappler and Straub 2005). However, much remains to be learned about the interplay between the environment and natural selection on microbial populations at the genome level. This is because until the advent of environmental genomics, we lacked the ability to correlate subtly different genotypes and phenotypes to the microenvironments to which they are adapted. Genomic characterization of microbial communities allows for the comprehensive identification of genetic traits that lead to differential adaptations within and among lineages. With enough genome coverage and population genomics tools, it may be possible to discern the environmental parameters that exert key selective pressures. For example, consider one clonal type found in a geothermally heated stream at 45 °C and a second found only above 65 °C (Miller and Castenholz 2000). Population genomics will lead to identification of the genetic differences that result in their niche specificity. The availability of genome sequences also enables the development of methods to evaluate gene expression, an approach that may help identify traits important for adaptation to specific conditions. For example, relative levels of expression can be monitored using microarrays that specifically bind mRNAs predicted from gene sequence information (Nelson and Methe 2005). In addition, proteomics on environmental samples can be used to identify the more abundant proteins in a culture or natural sample. For example, Ram et al. (2005) assessed the protein composition from an acid mine drainage biofilm sample. Similar proteomics experiments could also provide some information about relative protein abundance between samples. Prior microarry and proteomic studies have used genome sequences from isolated organisms. The availability of new data that capture gene sequence heterogeneity within populations will allow expression analyses with resolution to the strain level. The combination of genomic and gene expression analysis methods may provide an unprecedented opportunity to link the effects of natural selection to environmental dynamics within microbial communities. Below, we discuss how the environmental genomics data itself can be used to identify traits that are under selective pressure by exploring individual-level variation across the genomes of a population. Recognizing genes under selection in recombining populations Many methods have been developed for identifying genes under selection in sexual eukaryotes (Bamshad and Wooding 2003). The application of these tools to recombinant microbial populations is appropriate because recombinant microbial populations lack the extensive hitchhiking (physical linkage of genes, thus shared fate) that is a characteristic of clonal populations. One pattern within environmental genomic data that may be used to identify genes under positive selection relies on the assumption that positive selection in recombining populations may result in relatively low levels of neutral diversity relative to the rest of the genome. Purging of neutral diversity from regions of the genome subject to positive selection is analgous to the purging of diversity in clonal populations through selective sweeps. However, because the population is recombinant, selective forces act upon the gene rather than the genome. As

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shown in Figure 4, adaptive genes at a single genome position become fixed in a population while the other regions are left variable. Large regions of low variation were found in the genomes of two Ferroplasma species identified within the acid mine drainage community (Tyson et al. 2004). Identification of the function of genes within invariant regions will lead to determining genes that are under positive selection in this environment. Comparisons of invariant regions among samples collected across space and time may provide insight into ecologically relevant adaptations to specific environmental conditions. Where genes vary between individuals within a recombinant population, comparison of the relative proportion of nonsynonymous and synonymous substitutions among gene variants may identify the action of natural selection. As described above, nonsynonymous substitutions that change the amino acid sequence of a protein may result in a phenotypic change. If there were no natural selection, the relative frequency of nonsynonymous substitutions per nonsynonymous site (Ka) to synonymous substitutions per synonymous site (Ks) will be equal. A skew toward a higher relative frequency of synonymous substitutions suggests that nonsynonymous mutations are quickly removed because they are deleterious (negative selection). On the other hand, a higher relative frequency of nonsynonymous substitutions observed among gene variants in a population suggests that amino acid changes are beneficial (positive selection). Estimating the Ka/Ks ratio for different variable genes across the genome can be used to identify loci that are under positive and negative selection (McDonald and Kreitman 1991). Using codon-based methods for determining relative rates of nonsynonymous and synonymous substitutions (Yang 1997) Beilawski et al. identified specific residues responsible for differential light adaptation in proteorhodopsin genes recovered across light gradients in the ocean environment (Bielawski et al. 2004). Testing for genes under positive or diversifying selection across the genome without a priori assumptions of where they occur can uncover unexpected adaptive responses to different environmental conditions. Recognizing genes under selection in clonal populations Identifying specific genes under selection in populations with a clonal structure is difficult, because the action of selection on different genome regions cannot be isolated in a linked genome. However, if the presence of a novel gene acquired through HGT or the position of a mobile element confers a selective advantage, it may be recognized through careful assembly and comparative genomic analyses between clonal types. In community genomic data, the conserved location of mobile elements or novel genes within a single clonal type indicates an adaptive function. Differential position between individuals within a clonal population indicates that they move within a genome faster than they can be selected for or that they are essentially neutral. Recognizing of differences in gene content or position is also possible using similar methods in recombinant populations. For example, comparisons between syntenous genomic regions of the Ferroplasma type I populations from the acid mine drainage community and the near complete genome sequence of a Ferroplasma type I strain isolated from the same environment revealed differences in the position of mobile elements and differential insertion of novel genes (Allen and Banfield 2005 Figure 2). If the differential position of a mobile element is identified within an assembled genome sequence, its adaptive function may be inferred by examining the function of genes in its vicinity. For example, insertion of a novel gene into a recognizable regulatory element may suggest that modified expression confers adaptive function (Schneider and Lenski 2004). Similarly, if mobile elements are inserted within a gene, this suggests that loss of a particular function confers some advantage (Zinser et al. 2003). If the function of the genes around mobile elements is known, this allows a connection between the position of element and the adaptive trait (Cooper et al. 2001).

