Microbiology of Ethanol Fermentation in Sugarcane Biofuels: Fundamentals, Advances, and Perspectives 3031122917, 9783031122910

Table of contents :
Preface
Contents
About the Author
Chapter 1: Ethanolic Fermentation in Brazil: Characteristics and Peculiarities
1.1 Introduction
1.2 Biochemistry of Alcoholic Fermentation
1.3 Must Preparation
1.4 Systems for Conducting Fermentation
1.5 Yeast Treatment
1.6 Factors Affecting Fermentation
References
Chapter 2: The Use of Selected Yeasts in Ethanol Fermentation
2.1 Introduction
2.2 History of the Use of Yeast Strains in Ethanol Fermentation
2.3 Strain Selection: Yeast Characteristics and Selection Criteria
2.4 Using Omics to Explain the Superiority of Selected Yeasts
2.5 Genetically Modified Yeast Strains for Bioethanol Production
References
Chapter 3: Native Yeasts and Their Role in Ethanol Fermentation
3.1 Introduction
3.2 Non-Saccharomyces Yeasts
3.3 Saccharomyces cerevisiae Yeasts
3.4 Methods for Controlling the Growth of Native Yeasts
References
Chapter 4: Bacteria in Ethanol Fermentation
4.1 Introduction
4.2 Diversity of Bacteria in the Fermentation Process
4.3 Effects of Bacterial Contamination on the Fermentation Process
4.4 Methods to Control Bacterial Growth
References
Chapter 5: Methods for the Identification and Characterization of Yeasts from Ethanolic Fermentation
5.1 Introduction
5.2 Uses and Limitations of Identification Methods Based on Phenotypic Characteristics
5.3 Electrophoretic Karyotyping
5.4 Mitochondrial DNA
5.5 Microsatellites
5.6 Other Molecular Methods for Yeast Identification and Characterization of Ethanolic Fermentation
References
Chapter 6: Microbiological Techniques and Methods for the Assessment of Microbial Contamination
6.1 Introduction
6.2 Techniques for Assessing Yeast Viability in the Fermentation Process
Direct Counting Under a Microscope
Analytical Procedure
Serial Dilution and Plating on Culture Media
Analytical Procedure
6.3 Techniques for Assessing the Viability of Bacteria in the Fermentation Process
Direct Counting Under a Microscope
Analytical Procedure
Serial Dilution and Plating on Culture Media
Analytical Procedure
6.4 Gram Staining
Analytical Procedure
6.5 Tests of Susceptibility to Antimicrobials with Bacteria
Analytical Procedure
Preparation of the Inoculum
Test Performance
6.6 Composition of Culture Media and Solutions
References
Index

Citation preview

Sandra Regina Ceccato-Antonini

Microbiology of Ethanol Fermentation in Sugarcane Biofuels Fundamentals, Advances, and Perspectives

Microbiology of Ethanol Fermentation in Sugarcane Biofuels

Sandra Regina Ceccato-Antonini

Microbiology of Ethanol Fermentation in Sugarcane Biofuels Fundamentals, Advances, and Perspectives

Sandra Regina Ceccato-Antonini Department of Agroindustrial Technology and Rural Socio-Economics Center of Agrarian Sciences, Federal University of São Carlos (UFSCar) - Campus Araras São Paulo State, Brazil

The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content. 1st edition: © Sandra Regina Ceccato-Antonini 2021 ISBN 978-3-031-12291-0    ISBN 978-3-031-12292-7 (eBook) https://doi.org/10.1007/978-3-031-12292-7 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Switzerland AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland

Preface

Not so long ago, I wrote a book about the microbiology of alcoholic fermentation1 as a basic text for a subject that I taught in the undergraduate course of technology in sugar and alcohol production at Universidade Federal de São Carlos (UFSCar), São Paulo State, Brazil. Over the years, I realized that my book has been a guide used in the laboratory and that there was a scarcity of bibliographic material in the area that was concentrated in a single volume. The idea of writing a more comprehensive book, which would retain the characteristics of a guide for laboratory work, but would expand to the fundamentals, advances, and perspectives in the area of fermentation microbiology, has been with me over the past few years. The experience I accumulated while teaching in graduate courses, specialization courses, and lectures, and stimulated by the results of my own investigations, gave me the security to carry out the project of this book. The sugar-energy sector is of outstanding importance to Brazil’s economy, being the world’s largest producer of ethanol from sugarcane. The evolution in the sector, translated into increased ethanol production as well as the implementation of more environmentally sustainable technologies, occurred thanks to research developed in Brazil and in partnership with foreign groups. Gains in the sector have occurred in the agricultural and industrial areas, contributing to the projection that the sugarenergy sector has achieved nationally and internationally. Ethanol is produced through a fermentation process whose agent is the yeast Saccharomyces cerevisiae. The particularities of the Brazilian process allow high industrial yields to be obtained at the same time that they contribute to contamination by undesirable microorganisms. This is the context in which I intend to contribute here. The objective of this book, organized into six chapters, is to address the main issues related to the microbiology of fermentation for ethanol fuel production, regarding the yeast agent of the process, the contaminant microorganisms, and their interactions with the environment of the fermentative process. The book begins with

 Ceccato-Antonini, S.R. Microbiologia da fermentação alcoólica: a importância do monitoramento microbiológico em distilarias. São Carlos: EdUFSCar, 2011. 103p. 1

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Preface

an overview of ethanol fermentation in Brazil, its peculiarities and characteristics, passing through the native yeasts and bacteria that cause problems in fermentation, and highlighting the superiority of selected yeasts and the significant advance in recent years in research to unveil their most intrinsic characteristics. I could not fail to highlight the methods for the identification and characterization of yeasts and how much they have made it possible to advance in the gains of the fermentative process in terms of yield and productivity. I left for the last chapter the small guide of techniques and methods for the microbiological monitoring of fermentation, rescuing it from the aforementioned book, with the appropriate updates and additions. I hope that this book will be of use to undergraduate and graduate students and to workers in the sugar and ethanol industries. I hope that it will contribute to understanding microbial dynamics in fermentation tanks and applying microbiological monitoring methods safely and accurately. I leave in this book the result of my own trajectory at UFSCar as a researcher and professor since 1992, and I am thankful for the inspiration and motivation brought by the students in these decades of evolution of the research on the subject of microbiology of ethanolic fermentation. I also thank colleagues in the institution and those around the world for the discussion of major issues, partnerships, and projects that we had together, which contributed greatly to the reading that I could make of the body of knowledge. I also acknowledge the University Editor (EdUFSCar) for publishing this book in Portuguese in 2021 and for permitting it to be published in English language edition. I convey special thanks to my family (my husband João Batista and my beloved sons, João Fernando and João Henrique), my great inspiration and motivation. By them and for them always! To be great, be whole; don’t exaggerate Or leave out any part of you, Be complete in each thing. Put all you are Into the least of your acts. So too in each lake, with its lofty life, The whole moon shines. Fernando Pessoa

Araras, São Paulo, Brazil

Sandra Regina Ceccato-Antonini

Contents

1

 Ethanolic Fermentation in Brazil: Characteristics and Peculiarities ��������������������������������������������������������������������������������������    1 1.1 Introduction��������������������������������������������������������������������������������������    1 1.2 Biochemistry of Alcoholic Fermentation������������������������������������������    4 1.3 Must Preparation������������������������������������������������������������������������������    8 1.4 Systems for Conducting Fermentation����������������������������������������������   10 1.5 Yeast Treatment��������������������������������������������������������������������������������   11 1.6 Factors Affecting Fermentation��������������������������������������������������������   14 References��������������������������������������������������������������������������������������������������   17

2

 The Use of Selected Yeasts in Ethanol Fermentation����������������������������   21 2.1 Introduction��������������������������������������������������������������������������������������   21 2.2 History of the Use of Yeast Strains in Ethanol Fermentation ����������   22 2.3 Strain Selection: Yeast Characteristics and Selection Criteria����������   24 2.4 Using Omics to Explain the Superiority of Selected Yeasts ������������   30 2.5 Genetically Modified Yeast Strains for Bioethanol Production��������   37 References��������������������������������������������������������������������������������������������������   38

3

 Native Yeasts and Their Role in Ethanol Fermentation ����������������������   43 3.1 Introduction��������������������������������������������������������������������������������������   43 3.2 Non-Saccharomyces Yeasts��������������������������������������������������������������   44 3.3 Saccharomyces cerevisiae Yeasts������������������������������������������������������   51 3.4 Methods for Controlling the Growth of Native Yeasts����������������������   55 References��������������������������������������������������������������������������������������������������   57

4

 Bacteria in Ethanol Fermentation����������������������������������������������������������   63 4.1 Introduction��������������������������������������������������������������������������������������   63 4.2 Diversity of Bacteria in the Fermentation Process����������������������������   64 4.3 Effects of Bacterial Contamination on the Fermentation Process����   67 4.4 Methods to Control Bacterial Growth����������������������������������������������   72 References��������������������������������������������������������������������������������������������������   78

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Contents

5

 Methods for the Identification and Characterization of Yeasts from Ethanolic Fermentation ����������������������������������������������������������������   83 5.1 Introduction��������������������������������������������������������������������������������������   83 5.2 Uses and Limitations of Identification Methods Based on Phenotypic Characteristics����������������������������������������������������������   84 5.3 Electrophoretic Karyotyping������������������������������������������������������������   89 5.4 Mitochondrial DNA��������������������������������������������������������������������������   92 5.5 Microsatellites����������������������������������������������������������������������������������   94 5.6 Other Molecular Methods for Yeast Identification and Characterization of Ethanolic Fermentation������������������������������   97 References��������������������������������������������������������������������������������������������������   99

6

 Microbiological Techniques and Methods for the Assessment of Microbial Contamination��������������������������������������������������������������������  103 6.1 Introduction��������������������������������������������������������������������������������������  103 6.2 Techniques for Assessing Yeast Viability in the Fermentation Process����������������������������������������������������������������������������������������������  104 Direct Counting Under a Microscope��������������������������������������������   104 Serial Dilution and Plating on Culture Media��������������������������������   107 6.3 Techniques for Assessing the Viability of Bacteria in the Fermentation Process��������������������������������������������������������������  112 Direct Counting Under a Microscope��������������������������������������������   112 Serial Dilution and Plating on Culture Media��������������������������������   113 6.4 Gram Staining ����������������������������������������������������������������������������������  114 Analytical Procedure����������������������������������������������������������������������   115 6.5 Tests of Susceptibility to Antimicrobials with Bacteria��������������������  115 Analytical Procedure����������������������������������������������������������������������   116 6.6 Composition of Culture Media and Solutions����������������������������������  118 References��������������������������������������������������������������������������������������������������  121

Index������������������������������������������������������������������������������������������������������������������  123

About the Author

Sandra Regina Ceccato-Antonini,  Ph.D., is a full professor in the Department of Agroindustrial Technology and Rural Socio-Economics, Center of Agrarian Sciences, at the Federal University of São Carlos (UFSCar). She received her ­master’s and Ph.D. degrees in Biological Sciences at São Paulo State University (UNESP), Campus Rio Claro, in 1989 and 1993, respectively. Professor CeccatoAntonini did her postdoctoral studies at the Luiz de Queiroz College of Agriculture, University of São Paulo (Brazil), and in the University of Sheffield (United Kingdom) in molecular genetics of yeasts. She has experience in the area of microbiology, with emphasis on industrial microbiology and fermentation. She was a member of the Brazilian National Technical Biosafety Commission (CTNBio) from 2017 to 2023.

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Chapter 1

Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

1.1 Introduction Brazil is the largest sugarcane producer in the world, the main raw material for ethanol production, which guarantees to this country the second position in the world in this biofuel production nowadays (UNICA 2022). Brazilian production of ethanol accounts for approximately 30% of the total world production, whereas the United States is responsible for about 54% of the global ethanol production but primarily from corn (Jacobus et al. 2021). The big stimulus to ethanol production in Brazil came in the 1970s due to the petroleum crisis, when the federal government launched the “National Alcohol Program” (Proálcool). At that time, the ethanol produced was added to gasoline, but with the second oil crisis in 1979, the Brazilian automobile industry started producing cars powered by ethanol. Since then, ethanol production in Brazil has gone through different phases alternating between stimulus and stagnation, which are summarized in Table 1.1. Ethanol can be produced chemically or microbiologically, the latter being the most important route used for ethanol production worldwide, in a process known as alcoholic or ethanolic fermentation. During this process, sugars are converted by yeast into ethanol, energy, cell biomass, carbon dioxide (CO2) and other by-­products. The sources of sugar are varied, but in Brazil the main raw material is sugarcane, while in the United States ethanol is produced from corn, the two largest ethanol-­ producing countries in the world. Both sugarcane and corn are C4 plants with high efficiency in converting atmospheric CO2 and water into sugar and polymers such as starch, cellulose and hemicellulose through photosynthesis. In this process, the energy of sunlight is utilized to fix carbon and release oxygen into the atmospheric air. Thus, all the CO2 resulting from the burning of ethanol is recycled through photosynthesis. The reduction rate of greenhouse gas emissions is 40–62% when sugarcane ethanol is used in comparison with gasoline (Wang et  al. 2012; Lopes et al. 2016). © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_1

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1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

Table 1.1  Timeline showing the main events and consequences related to ethanol production in Brazil Date/period Until the 1970s

Main event Availability and low cost of petroleum products October 1973 Oil crisis

14 November Creation of Proálcool, 1975 to stimulate the national production of fuel ethanol 1975–1979 Production of (first phase of anhydrous alcohol to be Proálcool) mixed with gasoline 1980–1986 The second oil shock in (second 1979–1980 phase of consolidated the Proálcool) Program 1986–1995 Stagnation phase of (third phase Proálcool due to the of Proálcool) significant decrease in crude oil barrel prices 1995–2000 Program redefinition (fourth phase phase, with the of Proálcool) liberation of the anhydrous and hydrated alcohol markets in all production phases 2001–2008 Rush to expand units by private initiative decisions and development of flex fuel engine technology in 2003 2008–2015

Consequences Inhibition of the development of fuel ethanol

International crisis increased Brazil’s expenditures with oil imports, causing a deficit in the balance of trade and consequent increase in Brazil’s foreign debt and inflation Reduction of oil imports by encouraging the substitution of gasoline by ethanol

Brazilian ethanol production grew from 600 million to 3.4 billion litres/year in 4 years. Emergence of the first cars powered exclusively by ethanol in 1978 Ethanol production reached 12.3 billion litres in 1986–1987. Proportion of cars powered by alcohol increased from 0.46% in 1979 to 26.8% in 1980, reaching 76.1% in 1986 Lack of public resources to stimulate alternative fuels, low supply of ethanol compared to the growth in demand for ethanol-powered cars, creating a shortage crisis Prices determined by supply and demand conditions. There was a significant drop in the production of alcohol-powered vehicles

Production of flex fuel cars surpassed that of gasoline-­ powered cars in 2005. Increase in ethanol producers’ expectations of investing in crop expansion, evidenced by the steep increase in cane crushing over a 30-year period. Acceleration of the end of sugarcane burning, increased mechanization of harvesting and of the planted area Long crisis in the sugar Investors have suspended the construction of new mills, and ethanol sector due production units have closed, and the production of to internal and external sugarcane, sugar and ethanol has stagnated. The main factors internal and external factors generating the crisis are pre-salt oil reserves, gasoline subsidies, competition between sugarcane and food in terms of planted area, lack of biofuel support policy, climate factors and low productivity (continued)

1.1 Introduction

3

Table 1.1 (continued) Date/period 2016 to date

Main event Creation of the National Biofuel Policy (RenovaBio) in 2017

Consequences RenovaBio, aiming to stimulate the use of biofuels and reduce the consumption of oil derivatives, creates a new source of revenue for biofuel plants, which are the Decarbonization Credits (CBIOs), issued by producers and traded on the stock exchange. The issuing of CBIOs considers the volume of biofuel produced and the energy-environmental efficiency of each biofuel plant

Sources: Alcarde (2008); Cortez et al. (2016); Almeida et al. (2017); Ceise (2020); Rinke Dias de Souza et al. (2021)

Although Brazil and the United States are the world’s largest producers of ethanol, there are significant differences between the fermentation processes used. Brazilian distilleries use an improved process that was patented in 1937 by Firmino Boinot from the Melle region in France and called Melle-Boinot, which consists of recycling the yeast cells at the end of each fermentation cycle (Lopes et al. 2016). The fermentation process as it is used in Brazil has peculiarities that make it productive and allow fast fermentation cycles; however, they also make it susceptible to contamination by undesirable microorganisms. The recycle of the cells implies that at the end of each fermentation, the fermented must (called wine) is centrifuged for the separation of the yeast (Saccharomyces cerevisiae) cells from the wine, which follows to the distillation to obtain ethanol. The concentrated cream of cells undergoes treatment with an aqueous solution of sulfuric acid (pH 2.0–2.5, for 1–2 h) in the step known as yeast acid treatment, whose main objective is to reduce the amount of bacterial contaminants and promote yeast deflocculation, if applicable. The acid-treated cells return to the fermentation tanks where new fermentation mash is introduced for a new fermentation cycle (Lopes et al. 2016). The Brazilian fermentation process uses large fermentation tanks (0.5–3 million litres), high cell densities (10–15% w/v), short fermentation periods (6–12 h), sugarcane musts consisting of sugarcane juice or diluted molasses or a mixture of both and mostly the fed-batch operational model. Distilleries attached to sugar factories (mills) usually use molasses, a by-product of sugar manufacturing, diluted with water or mixed with sugarcane juice as fermentation mash, while independent distilleries use only sugarcane juice for fermentation (Amorim et  al. 2009). In fed-­ batch model, the must is first introduced into the fermentation tanks already containing a volume of acid-treated yeast cells derived from the previous fermentation cycle. The must feeding continues for around 6 h in three or four tanks simultaneously. During feeding, sucrose is hydrolysed to glucose and fructose which are converted to ethanol, CO2 and yeast cells. Yeast cell mass increases approximately 10% in relation to the initial value during the fermentation process. The must feeding continues until 80% of the total volume of the tank is reached, following a period of 2–4 h required for cells to consume the reducing sugars. Temperature is controlled at a maximum of 35 °C. The wine consists of water, yeast cells and ethanol, the latter reaching titres of 7–11% (on a volume basis), and the residual sugar

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1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

concentration in the wine is less than 0.1%. The wine is centrifuged to separate the yeast cells, which are treated with sulfuric acid and then returned to the fermentation tanks for a new fermentation cycle. The sugarcane harvest lasts around 200–300 days, and considering fermentation cycles of 12 h, the yeast cells are recycled approximately 400–600 times during the harvest. The cell recycling and the non-sepsis of the process are peculiarities of the Brazilian fermentation process (Amorim et al. 2011; Pereira et al. 2018). Distillation of wine results in hydrated ethanol (96% by volume) or anhydrous alcohol after dehydration with cyclohexane, monoethylene glycol or molecular sieves (Wheals et al. 1999). The main residue of the fermentative process in terms of volume is generated after distillation of the wine, constituting the vinasse, a dark, acidic liquid, rich in minerals, such as potassium, calcium, magnesium, nitrogen and phosphorus, and which is used as fertilizer on sugarcane plantations. Brazilian distilleries produce about 10–15 litres of vinasse for each litre of ethanol (Mutton et al. 2010; Amorim et al. 2011). Although cell recycling is a common characteristic in all ethanol-producing units, there is no single process standard adopted by all Brazilian distilleries, varying the fermentation system, the composition and treatment of the fermentation mash, the yeast strains used as starters, the operating conditions of the process and the treatment of the yeast, among others. When considering fermentation as a living process, it is important to have an understanding of how this process occurs at the microscopic level as well as the influences it is subject to as a result of the characteristics of the industrial process.

1.2 Biochemistry of Alcoholic Fermentation Ethanol can be produced by fermentation of fermentable sugars from agricultural products, cellulosic materials or plant residues (Baptista et al. 2006). Currently, the production of ethanol at industrial level obtained by alcoholic fermentation uses predominantly raw materials containing sugars and starches, because they are economically more favourable (Hira and Oliveira 2009). In Brazil, sugarcane is mostly used as raw material for ethanol production (Basso et  al. 2008; Della-Bianca et al. 2013). The production of ethanol by fermentation is basically composed of three stages, which are the preparation of the must, the fermentation process and the distillation of the fermented must (the wine). Initially, the sugarcane is milled, obtaining a juice with 78–86% of water and 10–20% of sucrose, besides reducing sugars, ashes and nitrogen compounds, which are 0.8–3.5% in total, with a pH ranging from 5.2 to 6.8. The yeast Saccharomyces cerevisiae performs the conversion of sugars into ethanol by the fermentative route (Lima et al. 2001) and is the microbial species most used in industrial processes due to its characteristics of high productivity in ethanol, high tolerance to ethanol and ability to ferment a wide range of sugars.