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Likewise, the adaptive significance of novel genes acquired through horizontal gene transfer may be inferred if their function is known. One challenge with such analyses to date is that the functions of many of the inserted genes are unknown. Without known function, it is difficult to determine the adaptive significance or even whether novel genes are expressed. Ram et al. (2005) presented an interesting approach to resolving this challenge using the detection of protein products (via mass spectrometry) in a natural biofilm community. The authors noted that protein products of novel, hypothetical genes were detected less commonly than those of genes for which a probable function could be ascribed. In addition, detection rates were especially low for genes encoded in blocks of putative phage or plasmid origin that were apparently inserted into the genome of a bacterial species of the Leptospirillum genera. Because proteins must be expressed to confer a function, this approach may be used to determine the adaptive importance of novel genes. This approach may further be used to determine the levels of expression of genes in different populations through comparative proteomics.

CONCLUSION: INTEGRATING GENETIC AND GEOCHEMICAL MOLECULAR TOOLS The focus of this chapter has been the relatively unexplored subject of microbial population dynamics. Because the topic is new, there is only a small literature to review. Consequently, we have emphasized tools and approaches that could be applied as data become available. We have described forms of variation, methods to assess them, and what their patterns can tell us about microbial evolution. At the beginning of this chapter, we asked a series of questions concerning how best to describe diversity within microbial populations. While we have described the tools needed to resolve these fundamental challenges, we have left these questions unanswered. For example, we asked whether biodiversity is partitioned into definable species and whether species are even the most ecologically relevant units of diversity in microbial systems. It is our view that both the genetic characteristics that unite groups and the processes that subdivide them into divergent phenotypes are best evaluated through population genomic analyses. With such information in hand, we may be better positioned to establish meaningful delineations between species and to understand mechanisms of diversification and lineage cohesion in microorganisms. As the field develops, two additional steps will be necessary. The first is the use of these methods to sample populations over time and across space. Each analysis described here represents a single snapshot in the natural history of a population. These snapshots allow develop-ment of hypotheses about mechanisms generating diversity (e.g., through rapid recombination, through selection for a certain genetic trait) that can be tested through comparisons between samples collected across time and space. For example, if an inserted mobile element is hypothesized to up-regulate genes important in metal resistance, sampling strategies designed to target multiple populations with different levels of metal contaminants might reveal the loss of this adaptation. Especially exciting are comparisons among geographically isolated endemic populations adapted to distinct local environments. Comparative population dynamics among isolated populations of similar microbes will shed light on their unique natural history and provide a means by which to correlate evolutionary and geological dynamics. The second step is to place microbial communities into a well-defined geochemical context. Characterizations of the geochemical gradients in time and space along which populations evolve will provide an essential basis for linking specific adaptations to environmental change. It is our hope that the methods described here, in combination with molecular tools to simultaneously characterize the organic and inorganic structure

274 of m i c r o b i a l c o m m u n i t i e s u r g e g e o m i c r o b i o l o g i s t s to population dynamics. With m i c r o o r g a n i s m s and their evolution.