1.2  Biochemistry of Alcoholic Fermentation

5

According to Lima et al. (2001), the industrial process of alcoholic fermentation can be divided into three phases: preliminary fermentation or pre-fermentation, main fermentation or tumultuous fermentation and complementary fermentation or post-fermentation. The preliminary fermentation begins with the addition of the must to the yeast mass. When the inoculum is small, this phase is characterized by the multiplication of the yeasts, with consequent consumption of sugars and slow alcohol production. Therefore, a larger quantity of yeasts of fast multiplication should be used. With the increase of alcohol production, evidenced by the production of CO2, this phase comes to an end, and the main or tumultuous fermentation phase begins. The main characteristics of the main fermentation phase are intense alcohol production and release of CO2; temperature increase, which must be controlled by cooling; progressive increase of foam; and elevation of must acidity. The main fermentation ceases when the gas release decreases and, consequently, the characteristic turbulence of the must. In the post-fermentation phase, the wine’s temperature decreases, the acidity increases, and the yeast’s fermentation activity decreases due to the accumulation of certain substances, the depletion of carbohydrates and the metabolic products of contaminants. Biochemically speaking, fermentation is the incomplete oxidation of sugar, generating as a by-product an oxidizable organic compound. Initially sucrose, which is the reserve sugar in sugarcane, is hydrolysed by the enzyme invertase and converted into the monosaccharides glucose and fructose. This enzyme is encoded by the SUC2 gene, and two variants of the enzyme are found in S. cerevisiae: a glycosylated form, subject to glucose repression and secreted into the periplasmic space (outside the cell, between the cell wall and the cytoplasmic membrane), also called extracellular invertase, and a non-glycosylated form, which is constitutively produced and present in the cytosol of the cell, known as intracellular invertase. The glycosylated form represents most of the activity of this enzyme in S. cerevisiae (Carlson and Botstein 1982). The monosaccharides glucose and fructose enter the cell by facilitated diffusion and undergo intracellular phosphorylation in the first step of the glycolytic cycle. However, in the case of the active transport of sucrose into the cell, the ATP yield is 25% lower (three ATPs are produced instead of four ATPs), since one ATP is consumed by the H+-ATPase pumps to release the proton that entered along with the disaccharide (Weusthuis et  al. 1994). Inside the cell, sucrose is converted into glucose and fructose by the action of intracellular invertase. One way or another, both monosaccharides enter the glycolytic pathway and, through a sequence of reactions, are converted to pyruvate. The latter is first decarboxylated by the enzyme pyruvate decarboxylase, forming acetaldehyde and releasing CO2. Subsequently, acetaldehyde is reduced to ethanol, and this reaction is catalysed by the enzyme alcohol dehydrogenase (Nelson and Cox 2014). Alcoholic fermentation can be schematized by the following equation:

C6 H12 O6  2 ADP  2 Pi  2 C2 H 5 OH  2 CO2  2 ATP  2 H 2 O

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1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

Alcoholic fermentation results from two distinct processes, glycolysis (Embden-­ Meyerhof-­ Parnas pathway) and anaerobic pyruvate metabolism. In eukaryotic microorganisms, glycolysis takes place in the cytoplasmic matrix and is divided into two parts: the initial six-carbon phase and the final three-carbon phase. The purpose of sugar metabolism is to generate a form of energy, ATP, which will be used in various physiological functions (absorption, excretion and others) and biosynthesis necessary for the maintenance of life, growth and multiplication of the yeast (Nelson and Cox 2014). In the six-carbon phase, glucose phosphorylates twice to fructose-1,6-­ diphosphate, consuming two molecules of ATP. Fructose-1,6-diphosphate is broken down to release two different trioses, glyceraldehyde-3-phosphate (aldose) and dihydroxyacetone phosphate (ketose) by the action of the enzyme aldolase. Only glyceraldehyde-3-phosphate can be directly degraded in the following reactions of glycolysis; however, dihydroxyacetone phosphate is rapidly and reversibly converted into glyceraldehyde-3-phosphate by the enzyme triose phosphate isomerase. Thus, the following steps up to ethanol formation run twice (Nelson and Cox 2014). In the three-carbon phase, conversion to pyruvate occurs, forming four ATP molecules. The process of reduction of pyruvate to ethanol can be divided into two steps: in the first step occurs the decarboxylation of pyruvate in an irreversible reaction catalysed by pyruvate decarboxylase, and in the second step, acetaldehyde is reduced to ethanol (Nelson and Cox 2014). The transformation of sucrose into ethanol and CO2 involves 12 reactions in an ordered sequence, each catalysed by a specific enzyme, as shown in Fig. 1.1. Ethanol and CO2 are not the only products obtained through alcoholic fermentation. Besides these, there are several by-products such as organic acids, other alcohols and glycerol (Bai et al. 2008). Glycerol is the main by-product of ethanolic fermentation. It is synthesized by the reduction of dihydroxyacetone phosphate to glycerol-3-phosphate and then by the dephosphorylation of this substance to glycerol. The enzymes that catalyse these reactions are products of the GPD1 or GPD2 and GPP1 or GPP2 genes, and this pathway seems to be the only route for glycerol production in S. cerevisiae, since gpd1/gpd2 mutants are unable to produce glycerol. Glycerol plays an important role in maintaining the redox balance of the cell, as a precursor of phospholipids and triacylglycerol lipids and as an osmoregulator (Nevoigt and Stahl 1997). It is important to highlight the role of glycerol in the redox balance during fermentation. Under anaerobic conditions, the coupling of glycolysis and ethanol production presents zero oxireduction balance; however, the synthesis of organic acids as well as some anabolic reactions produces excess NADH, causing redox imbalance. The reduction of dihydroxyacetone phosphate to glycerol-3-phosphate occurs at the expense of NADH (Pagliardini et al. 2013). A point worth noting is regarded to the methodology to calculate the process performance. The parameters commonly considered are ethanol titre, productivity (or rate) and yield, being the latter the most prioritized (Bermejo et al. 2021). Yield is commonly used as a synonym of efficiency, but these parameters have relevant differences in the form of calculation. “Yield” is measured as a unit of mass of ethanol produced per unit of mass of sugar consumed, whereas “efficiency” is an

1.2  Biochemistry of Alcoholic Fermentation

7

Fig. 1.1  Schematic representation of the steps for conversion of sugars to ethanol, CO2 and glycerol that occur in the cytosol of yeast cells. The scheme represents the hydrolysis of sucrose by the enzyme invertase that occurs both extracellularly and intracellularly. (Source: Costa 2017, modified)

expression (in percentage) of the fermentation yield in relation to the stoichiometric factor of 0.511, which considers that from 1 g of glucose, 0.511 g of ethanol and 0.489 g of CO2 could be produced (theoretical maximum yield is 0.511 g ethanol/g sugar). Several factors, such as contamination by bacteria and native yeasts, operational issues, production of cell and side products, limit the efficiency to around 92% of the theoretical yield (Della-Bianca et al. 2013). Ethanol yield calculated on sugar consumption is the most important parameter utilized in the industries because the substrate accounts for approximately 70% of all operational costs (Bermejo et  al. 2021). Although diverse methodologies are used industrially to calculate efficiency, some important variables have been neglected, and some have been overestimated, resulting in inaccurate values to express the process efficiency. Pereira et al. (2018) validated a new methodology applying to 18 industrial fed-batch fermentation units and to bench-scale fed-batch

8

1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

fermentations, comparing to the classical methodologies to calculate efficiency. The main difference of this proposed methodology in relation to the most usual methodology employed in industrial units is the fact that the volume of yeast cells is discounted from the determination of ethanol produced in the fermentation process. Only the extracellular ethanol is considered as final product because the intracellular ethanol is not possible to recover from cells in the actual model of Brazilian distilleries. As a result, the industrial ethanol efficiency is in reality around 85% of the theoretical maximum value, and not around 90–92% as it has been reported (Bermejo et al. 2021). What must be taken into account is that there are undetermined losses in the fermentation process, leading to an overestimation of the fermentation efficiency and raising questions regarding the need for greater investment in sampling and analysis techniques during the process.

1.3 Must Preparation With the deregulation of the sugar and ethanol sector in 1990, reducing government intervention and the liberalization of sugar exports, there was a considerable increase in the export of this product, and as a consequence, the mills were annexed to the existing autonomous distilleries, consolidating the model that persists to this day of integrated sugar and ethanol production (Dias et al. 2015). The sugar-ethanol integration reverberates significantly in the fermentation process for ethanol production, since the fermentation musts can vary between production units and even within the same harvest, depending on the prices of sugar, ethanol and gasoline in the domestic and foreign markets. This trade-off results in the variation of the availability of sugarcane juice or molasses for ethanol production, since with the preference for sugar production the sugarcane juice is mobilized to the mill, leaving the molasses, a by-product of sugar manufacturing, as the must for alcoholic fermentation. Figure 1.2 illustrates the integrated production processes of sugar and ethanol with emphasis on the main by-products generated, such as vinasse, molasses and bagasse. Some initial operations are common to both the mill and the distillery, namely, the reception of the cane, the preparation of the cane and the extraction of the juice from the cane. After the arrival of the cane in the industry, washing takes place to eliminate adhered soil and impurities. There are differences in the reception of cane harvested after burning or by mechanized harvesting. In the first case, it is the whole cane that is thus washed; in the second case, dry cleaning of the cut canes is used to avoid sugar loss (Leal 2010). Then, the cane is cut with knives and shredders, which promote the opening of the cells to release the juice. The juice is extracted by mills consisting of four to six suits arranged in series, each containing four rollers, where the extraction process occurs by mechanical pressure. Upon receiving the first compression, the chopped and shredded cane releases the juice known as primary juice, the bagasse follows the conveyor belt to the next suit, and so on. At the end of the process, the bagasse has about 50% of humidity and is sent

1.3  Must Preparation

9

Fig. 1.2  Representative diagram of the processes for the production of sugar and ethanol in Brazil, highlighting the main by-products such as bagasse, molasses and vinasse. (Source: From the author)

to the boilers for steam generation, which is necessary in all the processing and to drive the mills. Many times the soaking process is used, which consists in adding water or the extracted juice itself to the bagasse between one suit and another, with the purpose of increasing sucrose extraction. Usually, the primary juice is sent to the mill for sugar production because it is purer and more concentrated, while the juice of the second suit (mixed juice) goes to the production of ethanol (Dias et al. 2015). Some industrial units use the diffusion process for juice extraction, in which sucrose adsorbed to the fibrous material of the sugarcane is diluted and removed by leaching or washing in a countercurrent process. Sucrose extraction efficiency is higher in diffusers than in mills, and there is also less energy consumption in diffusion (Macedo and Cortez 2005; Dias et al. 2015). The treatment of the mixed juice, used in the production of ethanol, initially includes a sieving stage to eliminate coarser impurities such as fibres and sand. Initially, rotary sieves integrated with the extraction set are used, and then hydrodynamic sieves and hydrocyclones are used, which will enable the removal of smaller fibrous material, sand and soil, respectively. The juice thus treated undergoes preheating at a temperature of 70  °C, addition of lime, subsequent heating to

10

1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

approximately 105  °C, deaeration, addition of polymer to cause flocculation and final removal of impurities through decantation. The sludge obtained from clarification is filtered to increase sucrose recovery. The clarified juice is heated again to thermally kill the microorganisms and immediately pre-cooled, followed by final cooling to a temperature of 32 °C, before being directed to the fermentation vat. The juice thus produced has approximately 18–20o Bx (soluble solid content), which is equivalent to approximately 13–15% of total sugars (Oliva-Neto et al. 2013). The juice can be concentrated in continuous evaporators as a strategy to obtain fermentation with high alcohol content, due to the increase in total sugar content. In addition, concentration ensures the continuity of the fermentation process when milling stops, allowing the storage of the juice, now called syrup. The ideal concentration for storing the syrup is around 50–55° Bx, starting initially from a concentration of around 14–16° Bx in the juice (Macedo and Cortez 2005). The treatment of juice for sugar production comprises the same steps as the treatment of juice for ethanol production. However, more lime is required for sugar production, besides the addition of sulphur dioxide (SO2) in a process called sulphitation, which reduces the colour of the syrup for white sugar production, causes coagulation of soluble solids and reduces the viscosity of the juice to facilitate evaporation and crystallization operations (Macedo and Cortez 2005). During sugar production, the cane juice is clarified with lime and concentrated through repetitive evaporation and centrifugation steps. The concentrated juice goes through a crystallization step to form sucrose crystals that are removed by centrifugation. The resulting dark and viscous liquid is called molasses and contains 45–60% sucrose and 5–20% glucose and fructose (Amorim et al. 2011; Basso et al. 2011). Molasses can be used in combination with sugarcane juice to increase the sugar concentration in the must, or it can be diluted with water, replacing sugarcane juice. The composition of the musts prepared from juice or molasses or a mixture of both influences the fermentation performance (Amorim et  al. 2009; Basso et al. 2011).

1.4 Systems for Conducting Fermentation The fermentative processes can be classified according to the way they are developed in batch or discontinuous and continuous, with variations in each. In the batch process, the mash is placed at once along with the inoculum, and when the maximum production is reached, the process is terminated. In Brazilian distilleries, the fed-batch process is also used, consisting of intermittent feeding of must and without removal of the fermented broth. In this system, the yeast cream treated with acid is sent to the fermentation vat, which is filled with must in a controlled flow, which avoids the stress by osmotic shock. Several fermentation vats can be used, but each one ferments individually. Each vat is filled, handled and cleaned separately from the others. The following advantages are attributed to this system: reduction of substrate and end product inhibition, decreased fermentation time, higher ethanol

1.5  Yeast Treatment

11

productivity, easier measurement of fermentation yield as the volume is kept constant, less susceptibility to bacterial contamination as each vat is washed after each fermentation cycle reducing the use of antimicrobials, lower acidity of the wine, less risk of flocculation and better performance of the centrifuges, easier optimization of the feeding time of vats and possibility of extending the fermentation time if the residual sugar concentration is high. It is estimated that the fed-batch system is employed in about 83% of the distilleries, and yields of 92–95% can be achieved (Godoy et al. 2008). The continuous system was proposed in the 1980s and consists in the continuous feeding of all the inoculated must into one or more vats that are always kept full during the process. The partially fermented wine overflows into a second tank, which is kept full, and from this tank, it overflows into a third and fourth tank, in series, until all the sugars are consumed. From the last vat, the wine goes to the centrifuges, where the yeast cream is separated and follows to the acid treatment. Then, the treated yeast is sent back to the first vat where it is fed together with the must and a new cycle begins. In the continuous system, the must and yeast are added in the first vat, starting the fermentation. This inoculated must is then pumped to the other vats, finishing the fermentation in the last vat. All the vats ferment simultaneously and cannot be washed frequently (CNPEM 2017). Continuous fermentation has advantages over fed-batch fermentation because it is less expensive to implement, costing around 50–60% less, and is easier to automate. However, the disadvantages lie mainly in the difficulty of controlling contamination by native bacteria and yeasts, greater difficulty in assessing the fermentative yield due to volume variations in the vats and osmotic stress (Godoy et al. 2008). Regarding fermentative yield, better results have been obtained with fed-batch fermentation, and at best, the yields are comparable, because continuous fermentation rarely shows superior yield (Godoy et al. 2008; CNPEM 2017).

1.5 Yeast Treatment When fermentation ends, the yeast cells are separated from the wine by centrifugation, resulting in a yeast cream with 60–70% (w/v) cells. This concentrated cream is then diluted with water and treated with sulfuric acid at a pH ranging from 1.8 to 2.5 for a period of 1.5–3  h. This diluted and acidified yeast suspension is known in practice by the name of pé-de-cuba in Brazil. Then, this concentrated yeast cream is used to restart fermentation in the vat with fresh must (Lopes et al. 2016). The use of acid treatment to combat bacterial contamination is not a new practice in the fermentation industry, especially in brewing (Simpson and Hammond 1989). The acid treatment reduces bacterial contamination and yeast cell flocculation, either caused by bacteria or by an intrinsic characteristic of the strain (Amorim et al. 2011). There are few studies that show the efficiency of acid treatment in numbers. Gallo (1989) found a 44.55% reduction in the number of bacteria using sulfuric acid treatment of the cells. Laboratory experiments showed a three log cycle (99.9%)

12

1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

reduction in the number of the bacterium Lactobacillus fermentum using sulfuric acid treatment (Costa et al. 2018; Silva-Neto et al. 2020). Yeast can tolerate low pH but acid treatment can cause physiological disturbances in yeast cells, especially under specific conditions such as predominantly very young or very old cells (Oliva-Neto et al. 2013). Reserve carbohydrates, such as glycogen and trehalose, are attributed to the ability of yeast to withstand acid stress during yeast treatment (Basso et al. 2008). Melo et al. (2010) studied the molecular mechanisms that allow cells of an industrial strain of S. cerevisiae (JP1) to survive in low pH environments. About 65 genes were significantly overexpressed in the low pH condition (2.0), being related to stress response mechanisms, as well as to cell morphogenesis and cell wall biogenesis, and in the biosynthesis of stress-induced metabolites such as glycerol and trehalose. The results showed that low pH activates the general stress response (GSR), which is important for long-term cell survival. It was also suggested that there is a protein kinase A (PKA)-dependent regulatory mechanism that affects the cell cycle to acquire tolerance to the acidic environment. Lucena et al. (2012) complemented this study by using two experimental strategies (cell growth and gene expression) to show that genes involved in the cell wall integrity mechanism and the PKC-MAPK pathways (protein kinase C-mitogen-activated protein kinase) are essential for yeast cell growth in acidic environments. Lucena et  al. (2015) demonstrated that the survival of an industrial strain of S. cerevisiae depends on metabolic reprogramming of the cells to ensure cell viability by inhibiting cell growth under unfavourable conditions such as acidic conditions. In this situation, there is differential expression of a set of genes related to cell wall composition and integrity, oxidation-reduction processes, carbohydrate metabolism, ATP synthesis and iron absorption. Studies have shown the tolerance of industrial S. cerevisiae yeasts to the acid environment (Della-Bianca et al. 2014; Reis et al. 2017; Costa et al. 2018; Silva-­ Neto et al. 2020), so that the acid treatment does not cause significant impact to the process yeast if performed properly. There is also no doubt about the efficiency of acid treatment in reducing bacterial contamination and its effects such as in yeast deflocculation, but the main issue that ultimately falls on its use is the cost of the acid and safety in handling. It is necessary to search for safer and environmentally correct alternatives that assure the minimization of the contamination effects. The use of antibiotics should be avoided due to their retention in the by-products of fermentation such as in the dried yeast that is marketed for animal feed (Amorim et al. 2011) and in the vinasse, which by being used in fertigation can carry antibiotics that will be disseminated in the environment leading to the increase of bacterial resistance to antibiotics. Bacterial strains resistant to several antibiotics have already been isolated from ethanol production units (Murphree et al. 2014; Mendonça et al. 2016). Furthermore, the presence of antibiotics in vinasse can affect the process of anaerobic biodigestion of vinasse for biogas production because it inhibits acetogenic and methanogenic bacteria (Sanz et al. 1996; Assad 2017). A series of chemical agents with bacteriostatic and bactericidal action have been tested in laboratory scale, but the one that has stood out in industrial scale is the

1.5  Yeast Treatment

13

chlorine dioxide. This substance is usually employed in water treatment systems to combat bacteria, viruses and algae, having a strong oxidizing action (Lapolli et al. 2005). In 2012, the patent for chlorine dioxide for use in fermentation was approved, called DuPont™ Fermasure®. Many Brazilian distilleries have replaced antibiotics and about 40% of the acid treatment by the use of chlorine dioxide at a concentration of 30 mg/L (Furtado 2013). Ethanol itself, due to its bactericidal action, could be used in combination or not with sulfuric acid in an attempt to minimize or even eliminate the volume of acid spent in the treatment of yeast. The pioneering study by Ceballos-Schiavone (2009) evaluated the addition of 15, 20, 25, 30 and 35% concentrations of ethanol to acid solutions with different pH values (2.5–6.0) in order to assess the effect on the growth of seven Lactobacillus species. The combination of pH 2.5 and 20% ethanol for 2 h of incubation was the best condition to completely eliminate the number of bacteria. Increasing the pH to 6.0 required a concentration of 25% ethanol to cause the same effect. Costa et al. (2018) tested concentrations of less than 15% ethanol added to pH 2.0 acid solution and reported the complete loss of L. fermentum viability already at the end of the first treatment cycle with the concentration of 5% ethanol and pH 2.0. The experiments were carried out with sterilized cane juice in cocultures of S. cerevisiae and L. fermentum. The treatment was continued for six fermentation cycles, and although it had no effect on the viability of the industrial strain of S. cerevisiae, there was a decrease in ethanol production. In this context, Silva-Neto et al. (2020) tested this same concentration of ethanol in acidic solutions with pH higher than 2.0 and did not obtain significant reduction in the number of L. fermentum. To cause total loss of viability of the bacteria, a concentration of 20% ethanol in acid solution pH 3.0 or 22% ethanol in water without acid addition would be required. These results show that the total replacement of sulfuric acid with ethanol is not feasible due to the high concentration of ethanol required to cause the death of the bacteria. Reducing the amount of acid in the combined treatment with ethanol also had no effect in controlling contamination because a high concentration of ethanol (20%) is necessary to be added to the acid solution pH 3.0, that is, four times more ethanol compared to the acid solution pH 2.0 (5% ethanol), to cause total loss of L. fermentum viability. These concentrations of ethanol are too high to be used in the industrial context. Silva-Neto et al. (2020) also tested the application of acid treatment pH 2.0 with the addition of 5% ethanol in fermentation performed with the industrial strain PE-2  in non-sterile sugarcane broth contaminated with L. fermentum (108 CFU/ mL), resulting in total loss of viability of the bacteria in the first fermentative cycle. In other cycles, even using non-sterile broth but without inoculation of L. fermentum, only the acid treatment pH 2.0 (without addition of ethanol) was sufficient to cause loss of viability of native bacteria in the broth. The highest alcohol contents were obtained with the combined treatment pH 2.0 + 5% ethanol in fermentations contaminated with L. fermentum. The results point to the use of ethanol in combination with acid treatment in situations where only acid is not able to combat bacterial contamination, replacing the use of antibiotics.

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1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

The yeast treatment step is extremely important in the fermentation process as a whole, directly impacting the fermentation yield as it reduces bacterial contamination. However, it has received little attention in order to quantify the efficiency of sulfuric acid in combating the different species of bacteria present in the process and to seek safer and environmentally friendly alternatives to sulfuric acid.

1.6 Factors Affecting Fermentation The characteristics of the fermentation process impose on yeast a series of conditions that can affect their growth and fermentative capacity. Several factors can affect the fermentation such as high ethanol concentration, high osmotic pressure, low pH, temperature variations in the tanks, composition of the fermentation mash and contamination by bacteria and native yeasts. The effect of these factors can be intensified by the practice of cell recycle, which includes acid treatment of the yeast between each fermentation cycle (Basso et al. 2011). The composition of the fermentation mash is an important factor for the yeast performance in fermentation, because molasses and sugarcane juice have significant differences in their chemical composition. While sugarcane juice may present some nutritional deficiencies, molasses may contain substances considered inhibitory for yeasts, such as sulphite, for example, due to the juice sulphitation step for sugar production. As a result, the mixture of sugarcane juice and molasses can be a better alternative than each one separately (Amorim et al. 2009). The advantages of using molasses are that it is a medium already concentrated in sugars, eliminating the need to concentrate the sugarcane juice. The toxic effect of aluminium is lower in molasses than in juice probably due to the chelating properties of some components of molasses. Low pH of the fermentation medium converts aluminium present in musts to its toxic form (Al+3), causing reduction in yeast viability, trehalose levels and fermentation rates. Magnesium attenuates the effect of aluminium, highlighting the importance of adding dolomitic lime with high magnesium content in the juice treatment step. On the other hand, molasses presents high concentrations of potassium causing effects on yeast metabolism, with reduced fermentation yield, cell viability and trehalose levels; high concentrations of calcium, increasing the effect of flocculation caused by bacteria; and presence of substances inhibiting microbial growth such as furfural, formic acid and other compounds originating from Maillard reactions (Eggleston and Amorim 2006; Amorim et al. 2009). The presence of sulphite in molasses due to the sulphitation process in the sugar mill can inhibit yeast metabolism, especially considering that its inhibitory action is directly related to pH, being more toxic in more acidic media, such as alcoholic fermentation (Oliva-Neto et al. 2013). Must composition is a factor that interferes with the interactions between microorganisms during fermentation, potentially exerting a selection force to favour specific microorganisms (Tosetto 2008). Higher acetate production was found in molasses mash than in sugarcane juice mash when the fermentation conducted by

1.6  Factors Affecting Fermentation

15

S. cerevisiae was contaminated with D. bruxellensis (Pereira et al. 2014) or with native S. cerevisiae rough yeast and L. fermentum (Reis et al. 2018). The effect of molasses on the fermentative yield in fermentations contaminated with D. bruxellensis and L. fermentum was higher than with sugarcane juice (Bassi et al. 2018), showing that the must composition can interfere with the interactions between the different microorganisms present in the vat, with the risk of favouring the contaminants more than the main yeast. The pH of the fermentation mash is a factor of importance when considering the presence of organic acids in the medium, such as lactic acid and acetic acid, produced by bacterial contaminants. In addition, the sugarcane juice or molasses itself presents a complex composition of organic acids such as trans-aconitic, malic, citric, succinic, oxalic, tartaric and glycolic acids (Basso and Lino 2018). In the acidic medium of the fermentative environment, these acids in protonated form can enter yeast cells, and upon encountering the higher intracellular pH (around 7.0), they rapidly dissociate releasing the proton and acidifying the interior of the cells (Ullah et al. 2013). Glycolysis is one of the biological processes affected by intracellular pH acidification (Pearce et al. 2001). Dorta et al. (2006) evaluated the synergistic effect of sulphite, lactic acid, ethanol and low pH on fermentation conducted by two industrial strains of S. cerevisiae (M-26 and PE-2) and showed that low pH (3.6) followed by ethanol (9.5%) were the most stressful factors for yeast during fermentation. Fletcher et al. (2017) studied the genome alterations of a strain of S. cerevisiae evolved for tolerance to low pH towards an inorganic (hydrochloric acid) and an organic (lactic acid) acid and demonstrated that different paths are induced depending on the acid and the carbon source. With inorganic acid, there was modification in the sterol composition and modulation of the intracellular levels of iron; with lactic acid, a multicellular structure was observed with fortification of the cell wall and increased lactic acid degradation. The selection pressure and the nature of the acid direct the evolutionary paths to increase tolerance to low pH, and in the context of bioethanol production, the yeast S. cerevisiae is subject to both types of acid (during acid treatment and during fermentation with contamination by lactic acid bacteria) and selection pressures. Costa et al. (2019) verified that the stress imposed by low pH (1.5) on the growth of the industrial strain of S. cerevisiae PE-2 was more severe in the condition of extreme O2 limitation even with the supplementation of ergosterol and oleic acid. The acid stress was higher than the ethanol stress (100 g/L) under anaerobiosis. The composition of fatty acid and sterol altered substantially, and decreased cell viability was observed in the condition of anaerobiosis without supplementation when compared to the composition observed in cells growing aerobically or anaerobically with supplementation. Ethanol causes an effect on the cytoplasmic membrane of yeast cells, increasing its fluidity and consequently the permeability of the membrane to some ions, especially H+ ions. The entry of these ions causes a dissipation of the electrochemical gradient in the membrane, affecting the maintenance of the protomotive force with a decrease in the intracellular pH.  Besides affecting the membrane composition,

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1  Ethanolic Fermentation in Brazil: Characteristics and Peculiarities

ethanol causes growth inhibition and inactivation of enzymes, leading to loss of cell viability (Stanley et al. 2010). The tolerance of yeast to ethanol is one of the factors that limit the development of high alcoholic fermentations. In S. cerevisiae, the maximum concentration of ethanol that allows growth is 10% (w/v), according to Dorta et  al. (2006). The search for ethanol-tolerant strains should be stimulated, because the industrial strains CAT-1, PE-2, BG-1 and SA-1 did not show ethanol tolerance comparable to that presented by the native rough yeasts, contaminants of fermentation (Reis et al. 2017). The inhibitory effect of ethanol is enhanced with increasing temperature. The optimum temperature range for alcoholic fermentation is 26–35 °C. However, with the increase in ambient temperature along the sugarcane harvest (especially in the summer season) and because alcoholic fermentation is an exothermic process, the temperature of the vats can reach 38°C, requiring cooling by heat exchangers in the fermentation vats (Lima et al. 2001; Macedo and Cortez 2005). It is known that the increase in temperature causes an increase in the fermentation speed, but although it is interesting to select thermotolerant yeast strains for industrial application, it is necessary to remember that the growth of bacteria is stimulated at temperatures above 32 °C and that milder temperatures (below 27 °C) reduce the toxicity of ethanol (Basso et al. 2011). High alcohol content fermentation has been one of the priorities of the sugar-­ alcohol sector because it provides economic and technical advantages, especially the reduction of the volume of vinasse (Cruz et al. 2021). However, it is necessary to search for yeast strains adapted to the high concentration of ethanol in fermentation musts, above 10% (CNPEM 2017). Osmotic stress caused by high initial sugar concentration in the fermentation medium can lead to a decrease in ethanol production due to the regulation of the synthesis of glycolytic enzymes and the enzymes of the hexose monophosphate pathway (Thomas et al. 1996) or inhibition of sugar transport (Mauricio and Salmon 1992). The very high-gravity (VHG) technology results in fermentation with up to 12% of ethanol with moderately high sugar concentrations (≥250 g/L), but the yeast viability and may decrease due to the effect of high initial sugar concentration and the high titres of ethanol (Cruz et al. 2021). The osmotic stress causes water loss from inside the cell to the environment (Mager and Siderius 2002). Synergism may occur between osmotic stress and those caused by ethanol and other compounds present in the medium, such as organic acids,, for example, increasing the toxicity of these compounds (Graves et al. 2006). High specific growth and ethanol production rates are required from yeast strains in ethanolic fermentations for a rapid fermentation. During the single-batch fermentative process, a decrease in the specific growth rate of yeast caused by either the substrate or the final product occurs. To overcome inhibition by product or substrate, fed-batch, continuous or semi-continuous systems are most appropriate. In fed-batch cultures, high ethanol concentration and yield were achieved with sugar concentration up to 260 g/L (Chang et al. 2018). The fed-batch system, the most extensively used in Brazilian distilleries, consists of intermittent feeding of sugar without removing the fermentation broth, thus reducing inhibition by substrate and

References

17

the final product, resulting in shorter fermentation time and higher ethanol productivity. Thus, in a system like this, osmotic stress is not significant to the point of impacting the growth and metabolism of the process yeast. When comparing industrial strains with laboratory strains, the yeasts demonstrated no difference concerning the osmotic stress caused by high sugar concentration. However, high temperature and low pH stresses distinguished industrial strains than laboratory strains, confirming that these conditions exert selective pressure on the yeast cells in the industrial process (Della-Bianca and Gombert 2013). It is important to point out that factors affecting fermentation do not occur in isolation during the process, so that stresses imposed simultaneously or sequentially have a much greater effect than the effect of each of the stresses alone, as described for osmotic-acidity-temperature-ethanol conditions, for example.

References Alcarde, A.R.: Do Próalcool ao flex fuel, etanol migrou do Estado para o mercado. Visão Agrícola. 8, 26–28 (2008) Almeida, V.P., Longhi, G.M., Santos, L.R.: Ethanol: 40 years of evolution of the fuel and automobile market in Brazil. Econ. Theory Evid. 49, 462–484 (2017) Amorim, H.V., Basso, L.C., Lopes, M.L.: Sugar cane juice and molasses, beet molasses and sweet sorghum: composition and usage. In: Ingledew, W.M., Kelsall, A.G.D., Kluhspies, C. (eds.) The Alcohol Textbook, pp. 39–46. University Press, Nottingham (2009) Amorim, H.V., Lopes, M.L., Oliveira, J.V.C., Buckeridge, M.S., Goldman, G.H.: Scientific challenges of bioethanol production in Brazil. Appl. Microbiol. Biotechnol. 91, 1267–1275 (2011) Assad, L.: Aproveitamento de resíduos do setor sucroalcooleiro desafia empresas e pesquisadores. Ciência e Cultura. 69, 13–16 (2017) Bai, F.W., Anderson, W.A., Moo-Young, M.: Ethanol fermentation technologies from sugar and starch feedstocks. Biotechnol. Adv. 26, 89–105 (2008) Baptista, C.M.S.G., Cóias, J.M.A., Oliveira, A.C.M., Oliveira, N.M.C., Rocha, J.M.S., Dempsey, M.J., Lanningan, K.C., Benson, P.S.: Natural immobilisation of microorganisms for continuous ethanol production. Enzyme Microb. Technol. 40, 127–131 (2006) Bassi, A.P.G., Meneguello, L., Paraluppi, A.L., Sanches, B.C.P., Ceccato-Antonini, S.R.: Interaction of Saccharomyces cerevisiae-Lactobacillus fermentum-Dekkera bruxellensis and feedstock on fuel ethanol fermentation. Antonie van Leeuwenhoek. 111, 1661–1672 (2018) Basso, T.O., Lino, F.S.O.: Clash of kingdoms: how do bacterial contaminants thrive in and interact with yeasts during ethanol production? In: Fuel Ethanol Production from Sugarcane, pp. 23–38. InTechOpen, London (2018) Basso, L.C., Amorim, H.V., Oliveira, A.J., Lopes, M.L.: Yeast selection for fuel ethanol production in Brazil. FEMS Yeast Res. 8, 1155–1163 (2008) Basso, L.C., Basso, T.O., Rocha, S.N.: Ethanol production in Brazil: the industrial process and its impact on yeast fermentation. In: Bernardes, M.A.S. (ed.) Biofuel Production  – Recent Developments and Prospects, pp. 85–100. InTech, Rijeka (2011) Bermejo, P.M., Badino, A., Zamberlan, L., Raghavendran, V., Basso, T.O., Gombert, A.K.: Ethanol yield calculations in biorefineries. FEMS Yeast Res. 21, foab065 (2021) Carlson, M., Botstein, D.: Two differentially regulated mRNAs with different 5′ ends encode secreted and intracellular forms of yeast invertase. Cell. 28, 145–154 (1982) Ceballos-Schiavone, C.H.M.: Tratamento térmico do caldo de cana-de-açúcar visando a redução de contaminantes bacterianos – Lactobacillus na produção de etanol e eficiência de tratamento

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do fermento por etanol. Dissertation, Escola Superior de Agricultura “Luiz de Queiroz”  – Universidade de São Paulo (2009) Ceise.: Renovabio: novo momento no setor sucroenergético (2020). Available at: http://www. ceisebr.com/conteudo/renovabio-­novo-­momento-­no-­setor-­sucroenergetico.html. Accessed 22 Mar 2020 Chang, Y.H., Chang, K.S., Chen, C.Y., Hsu, C.L., Chang, T.C., Jang, H.D.: Enhancement of the efficiency of bioethanol production by Saccharomyces cerevisiae via gradually batch-wise and fed-batch increasing the glucose concentration. Fermentation. 4, 45 (2018) CNPEM.: Fermentação: contínua ou batelada? (2017). Available at: http://cnpem.br/fermentacao-­ continua-­ou-­em-­batelada/. Accessed 22 Mar 2020 Cortez, L.A.B., Cruz, C.H.B., Souza, G.M., Cantarella, H., van Sluys, M.A., Maciel Filho, R.: Universidades e empresas: 40 anos de ciência e tecnologia para o etanol brasileiro, 224 p. Blucher, São Paulo (2016) Costa, M.A.S.: Efeito do sistema de fermentação, da adição de etanol ao tratamento ácido e da contaminação por Lactobacillus sp na produção de etanol. Dissertation, Universidade Federal de São Carlos (2017) Costa, M.A.S., Cerri, B.C., Ceccato-Antonini, S.R.: Ethanol addition enhances acid treatment to eliminate Lactobacillus fermentum from the fermentation process for fuel ethanol production. Lett. Appl. Microbiol. 66, 77–85 (2018) Costa, B.L.V., Raghavendran, V., Franco, L.F.M., Chaves Filho, A.B., Yoshinaga, M.Y., Miyamoto, S., Basso, T.O., Gombert, A.K.: Forever panting and forever growing: physiology of Saccharomyces cerevisiae at extremely low oxygen availability in the absence of ergosterol and unsaturated fatty acids. FEMS Yeast Res. 19, foz054 (2019) Cruz, M.L., Resende, M.M., Ribeiro, E.J.: Improvement of ethanol production in fed-batch fermentation using a mixture of sugarcane juice and molasse under very high-gravity conditions. Bioprocess Biosyst. Eng. 44, 617–625 (2021) Della-Bianca, B.E., Gombert, A.K.: Stress tolerance and growth physiology of yeast strains from the Brazilian fuel ethanol industry. Antonie van Leeuwenhoek. 104, 1083–1095 (2013) Della-Bianca, B.E., Basso, T.O., Stambuk, B.U., Basso, L.C., Gombert, A.K.: What do we know about the yeast strains from the Brazilian fuel ethanol industry? Appl. Microbiol. Biotechnol. 97, 979–991 (2013) Della-Bianca, B.E., Hulster, E., Pronk, J.T., van Maris, A.J., Gombert, A.K.: Physiology of the fuel ethanol strain Saccharomyces cerevisiae PE-2 at low pH indicates a context-dependent performance relevant for industrial applications. FEMS Yeast Res. 14, 1196–1205 (2014) Dias, M.O.S., Maciel Filho, R., Mantelatto, P.E., Cavalett, O., Rossell, C.E.V., Bonomi, A., Leal, M.R.L.V.: Sugarcane processing for ethanol and sugar in Brazil. Environ. Dev. 15, 35–51 (2015) Dorta, C., Oliva-Neto, P., Abreu-Neto, M.S., Nicolau-Junior, N., Nagashima, A.I.: Synergism among lactic acid, sulfite, pH and ethanol in alcoholic fermentation of Saccharomyces cerevisiae (PE-2 and M-26). World J. Microbiol. Biotechnol. 22(2), 177–182 (2006) Eggleston, G., Amorim, H.: Reasons for the chemical destruction of sugars during the processing of sugarcane for raw sugar and fuel alcohol production. Int. Sugar J. 108, 271–282 (2006) Fletcher, E., Feizi, A., Bisschops, M.M.M., Hallstrom, B.M., Khoomrung, S., Siewers, V., Nielsen, J.E.: Evolutionary engineering reveals divergent paths when yeast is adapted to different acidic environments. Metab. Eng. 39, 19–28 (2017) Furtado, M.: Ambiente – Beraca uses ClO2 in alcoholic fermentation (2013). Available at: https:// www.quimica.com.br/ambiente-­beraca-­usa-­clo2-­na-­fermentacao-­alcoolica. Accessed 22 Mar 2020 Gallo, C.R.: Determinação da microbiota bacteriana do mosto e de dornas na fermentação alcoólica. Thesis, Universidade Estadual de Campinas (1989) Godoy, A., Amorim, H.V., Lopes, M.L., Oliveira, A.J.: Continuous and batch fermentation processes: advantages and disadvantages of these processes in the Brazilian ethanol production. Int. Sugar J. 110(1311), 175–181 (2008)

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Graves, T., Narendranath, N.V., Dawson, L., Power, R.: Effect of pH and lactic or acetic acid on ethanol productivity by Saccharomyces cerevisiae in corn mash. J. Indu. Microbiol. Biotechnol. 33, 469–474 (2006) Hira, A., Oliveira, L.G.: No substitute for oil? How Brazil developed its ethanol industry. Energy Policy. 37, 2450–2456 (2009) Jacobus, A.P., Gross, J., Evan, J.H., Ceccato-Antonini, S.R., Gombert, A.K.: Saccharomyces cerevisiae strains used industrially for bioethanol production. Essays Biochem. 65(2), 147–161 (2021) Lapolli, F.R., Hassemer, M.E.N., Camargo, J.G., Damásio, D.L., Lobo-Recio, M.A.: Sanitary effluent disinfection using chlorine dioxide. Engenharia Sanitária e Ambiental. 10(3), 200–208 (2005) Leal, M.R.L.V.: Evolução tecnológica do processamento da cana-de-açúcar para etanol e energia elétrica. In: Cortez, L.A.B. (ed.) Bioetanol de cana-de-açúcar: P&D para produtividade e sustentabilidade, pp. 561–575. Blucher, São Paulo (2010) Lima, U.A., Basso, L.C., Amorim, H.V.: Produção de etanol. In: Aquarone, E., Borzani, W., Schmidell, W. (eds.) Biotecnologia Industrial: processos fermentativos e enzimáticos, pp. 1–43. Blucher, São Paulo (2001) Lopes, M.L., Paulillo, S.C.L., Godoy, A., Cherubin, R.A., Lorenzi, M.S., Giometti, F.H.C., Bernardino, C.D., Amorim Neto, H.B., Amorim, H.V.: Ethanol production in Brazil: a bridge between science and industry. Braz. J. Microbiol. 47(1), 64–76 (2016) Lucena, R.M., Elsztein, C., Simões, D.A., Morais Jr., M.A.: Participation of CWI, HOG and Calcineurin pathways in the tolerance of Saccharomyces cerevisiae to low pH by inorganic acid. J. Appl. Microbiol. 113, 629–640 (2012) Lucena, R.M., Elsztein, C., Pita, W., Souza, R.B., Paiva Jr., S.S.L., Morais Jr., M.A.: Transcriptomic response of Saccharomyces cerevisiae for its adaptation to sulphuric acid-induced stress. Antonie van Leeuwenhoek. 108, 1147–1160 (2015) Macedo, I.C., Cortez, L.A.B.: O processamento industrial da cana-de-açúcar no Brasil. In: Rosillo-­ Calle, F., Bajay, S.V., Rothman, H. (eds.) Uso da biomassa para produção de energia na indústria brasileira, pp. 247–268. Editora da Unicamp, Campinas (2005) Mager, W.H., Siderius, M.N.: Insights into the osmotic stress response of yeast. FEMS Yeast Res. 2, 251–257 (2002) Mauricio, J.C., Salmon, J.M.: Apparent loss of sugar transport activity in Saccharomyces cerevisiae may mainly account for maximum ethanol production during alcoholic fermentation. Biotechnol. Lett. 14, 577–582 (1992) Melo, H.F., Bonini, B.M., Thevelein, J., Simões, D.A., Morais Jr., M.A.: Physiological and molecular analysis of the stress response of Saccharomyces cerevisiae imposed by strong inorganic acid with implication to industrial fermentations. J. Appl. Microbiol. 109, 116–127 (2010) Mendonça, A.A., Lucena, B.T.L., Morais, M.M.C., Morais Jr., M.A.: First identification of Tn916-­ like element in industrial strains of Lactobacillus vini that spread the tet-M resistance gene. FEMS Microbiol. Lett. 363, fnv240 (2016) Murphree, C.A., Li, Q., Heist, P.E., Moe, L.A.: A multiple antibiotic-resistant Enterobacter cloacae strain isolated from a bioethanol fermentation facility. Microbes and Environ. 29(3), 322–325 (2014) Mutton, M.A., Rossetto, R., Mutton, M.J.R.: Uso agrícola da vinhaça. In: Cortez, L.A.B. (ed.) Bioetanol de cana-de-açúcar: P&D para produtividade e sustentabilidade, pp.  423–440. Blucher, São Paulo (2010) Nelson, D.L., Cox, M.M.: Princípios de bioquímica de Lehninger, p.  456. Artmed, Porto Alegre (2014) Nevoigt, E., Stahl, U.: Osmoregulation and glycerol metabolism in the yeast Saccharomyces cerevisiae. FEMS Microbiol. Rev. 21, 231–241 (1997) Oliva-Neto, P., Dorta, C., Carvalho, A.F.A., Lima, V.M.G., Silva, D.F.: The Brazilian technology of fuel ethanol fermentation-yeast inhibition factors and new perspectives to improve the ­technology. In: Mendez-Vilas, A. (ed.) Materials and Processes for Energy: Communicating Current Research and Technological Development, pp. 372–279. Formatex, Badajoz (2013)