Whitaker & Banfield (Gilbert et al. 2 0 0 5 ) , set the stage f o r this d e v e l o p m e n t . W e e m b r a c e all of these n e w m o l e c u l a r - l e v e l m e t h o d s to e x p l o r e these tools, w e c a n b e g i n to u n r a v e l the i n t i m a t e links b e t w e e n e n v i r o n m e n t and h o w g e o c h e m i c a l c h a n g e s drive m i c r o b i a l

ACKNOWLEDGMENTS W e t h a n k J a v i e r a Cervini-Silva, C h r i s B e l n a p , K. B l a k e Suttle and S t e p h e n M . W a l d for h e l p f u l r e v i e w s and the N a t i o n a l S c i e n c e F o u n d a t i o n B i o c o m p l e x i t y P r o g r a m , the N A S A A s t r o b i o l o g y Institute, and the D e p a r t m e n t of E n e r g y M i c r o b i a l G e n o m e P r o g r a m and G e n o m i c s : G e n o m e s to L i f e p r o g r a m s f o r s u p p o r t of r e s e a r c h and d e v e l o p m e n t of ideas p r e s e n t e d in this chapter.

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Reviews in Mineralogy & Geochemistry Vol. 59, pp. 279-294, 2005 Copyright © Mineralogical Society of America

Metabolism and Genomics: Adventures Derived From Complete Genome Sequencing Karen E. Nelson and Barbara Methe The Institute for Genomic Research 9712 Medical Center Drive Rockville, Maryland, 20850, U.S.A. kenelson @ tigr. org

bmethe @ tigr.org

INTRODUCTION The genomic era has provided us with hundreds of complete microbial genome sequences (current estimates as of July 12, 2005, are 266 microbial genomes completed and an additional 730 in progress; see http://www.GenomesOnline.org) (Mongodin et al. 2005a). Collectively, the sequencing of individual genomes and whole communities has enabled the realization of a level of genetic diversity and complexity that was previously unappreciated (Venter et al. 2004; Mongodin et al. 2005b). This is particularly evident when the results of these endeavors are related to the study of physiological processes and metabolic capabilities of both the individual species and community members from a range of environments. Often, species are found to harbor the genetic material for metabolic pathways that had not been identified or tested in the laboratory setting, and it has become increasingly evident that we are some distance away from understanding the tremendous biological, physiological and metabolic diversity and potential that clearly exists in the microbial world. The chemical process of sequencing allows for the determination of the primary structure of a region of DNA (the main information carrier in a cell). The result of this process is a determination of the exact order of the four-nucleotide building blocks (adenine, cytosine, guanine and thymidine abbreviated A, C, G, T, respectively) that make up the DNA region in question. Completing the entire genome sequence of an organism thus provides a comprehensive representation of the entire sequence of the organism under study and its genome structure including the presence of chromosomes and in the case of prokaryotes, the presence of plasmids.

GENOME SEQUENCING AND ASSEMBLY Upon completing the sequence of a microbial genome, a thorough analysis of the genetic data should follow (detailed in Fig. 1). This process typically begins with the identification of all open reading frames (ORFs). A variety of ORF finding software is available to enable gene identification. Once gene predictions are completed, assignment of biological functions is made possible by searching all the ORFs against a database of non-redundant sequences. Among the most popular tools for searching sequence databases is BLAST (Basic Local Alignment Search Tool) (Altschul et al. 1990), which performs pair-wise sequence comparisons and seeks to define regions of local similarity, as opposed to optimal global alignments between entire sequences. Hidden Markov models (HMMs), which are statistical representations of consensus sequences describing a family of protein sequences, are also frequently used to accurately search large data sets of genome sequence. The goal of HMM searches is to 1529-6466/05/0059-0012$05.00

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Overview of Genome Sequencing and Analysis

Sequencing and Assembly

Annotation and Analysis

Functional Analysis

Figure 1. A schematic of some of the major components of a microbial genome sequencing project, as well as some of the post genomic applications that can be applied.

determine if the query sequence is a member of a protein family for which an H M M has been described. The collective results of investigations such as B L A S T and H M M searches are used to characterize the gene prediction and the results are stored in relational databases designed to allow for further data mining. Typical information that is obtained about an O R F prediction includes: assignment of a biological role, common name, percent identity and similarity of other sequence matches, the pair-wise sequence alignment, and taxonomy associated with the match assigned to the predicted coding region. In addition to O R F analysis and gene identification, a number of other features of the genome can be identified using a variety of computer algorithms. TopPred for example allows for the identification of membrane-spanning domains (Claros and von Heijne 1994). Signal peptides and the probable position of a cleavage site in secreted proteins can be detected with SignalP (Nielsen et al. 1997). Genes coding for untranslated R N A s can be identified by database searches at the nucleotide level, and searches for tRNAs can be performed using tRNAScan-SE (Lowe and Eddy 1997). Repetitive sequences can be identified by various repeat finding programs, as well as by using an algorithm based on suffix trees which are versatile data structures that are particularly useful in genomic analyses for solving many string (sequences of characters) matching problems (Delcher et al. 1999). The determination of metabolic pathways can be aided by comparison of genome annotation to known pathways. Resources which can enable this analysis include the Kyoto Encyclopedia of Genes and Genomes or K E G G database (http://www.genome.ad.jp/kegg/). Operons represent a basic organizational unit of genes on prokaryotic chromosomes. A variety of computational methods have been suggested which can predict operon structure (Chen et al. 2004) although no one method of choice currently exists.

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SIMULTANEOUS COMPARISON OF MULTIPLE GENOMES Bioinformatics tools have had to be (and continue to be) developed and refined so that they can handle large quantities of biological sequence information, as well as provide the capacity to compare genome information derived from closely as well as distantly related strains and species. MUMmer (Delcher et al. 1999) allows the rapid alignment of whole genome sequences. This is made possible by an algorithm that is based on a suffix tree data structure. The NUCmer utility that is also included with the system can align sequences from genomes that have not been closed, being capable of aligning thousands of smaller assemblies to another sequence data set. The PROmer utility permits the alignment of genomes for which the proteins are similar but the DNA sequence is too divergent to detect similarity. The Comprehensive Microbial Resource (CMR) (http://www.tigr.org/tigr-scripts/CMR2/ CMRHomePage.spl) is one of the few publicly available tools that allows for access to all the prokaryotic genomes or any subset of prokaryotic genomes that have been completed to date (Peterson et al. 2001). The CMR was introduced primarily to reduce annotation inconsistency across completed genome, and displays the primary annotation taken from the original sequencing center where the data was generated, and an annotation generated by an automated annotation process at The Institute for Genomic Research (TIGR) (Peterson et al. 2001). Complex queries based on role assignments, database matches, protein families, membrane topology and other features are feasible. The CMR also provides access to web-based tools that allow for data mining using pre-run homology searches, whole genome dot-plots, batch downloading and traversal across genomes using a variety of datatypes. Querying data can be based on a variety of gene properties including molecular weight, hydrophobicity, G+C-content, functional role assignments, and taxonomy. When viewing an individual genome, graphical displays highlight genes placed linearly on regions of the chromosome, or as a complete circle for an entire chromosome. At an even broader level, the CMR presents comparative information between microbial genomes (Peterson et al. 2001). The Genome Properties (Haft et al. 2005) is a relational database system that includes tools and web interfaces for the investigation of the metabolism, phenotypes, and other biological properties of microbial species. The results of searches from the Genome Properties system reflects gene content, phenotype, and phylogeny for example, with the results of HMM searches allowing for a deduction of basic characteristics that include families of proteins that are conserved in function. In addition, some properties can be derived from curation, publications on the organism of interest, and other forms of evidence (Haft et al. 2005). Finally, reconstruction of biochemical pathways and transporter profiles associated with an organism of interest provides an overview of the metabolic capacity of the cell, and often reveals new aspects of the basic biochemistry of the species (see for example Nelson et al. 1999, 2002; Nierman et al. 2001). Some environmental species such as Pseudomonas putida for example (Nelson et al. 2002) have revealed a higher number of metabolic pathways for the conversion of atypical compounds than have been previously identified. Other organisms such as Caulobacter crescentus that have been sequenced for insights into biological processes such as cell cycle control have revealed the presence of unsuspected pathways such as the beta ketoadipate pathway for the metabolism of atypical compounds (Nierman et al. 2001). Considering that on average 40% of each microbial genome is considered to be hypothetical or conserved hypothetical proteins, it is obvious that a significant amount remains to be elucidated about the biology of microbial species. It should be highlighted that although tremendous insight is gained into the metabolic diversity of the species that is being analyzed, many other pathways are likely missed due to the limited characterization of many of these species that is reflected in the high number of conserved hypothetical and hypothetical proteins that remain at the end of the average genome sequencing project.