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Pagliardini, J., Hubmann, G., Alfenore, S., Nevoigt, E., Bideaux, C., Guillouet, S.E.: The metabolic costs of improving ethanol yield by reducing glycerol formation capacity under anaerobic conditions in Saccharomyces cerevisiae. Microb. Cell Fact. 12, 29 (2013) Pearce, A.K., Booth, I.R., Brown, A.J.P.: Genetic manipulation of 6-phosphofructo-1-kinase and fructose 2, 6-bisphosphate levels affects the extent to which benzoic acid inhibits the growth of Saccharomyces cerevisiae. Microbiol. 147, 403–410 (2001) Pereira, L.F., Lucatti, E., Basso, L.C., Morais Jr., M.A.: The fermentation of sugarcane molasses by Dekkera bruxellensis and the mobilization of reserve carbohydrates. Antonie van Leeuwenhoek. 105, 481–489 (2014) Pereira, R.D., Rodrigues, K.C.S., Sonego, J.L.S., Cruz, A.J.G., Badino, A.C.: A new methodology to calculate the ethanol fermentation efficiency at bench and industrial scales. Ind. Eng. Chem. Res. 57(48), 16182–16191 (2018) Reis, V.R., Antonangelo, A.T.B.F., Bassi, A.P.G., Colombi, D., Ceccato-Antonini, S.R.: Bioethanol strains of Saccharomyces cerevisiae characterised by microsatellite and stress resistance. Braz. J. Microbiol. 48, 268–274 (2017) Reis, V.R., Bassi, A.P.G., Cerri, B.C., Almeida, A.R., Carvalho, I.G.B., Bastos, R.G., Ceccato-­ Antonini, S.R.: Effects of feedstock and co-culture of Lactobacillus fermentum and wild Saccharomyces cerevisiae strain during fuel ethanol fermentation by the industrial yeast strain PE-2. AMB Express. 8, 23 (2018) Rinke Dias de Souza, N., Klein, B.C., Chagas, M.F., Cavalett, O., Bonomi, A.: Towards comparable carbon credits: harmonization of LCA models of cellulosic biofuels. Sustainability. 13, 10371 (2021) Sanz, J.L., Rodriguez, N., Amils, R.: The action of antibiotics on the anaerobic digestion process. Appl. Microbiol. Biotechnol. 46, 587–592 (1996) Silva-Neto, J.M., Covre, E.A., Rosa, B.C., Ceccato-Antonini, S.R.: Can ethanol replace partially or fully sulfuric acid in the acid wash step of bioethanol production to fight contamination by Lactobacillus fermentum? Braz. J. Chem. Eng. 37, 323–332 (2020) Simpson, W.J., Hammond, J.R.M.: The response of brewing yeasts to acid washing. J. Inst. Brew. 95, 347–354 (1989) Stanley, D., Bandara, A., Fraser, S., Chambers, P.J., Stanley, G.A.: The ethanol stress response and ethanol tolerance of Saccharomyces cerevisiae. J. Appl. Microbiol. 109, 13–24 (2010) Thomas, K., Hynes, S.H., Ingledew, W.M.: Effect of nitrogen limitation on synthesis of enzymes in Saccharomyces cerevisiae during fermentation of high concentration of carbohydrates. Biotechnol. Lett. 18, 1165–1168 (1996) Tosetto, G.M.: Comportamento de linhagens industriais de Saccharomyces frente a compostos inibitórios presentes no melaço de cana-de-açúcar na produção de bioetanol. Thesis, Universidade Estadual de Campinas (2008) Ullah, A., Chandrasekaran, G., Brul, S., Smits, G.J.: Yeast adaptation to weak acids prevents futile energy expenditure. Front. Microbiol. 4, 1–10 (2013) Unica.: Sugarcane sector. Available at: https://unica.com.br/en/sugarcane-­sector/. Accessed 26 May 2022 Wang, M., Han, J., Dunn, J.B., Cai, H., Elgowainy, A.: Well-to-wheels energy use and greenhouse gas emissions of ethanol from corn, sugarcane and cellulosic biomass for US use. Environ. Res. Lett. 7, 045905 (2012) Weusthuis, R.A., Pronk, J.T., van den Broek, P.J.A., van Dijken, J.P.: Chemostat cultivation as a tool for studies on sugar transport in yeasts. Microbiol. Rev. 58(4), 616–630 (1994) Wheals, A.E., Basso, L.C., Alves, D.M.G., Amorim, H.V.: Fuel ethanol after 25 years. Trends Biotechnol. 17, 482–487 (1999)

Chapter 2

The Use of Selected Yeasts in Ethanol Fermentation

2.1 Introduction Throughout the evolution of the ethanol industry in Brazil, it can be seen that the gains in ethanol yields were due not only to advances in the agricultural sector with the release of new sugarcane varieties but also to improvements in the fermentation process in terms of fermentation per se, i.e. the performance of the yeast fermentation agent in the industrial environment. The yeast Saccharomyces cerevisiae is the main agent of fermentation for the production of ethanol fuel. Although there are other microorganisms with ethanol production capacity, this yeast stands out for its robustness, easy genetic manipulation, high fermentative yield and resistance to various stresses. However, there is a high intraspecific variability, so the selection of strains more productive and adapted to the fermentative environment is of importance for the fermentation industry. It is possible to trace a timeline demarcating the main events that resulted in the advances occurred in the Brazilian fermentative process: • 1970s and 1980s: use of baking yeast as inoculum for fermentation or yeasts from other types of fermentation • 1990s: by means of electrophoretic karyotyping, the finding that baker’s yeast did not persist throughout the fermentation cycles, being replaced by native yeasts • 2000s: isolation and selection of native yeasts with persistence and dominance characteristics in the fermentation process to be used as inocula in fermentation • 2010s: study at the physiological and genetic level of the selected yeasts in order to understand the mechanisms by which these yeasts remain in the fermentation process with high yield in spite of the stresses of the industrial environment • 2010s onwards: selection of yeasts better adapted to the fermentation conditions of each distillery and to changes in the industrial process during the harvest, the so-called customized yeasts

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_2

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The sugar-energy sector has already passed the barrier of 50  years since the Proálcool, and it is important to bring the science that has been produced to the sector, especially the results of genomic, proteomic and transcriptomic studies of the most important Brazilian industrial yeasts. The migration from the use of baker’s yeasts to the selected yeasts occurred thanks to the use of molecular biology techniques for the monitoring of fermentation and the efforts of Brazilian researchers in partnerships with foreign institutions to study the yeasts in their physiological, genetic and resistance aspects to the stresses of the industrial environment. The selection of yeast strains adequate to the peculiarities of the Brazilian industrial process is based, therefore, on the use of the industrial process itself to impose a selective pressure on the S. cerevisiae population present in the fermentation vats. This strategy has resulted in major advances for the development of the ethanol industry in Brazil.

2.2 History of the Use of Yeast Strains in Ethanol Fermentation The vast majority of alcohol and spirit industries in Brazil in the 1930s used the so-­ called spontaneous fermentation, i.e. fermentation conducted by the native microorganisms of the raw material. With the availability of biological yeast on the market by some foreign companies, the situation began to change, and gradually, Brazilian ethanol manufacturers became aware of the importance of using industrialized yeast (Amorim 2005). With this innovation, the need for the preparation and conservation of pure cultures was discarded as well as the use of multiplication apparatus, which considerably simplified the work of the factories. The low cost and the availability in large quantities were important criteria that supported the use of baker’s yeasts in Brazil. However, in the 1990s, with the use of the electrophoretic karyotyping technique, it was verified that baker’s yeasts were unable to compete with the native strains that contaminated the process, and these ended up dominating the fermentation vats after about 20–30 days from the beginning of the harvest (Basso et al. 1993, 2008; Silva-Filho et al. 2005). The first yeast strain to be used industrially as starter of fermentation was the strain of Saccharomyces uvarum, called IZ-1904, from the Zimo Technical Institute “Prof. Jayme Rocha de Almeida”, of the College of Agriculture Luiz de Queiroz, University of São Paulo, in Piracicaba, São Paulo State, Brazil. This yeast, together with the IZ-1830 strain isolated from fermentation tanks, was widely sold to the industry, but with time they ended up being contaminated with the so-called “regional” yeasts. Later, it was also verified that these yeasts did not remain in the process with cell recycling and their use was abandoned (Amorim 2005). Besides, it was difficult for the mills to obtain large volumes of inoculum of these yeasts, so the option of using baker’s yeast was more advantageous (Andrietta et al. 2006).

2.2  History of the Use of Yeast Strains in Ethanol Fermentation

23

The verification that the starter yeasts of the process, both the baker’s yeast and the isolated yeasts, were not able to maintain themselves in the industrial process was possible thanks to the use of the electrophoretic karyotyping technique. Karyotyping through pulsed field electrophoresis allows the separation of chromosomes by size, and in this way, it is possible to evaluate both the number and the size of the chromosomes, allowing the identification of the yeast. As S. cerevisiae strains can present chromosome size polymorphism, these variations indicate the genetic variability of the yeast population at the intraspecific level (Stroppa 2002). Therefore, in the mid-1990s, with the use of karyotyping, it was possible to identify and monitor the yeasts isolated from the fermentation vats and thus establish the percentages of “dominance” and “persistence” of each strain in the fermentation process. Dominance refers to the abundance of a strain in relation to other strains present in the same sample; persistence means the permanence of the strains throughout the harvest (Lopes et al. 2015). It is undeniable the role that karyotyping played for the industrial process, as it started to be used to monitor the yeasts during the industrial process, to select those with the best profile for fermentation and that could be used in the next harvests. Basso et al. (2008) reported the results of the selection program of S. cerevisiae strains that was developed during 12 years (1993–2005) in more than 70 distilleries. The large yeast biodiversity found in the industry environments was an important source of selected strains for their characteristics not only of high fermentative yield but also due to the characteristics of low glycerol production, low foam formation and high levels of cell viability exhibited during cell recycles. These impose on the yeasts a selective pressure (a form of adaptive evolution) that allows selecting strains with higher tolerance to the stressful conditions of industrial fermentation. The authors of this important strain selection work verified that in 1993, at the beginning of the study, the available strains were the baker’s yeast of two commercial brands (Fleishmann and Itaiquara) and the strains JA-1, TA and IZ-1904 and, soon after, BG-1, CR-1 and SA-1. The selected strains began to be called with the initials of the units of origin, for example, BG-1 from Barra Grande Plant, CR-1 from Cresciumal Plant, SA-1 from Santa Adélia Plant, CAT-1 from Catanduva Plant and PE-2 from Pedra Plant (Andrietta et al. 2006). With the monitoring carried out through electrophoretic karyotyping, it was found that the baker’s yeasts and some of other strains lasted only 20–30 days of recycle or 50–60 days in some few distilleries, being replaced by native strains. It was observed at that time that the strains that were isolated from the fermentative environment itself (JA-1, CR-1 and SA-1) showed higher persistence, surviving for about 180–190  days of recycle (Basso et al. 2008). In 1994 and 1998, two native S. cerevisiae strains were isolated with high capacity of implantation in the industrial environment, high fermentative yield and desired qualities of dominance and persistence, denominated PE-2 and CAT-1. These strains have been used until today in combination with other strains and with baker’s yeast in many industrial units distributed throughout Brazil. Although more than 340 yeast strains were isolated and analysed and 14 of them were selected during the 12-year selection program, it was observed that most of them had a low capacity of

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implantation in the distilleries, although they showed good fermentative performance in many distilleries and for some harvests. The most promising were PE-2, CAT-1, VR-1, BG-1, CR-1 and SA-1, showing dominance and prevalence in industrial fermentations (Basso et al. 2008). The PE-2 strain shows high tolerance to low pH, indicating that the step of sulfuric acid treatment used between the fermentative cycles should exert an important selective pressure on the microbial populations present in the fermentative environments (Della-Bianca et al. 2014; Reis et al. 2017). Since 2008, the concept of customized yeasts has taken shape in the industrial environment. These are yeasts best adapted to the fermentation conditions of each distillery and to the changes in the industrial process and which end up being selected due to the selection pressure imposed by these conditions. A yeast with the potential to become a customized yeast is one that dominates the yeast population in industrial fermenters in a specific production unit. These yeasts arise due probably to a large number of mutations that accumulate in the high yeast population because of cell recycle in high-volume fermenters and are often genetic variants of the introduced yeast, for example, the strain FT859L, which was selected from Usina Ipiranga (Mococa, São Paulo State, Brazil) and used to start fermentation in the following harvest together with PE-2, persisting for 36 weeks of harvest, with increased productivity in ethanol and reduced fermentation time. Both karyotyping and mitochondrial DNA analyses revealed that strain FT859L was a variant of strain PE-2. However, the custom strain FT1255L, which was selected for its tolerance to alcohol content of 10–11% in fermentation with low-quality molasses at Usina Alta Mogiana (São Joaquim da Barra, São Paulo State, Brazil), did not show any origin related to any known industrial yeasts (Lopes et al. 2015).

2.3 Strain Selection: Yeast Characteristics and Selection Criteria As previously discussed, both dominance and persistence are important criteria to be considered in a selection programme. However, it should be considered that simply selecting strains that have persisted to the end of the season is not appropriate. These strains may show tolerance to environmental stresses and dominance in the fermentation tanks, but they do not necessarily exhibit desirable fermentation characteristics (Basso et al. 2008). Selected yeasts should present high fermentative performance, i.e. higher ethanol yield (conversion of sugar into ethanol), higher productivity (ethanol production rate per unit time) and low residual sugar content in the fermentation medium. High cell viability rates over recycles, low glycerol production and intracellular trehalose accumulation are equally desirable characteristics. However, there are others that are not desirable in selected yeasts, such as excessive foaming, high sedimentation rate during fermentation or flocculation and longer fermentation time (Fig.  2.1). Flocculation reduces the efficiency of the centrifugation used to separate the yeast

2.3  Strain Selection: Yeast Characteristics and Selection Criteria

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Fig. 2.1  Fermentations conducted by yeast strains with undesirable characteristics such as foaming (a) and flocculation (b). (Source: From the author)

cells from the fermented must (wine), and thus a less concentrated yeast cream is obtained, with a greater amount of wine. Due to the buffering capacity of wine, more sulfuric acid is spent to reduce the pH in the yeast treatment step. More intense acid stress can reduce yeast activity or even cause cell death (Amorim et al. 2011). Many factors influence foam formation, but the main factor is the yeast itself, since foam stability is strongly influenced by the yeast cell wall mannoproteins adsorbed at the gas/liquid interface (Blasco et  al. 2011). The consumption of defoamers increases production costs in addition to impacting yeast physiology. Nielsen et al. (2017) found that an industrial defoamer reduced cell viability of the CAT-1 strain and the effects were intensified with increasing concentration of the defoamer. Through transcriptomic analysis, it was found that the addition of defoamer showed upregulation of stress-specific genes and downregulation of lipid biosynthesis, especially ergosterol. This substance plays a role in ethanol and acidity tolerance (Guo et al. 2018). The evaluation of the potential of a strain in the selection process should take into account all these characteristics together with its ability to resist the stresses caused by the increase in temperature during fermentation, low pH in the acid treatment, high ethanol concentration at the end of fermentation and osmotic stress due to the high sugar concentration at the beginning of fermentation. Another important point to be evaluated in this context is the competitiveness of this selected strain against the usual fermentation contaminants, such as other S. cerevisiae and non-­ Saccharomyces yeasts and bacteria. Table 2.1 presents the results of the physiological and technological parameters of a selected yeast (PE-2) in comparison with the baker’s yeast in laboratory scale, using fermentation with cell recycle with must consisting of sugarcane juice and molasses. From Table  2.1, considerations about the parameters and their

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Table 2.1  Physiological and technological parameters of the selected strain PE-2 and the bread strain during fermentation cycles using sugarcane juice and molasses as substrates at 33 °C and reaching 9.1% (v/v) of ethanol Fermentative parameter Ethanol yield (%)1 Glycerol (%)a Biomass gain (%)b Viability (%)c Trehalose (% dry basis)d Glycogen (% dry basis)d

Strains Baking yeast 88.1 ± 1.01 5.40 ± 0.25 5.8 ± 0.61 48 ± 1.1 4.0 ± 0.22 9.0 ± 0.43

PE-2 92.0 ± 1.12 3.38 ± 0.33 8.2 ± 0.84 94 ± 1.9 9.5 ± 0.29 16.0 ± 0.51

Source: Basso et al. 2008, with permission from Oxford University Press The data refer to the average of five fermentation cycles (in triplicate) a Fraction of sugar converted to ethanol or glycerol (g per 100-g sugar) b Average biomass increase per fermentation cycle c Cell viability at the end of the last fermentation cycle (% viable cells) d Reserve carbohydrate at the end of the last fermentative cycle

implications for the industrial fermentation process will be made in order to highlight the importance of these characteristics in a selection program of yeast strains for ethanol fermentation. The selected yeast PE-2 presented a fermentative yield higher than the baker’s yeast. In terms of the amount of ethanol produced, the difference (four percentage points) is about 2 million litres of ethanol in one harvest considering a distillery of medium capacity. It is important to emphasize that this parameter – yield – expresses the amount of ethanol produced per amount of sugar consumed in relation to the theoretical yield of the alcoholic fermentation (0.511-g ethanol/g glucose, Della-­ Bianca et al. 2013), which indicates how efficient the yeast was in converting the sugar of the must into ethanol compared to the theoretical yield. Besides the catabolic reactions that produce ATP and ethanol, there are alternative routes that lead to the formation of secondary compounds such as glycerol, organic acids, higher alcohols, acetoin, butylene glycol and others, which are excreted in the fermentation medium. Concomitantly, anabolic reactions occur leading to biomass formation. It is estimated that 5% of the sugar consumed by the yeast is used for the generation of secondary fermentation products, which would lead the yield to reach a maximum of 95% of the theoretical yield. Since in the industry it is admitted a percentage of 10% diverted for the formation of products other than ethanol, a yield of 90% is considered optimal (Lima 2019). Glycerol is the main secondary product of ethanolic fermentation (Fig. 2.2). The more glycerol is formed, the less sugar is available for conversion into ethanol, so low glycerol production is a desirable characteristic in selected S. cerevisiae strains. Table 2.1 shows a lower production of glycerol by the selected yeast PE-2 in comparison with the baker’s yeast. However, this characteristic – glycerol production – needs to be evaluated from another point of view. Studies have shown that

2.3  Strain Selection: Yeast Characteristics and Selection Criteria

27

Fig. 2.2  Simplified metabolic routes from sucrose (the main substrate in sugarcane musts) to produce ethanol (the main product), glycerol, trehalose and glycogen in S. cerevisiae during the fermentation for fuel ethanol production. Trehalose, glycogen and glycerol are accumulated intracellularly; however, glycerol can move in and out of cells depending on the external conditions. Their roles are depicted in the dialog boxes. (Source: Ceccato-Antonini and Covre 2020, with permission from Oxford University Press)

suppression or substantial reduction of glycerol production by process optimization or genetic engineering is possible; however, these strategies can produce deleterious effects on yeast growth and fermentative performance. These effects can be explained by the fact that glycerol is a central element in the redox balance of the cell, as well as a precursor in the formation of phospholipids and triglycerides, and a major constituent of the resistance system to stress, especially osmotic stress (Hohmann 2002; Pagliardini et al. 2013). Glycerol plays a central role in the cultivation of yeast under anaerobic conditions. The glycolytic and ethanol formation reactions have a zero oxireduction balance, but as synthesis of other compounds and anabolic reactions occur, there is an excess of NADH produced. Under anaerobic conditions, the reduction of dihydroxyacetone phosphate to glycerol-3-phosphate consumes one NADH, resulting in dephosphorylation of glycerol-3-phosphate to glycerol as the final metabolite (Bjorkqvist et al. 1997) (Fig. 2.2). Therefore, glycerol plays a key role in maintaining the redox balance of the cell under anaerobic conditions, in view of the absence of the electron transport chain in anaerobiosis.

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2  The Use of Selected Yeasts in Ethanol Fermentation

When yeast cells are exposed to the osmotic stress of the fermentation medium (sugarcane juice and/or molasses), constituted of high concentration of sugars and salts, there is an initial loss of water from the cell to the medium. The cellular response, called osmoregulation, acts to restore and maintain volume, turgor pressure and normal biological activities of the cells. One of the mechanisms of osmoregulation is the intracellular accumulation of one or more solutes called “compatible”, since they do not affect the physical and biochemical processes of the cell. Glycerol is the most prominent compatible solute used by S. cerevisiae to counteract dehydration caused by osmotic variations (Reed et al. 1987; Nevoigt and Stahl 1997). In addition to osmotic stress, glycerol also protects the cell against oxidative stress and those generated by temperature and ethanol (Pagliardini et al. 2013). The selected strain PE-2 presents a balanced glycerol production, guaranteeing high ethanol yield and at the same time ensuring stress tolerance. In a situation of contamination of the process with the bacterium Lactobacillus fermentum, which induced yeast flocculation, there was a decrease in glycerol production by yeast PE-2, causing a metabolic imbalance with reduced ethanol production, slow rate of sucrose hydrolysis and even lower tolerance to the stressful environment of fermentation (Carvalho-Neto et al. 2015). The characteristic of glycerol production needs to be evaluated in conjunction with other variables in order to combine with the fermentative yield and the ability to resist to the various stresses of the industrial fermentative environment. Cell viability, estimated by the ratio between live and dead cells, is an important parameter to consider in the fermentation system with cell recycle. Yeast cells need to stay alive until the end of the fermentation process because they will be recycled hundreds of times during the harvest time. Reduced cell viability indicates that the yeast does not survive in the fermentation conditions, which explains the short lifespan of this strain during harvest time (Basso et al. 2008; Amorim et al. 2010). The loss of cell viability can lead to fermentation stalling (stuck fermentation), resulting in longer fermentation time, high residual sugar content and higher probability of bacterial contamination (Basso and Lino 2018). The selected yeast PE-2 showed much higher cell viability than the baker’s yeast at the end of the fermentation cycles (Table  2.1), which gives this yeast a high capacity for implementation in bioethanol production units. Trehalose and glycogen are the two main reserve carbohydrates in S. cerevisiae (Fig.  2.2), representing up to 30% of the yeast dry matter (Ferreira et  al. 1999). Trehalose increases the fermentative capacity of yeast, acts in the protection of the cell against oxidative damage to proteins and lipids and increases tolerance to water loss (Eleutherio et al. 2015). Cell viability of S. cerevisiae drops dramatically when trehalose levels are below 0.2%, suggesting that the ability to maintain high trehalose levels during cell recycle contributes to enhanced stress tolerance (Basso et al. 2008). Glycogen accumulates when glucose is still present in the medium, but trehalose accumulates only after glucose depletion (François et al. 2012). Both trehalose and glycogen are mobilized when the carbon sources are exhausted, in a process called endogenous fermentation. This process can increase the protein content of the yeast cell, which enriches the dried yeast for sale as

2.3  Strain Selection: Yeast Characteristics and Selection Criteria

29

animal feed. Endogenous fermentation of trehalose and glycogen increased the protein content of the yeast cell by about 9% for two industrial yeasts (PE-2 and SA-1), as shown by Paulillo et al. (2003), who also studied the effect of temperature on the mobilization of reserve carbohydrates. The industrial strains PE-2 and VR-1 were studied regarding the utilization of trehalose and glycogen for ethanol and protein production during fermentation at 40 °C for 24 h, in wine with alcohol content around 3–4%. Trehalose was depleted over this time, but glycogen oscillated and was not depleted. With the decrease in glycogen and trehalose concentration, there was an increase in nitrogen contents, a decrease in cell viability and an increase in alcohol content. Endogenous fermentation yielded 40 and 68 l of alcohol per ton of dry yeast with an increase of 25 and 27% of protein in the yeast for the PE-2 and VR-1 strains, respectively (Ferreira et al. 1999). However, the increase in ethanol production may not be a direct effect of the degradation of intracellular trehalose, but can be explained by the protection exerted by trehalose against oxidative stress that occurs during the fermentative process. Yeast cells present high levels of lipid peroxidation and protein oxidation after fermentation, and due to the cell recycles, a reduced fermentative yield is expected (Trevisol et al. 2011; Santos et al. 2017). A mutant strain deficient in neutral trehalase accumulated trehalose under heat treatment, with the highest concentration of this carbohydrate after fermentation, and did not show any oxidative damage. Thus, the accumulation of intracellular trehalose avoiding oxidative stress ends up being crucial for better fermentation results, extending yeast life longevity, reducing petite generation and consequently increasing ethanol production (Trevisol et al. 2011). Comparing the industrial strains PE-2 and CAT-1, the increase in the levels of lipid peroxidation was lower for CAT-1. The latter strain showed higher levels of trehalose (increased expression of the proteins of the trehalose synthesis complex, Tps1 and Tps2) and oxidant enzymes Sod1, Trx1 and Trx2. CAT-1 demonstrated also higher expression of the protein Tps3, which is activator of Tps2, reinforcing the role of trehalose in the reduction of the oxidative damage for yeast cells (Santos et al. 2017). The accumulation of reserve carbohydrates in yeast cells is then an advantage for the industry, since it increases the fermentative yield and adds value to an important by-product of the sugar-energy industry, which is the post-fermentation yeast mass marketed for animal feed. Therefore, higher intracellular glycogen and trehalose content in the selected yeast strains is an important characteristic to be considered in the selection program. As can be observed in Table 2.1, the selected yeast PE-2 presented 80 and 140% more glycogen and trehalose accumulated intracellularly, respectively, comparing to the baker’s yeast. The importance of accumulating glycogen lies in the fact that this carbohydrate has little effect on the internal osmotic pressure of the cell, which confers an advantage when the cell is in a nutritionally deficient environment for a long time. Trehalose stabilizes the structure of the lipid bilayer of the cell membrane and proteins, avoiding aggregation of proteins and chemical changes in biomolecules, especially with thermal shock (Singer and Lindquist 1998; Eleutherio et al. 2015).

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Gibney et al. (2015) described and characterized a system in S. cerevisiae that allowed manipulation of intracellular trehalose concentrations independently of biosynthetic enzymes and any stresses. In this way, the authors found that many of the physiological roles attributed to intracellular trehalose were not due to the presence of trehalose per se. A system based on the constitutive expression of the AGT1 gene, which encodes a variant of the maltose transporter with specificity for other sugars including trehalose, was used in S. cerevisiae strains mutant for two genes, TPS1 and TPS2. These genes have function in the biosynthesis of trehalose, encoding the enzymes trehalose-6-phosphate synthase (in the case of TPS1 gene) and trehalose-6-phosphate phosphatase (in the case of TPS2 gene) (Fig. 2.2). By applying this strategy, the authors were able to verify if the accumulation of intracellular trehalose (provided by the expression of the AGT1 transporter) could repair the growth deficiencies in heat stress condition in the strains mutated precisely so that no trehalose biosynthesis may occur. Trehalose was found not to repair the growth deficiency in the ∆tps1 mutant strain (unable to produce trehalose or its intermediate metabolite, trehalose-6-phosphate) under high-temperature conditions (37–39 °C), but it did so in the ∆tps2 mutant strain. Thus, many of the metabolic and growth defects associated with mutations in the trehalose biosynthesis pathways were not abolished under the condition of high intracellular trehalose concentration. On the contrary, this intracellular accumulation of trehalose or maltose inhibited the growth of the strains, triggering changes in the expression of genes related to environmental stress response. The authors concluded that the role of trehalose is fundamentally metabolic, mainly related to the activity of the enzyme trehalose-6-phosphate synthase, and more complex than simply the consequence of intracellular trehalose accumulation and its physical properties. It is evident that the selection criteria for yeast strains cannot privilege only the parameters of productivity and ethanol yield. Strains with such beneficial characteristics may disappear throughout the fermentation cycles due to the constant cell recycles and various stresses imposed by the industrial conditions if they do not present characteristics that protect them from the adversities of the fermentative environment. The roles of glycerol, trehalose and glycogen are very important in this context of survival.

2.4 Using Omics to Explain the Superiority of Selected Yeasts The fact that yeasts isolated from the fermentative environment exhibit greater adaptation to industrial conditions than baker’s yeast or laboratory yeast is undeniable. The selection of strains employs production parameters but also stress resistance criteria, revealing the yeast characteristics that allow both dominance and persistence in the fermentative environment. In this context, the omics sciences can contribute, since they seek to understand the cellular functioning of organisms and

2.4  Using Omics to Explain the Superiority of Selected Yeasts

31

their biological changes. Genomics is the starting point for understanding the structure, function and evolution of the genome and its components, by sequencing the DNA molecule. In addition to genomics, omics sciences comprise transcriptomics (study of changes in transcripts), proteomics (study of changes in proteins) and metabolomics (study of changes in metabolites), thus allowing understanding an organism at a systemic level, with specificity and dynamics (Souza et  al. 2014; Canuto et al. 2018) (Fig. 2.3). A study by Argueso et  al. (2009) explored the genomic characteristics of the selected yeast PE-2  in order to explain the high adaptability of this strain to the industrial environment. The authors presented the molecular genetic characterization of a diploid strain derived from PE-2, named JAY270, and the complete genome sequence of a haploid strain also derived from PE-2, JAY291. The diploid strain JAY270 is highly heterozygous, heterothallic, has high sexual spore viability (ascospores) and has high level of SNPs (single-nucleotide polymorphism), approximately 2 SNPs/kb. Karyotyping analysis by pulsed-field gel electrophoresis (PFGE) showed size polymorphisms between the reference strain S288c and the JAY270 strain. However, in the latter strain, some chromosomes appeared as two bands (L, long, and S, short, Fig. 2.4a), each present in one copy in the diploid, i.e. polymorphisms between homolog pairs within the JAY270 strain genome. One example is chromosome 6, whose homologs (L and S) differed by about 60  kb. At least six other chromosomes also showed size polymorphisms in strain JAY270 (Fig. 2.4a). Several structural polymorphisms were also found among homologous chromosomes confined to peripheral regions, which are plastic and susceptible to ectopic recombination in the PE-2 genome. These rearrangements located near the

Fig. 2.3  The omics sciences (genomics, transcriptomics, proteomics and metabolomics), target study molecules and definitions. (Source: From the author)

JAY270

S288c

Chr3 (352) Chr6L (322) Chr6S (261) Chr1 (219)

Chr9 (461)

Chr8S (571)

Chr5,8L (609)

Chr10 (761) Chr11L (716) Chr11S (687)

Chr2,14 (840)

Chr13,16 (963)

Chr7,15 (1112)

Chr4 (-1500)

Chr12 (-25000)

loading well

(B)

peripheral regions niche-specific genes, variable

central core region essential genes, conserved

Fig. 2.4  Molecular karyotype (a) and model of chromosome structural diversity (B) in S. cerevisiae industrial strain PE-2 derivatives. In (a), karyotype obtained by karyotyping (PFGE) of strains S288c (laboratory) and JAY270 (industrial). Each chromosomal band designated by Chr is accompanied by the chromosome number (1–16) and the chromosome size, in kilobases, in parentheses. L (long) and S (short) refer to homologous chromosomes with size polymorphisms. In (b), the model shows a set of homologs of a hypothetical chromosome, with the upper one (in grey) referring to the laboratory reference strain S288c, while the chromosomes below the upper one represent the rearrangements found in the industrial strains. (Source: Argueso et al. 2009, with permission from Cold Spring Harbor Laboratory Press via Creative Commons License)

(254) Chr1

(290) Chr6

(367) Chr3

(458) Chr9

(617) Chr5,8

(698) Chr11

(835) Chr2 (805) Chr14 (771) Chr10

(971) Chr13,16

(1129) Chr7,15

(-1550) Chr4

(-25000) Chr12

loading well

(A)

32 2  The Use of Selected Yeasts in Ethanol Fermentation

2.4  Using Omics to Explain the Superiority of Selected Yeasts

33

chromosome endings do not impair meiosis because they do not encompass regions containing essential genes. The central regions of the chromosomes, where the essential genes are located, remain structurally conserved and are refractory to rearrangements (Fig. 2.4b). The genes found in the peripheral regions are those involved in the utilization of alternative carbon sources, vitamin metabolism, ion and amino acid transport, flocculation and other nonessential processes. Many of these genes occur as multicopy gene families, allowing structural variation to occur through ectopic homologous recombination, very similar to the events observed in the JAY270 strain. This model that assumes the structure of the yeast genome divided into two sectors of the chromosomes, one rigid (core, central region) and the other plastic (peripheral region), was proposed by Pryde et  al. (1997) and applied by Argueso et al. (2009) to demonstrate the results found in the analysis of the genome of industrial strain PE-2. This pattern of structural variation is compatible with the formation of viable ascospores, and the chromosomal rearrangements probably resulted in the amplification of genes related to tolerance to environmental stresses. In the industrial strain JAY291, the retrotransposon Ty1 element inserted in the HAP1 gene was not found, but it was verified in the genome of the reference strain S288c (Argueso et al. 2009). This gene encodes a transcription factor that controls the expression of genes involved in ethanol tolerance (Inoue et al. 2000). Many of the genes upregulated by Hap1p showed higher expression in the industrial strain than in the reference strain (Argueso et al. 2009). The low production of petite colonies in strain JAY270 was attributed to probable mutations occurring in the sequence of the MIP1 gene, a mitochondrial DNA polymerase encoded in the nucleus. Petite colonies of S. cerevisiae are respiration-deficient mutants and exhibit altered membrane and cell wall morphology, besides presenting low fermentation rate due to reduced utilization of fermentable sugars and low cell viability (Ernandes et  al. 1993). This characteristic  – low production of petites  – is desirable in industrial yeasts. The genome of another important selected yeast in the industrial setting, CAT-1, was reported by Babrzadeh et al. (2012). Like strain PE-2, yeast CAT-1 is a highly heterozygous diploid with a genome size of 12  Mb. Compared to the reference strain S288c, 36,000 homozygous SNPs and 30,000 heterozygous SNPs were found. About 58% of the 6652 genes in the CAT-1 strain have different alleles and a reduced number of transposable elements. The telomeric regions of the chromosomes showed many gene deletions and duplications correlated to the physiology of this industrial strain, resulting in important traits for ethanol production. Babrzadeh et al. (2012) demonstrated that there is genomic proximity between CAT-1 and JAY291 (haploid derivative of the PE-2 strain) when evaluating the number of SNPs and when comparing CAT-1 with other S. cerevisiae strains and with S. paradoxus. However, when the authors built the phylogenetic trees considering the IRA1 and IRA2 genes, they found that multiple events must have occurred along the evolutionary line of these two strains. With IRA1, no greater genetic proximity between CAT-1 and PE-2 was observed, but with IRA2, it was. The IRA1 and IRA2 genes have specific and nonredundant functions and are involved in the response to different environmental stresses (Park et al. 2005). Both participate as inhibitors of

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the Ras-cAMP-PKA pathway, which plays a central role in regulating the transcriptional response of yeast cells to the presence of fermentable sugars, leading to rapid growth and determining yeast cell resistance/sensitivity. Polymorphisms in the IRA2 gene have been related to most of the variations that occur in the expression of many genes related to growth and energy metabolism when in the presence of glucose (Smith and Kruglyak 2008; Litvin et al. 2009). The presence of this IRA2 allele in both industrial strains may be involved in the stress resistance demonstrated by these strains (Babrzadeh et al. 2012). Other important comparisons between the two industrial strains refer to FLO and SUC genes, involved in flocculation/foam formation and sucrose hydrolysis, respectively. The reference strain S288c does not flocculate due to a mutation in the FLO8 gene (Liu et  al. 1996); however, both industrial strains have no mutation in this gene. As for the other genes of the FLO family, they are either absent (FLO1 and FLO9) or present a gap in the middle of the coding region (FLO10) or present only the terminal part of the genes (FLO5 and FLO11). These events explain the non-­ flocculent character and the absence of foam formation in these industrial strains. Within the SUC gene family, only SUC2 (related to sucrose hydrolysis) was found in the industrial strains, in a single copy, as well as in the reference strain. The RTM1 gene, involved in resistance to toxins found in sugarcane molasses and often associated with telomeric SUC genes, was also not found in CAT-1 and PE-2 strains (Argueso et al. 2009; Stambuk et al. 2009; Babrzadeh et al. 2012). The diploid strain BG-1, isolated from the Barra Grande Plant, is also heterothallic, with a genome of about 11.7 Mb. The G + C content (about 38%) of the nuclear genome is very similar to that of the reference strain S288c. A total of 5,607 putative protein-coding genes were identified, and about 89% of them have homologs in the reference strain S288c, with similarity greater than 98%. About 280 tRNA-­encoding genes were also found (Coutouné et al. 2017). Stambuck et al. (2009) determined gene copy number variations (CNVs) in five selected S. cerevisiae strains (PE-2, SA-1, VR-1, BG-1 and CAT-1) by microarray-­ based comparative genome hybridization technique in comparison with bakery, brewery, wine and reference (S288c) strains. All selected strains showed significant amplifications of the telomeric genes SNO and SNZ, which are involved in the biosynthesis of vitamins B6 (pyridoxine) and B1 (thiamine) (Fig. 2.5). The role of vitamins B6 and B1 in S. cerevisiae needs to be explained in order to understand the significance of the additional copies of the SNO and SNZ genes in the industrial strains compared to the reference strain S288c. Vitamin B6 is important in amino acid metabolism and many other metabolic pathways, but the biologically active form of this vitamin (pyridoxal 5-phosphate or PLP) is also a precursor of thiamine, which is vitamin B1. This in turn forms the cofactor thiamine pyrophosphate, which is essential in the fermentation of sugars by S. cerevisiae. However, the repressive effect of thiamine on PLP biosynthesis is well known, and due to the decrease in vitamin B6 concentration, many metabolic pathways are repressed causing decreased respiration and altered cell membrane lipid composition. Due to this interaction between vitamins B1 and B6 in yeast and their effects on growth and sugar utilization, it is expected that multiple copies of SNO and SNZ genes may

2.4  Using Omics to Explain the Superiority of Selected Yeasts

35

Fig. 2.5  Dendrogram (a) obtained with microarray-based comparative genomic hybridization (CGH) data using selected bioethanol production strains (PE-2, SA-1, VR-1, BG-1 and CAT-1), baker’s, brewer’s, wine and reference (S288c) strains. The relative copy number of the genes of the selected strains is represented in (b), where red refers to amplified genes, black to polymorphic loci and green to absent genes. The scale of the relative copy number of genes is shown in (c). (Source: Stambuk et  al. 2009, with permission from Cold Spring Harbor Laboratory Press via Creative Commons License)

allow industrial yeast to grow more robustly than those with fewer copies of these genes under conditions of thiamine-mediated repression (Stambuk et  al. 2009). Experiments performed by the authors showed that the industrial strains grew at a high specific growth rate regardless of the presence of thiamine in the culture medium and at high sugar concentration (20% glucose), and this result was not observed for the reference strain S288c. The results of the work of Stambuk et  al. (2009) showed that the significant amplification of telomeric genes SNO and SNZ indicate problems with the bioavailability of vitamins B1 and B6  in the industrial environment, so that the demand should be high especially due to the fact that the active form of thiamine suffers slow and gradual degradation during the production of acetaldehyde and consequently ethanol (McCourt et  al. 2006). The success of the selected yeasts in the industrial environment should also be attributed to this genetic characteristic, i.e. the presence of multicopies of SNO and SNZ genes, giving them an important adaptive advantage. Transcriptomics and proteomics studies can help to elucidate possible characteristics related to the best fermentative performance and resistance to industrial stresses. Brown et  al. (2013) conducted transcriptomic analysis of the selected strains CAT-1 and PE-2 during small-scale fermentative process simulating industrial conditions compared to the reference strain S288c. The environmental stress response genes were upregulated after feeding the vat, demonstrating the effect of the acid treatment performed previously and the high sugar concentration in the vat. The expression of genes related to cell wall biogenesis and tolerance to oxidative stress was also higher in the selected strains. At the end of fermentation, numerous genes related to protein synthesis were found to be downregulated, showing the

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2  The Use of Selected Yeasts in Ethanol Fermentation

impact of alcoholic stress. The industrial yeasts showed higher ethanol tolerance and disruption of endoplasmic reticulum homeostasis, which induces the UPR (unfolded protein response) pathway, a protective response to the cell. The increased tolerance to ethanol was also reflected in increased splicing of the transcription factor HAC1. Quantitative proteomics analysis (iTRAQ) results obtained by Santos et  al. (2017) showed that proteins involved in the response to oxidative stress (Sod1 and Trx1) and trehalose synthesis (Tps3) are more abundant in CAT-1 strain than in PE-2 after one fermentative cycle. The chaperones (assist in protein coiling and prevent protein aggregation) Ssa1, Hsp26 and Hsp104 were found in higher concentration in the CAT-1 strain, as well as Mbf1 (suppressor of DNA mutations), Hor7 (related to osmotic stress) and Ino1 (related to ethanol tolerance), among others. Bonatelli et al. (2017) performed metabolomic analysis of fed-batch fermentation with cell recycle conducted by the industrial yeast CAT-1 in sugarcane juice by means of gas chromatography coupled to mass spectroscopy (GC-MS), which allows the detection of low molecular weight metabolites. A total of 242 metabolites were reported, the majority unknown (43%), followed by organic oxygen compounds (18%, represented by alcohols and polyols) and organic acids and derivatives (16%, especially carboxylic acids and derivatives). The proportion of unknown compounds indicates that the fermentative environment is still poorly known in terms of its composition. The main limitation of microbial metabolomics lies in the high complexity of metabolites that are still little explored and known (Belinato et al. 2019). The metabolomics approach can indicate target genes for genetic improvement of S. cerevisiae strains aiming resistance to various stresses. Ohta et al. (2016) used GC-MS to identify and quantify 36 compounds in 14 S. cerevisiae mutant strains exhibiting ethanol tolerance. The authors found a strong relationship between the metabolome of these mutants and ethanol tolerance, showing that compounds such as trehalose, proline, inositol and valine contributed to ethanol tolerance, with the latter two substances standing out. The diverse and advanced techniques of genome evaluation associated to transcriptomics, proteomics and metabolomics allow us to understand how the strains of industrial environment survive in conditions of intense stress for hundreds of fermentation cycles in one harvest. Furthermore, these techniques open the way for the genetic engineering of these yeasts in order to obtain strains with better production characteristics and resistance to industrial stresses (Abreu-Cavalheiro and Monteiro 2013).