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The burgeoning information produced from genome sequencing, annotation and comparative analyses has led to advances in the field of functional genomics. Functional genomic approaches seek to capitalize on the knowledge of genomes through the application of technologies in a comprehensive manner (from a whole organism or "systems-level") to elucidate genes, their functions and products, and how these products interact with the ultimate goal of understanding how an organism functions in the manner in which it does. Examples of functional genomic approaches include but are certainly not limited to the following discussion. Microarray technology (Dharmadi and Gonzalez 2004) can be used to examine gene expression patterns by measuring relative gene transcript abundance of the cellular mRNA pool (the transcriptome) or can be used to determine the presence or absence of genes (using DNA) in a query genome relative to a reference genome in a process known as comparative genomic hybridization (CGH). Proteomic approaches include 2-dimensional gel electrophoresis and mass spectrometry which seek to measure proteins synthesized in a cell (the proteome) and can provide information on how those proteins function and interact with each other. Metabolomic approaches can measure changes in low molecular weight chemical complement of a cell (metabolome) using among other techniques liquid and gas chromatography, mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy (Nielsen and Oliver 2005). Structural proteomics is another field of study benefiting from the increase in genome information. This area of research aims to provide information on protein identification at the level of the genome (proteome identification), characterizing three-dimensional structures of proteins and determining structure-function relationships. Experimental methods for determining protein structures typically include techniques such as X-ray crystallography or NMR spectroscopy (Forster 2002). However, elucidation of three-dimensional structures by these techniques is still limited. Therefore, computational methods are an active area of interest for providing new tools that can augment traditional experimental techniques in determining three-dimensional structure. Approaches include comparative or homology modeling which seeks to create a three-dimensional protein model of an unknown structure using sequence similarity to proteins of known structure (proteins whose structures have been solved; Centeno et al. 2005). Other approaches rely on de novo or ab initio structure prediction of proteins to elucidate three-dimensional protein structure based on using only the primary amino acid sequence (Klepeis et al. 2005).

EXAMPLES OF WHOLE GENOME RECONSTRUCTIONS AND DERIVED INFORMATION Metabolic reconstructions for the genomes of a number of microbial species of both environmental and pathogenic significance have been successfully completed. The reconstruction of biochemical pathways and transporter profiles associated with an organism of interest provides an overview of the metabolic capacity of the cell, and often reveals new aspects of the basic biochemistry of the species. Although at present no computational tool can accurately predict all of the potential metabolic pathways and regulatory networks of the cell, the development of these reconstructions has been aided through the use of a variety of genome tools and information including genome annotations, in some cases predictions based on the Genome Properties tool Qittp:llwww.tigr.orglGenome_Propertiesl) and sequence searches against transporter databases (http://www. membranetransport. org!) as well as other comparative genomic and functional genomic approaches. Presented in detail below are several examples of genome analyses in which various computational and functional genomic approaches have been applied to understand the organism in question at a systems-level of biology.