2.5  Genetically Modified Yeast Strains for Bioethanol Production

37

2.5 Genetically Modified Yeast Strains for Bioethanol Production Genetically modified (GM) yeast strains are not predominant in the bioethanol plants in Brazil. A list of commercial yeast strains for ethanol production from sucrose and other substrates is available at the work by Jacobus et  al. (2021), in which the majority of strains are non-genetically modified. Sucramax™ was the first GM yeast strain for the cell recycle fermentation process, launched in 2017 by Lallemand Biofuels/Mascona. Using the industrial strain PE-2 as basis, Sucramax™ was modified to overexpress STL1, a glycerol/proton symporter, for a reduced glycerol production and better ethanol yield (Jacobus et al. 2021). The traits that have also received attention to obtain GM yeast strains for the bioethanol production include improved ethanol yield, higher tolerance to stresses (ethanol, heat and acids) and self-ability to combat bacterial contaminations. Increased ethanol production can be achieved by introducing genes related to ATP-­ degrading enzymes or activating futile cycles that dissipate ATP generated during glycolysis, thus decreasing biomass production. Another strategy is to modify the expression of invertase to the intracellular mode only, activating the active transport of sucrose into the cell via proton symport, which demands ATP to maintain proton motive force across the membrane, with consequent decrease in biomass and glycerol production. In regard to stresses, much attention has been deserved to ethanol, heat and acid tolerance, the most important challenges that the yeast cope with during ethanolic fermentation (Ceccato-Antonini and Covre 2020). In parallel with the genetic engineering techniques, the new breeding techniques (NBTs) include genome-editing approaches that could be promising to the bioethanol industry. CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9) is an innovative technology that allows precise genomic targeting of multiple loci, no requirement of a selection marker and negligible off-target effects (DiCarlo et al. 2012). If exogenous DNA/RNA is absent, the organism is exempted from regulation directives applied to GM organisms in Brazil, and consequently it does not require risk assessment (Nepomuceno et  al. 2020). The application of CRISPR-Cas9 in the biofuel industry to enhance product formation has been reported, especially regarding ethanol and inhibitor tolerance, thermotolerance and improved ethanol yield (Deparis et al. 2017). The Brazilian National Technical Biosafety Commission (CTNBio) approved in mid-2018 the first yeast obtained by NBT to increase efficiency in ethanol production. The company GlobalYeast (a consortium of shareholders from Brazil and Belgium) used the CRISPR/Cas9 system to edit the genome of the S. cerevisiae strain “Excellomol 4.0 Next” and introduce point polymorphisms in genes of interest, simulating what occurs naturally in the CBS6412 strain of S. cerevisiae used in sake production. Since no other region of the genome was manipulated, no additional copies were introduced and there is no heterologous DNA in the edited strain, this microorganism was not considered a “genetically modified organism” (GMO)

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2  The Use of Selected Yeasts in Ethanol Fermentation

and was released from GMO regulation procedures in Brazil (Diário Oficial da União 2018). Comparing to the American corn-based production of ethanol, the adoption of GM strains is justified by the mode of fermentation operation (batch fermentation without cell recycle) and well-designed trials. In Brazilian sugarcane-based bioethanol production, a less controlled process operating in fed-batch system with cell recycle makes the option for GM yeasts less attractive (Jacobus et al. 2021). The fact is that ethanol producers must always have new options for yeast strains, whether genetically modified or not. Steensels et al. (2014) discussed different strategies for yeast strain selection and improvement based on genetic modification techniques as well as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution approaches. The natural diversity of S. cerevisiae found in the industrial environment can be exploited to identify desired traits and genetic background in order to combine conventional and advanced technologies to obtain yeast strains with better fitness and high ethanol yields for the bioethanol industry.

References Abreu-Cavalheiro, A., Monteiro, G.: Solving ethanol production problems with genetically modified yeast strains. Braz. J. Microbiol. 44(3), 665–671 (2013) Amorim, H.V.: Fermentação alcoólica – ciência e tecnologia. Fermentec, Piracicaba (2005) 448p Amorim, H.V., Gryschek, M., Lopes, M.L.: The success and sustainability of the Brazilian sugarcane-­ fuel ethanol industry. In: Eggleston, G. (ed.) Sustainability of the Sugar and Sugar Ethanol Industries ACS symposium series, pp.  73–82. American Chemical Society, Washington, DC (2010) Amorim, H.V., Lopes, M.L., Oliveira, J.V.C., Buckeridge, M.S., Goldman, G.H.: Scientific challenges of bioethanol production in Brazil. Appl. Microbiol. Biotechnol. 91, 1267–1275 (2011) Andrietta, M.G.S., Steckelberg, C., Andrietta, S.R.: Bioetanol – Brazil, 30 years at the forefront. MultiCiência. 7, 1–16 (2006) Argueso, J.L., Carazzolle, M.F., Mieczkowski, P.A., Duarte, F.M., Carvalho-Netto, O.V., Missawa, S.K., Galzerani, F., Costa, G.G.L., Vidal, R.O., Noronha, M.F., Dominska, M., Andrietta, M.G.S., Andrietta, S.R., Cunha, A.F., Gomes, L.H., Tavares, F.C.A., Alcarde, A.R., Dietrich, F.S., McCusker, J.H., Petes, T.D., Pereira, G.A.G.: Genome structure of a Saccharomyces cerevisiae strain widely used in bioethanol production. Genome Res. 19, 2258–2270 (2009) Babrzadeh, F., Jalili, R., Wang, C., Shokralla, S., Pierce, S., Robinson-Mosher, A., Nyren, P., Shafer, R.W., Basso, L.C., Amorim, H.V., Oliveira, A.J., Davis, R.W., Ronaghi, M., Gharizadeh, B., Stambuk, B.U.: Whole-genome sequencing of the efficient industrial fuel-ethanol fermentative Saccharomyces cerevisiae strain CAT-1. Mol. Gen. Genomics. 287, 485–494 (2012) Basso, L.C., Amorim, H.V., Oliveira, A.J., Lopes, M.L.: Yeast selection for fuel ethanol production in Brazil. FEMS Yeast Res. 8, 1155–1163 (2008) Basso, L.C., Oliveira, A.J., Orelli, V.F.M., Campos, A.A., Gallo, C.R., Amorim, H.V.: Dominance of contaminant yeasts over industrial strains evaluated by the karyotyping technique. Anais do V Congresso Nacional da STAB. 5, 246–250 (1993) Basso, T.O., Lino, F.S.O.: Clash of kingdoms: how do bacterial contaminants thrive in and interact with yeasts during ethanol production? In: Fuel Ethanol Production from Sugarcane, pp. 23–38. InTechOpen, London (2018) Belinato, J.R., Bazioli, J.M., Sussulini, A., Augusto, F., Fill, T.P.: Microbial metabolomics: innovations and applications. Química Nova. 42(5), 546–559 (2019)

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Bjorkqvist, S., Ansell, R., Adler, L., Liden, G.: Microbiology physiological response to anaerobicity of glycerol-3-phosphate dehydrogenase mutants of Saccharomyces cerevisiae. Appl. Environ. Microbiol. 63(1), 128–132 (1997) Blasco, L., Viñas, M., Villa, T.G.: Proteins influencing foam formation in wine and beer: the role of yeast. Int. Microbiol. 14, 61–71 (2011) Bonatelli, M.L., Ienczak, J.L., Cataldi, T.R., Budzinski, I.G.F., Labate, C.A.: First-generation fermentation metabolomics by GC-MS: establishment of analysis methodology. Proceedings of National Bioprocesses Symposium and Enzymatic Hydrolysis of Biomass Symposium (2017). Available at: https://proceedings.science/sinaferm/sinaferm-­2017/papers/first-­generation-­ fermentation-­metabolomics-­by-­gc-­ms%2D%2Destablishment-­of-­analysis-­methodology-. Accessed 24 Mar 2020. Brown, N.A., Castro, P.A., Figueiredo, B.C.P., Savoldi, M., Buckeridge, M.S., Lopes, M.L., Paulillo, S.C.L., Borges, E.P., Amorim, H.V., Goldman, M.H., Bonatto, D., Malavazi, I., Goldman, G.H.: Transcriptional profiling of Brazilian Saccharomyces cerevisiae strains selected for semi-­continuous fermentation of sugarcane must. FEMS Yeast Res. 13, 277–290 (2013) Canuto, G.A.B., Costa, J.L., Cruz, P.L.R., Souza, A.R.L., Facci, A.T., Klassen, A., Rodrigues, K.T., Tavares, M.F.M.: Metabolomics: definitions, state-of-the-art and representative applications. Química Nova. 41(1), 75–91 (2018) Carvalho-Netto, O.V., Carazzolle, M.F., Mofatto, L.S., Teixeira, P.J.P.L., Noronha, M.F., Calderón, L.A.L., Mieczkowkski, P.A., Argueso, J.L., Pereira, G.A.G.: Saccharomyces cerevisiae transcription reprogramming due to bacterial contamination during industrial scale bioethanol production. Microb. Cell Factories. 14(13), 1–13 (2015) Ceccato-Antonini, S.R., Covre, E.A.: From baker’s yeast to genetically modified budding yeasts: the scientific evolution of bioethanol industry from sugarcane. FEMS Yeast Res. 20, foaa065 (2020) Coutouné, N., Mulato, A.T.N., Riaño-Pachón, D.M., Oliveira, J.V.C.: Draft genome sequence of Saccharomyces cerevisiae Barra Grande (BG-1), a Brazilian industrial bioethanol-producing strain. Genome Announc. 5(13), e00111–e00117 (2017) Della-Bianca, B.E., Basso, T.O., Stambuk, B.U., Basso, L.C., Gombert, A.K.: What do we know about the yeast strains from the Brazilian fuel ethanol industry? Appl. Microbiol. Biotechnol. 97, 979–991 (2013) Della-Bianca, B.E., Hulster, E., Pronk, J.T., van Maris, A.J., Gombert, A.K.: Physiology of the fuel ethanol strain Saccharomyces cerevisiae PE-2 at low pH indicates a context-dependent performance relevant for industrial applications. FEMS Yeast Res. 14, 1196–1205 (2014) Deparis, Q., Claes, A., Foulquié-Moreno, M.R., Thevelein, J.M.: Engineering tolerance to industrially relevant stress factors in yeast cell factories. FEMS Yeast Res. 17, fox036 (2017) Diario Oficial da União: Extrato de Parecer Técnico 5904/2018 e 5905/2018 (2018), p.  11. Available at: https://pesquisa.in.gov.br/imprensa/jsp/visualiza/index.jsp?data=22/06/2018&jo rnal=515&pagina=11. Accessed 29 May 2022. DiCarlo, J.E., Norville, J.E., Mali, P., Rios, X., Aach, J., Church, G.M.: Genome engineering in Saccharomyces cerevisiae using CRISPR–Cas systems. Nucleic Acids Res. 41, 4336–4343 (2012) Eleutherio, E., Panek, A., Freire, J., Eduardo, D.M.: Revisiting yeast trehalose metabolism. Curr. Genet. 61, 263–274 (2015) Ernandes, J.R., Williams, J.W., Russell, I., Stewart, G.G.: Respiratory deficiency in brewing yeast strains – effects on fermentation, focculation and beer flavour components. J. Am. Soc. Brew. Chem. 51, 16–20 (1993) Ferreira, L.V., Amorim, H.V., Basso, L.C.: Fermentation of trehalose and endogenous glycogen in Saccharomyces cerevisiae. Cienc. Tecnol. Aliment. 19(1), 29–32 (1999) François, J.M., Walther, T., Parrou, J.L.: Genetics and regulation of glycogen and trehalose metabolism in Saccharomyces cerevisiae. In: Liu, Z.L. (ed.) Microbial Stress Tolerance for Biofuels, pp. 29–55. Springer, Berlin (2012)

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Gibney, P.A., Schieler, A., Chen, J.C., Rabinowitz, J.D., Botstein, D.: Characterizing the in vivo role of trehalose in Saccharomyces cerevisiae using the AGT1 transporter. Proc. Natl. Acad. Sci. USA. 112(19), 6116–6121 (2015) Guo, Z., Khoomrung, S., Nielsen, J., Olsson, L.: Changes in lipid metabolism convey acid tolerance in Saccharomyces cerevisiae. Biotechnol. Biofuels. 11, 297 (2018) Hohmann, S.: Osmotic stress signaling and osmoadaptation in yeasts. Microbiol. Mol. Biol. Rev. 66(2), 300–372 (2002) Inoue, T., Iefuji, H., Fujii, T., Soga, H., Satoh, K.: Cloning and characterization of a gene complementing the mutation of an ethanol-sensitive mutant of sake yeast. Biosci. Biotechnol. Biochem. 64, 229–236 (2000) Jacobus, A.P., Gross, J., Evan, J.H., Ceccato-Antonini, S.R., Gombert, A.K.: Saccharomyces cerevisiae strains used industrially for bioethanol production. Essays Biochem. 65(2), 147–161 (2021) Lima, U.A.: Produção de etanol com matérias primas sacarinas. In: Lima, U.A. (ed.) Processos fermentativos e enzimáticos, vol. 3, pp. 19–70. Blucher, São Paulo (2019) Litvin, O., Causton, H.C., Chen, B.J., Pe’er, D.: Modularity and interactions in the genetics of gene expression. Proc. Natl. Acad. Sci. USA. 106, 6441–6446 (2009) Liu, H., Stylest, C.A., Fink, G.R.: Saccharomyces cerevisiae S288C has a mutation in FL08, a gene required for filamentous growth. Genetics. 144, 967–978 (1996) Lopes, M.L., Paulillo, S.C.P., Cherubin, R.A., Godoy, A., Amorim Neto, H.B., Amorim, H.V.: Tailored Yeast Strains for Ethanol Production: The Process-Driven Selection. Fermentec, Piracicaba (2015) 41p McCourt, J.A., Nixon, P.F., Duggleby, R.G.: Thiamin nutrition and catalysis-induced instability of thiamin diphosphate. Br. J. Nutr. 96, 636–638 (2006) Nepomuceno, A.L., Fuganti-Pagliarini, R., Felipe, M.S.S., Molinari, H.B.C., Velini, E.D., Pinto, E.R.C., Dagli, M.L.Z., Andrade Filho, G., Fernandes, P.M.B.: Brazilian biosafety law and the new breeding technologies. Front. Agric. Sci. Eng. 7, 204–210 (2020) Nevoigt, E., Stahl, U.: Osmoregulation and glycerol metabolism in the yeast Saccharomyces cerevisiae. FEMS Microbiol. Rev. 21, 231–241 (1997) Nielsen, J.C., Lino, F.S.O., Rasmussen, T.G., Thykaer, J., Workman, C.T., Basso, T.O.: Industrial antifoam agents impair ethanol fermentation and induce stress responses in yeast cells. Appl. Microbiol. Biotechnol. 101, 8237–8248 (2017) Ohta, E., Nakayama, Y., Mukai, Y., Bamba, T., Fukusaki, E.: Metabolomic approach for improving ethanol stress tolerance in Saccharomyces cerevisiae. J. Biosci. Bioeng. 121(4), 399–405 (2016) Pagliardini, J., Hubmann, G., Alfenore, S., Nevoigt, E., Bideaux, C., Guillouet, S.E.: The metabolic costs of improving ethanol yield by reducing glycerol formation capacity under anaerobic conditions in Saccharomyces cerevisiae. Microb. Cell Factories. 12, 29 (2013) Park, J.I., Grant, C.M., Dawes, I.W.: The high-affinity cAMP phosphodiesterase of Saccharomyces cerevisiae is the major determinant of cAMP levels in stationary phase: involvement of different branches of the Ras-cyclic AMP pathway in stress responses. Biochem. Biophys. Res. Commun. 327, 311–319 (2005) Paulillo, S.C.L., Yokoya, F., Basso, L.C.: Mobilization of endogenous glycogen and trehalose of industrial yeasts. Braz. J. Microbiol. 34, 249–254 (2003) Pryde, F.E., Gorham, H.C., Louis, E.J.: Chromosome ends: all the same under their caps. Curr. Opin. Genet. Dev. 7, 822–828 (1997) Reed, R.H., Chudek, J.A., Foster, R., Gadd, G.M.: Osmotic significance of glycerol accumulation in exponentially growing yeasts. Appl. Environ. Microbiol. 53(9), 2119–2123 (1987) Reis, V.R., Antonangelo, A.T.B.F., Bassi, A.P.G., Colombi, D., Ceccato-Antonini, S.R.: Bioethanol strains of Saccharomyces cerevisiae characterised by microsatellite and stress resistance. Braz. J. Microbiol. 48, 268–274 (2017) Santos, R.M., Nogueira, F.C.S., Brasil, A.A., Carvalho, P.C., Leprevost, F.V., Domont, G.B., Eleutherio, E.C.A.: Quantitative proteomic analysis of the Saccharomyces cerevisiae industrial strains CAT-1 and PE-2. J. Proteome. 151, 114–121 (2017)

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Silva-Filho, E.A., Santos, S.K.B., Resende, A.M., Morais, J.O.F., Morais Jr., M.A., Simões, D.A.: Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR fingerprinting. Antonie Van Leeuwenhoek. 88, 13–23 (2005) Singer, M.A., Lindquist, S.: Effects of trehalose on protein folding in vitro and in vivo. Mol. Cell. 1, 639–638 (1998) Smith, E.N., Kruglyak, L.: Gene-environment interaction in yeast gene expression. PLoS Biol. 6, e83 (2008) Souza, L.L., Rhoden, S.A., Pamphile, J.A.: The importance of omics as tools for the study of microorganism prospection: perspectives and challenges. Revista Uningá Rev. 18(2), 16–21 (2014) Stambuk, B.U., Dunn, B., Alves, J.S.L., Duval, E.H., Sherlock, G.: Industrial fuel ethanol yeasts contain adaptive copy number changes in genes involved in vitamin B1 and B6 biosynthesis. Genome Res. 19, 2271–2278 (2009) Steensels, J., Snoek, T., Meersman, E., Nicolino, M.P., Voordeckers, K., Verstrepen, K.J.: Improving industrial yeast strains: exploiting natural and artificial diversity. FEMS Microbiol. Rev. 38, 947–995 (2014) Stroppa, C.T.: Dinâmica populacional de leveduras caracterizadas por eletro-cariótipo e desempenho fermentativo em processos de fermentação alcoólica. Thesis, Universidade Estadual de Campinas (2002) Trevisol, E.T.V., Panek, A.D., Mannarino, S.C., Eleutherio, E.C.A.: The effect of trehalose on the fermentation performance of aged cells of Saccharomyces cerevisiae. Appl. Microbiol. Biotechnol. 90, 697–704 (2011)

Chapter 3

Native Yeasts and Their Role in Ethanol Fermentation

3.1 Introduction The fermentation process carried out in Brazil has peculiarities, such as the fact that the fermentation does not take place under aseptic conditions and cell recycling is used. In view of this, ethanol fermentation is considered a complex process with succession of yeast strains. The yeasts found in industrial processes can present a wide range of variations in the kinetic parameters (yield, productivity and specific growth rate) and resistance to the stresses of the fermentation environment, not always causing problems of decrease in the fermentative yield. However, it appears that not a single factor is responsible for the installation and permanence of these strains in the process, but a series of variables, and the dynamics is unique to each of the processes. Native or wild yeasts are the yeasts that invade the fermentation process, often coming from the soil, the cane itself and the cane washing water. The main genera are Saccharomyces, Schizosaccharomyces, Candida and Dekkera. The yeasts Saccharomyces cerevisiae that have pseudohyphae (buds that do not separate from the mother cell), also called rough yeasts, are very common in fermentation tanks and can cause several problems, including loss in fermentation yield due to its slow ability to convert sugar into ethanol. Among the non-Saccharomyces yeasts, the genus Dekkera presents high growth capacity but reduced fermentative capacity compared to the process yeast S. cerevisiae, under the conditions in which fermentation is performed in Brazil. These characteristics cause distilleries contaminated with these yeasts to present both a decrease in ethanol production and an increase in the fermentation time, causing operational problems in the production unit. The traditional methods employed by the sugar and ethanol industry to reduce the contaminating microbial load recommend the use of antibiotics and other biocides and concentrated sulfuric acid in the yeast treatment step, which occurs © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_3

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between fermentation cycles. These techniques, although efficient against bacteria, have no effect against native yeasts, often selecting microbial cells even more resistant to low pH and concentrations of antibiotics. Therefore, it is essential to know the characteristics of the contaminant yeast in comparison with the process yeast S. cerevisiae, in order to find strategies for the elimination or management of the contaminant yeast in the fermentative environment.

3.2 Non-Saccharomyces Yeasts Although a diversity of yeasts can be found in the fermentative environment, few are the species responsible for episodes of acute contamination that lead to a decrease in fermentative yield. Basso et al. (2008) evaluated that non-­Saccharomyces yeasts are of low prevalence, representing about 5% of the total strains observed in the fermentation process. In the Central and Southeast regions of Brazil, less than 5% of the distilleries exhibited contamination by non-Saccharomyces yeasts, while in the Northeast of the country, a much higher number of distilleries – 30% – are affected by contamination by non-Saccharomyces yeasts (Basílio et al. 2008; Basso et al. 2008). Oliveira and Pagnocca (1988) detected the yeasts Hansenula anomala, Candida famata, Saccharomyces kluyveri and S. cerevisiae as contaminants in an industrial unit from centrifuged yeast cream, treated yeast cream and fermenting must samples. Species such as Dekkera bruxellensis, Candida tropicalis, Pichia galeiformis, Schizosaccharomyces pombe and Candida krusei have also been reported in distilleries associated with decreased fermentative yield (Basílio et al. 2008). Analyses performed in two units in the state of Goiás (Brazil) indicated the predominance of the species S. cerevisiae, C. tropicalis and Pichia kudriavzevii (Rodrigues 2017). The genus Candida was isolated more frequently, alongside Saccharomyces, in producing units in the State of São Paulo (Castro 1995; Ceccato-Antonini and Silva 2000). S. pombe species was found in higher proportion than a selected S. cerevisiae strain (CAT-1) but the distillery operated with low ethanol concentration (6% v/v). In laboratory experiments, the S. pombe strain showed longer fermentation time, lower cell viability and reduced growth in wines with higher ethanol concentrations, 7.8% and 9% (Basso et al. 2008). Within the genus Candida, the species C. tropicalis has been reported as one of the most relevant contaminants in Brazilian distilleries. Basílio et al. (2008) verified that this yeast had about 63% of the fermentative capacity of S. cerevisiae yeast. Lower ethanol production and lower consumption rate of sugars, especially sucrose and glucose, were presented by C. tropicalis yeast compared to S. cerevisiae in sugarcane juice (Lourencetti 2018). Studies have shown that the similarities between the two yeast species go beyond phenotypic characteristics and fermentative profile. The transcriptional profile of C. tropicalis showed correlation between the expressions of many genes in both species, including those genes essential for ethanol

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production. This contaminant expressed genes for adaptation, growth, competitiveness for nutrients, multiplication and tolerance to the stresses of the fermentative process such as temperature increase, osmotic stress, nutrient depletion and ethanol toxicity. The species C. tropicalis showed activation of specific genes for ethanol production and resistance as early as the first hours of fermentation, and the expression continued during the fermentative cycle. In contrast, in S. cerevisiae, the genes predominantly expressed throughout the fermentative cycle are those related to ethanol production (Lourencetti et al. 2018). Among the non-Saccharomyces yeasts, the species D. bruxellensis has been considered the main contaminant of alcoholic fermentation. Although reports on the effects of Dekkera contamination are predominant in vinification, where it causes sensory problems in the beverage, the species D. bruxellensis has been detected as the main contaminant yeast in the production of fuel ethanol, presenting a surprising capacity for growth and adaptation in sugarcane substrates. The genus Dekkera presents spheroidal to ellipsoidal cells, many times ogival, characterized by a structure similar to a candle flame at the extremities, and may also be cylindrical or elongated (Fig. 3.1). Vegetative reproduction is by budding and exhibits pseudomycelium. It is also characterized as slow-growing yeast, short lifespan in Petri dishes, characteristic aroma, strong production of acetic acid from glucose, stimulation of fermentation by molecular oxygen and requirement of external source of vitamins. The genus Brettanomyces is the imperfect form of the genus Dekkera, showing no ascospore formation (Kreger-van Rij 1984; Barnett et al. 2000). In Brazil, the first report of contamination of the alcoholic fermentation process by this yeast is presented by Silva (1994). In this work, it was documented the occurrence of severe contamination by a native yeast in the continuous process of industrial ethanol production, demonstrating the non-stability of the initial yeast inoculum, which was practically replaced by D. bruxellensis. The population evolved from approximately 62–96% of the total number of yeasts in 8  days of operation of the production unit. Fig. 3.1  Cell morphology of yeast D. bruxellensis, showing elongated (E), spheroidal (S) and ogival (O) cells in YPD medium. Magnification 400X under optical microscope. (Source: From the author)

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3  Native Yeasts and Their Role in Ethanol Fermentation

Guerra (1998) detected D. bruxellensis as contaminant in an industrial unit that suffered constant drops in fermentation yield and had its starter yeast replaced seven times during a single harvest. The control of this yeast growth was successful by minimizing the availability of oxygen and the use of ethanol. Since the mid-2000s, works started to appear in Brazil pointing D. bruxellensis as an important and common contaminant of fermentation tanks, studying its adaptability, characteristics and physiology, especially related to the environment of the fermentative process. Despite exhibiting growth capacity in sugarcane juice, physiological analyses showed that D. bruxellensis yeasts have low fermentative capacity when compared to S. cerevisiae in sugarcane musts and in the conditions in which the industrial fermentation occurs. Longer fermentation time and lower industrial yield result in sugar accumulation in the industrial tanks at the end of fermentation and consequently slower fermentations (Araújo et al. 2005). Low initial counts of D. bruxellensis (10–103 cells/mL) in cocultures with S. cerevisiae using batch system with cell recycle in sugarcane broth resulted in low ethanol productivity, substantial growth of the contaminant yeast over 14 cycles of fermentation and decreased fermentation efficiency (Meneghin et al. 2013). The low fermentative capacity of D. bruxellensis yeast may be related to the fact that this species exhibits only 10% of the invertase enzyme activity (which hydrolyses sucrose to glucose and fructose) as being extracellular, implying the need for sucrose transport into the cells, with probable energy expenditure (Leite et al. 2013). The invertase enzyme of S. cerevisiae hydrolyses most of the sucrose in the extracellular medium (Carlson and Botstein 1982). Meneghin et al. (2013) found that ethanol production was higher in stirred cultures with glucose than with sucrose as carbon source in D. bruxellensis strains isolated from the fermentative process. The assimilation of nitrate as nitrogen source is a characteristic that distinguishes D. bruxellensis from S. cerevisiae, the latter incapable of growing in medium containing nitrate as the only source of nitrogen. The presence of nitrate increased the fermentative efficiency of D. bruxellensis under anaerobic conditions, which can be explained by the fact that in D. bruxellensis the “Custer” effect occurs, in which fermentation is inhibited under oxygen limitation (Wijsman 1984). In this situation, a redox imbalance occurs due to the inability of this yeast to reoxidize the NADH produced during the glycolytic cycle. Since nitrate utilization pathways depend on NAD(P)H, the use of nitrate as a nitrogen source would serve to maintain the redox balance (redox sink). In the presence of nitrate in the fermentation medium, the yeast consumed more sucrose and produced more ethanol, which may explain why the presence of D. bruxellensis is not always associated with a drop in ethanol production (Pita et al. 2011, 2013; Galafassi et al. 2013). It is important to note that the sugarcane juice used in Brazilian distilleries for bioethanol production may contain both ammonium and nitrate as nitrogen sources. In the presence of both sources, the yeast S. cerevisiae initially has the advantage in competition with D. bruxellensis, but as the ammonia is depleted in the medium, nitrate will be assimilated by D. bruxellensis, which will be able to grow continuously, although more slowly, and produce ethanol. Nitrate assimilation is a way for the contaminating yeast to

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maintain itself in the industrial process under anaerobic conditions, with the ability to produce ethanol and promote growth due to the increased demand for ATP that leads to increased glycolytic flux (Pita et al. 2013; Peña-Moreno et al. 2019). The relationship between oxygen availability and assimilation of nitrogen sources may help explain the adaptation of D. bruxellensis cells in the industrial environment. Parente et al. (2018) showed that amino acid catabolism is more efficient in the absence of oxygen when arginine, aspartate, glutamate and glutamine are present in the medium, with glutamine being the preferred source of nitrogen regardless of the presence of oxygen. The authors also verified a mechanism independent of oxygen availability that acts to overexpress genes such as GAP1, GDH1, GDH2 and GLT1, which ensure yeast growth even in the presence of the non-­ preferential nitrogen source. Dekkera/Brettanomyces yeasts are capable of producing significant amounts of acetic acid (Miniac 1989), and for some time, it was inferred that the acetic acid produced by this contaminant could interfere with the growth of S. cerevisiae and thus confer a competitive advantage over this yeast. However, under industrial conditions, the amount of oxygen available is limited, which would not provide an increase in acetic acid concentration capable of inhibiting or even interfering with the growth of S. cerevisiae (Phowchinda et al. 1995; Abbott et al. 2005; Blomqvist et al. 2010). The inhibition of growth and interference in the fermentative capacity of S. cerevisiae by D. bruxellensis cells only occurs when the concentration of acetic acid reaches levels higher than 2 g/L (Yahara et al. 2007). Blomqvist (2011), using cultures in a continuous system and with 5% dissolved oxygen, observed that D. bruxellensis cells produced amounts of acetic acid lower than 1 g/L, a concentration that was not enough to affect the growth and development of D. bruxellensis and S. cerevisiae yeasts in industrial fermentation processes. Pereira et al. (2012) did not detect acetic acid production by D. bruxellensis in eight 12-h fermentation cycles in sugarcane juice in ethanol fermentation. On the contrary, in pure culture of S. cerevisiae, there was higher acid production than in the pure culture of the contaminant. The authors also verified that both yeasts were equally sensitive to the addition of acetic acid and lactic acid to the fermentation medium. In molasses, there was a stimulus in the production of acetic acid by the cells of D. bruxellensis even under anaerobic conditions, possibly by the presence of some final electron acceptor still unknown, which did not occur in sugarcane juice medium. There was also an increase in the fermentation yield in molasses when compared to sugarcane juice and higher cell viability of D. bruxellensis compared to S. cerevisiae (Pereira et al. 2012, 2014). Although yeasts of the genus Dekkera are evolutionarily separated from S. cerevisiae about 200 million years (Woolfit et al. 2007), they share some characteristics, one of them being the ability to produce ethanol even in the presence of oxygen, which characterizes the so-called positive “Crabtree” effect (Pronk et  al. 1996; Procházka et al. 2010; Hagman et al. 2014).

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Blomqvist et al. (2010) pointed out that D. bruxellensis has a higher energy efficiency than S. cerevisiae, which leads to higher biomass production and lower glycerol production. Glycerol is produced under oxygen limitation conditions in order to reoxidize the NADH produced during the oxidation process. Some authors claim that Dekkera yeasts are not able to produce glycerol to restore the NAD+/NADH balance, and this inability would lead to the “Custer” effect, i.e. the temporary inhibition of fermentation under anaerobic conditions, as discussed earlier. However, studies show that D. bruxellensis produces glycerol, however, in much smaller amounts when compared to S. cerevisiae (Souza-Liberal et  al. 2007; Blomqvist et al. 2010; Blomqvist and Passoth 2015), and in this case, balancing of the redox condition occurs in the presence of nitrate, resulting in growth under anaerobic conditions and improving fermentative yield (Galafassi et al. 2013), as discussed earlier about nitrate. The ability of D. bruxellensis yeasts to persist in industrial environment for a long time is well known (Cibrario et al. 2020). Such persistence may be attributed to the capacity of living in different physiological states such as free-living cells, biofilms, pseudomycelia, chlamydospore-like structures and viable but nonculturable cell state (Harrouard et al. 2022). This species also display a strong genetic variability evidenced by the sequencing of a great number of strains from different origins and regions. The robustness and resistance to environmental stresses in industrial yeasts may also be attributed to polyploidy, which confers genome plasticity. About 50% of D. bruxellensis strains studied by Avramova et  al. (2018) showed more than two alleles for at least one locus. Aneuploidy occurred more rarely in D. bruxellensis (Gounot et al. 2020). The fact that D. bruxellensis yeast does not accumulate trehalose (Pereira et al. 2014) may be related to the sensitivity of this yeast to thermal and oxidative stresses. Leite et al. (2016) demonstrated that there is no intracellular accumulation of trehalose due to the high constitutive activity of the neutral enzyme trehalase, together with the indication that the limitation in trehalose synthesis may be linked to a deficiency in the activity of the enzyme trehalose-6-phosphate synthase, giving this yeast a higher sensitivity to high temperatures than S. cerevisiae yeast. The genus Dekkera produces volatile phenols from hydroxycinnamic acids (Chatonnet et al. 1992; Suárez et al. 2007). The origin of these compounds involves the sequential action of two enzymes, hydroxycinnamate decarboxylase (HCD), which converts hydroxycinnamic acid to hydroxystyrenes (vinylphenols), which are reduced to ethyl derivatives by the enzyme vinylphenol reductase (VR). The most important molecules in the class of volatile phenols are 4-viniphenol, 4-­ethylphenol, 4-vinylguaiacol and 4-ethylguaiacol (Chatonnet et al. 1992; Edlin et al. 1995). There are reports that the yeast Dekkera can balance its metabolic functions through the production of volatile phenols, specifically by the reduction of 4-­vinylphenol to 4-ethylphenol. The results by Silva et al. (2011) suggest that the conversion of 4-vinylphenol to 4-ethylphenol catalysed by the VR enzyme can lead to reoxidation of NADH. This reduction is a source of NAD+ during the growth of this microorganism, thus maintaining the redox balance of its cells (Fugelsang and Edward 1997; Šućur et al. 2016).

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49

Studies indicate the presence of hydroxycinnamic acids in sugarcane juice and molasses (Duarte-Almeida et al. 2006). Silva et al. (2018), evaluating the enzymatic activity of HCD and VR in three strains of D. bruxellensis isolated from ethanol fermentation, found that these strains showed higher enzymatic activity than the strains isolated from the vinification process. Compared to these, the strains of D. bruxellensis isolated from alcoholic fermentation presented an average HCD activity 16.5 times higher and an average VR activity 2.5 times higher. The authors also found 4-ethylphenol concentrations on the order of 9.47 mg/L in fermentation conditions with cell recycle, much higher than the concentrations found in beverages (wines) contaminated by D. bruxellensis. Phenolic compounds are also known to negatively affect yeast metabolism during alcoholic fermentation, impairing cell viability, increasing fermentation time and reducing sugar consumption (Polakovic et al. 1992; Colombi et al. 2017). In this context, the presence of such compounds during the ethanol production process can lead to the inhibition of S. cerevisiae growth and fermentation because it directly affects the integrity of the cell membrane, thus interfering with its ability to serve as a selective barrier and enzymatic matrix (Heipieper et al. 1994). Furthermore, the presence of more than one microbial inhibitor in the medium can result in a synergistic or antagonistic effect depending on the interaction of the inhibitors present (Palmqvist et  al. 1999; Klinke et  al. 2004). Regarding the interaction between S. cerevisiae and volatile phenols in the ethanol production process, a study conducted by Covre et al. (2019) found that 4-ethylphenol affected the growth rate of S. cerevisiae under conditions prevalent in industrial ethanol production, such as low pH and high ethanol concentration. During the fermentative process, the addition of 4-ethylphenol resulted in significant effect on S. cerevisiae cell number, pH of the medium and ethanol production, with decrease in fermentative efficiency from 86% to 65–74%. Cibrario et al. (2020) verified that the ability of D. bruxellensis to use various types of carbohydrate (glucose, D-mannose, D-fructose, D-galactose, trehalose, cellobiose and sucrose) or to produce volatile phenols is common to a high number of strains studied; however, the tolerance to low pH or high ethanol content varied among the strains. The authors did not observe a clear link between these phenotypes of tolerance and the genetic groups examined. The metabolization of a variety of carbon and nitrogen sources was also assumed to play a role in the colonization of already fermented musts that present low-nutrient contents (Harrouard et al. 2022). The interactions of D. bruxellensis with lactic bacteria in fermentative processes have been reported in several situations. An industrial process of fuel ethanol production dominated by D. bruxellensis and Lactobacillus vini showed no decrease in ethanol productivity, and the process remained stable (Passoth et  al. 2007). The addition of this bacterium to S. cerevisiae culture had no effect on yeast; however, it stimulated the fermentative activity of D. bruxellensis (Souza et al. 2012). L. vini induced the flocculation of S. cerevisiae and D. bruxellensis cells, with more intensity when in the presence of S. cerevisiae. With D. bruxellensis, an arrangement between the small flakes of the bacteria and the elongated cells of the yeast occurred, allowing better nutrient uptake and protection against stressful conditions (Tiukova

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3  Native Yeasts and Their Role in Ethanol Fermentation

et  al. 2014). However, with Lactobacillus fermentum, there was a stimulation of D. bruxellensis growth, which in turn affected the cell viability of S. cerevisiae with consequent impairment of ethanol yield (Bassi et al. 2018). The nature of the interactions between D. bruxellensis – lactic acid bacteria – S. cerevisiae still remains unknown, stimulating studies that can determine their role during the fermentative process. The effect of D. bruxellensis yeast during ethanol fermentation should not be evaluated only considering its lower growth rate compared to S. cerevisiae. Depending on the fermentation system, for example, in continuous system, the contaminating yeast is more efficient in utilizing the substrate and especially more tolerant to the inhibitors present in the medium. These factors become more important for competitiveness than high potential growth rates. In addition, one should consider the versatility regarding the assimilation and fermentation of industrially important monosaccharides and disaccharides demonstrated by D. bruxellensis and the fact that the glucose catabolic repression system is less regulated in this yeast than in S. cerevisiae, which would allow an efficient co-assimilation of sugars in complex industrial media (Silva et al. 2019). The yeast D. bruxellensis is undoubtedly a microorganism with multiple facets that could be used in a variety of biotechnological processes (Pita et al. 2019). The main characteristics of D. bruxellensis yeast and their implications for ethanolic fermentation are summarized in Fig. 3.2.

Fig. 3.2  Main characteristics of D. bruxellensis yeast and their implications for ethanol fermentation. (Source: From the author)

3.3  Saccharomyces cerevisiae Yeasts

51

3.3  Saccharomyces cerevisiae Yeasts S. cerevisiae yeasts frequently associated with problems in the fermentation process present very particular cell and colony phenotypes that are easy to recognize. It is a yeast biotype with cells arranged in clusters, also called pseudohyphae, and an opaque colony with a rough surface, so they are commonly referred to as “rough yeasts” (Fig. 3.3). Cell clusters are formed due to the failure of the young bud to separate from the parent cell, remaining attached to its parent cell after mitosis (Fig.  3.4a, b). The process that allows the cell aggregation originating the

Fig. 3.3  Colony and cell morphology of the rough yeast (R) compared to the non-rough yeast (NR). The plate contains WLN medium inoculated with yeast sample from an ethanol production unit. The photos of the cells were taken under microscope at 400× magnification. (Source: From the author)

Fig. 3.4  Schematic diagram of the growth of non-rough (a) and rough (b) yeast. In (c), sedimentation assay with non-rough yeast (NR) and with rough yeast (R), with the arrow indicating the sedimented cells at the bottom of the tube. (Source: From the author)

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3  Native Yeasts and Their Role in Ethanol Fermentation

pseudohyphae should not be confused with flocculation, because in this case the cells can be separated by mechanical or chemical means, while the cells of rough yeasts do not separate by these means (Soares 2010). Although the term pseudohyphae is used to designate cell groupings, it is necessary to distinguish it from the pseudohyphae growth originated under nutritional stress situations. In this condition, and also in the presence of higher alcohols, S. cerevisiae yeasts present cell elongation and agglomeration, constituting the phenomenon called filamentation. This is a reversible process, as the cells start to present unicellular morphology under standard culture conditions, without the stresses that induce filamentation (Ceccato-Antonini 2008). The rough yeasts, however, are phenotypically stable (Ratcliff et al. 2012). Rough yeasts are also referred to as snowflake yeasts. As the chains continue to increase by cell division, the tension between the cells increases until it exceeds the tensile strength existing in the cell-cell connection, resulting in the release of multicellular propagules (Ratcliff et al. 2015). Yeasts with these characteristics – rough colonies and cells in cell clusters – are able to dominate the fermentation process, replacing the starter yeast. They present a high rate of cell sedimentation (Fig.  3.4c), causing similar problems to those observed with flocculent yeasts. Ceccato-Antonini and Parazzi (2000) showed that these yeasts can also remain on the surface of the vats (flotation), forming a kind of thick and sticky foam (scum), which results in the spillage of the must from the vats and consequently loss of sugar and ethanol. Ceccato-Antonini and Parazzi (1996) verified a proportion of 1:1 between rough and non-rough yeasts in the yeast cream and wine, causing a decrease of 10% in the fermentation yield and 18% in the alcohol production in a distillery in Jaú, São Paulo State, Brazil. The ethanol yield (efficiency) returned to approximately 89% when the yeast mass was replaced by a new starter yeast. A study conducted during three consecutive harvests on the characteristics of 300 wild yeasts isolated from 46 distilleries showed that 57% of the colonies had a smooth border and 43% had a rough border. All the yeasts presenting colonies with rough border showed fermentation problems such as excessive foaming, sedimentation and/or sugar leftovers in the wine. The cell clusters in the rough-edged yeasts reduce the contact of the cells with the substrate, causing increased fermentation time and higher residual sugar content. Among the yeasts from smooth-edged colonies, 65% presented at least one of the problems mentioned above (Basso et  al. 2008). These results show that this yeast biotype is very frequent in the fermentative environment. A comparative study of the fermentative capacity of yeast from rough and non-­ rough S. cerevisiae colonies showed that the rough ones have slower fermentation in batch system with a single cycle. Using cell recycle, a fermentation efficiency of 60% was obtained with the rough colony (Reis et al. 2013). Although this contaminant yeast showed lower invertase activity than the industrial yeast S. cerevisiae PE-2, no residual sucrose was detected after fermentation with the coculture of strain PE-2 and rough yeast, which can be credited to the enzymatic activity of the industrial yeast. Thus, the observed difference in invertase activity should not be the