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One example of a successful approach using computational predictions to elucidate metabolic functions is shown by the results of the data mining of P. putida KT2440, a metabolically versatile saprophytic soil bacterium that has been certified as a biosafety host for the cloning of foreign genes. The genome of P. putida strain KT2440 is a single circular chromosome, 6,181,863 bp in length with an average G+C content of 61.6% (Nelson et al. 2002). A total of 5420 ORFs with an average length of 998 bp were identified. Genome analysis reveals metabolic pathways for the transformation of a variety of aromatic compounds including ferulate, coniferyl- and coumaryl alcohols, aldehydes and acids, vanillate, phydroxybenzoate, protocatechuate, many of which may arise during the decomposition of plant materials (Nelson et al. 2002). P. putida KT2440 appears to modify the diverse structures of these aromatics to common intermediates that can be fed into central pathways. Initial steps in the metabolism of ferulic acid, 4-hydroxybenzoate and benzoate for example, could be mediated by different enzymes with all routes ultimately converging via protocatechuate or catechol to the 3-oxoadipate pathway. This convergent strategy is also seen with substrates that can be metabolized by the phenylacetyl-CoA pathway (Nelson et al. 2002). Consistent with the extensive metabolic versatility for the degradation of aromatics, the genome sequence of P. putida KT2440 includes many putative transporters for aromatic substrates, including multiple homologs of the Acinetobacter calcoaceticus BenE benzoate transporter, and of the P. putida PcaK 4-hydroxybenzoate transporter. In addition, KT2440 has 23 members of the BenF/PhaK/OprD family of porins that includes outer membrane channels implicated in the uptake of aromatic substrates. Strain KT2440 also possesses approximately 350 cytoplasmic membrane transport systems, 15% more than P. aeruginosa, including twice as many predicted ATP-Binding Cassette (ABC) amino acid uptake transporters. This is consistent with its ability to colonize plant roots, since root exudates are rich in amino acids, and reflects a physiological emphasis on the metabolism of amino acids and their derivatives for successful competition in the rhizosphere. The details of this study, metabolic reconstruction and all references associated with the publication of the genome can be found in (Nelson et al. 2002).

GEOBACTER

SULFURREDUCENS

Analysis of the Geobacter sulfurreducens genome (Methe et al. 2003), a bacterium known primarily for its ability to carry out extensive metal reduction in subsurface environments revealed many significant and unsuspected capabilities, including evidence of aerobic metabolism, one-carbon and complex carbon metabolism, motility, and chemotactic behavior, which had not been previously revealed even though this bacterium has been extensively studied. These characteristics coupled with the possession of many c-type cytochromes (111 putative c-type cytochromes were identified) and many other genes predicted to be important in electron transport revealed an ability of this organism to create alternative, redundant electron transport networks offering new insights into the process of metal reduction in subsurface environments. As a member of a family of dissimilatory metal-ion reducers, G. sulfurreducens prefers to couple acetate or hydrogen oxidation to the dissimilatory reduction of iron (III) to iron (II), thereby linking the global iron and carbon cycles. In this respiratory process, G. sulfurreducens and other members of its family have solved the riddle of using insoluble metal-oxides as terminal electron acceptors. They employ a strategy of direct contact on the metal-oxide facilitating deposition of transported electrons external to the cell. This contrasts with its use of other soluble electron acceptors such as fumarate and with most other forms of respiration including aerobic respiration, in which the terminal electron acceptor is reduced inside the cytoplasm of the cell. Among the metals reduced by Geobacter spp. is uranium

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(VI) to uranium (IV), which has the added benefit of decreasing uranium solubility and leading to its precipitation. This ability to precipitate uranium from solution is currently under investigation as an in situ (in place) strategy for bioremediating uranium contaminated subsurface environments (Anderson et al. 2003). The capacity to move electrons external to the cytoplasm as part of its respiratory process also creates an electrical current, which can be captured via the growth of Geobacter spp. as a biofilm on energy harvesting electrodes (Anderson et al. 2003; Bond and Lovley 2003). The genome analysis and metabolic prediction analysis of G. sulfurreducens revealed conclusively that this bacterium, possesses an ability to play critical roles in the global cycling of metals and carbon, and provided new insights into its potential as an agent of bioremediation of metals including uranium and in the generation of electricity (Anderson et al. 2003; Bond and Lovley 2003; Methe et al. 2003). Functional genomic approaches such as the use of microarray technology to examine global gene expression patterns have provided confirmations of genome predictions and discerned new information regarding G. sulfurreducens physiology. For instance a G. sulfurreducens microarray fabricated from PCR amplicons representing the complete genome and printed on glass slides was used to examine growth when using soluble iron as a sole electron acceptor. cDNA targets synthesized from mRNA extracted from cells grown when using soluble iron as a sole electron acceptor were compared to those derived from cells grown under identical conditions except for using fumarate as a sole electron acceptor. In this experiment differential expression of a number of transcription factors was determined consistent with the prediction based on genome analyses of tight gene regulation in this organism. Elucidation of increased expression of a number of metal efflux transporters during growth with iron suggested they may play an important role in metal homeostasis under this condition which was previously unknown (Methe et al. 2005b). THERMOTOGA MARITIMA METABOLISM BASED ON GENOMICS AND COMPARATIVE GENOME HYBRIDIZATION The Thermotoga maritima strain MSB8 genome revealed a number of pathways for the metabolism of plant compounds including hemicellulose and xylan, as well for the metabolism of sugars (Nelson et al. 1999). The bacterium also has a significantly high number of transporter systems that are devoted to the import of polysaccharides and oligopeptides and that appear to be a reflection of the environmental niche that this bacterium occupies. The results of a recent study (Mongodin et al. 2005b) highlight the dynamic nature of the genome of members of this genus and support the idea that there has been extensive lateral gene transfer (LGT) in the Thermotoga lineage. This genome variability is independent of the closeness of strains based on 16S rRNA phylogenetic analysis, and it highlights the limitations of using 16S rDNA sequencing and analysis as a tool to describe microbial species diversity (also see Whitaker and Banfield 2005). Although T. maritima has so far not been shown to be competent, most certainly due to the lack of efficient molecular biology tools, various type II secretion pathway proteins and type IV pilin-related proteins that function in natural competence in other bacterial species could be identified in the T. maritima MSB 8 genome (Nelson et al. 1999). Homologs of various competence genes could also be identified, suggesting that there may be an inherent system for the uptake of exogenous DNA, thereby facilitating the exchange of DNA with other organisms. From the whole-genome CGH study (in which genomic DNA from query strains of T. maritima were compared to a reference strain, T. maritima MSB8, using microarray technology), it is evident that T. maritima strains vary in the total number of genes and metabolic capabilities when compared to the reference T. maritima MSB8 (Mongodin et al. 2005b).

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For example, strain PBlplatt is most divergent in terms of metabolic capabilities, and either does not use the plant polymers pectin or xylan, or glycerol, maltose, tagatose, or cellobiose for energy, or it uses systems that are divergent from those employed by strain MSB 8 and were therefore not detectable using microarrays. Compared to the other Thermotoga strains used in this study, strain PBlplatt was isolated from a unique environment, the upcoming produced fluids (oil-water-gas mixtures) from the Prudhoe Bay oil fields (for details of the organic chemistry of such materials see Brock and Pearson 2005). These geothermally heated reservoirs may represent isolated pockets of microbial communities situated deep down below the permafrost soil hostile to hyperthermophilic life. Therefore, microorganisms such as PBlplatt could represent survivors from the times where this crude oil had been formed. It is also possible that they have invaded their hot biotope very recently during the procedure used for secondary oil recovery, i.e., when seawater (which may possibly harbor some dormant hyperthermophiles which had originated from submarine vents) is pumped down into the oil reservoirs. In both hypotheses, strain PBlplatt had to adapt to an environment in which sugars and plant polymers are not (or are no longer) available. Therefore, LGT and genome plasticity are important features for genetic and metabolic evolution of the Thermotogales, and most likely in other microbial species. It is also likely that shared regulatory elements/promoters among microbial species have enabled the efficient activity of acquired genes. Alternatively, regulatory elements from other locations in the chromosome can be tapped to regulate these acquired genes and/or pathways, allowing for the success of these transfer events. COMPARATIVE GENOMICS AND PROTEOMICS, COLWELLIA PSYCHRERYTHRAEA 34H By volume, most of Earth's biosphere is cold and marine, with 90% of the ocean's waters at 5 °C or colder and fully 20% of Earth's surface environment is frozen, including permanently frozen soil (permafrost), terrestrial ice sheets (glacial ice), polar sea ice, and snow cover (Bowman et al. 1997). In terms of metabolically active biomass, these permanently cold environments are colonized principally by cold-adapted microorganisms. Psychrophilic bacteria which make up much of this active biomass are generally defined as having growth temperature optima of