3.3  Saccharomyces cerevisiae Yeasts

53

cause of the slow fermentation rate presented in the fermentations contaminated with rough yeast. In this contamination situation, the main issues related to the slow and incomplete fermentation should be slower sugar consumption rate, acetate production and lower preference for fructose. The lower sugar consumption rate presented by the rough yeast could be attributed either to the cellular arrangement that hinders nutrient uptake or to physiological differences regarding hexose transporters; however, these issues have not yet been clarified. The presence of L. fermentum, one of the main bacterial contaminants in ethanol fermentation, did not enhance the effect of rough yeast on the fermentation process when in coculture, as it was expected to happen due to the fact that the bacterium in question is able to induce yeast flocculation, which would bring greater loss to the fermentation (Reis et al. 2018). Rough S. cerevisiae yeasts showed higher resistance to stressful conditions such as high sugar and ethanol concentration than non-rough yeasts (Reis et al. 2017). Clustering of cells protects them from stresses; however, it would be disadvantageous for rough yeasts compared to non-rough yeasts under non-stressful conditions because rough yeasts have slower growth under standard conditions. Thus, the yeast either grows faster and dies due to stress (unicellular phenotype) or grows slower but resists to stress (multicellular phenotype). Studies have shown that environmental stress plays a key role in the emergence and maintenance of multicellularity, as both the physical protection to cells provided by clusters and physiological changes appear to matter in stress tolerance (Smukalla et al. 2008; Kuzdzal-Fick et al. 2019). Conjaerts and Willaert (2017) obtained an S. cerevisiae strain with snowflake characteristics after adaptive evolution from a strain that does not form cell clusters using a minifermenter after 14 days of continuous cultivation. The cell-cell interactions in the clusters did not result from adhesion by flocculins, but arose probably by mutation in genes involved in the mother-daughter separation process. Kuzdzal-­ Fick et al. (2019) took the reverse pathway, i.e. they obtained a unicellular strain (without cell clusters) from directed evolution of a snowflake strain, and found that the unicellular strain differed from snowflake strain mainly due to mutations in the AMN1 (Antagonist of Mitotic exit Network) gene, a gene related to the postmitotic cell separation process in yeast. Fang et  al. (2018) identified a novel 11-residue domain by which Amn1 binds to the transcription factor Ace2, a major transcription factor related to genes responsible for mitotic cell separation. Amn1 induces proteolysis of Ace2 through the ubiquitin-proteasome system that in turn downregulates downstream Ace2 target genes involved in hydrolysis of the primary septum, leading to inhibition of cell separation and the appearance of cell clusters in haploid cells. The results indicated that the AMN1 gene inhibits cell separation after mitosis, inducing cell cluster formation. Attempts to show genomic differences between the two biotypes were ineffective. Molecular techniques, such as microsatellites, mitochondrial DNA restriction analysis (RFLP-mtDNA), karyotyping profiling (PFGE) and single-nucleotide polymorphism (SNPs) in specific genes linked to pseudohyphal growth and flocculation, showed no differences between the two biotypes that could reveal

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intraspecific molecular markers (Jubany et  al. 2008; Lopes 2010; Antonangelo 2012; Reis et al. 2017). These results suggest that the differences between biotypes can be attributed more to gene expression than to differences in DNA sequences. Ratcliff et al. (2015) found that 1035 genes were differentially expressed when comparing a single-cell strain of S. cerevisiae and a rough yeast strain obtained by adaptive evolution. Among ten major downregulated genes, seven genes are involved with the degradation of the primary septum at the bud base and are regulated by the transcription factor Ace2. Non-synonymous mutations in the ACE2 gene were identified in the rough strains on both alleles of this gene, i.e. the rough yeast had both mutated copies of this gene. The rough yeast therefore became homozygous for this gene through gene conversion, a common occurrence in yeast. On the other hand, a single functional copy of the ACE2 gene results in the unicellular phenotype, so the unicellular strain is heterozygous for this mutation in ACE2. Loss of heterozygosity in the ACE2 gene (caused by a phase-shift mutation) was responsible for the rough colony phenotype in the strains studied by Rodrigues-­ Prause et  al. (2018), using spontaneous derivatives of the S. cerevisiae strain JAY270/PE-2. The rough phenotype occurred by mitotic recombination associated with loss of heterozygosity, presenting two mutated copies of the ACE2 gene. The rough strain presented colonies with rough surfaces, irregular borders and cell sedimentation similar to flocculation in liquid medium, characteristics that are not found in the selected yeast strain PE-2. Speculations about the origin and evolution of multicellularity use the rough yeasts (snowflakes) as a model. By means of directed evolution, from a unicellular S. cerevisiae yeast, it was possible to obtain rough strains that exhibited cell-cell bonding and that presented a high sedimentation rate. Multicellularity results in cell differentiation; however, it must be considered that the cell, in the single-cell condition, has “sacrificed” direct reproduction for the benefit of the cluster and thus the benefit of division of labour must compensate for the loss of reproduction. Experiments have shown that programmed cell death, also called apoptosis, is a mechanism by which rough yeast increase the number of propagules (for reproduction) at the expense of propagule size. Apoptotic cells have weak connections, allowing smaller cell clusters to separate from larger ones, allowing the number of propagules to increase. The production of smaller propagules results in increased growth rate, as these grow faster than larger propagules (Ratcliff et al. 2012; Ratcliff and Travisano 2014). Pentz et al. (2016) proved that larger cell clusters contained a greater amount of senescent cells and were more apoptotic, showing that high apoptosis is a characteristic strictly related to cell cluster size. This study refuted the hypothesis that apoptosis is not an adaptive trait and that it is caused by the accumulation of toxic substances inside large cell clusters. The formation of large cell clusters depends on geometric shaping, since modifying the cell shape and budding angle turns out to be more efficient than increasing the strength of cell connections to hold cells together, resulting in decreased internal stress (Jacobeen et al. 2018).

3.4  Methods for Controlling the Growth of Native Yeasts

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3.4 Methods for Controlling the Growth of Native Yeasts The control of the contamination by native yeasts in the fermentation process is not easy to achieve by means of growth-inhibiting substances such as antibiotics, for example, since the process yeast may also be affected. In this sense, it is essential to know the contaminant yeast in its physiological, genetic and resistance aspects to stresses, in order to find differences in relation to the S. cerevisiae inoculated in the process (the starter yeast) and thus be possible to manage the fermentative process to minimize the effect of contamination. Regarding the yeast D. bruxellensis, there are a number of physical and chemical agents used to control its growth, especially because this yeast is a contaminant of the wine beverage, such as chitosan, sulphur dioxide, dimethyl dicarbonate, electric pulse, ozone, ultrasound and filtration (Zuehlke et al. 2013). None of these agents has been tested in industrial scale to control the growth of D. bruxellensis in the fermentative process for biofuel production, but there are studies in laboratory scale indicating the feasibility of using some of them. Potassium metabisulphite, a source of sulphur dioxide, was evaluated for its biocidal action against strains of D. bruxellensis and its effect on ethanolic fermentation. In the range of 200–400  mg/L of potassium metabisulphite, the growth of D. bruxellensis was controlled. When added to the fermentation medium at a concentration of 250 mg/L, a fungistatic effect was observed for D. bruxellensis, without affecting S. cerevisiae, but there was a decrease in fermentation efficiency. A possible explanation for the effect on fermentation lies in the fact that sulphur dioxide is a highly reactive molecule, which can bind to enzymes of the glycolytic cycle or even be inactivated by acetaldehyde, which would be converted into ethanol. In both situations, the fermentation yield is impaired (Bassi et al. 2015). Chitosan, a biopolymer obtained through the deacetylation of chitin, is a potential antimicrobial for the fermentative process, especially due to its action against D. bruxellensis in the wine industry. Preliminary studies have shown that chitosan has action against this yeast contaminant under laboratory fermentation conditions (Tanganini 2019). Hydroalcoholic extracts of propolis, constituted of a mixture of pollen, wax and plant resin collected by bees, showed selectivity in its antimicrobial action against S. cerevisiae and D. bruxellensis, demonstrating greater efficacy against the contaminating yeast (Fernández et  al. 2019). Propolis also has antibacterial action, which qualifies it as a potential biocide to be used in the context of ethanolic fermentation. Bassi et al. (2013) verified that the use of a cell treatment combining addition of ethanol (11% or 13%) to the acid solution (pH 2.0) resulted in about three times higher decrease in cell viability of D. bruxellensis compared to S. cerevisiae. When applied to a cell recycle fermentation system contaminated with D. bruxellensis, the acid (pH 2.0) + ethanol (13% v/v) treatment applied to the cells between fermentative cycles was able to decrease and maintain the D. bruxellensis population under control, while S. cerevisiae dominated the fermentation over six fermentative cycles, although a slower fermentation was observed.

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For the S. cerevisiae rough yeasts, decreasing the pH of the acid treatment from 2.0 to 1.5 had an effect on the growth of these yeasts, without affecting the growth of the starter strain (Reis et al. 2013). However, using more sulfuric acid is not an advantageous strategy due to the cost and risks in handling this substance. Lourencetti et  al. (2018) investigated the presence of coding and non-coding RNAs, especially miRNAs (XenomiRs) from sugarcane that could interfere with the growth of the contaminant yeast C. tropicalis during the fermentative process. XenomiRs are biomolecules that can act on transcriptional and post-transcriptional processes in order to inhibit or potentiate gene expression. Six C. tropicalis target genes were identified that interacted with the four miRNAs extracted from sugarcane, and these genes were also present with high identity percentage in 36 other yeast species, many of them contaminants of ethanol fermentation. It is also noteworthy that the four miRNAs identified showed no interaction with S. cerevisiae in in silico study, which enables them to be used as antifungal biomolecules to control contaminations in the fermentation process for bioethanol production. S. cerevisiae yeasts can secrete antimicrobial peptides called AMPs, which are derived from the enzyme glyceraldehyde-3-phosphate dehydrogenase of the glycolytic cycle. Although AMPs, also called saccharomycin, are active against D. bruxellensis, the levels secreted by S. cerevisiae were insufficient to cause the death of the contaminating yeast. An S. cerevisiae strain genetically modified for overproduction of AMPs was constructed, such that cell viability of D. bruxellensis was completely lost within 96  h in cocultures with the transformed S. cerevisiae strain, regardless of initial cell densities (Branco et al. 2019). The killer system in yeast has also been evaluated as a method to control contaminations by native yeasts in the fermentation process. Killer yeasts secrete proteins that inhibit the growth of other yeasts called sensitive yeasts. Since the killer character was first identified in S. cerevisiae in the 1960s, many applications have been proposed such as in the production of fermented beverages, food technology, biological control in agriculture, medicine, etc., including the introduction of killer character in S. cerevisiae yeasts of industrial interest (Bajaj and Sharma 2010). For ethanol fuel production, studies have shown that the killer characteristic is not a factor that guarantees the permanence of yeast in the fermentation vat, mainly due to temperature and pH variations that are not favourable to killer activity and the fact that contaminating yeasts may have a neutral phenotype, i.e. they do not produce killer proteins and are not sensitive to killer proteins produced by other yeasts (Amorim et  al. 1998; Ceccato-Antonini et  al. 1999). Although killer toxins produced by yeasts such as Kluyveromyces wickerhamii, Pichia anomala, Pichia membranifaciens and Candida pyralidae have an effect on D. bruxellensis, they are only efficient when the contamination levels by this yeast are low, below 104 cells/mL (Comitini and Ciani 2011; Mehlomakulu et al. 2017). In fact, to date, there is no product that can be used to prevent or reduce contamination by native yeasts at industrial level in the fermentative process for ethanol production. There is a need to test substances that have been used in other types of fermentations to control common contaminants, applying to the particularities of the ethanol fermentation process. In this context, deepening the knowledge about

References

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the physiology and response to the stresses of the contaminant yeasts in comparison with the S. cerevisiae yeast is of fundamental importance to find weaknesses in the contaminant yeast that are inexistent or minimal in the yeast utilized as starters of the fermentation and thus be able to propose a management of the process that avoids losses in the fermentation yield.

References Abbott, D.A., Hynes, S.H., Ingledew, W.M.: Growth rates of Dekkera/Brettanomyces yeasts hinder their ability to compete with Saccharomyces cerevisiae in batch corn mash fermentations. Appl. Microbiol. Biotechnol. 66(6), 641–647 (2005) Amorim, H.V., Basso, L.C., Lopes, M.L., Fonseca, A.J.: The relative importance of killer activity for the industrial fuel ethanol fermentation process. Yeast. 47, 9 (1998) Antonangelo, A.T.B.F.: Genotipagem de leveduras presentes no processo industrial de produção de álcool combustível e estudo do polimorfismo de genes envolvidos no processo fermentativo em Saccharomyces cerevisiae. Thesis, Universidade Estadual Paulista Julio de Mesquita Filho (2012) Araújo, P.R.L., Basílio, A.C.M., Simões, D.A., Morais Jr, M.A., Morais, J.O.F.: Informações sobre algumas leveduras contaminantes da fermentação alcoólica industrial isoladas no Nordeste do Brasil. Anais do XV Simpósio Nacional de Bioprocessos, pp. 1–7 (2005) Avramova, M., Cibrario, A., Peltier, E., Coton, M., Coton, E., Schacherer, J., Spano, G., Capozzi, V., Blaiotta, G., Salin, F., Dols-Lafargue, M., Grbin, P., Curtin, C., Albertin, W., Masneuf-­ Pomarede, I.: Brettanomyces bruxellensis population survey reveals a diploid-triploid complex structured according to substrate of isolation and geographical distribution. Sci. Rep. 8(1), 4136 (2018) Bajaj, B.K., Sharma, S.: Construction of killer industrial yeast Saccharomyces cerevisiae HAU-1 and its fermentation performance. Braz. J. Microbiol. 41(2), 477–485 (2010) Barnett, J.A., Payne, R.W., Yarrow, D.: Yeasts: Characteristics and Identification. Cambridge University Press, Cambridge (2000). 1139p Basílio, A.C.M., Araújo, P.R.L., Morais, J.O.F., De Silva, E.A., Morais Jr., M.A., Simões, D.A.: Detection and identification of wild yeast contaminants of the industrial fuel ethanol fermentation process. Curr. Microbiol. 56(4), 322–326 (2008) Bassi, A.P.G., Silva, J.G., Reis, V.R., Ceccato-Antonini, S.R.: Single and combined effects of low pH and high concentrations of ethanol on the growth of Dekkera/Brettanomyces and Saccharomyces cerevisiae strains from the fermentation for fuel alcohol production. World J. Microbiol. Biotechnol. 29(9), 1661–1676 (2013) Bassi, A.P.G., Paraluppi, A.L., Reis, V.R., Ceccato-Antonini, S.R.: Potassium metabisulphite as a potential biocide against Dekkera bruxellensis in fuel ethanol fermentations. Lett. Appl. Microbiol. 60(3), 248–258 (2015) Bassi, A.P.G., Meneguello, L., Paraluppi, A.L., Sanches, B.C.P., Ceccato-Antonini, S.R.: Interaction of Saccharomyces cerevisiae – Lactobacillus fermentum – Dekkera bruxellensis and feedstock on fuel ethanol fermentation. Antonie Van Leeuwenhoek. 111(9), 1661–1672 (2018) Basso, L.C., Amorim, H.V., Oliveira, A.J., Lopes, M.L.: Yeast selection for fuel ethanol production in Brazil. FEMS Yeast Res. 8(7), 1155–1163 (2008) Blomqvist, J.: Dekkera bruxellensis: a competitive yeast for ethanol production from conventional and non-conventional substrates. PhD thesis, Swedish University of Agricultural Sciences (2011) Blomqvist, J., Passoth, V.: Dekkera bruxellensis-spoilage yeast with biotechnological potential, and a model for yeast evolution, physiology and competitiveness. FEMS Yeast Res. 15(4), 1–9 (2015)

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Blomqvist, J., Eberhard, T., Schnurder, J., Passoth, V.: Fermentations characteristics of Dekkera bruxellensis strains. Appl. Microbiol. Biotechnol. 87(4), 1487–1497 (2010) Branco, P., Sabir, F., Diniz, M., Carvalho, L., Albergaria, H., Prista, C.: Biocontrol of Brettanomyces/ Dekkera bruxellensis in alcoholic fermentations using saccharomycin-­ overproducing Saccharomyces cerevisiae strains. Appl. Microbiol. Biotechnol. 103, 3073–3083 (2019) Carlson, M., Botstein, D.: Two differentially regulated mRNAs with different 5′ends encode secreted with intracellular forms of yeast invertase. Cell. 28(1), 145–154 (1982) Castro, M.M.S.: Leveduras contaminantes do processo de fermentação alcoólica: diversidade taxonômica e metabólica. Dissertation, Universidade Estadual de Campinas (1995) Ceccato-Antonini, S.R.: Biotechnological implications of filamentation in Saccharomyces cerevisiae. Biotechnol. Lett. 30(7), 1151–1161 (2008) Ceccato-Antonini, S.R., Parazzi, C.: Isolamento de levedura selvagem floculante e efeitos da contaminação em processo de fermentação etanólica contínua. Anais do VI Congresso Nacional da STAB, pp. 23–29 (1996) Ceccato-Antonini, S.R., Parazzi, C.: Monitoramento microbiológico da fermentação etanólica: uma experiência. Jornal Cana, 25–26 (2000) Ceccato-Antonini, S.R., Silva, D.F.: Eficiência de meios diferenciais no isolamento de cepas de leveduras de processos industriais de fermentação alcoólica. STAB. 18(4), 40–46 (2000) Ceccato-Antonini, S.R., Cremonini, L.C.M., Regenfuss, C.: Killer character of yeasts isolated from ethanolic fermentations. Sci. Agric. 56(3), 631–635 (1999) Chatonnet, P., Dubordieu, D., Boidron, J.N.: The origin of ethylphenols in wines. J.  Sci. Food Agric. 60(2), 165–178 (1992) Cibrario, A., Miot-Sertier, C., Paulin, M., Bullier, B., Riquier, L., Perello, M.C., Revel, G., Albertin, W., Masneuf-Pomarède, I., Ballestra, P., Dols-Lafargue, M.: Brettanomyces bruxellensis phenotypic diversity, tolerance to wine stress and wine spoilage ability. Food Microbiol. 87, 103379 (2020) Colombi, B.L., Ortiz, M.A., Zanoni, P.R.S., Magalhães, W.L.E., Tavares, L.B.B.: Efeito de compostos inibidores na bioconversão de glicose em etanol por levedura Saccharomyces cerevisiae. Engevista. 19(2), 339–352 (2017) Comitini, F., Ciani, M.: Non-Saccharomyces wine yeasts have a promising role in biotechnological approaches to winemaking. Ann. Microbiol. 61(1), 25–32 (2011) Conjaerts, A., Willaert, R.G.: Gravity-driven adaptive evolution of an industrial brewer’s yeast strain towards a snowflake phenotype in a 3d-printed mini tower fermentor. Fermentation. 3, 4 (2017) Covre, E.A., Silva, L.F.L., Bastos, R.G., Ceccato-Antonini, S.R.: Interaction of 4-ethylphenol, pH, sucrose and ethanol on the growth and fermentation capacity of the industrial strain of Saccharomyces cerevisiae PE-2. World J. Microbiol. Biotechnol. 35(136), 4–11 (2019) Duarte-Almeida, M.J., Novoa, A.V., Linares, A.F., Lajolo, F.M., Genovese, M.I.: Antioxidant activity of phenolics compounds from sugar cane (Saccharum officinarum L.) juice. Plant Foods Hum. Nutr. 61(4), 87–192 (2006) Edlin, D.A.N., Narbad, A., Kickinson, J.R., Lloyd, D.: The biotransformation of simple phenolic compounds by Brettanomyces anomalus. FEMS Microbiol. Lett. 125(2-3), 311–316 (1995) Fang, O., Hu, X., Wang, L., Jiang, N., Yang, J., Li, B., Luo, Z.: Amn1 governs post-mitotic cell separation in Saccharomyces cerevisiae. PLoS Genet. 14(10), e1007691 (2018) Fernández, L.A., Cibanal, I.L., Paraluppi, A.L., Freitas, C., Gallez, L.M., Ceccato-Antonini, S.R.: Propolis as a potential alternative for the control of Dekkera bruxellensis in bioethanol fermentation. Semina Ciências Agrárias. 40(5), 2071–2078 (2019) Fugelsang, K.C., Edward, C.G.: Wine Microbiology: Practical Applications and Procedures. The Chapman & Hall Enology Library, New York (1997). 393 p Galafassi, S., Capusoni, C., Moktaduzzaman, M., Compagno, C.: Utilization of nitrate abolishes the “Custers effect” in Dekkera bruxellensis and determines a different pattern of fermentation products. J. Ind. Microbiol. Biotechnol. 40(2-3), 297–303 (2013)

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Parente, D.C., Cajueiro, D.B., Peña-Moreno, I.C., Leite, F.C.B., Pita, W.B., Morais Jr., M.A.: On the catabolism of amino acids in the yeast Dekkera bruxellensis and the implications for industrial fermentation processes. Yeast. 35, 299–309 (2018) Passoth, V., Blomqvist, J., Schnurer, J.: Dekkera bruxellensis and Lactobacillus vini form a stable ethanol-producing consortium in a commercial alcohol production process. Appl. Environ. Microbiol. 73(13), 4354–4356 (2007) Peña-Moreno, I.C., Parente, D.C., Silva, J.M., Mendonça, A.A., Rojas, L.A.V., Morais Jr., M.A., Pita, W.B.: Nitrate boosts anaerobic ethanol production in an acetate-dependent manner in the yeast Dekkera bruxellensis. J. Ind. Microbiol. Biotechnol. 46, 209–220 (2019) Pentz, J.T., Taylor, B.P., Ratcliff, W.C.: Apoptosis in snowflake yeast: novel trait, or side effect of toxic waste? J. R. Soc. Interface. 13, 20160121 (2016) Pereira, L.F., Bassi, A.P.G., Avansini, S.H., Neto, A.G., Brasileiro, B.T., Ceccato-Antonini, S.R., Morais Jr., M.A.: The physiological characteristics of the yeast Dekkera bruxellensis in fully fermentative conditions with cell recycling and in mixed cultures with Saccharomyces cerevisiae. Antonie Van Leeuwenhoek. 101(3), 529–539 (2012) Pereira, L.F., Lucatti, E., Basso, L.C., Morais Jr., M.A.: The fermentations of sugarcane molasses by Dekkera bruxellensis and the mobilization of reserve carbohydrates. Antonie Van Leeuwenhoek. 105(3), 481–489 (2014) Phowchinda, O., Delia-Dupuy, M.L., Strehaiano, P.: Effects of acetic acid on growth and fermentative activity of Saccharomyces cerevisiae. Biotechnol. Lett. 17, 327–242 (1995) Pita, W.B., Leite, F.C., Souza-Liberal, A.T., Simões, D.A., Morais Jr., M.A.: The ability to use nitrate confers advantage to Dekkera bruxellensis over S. cerevisiae and can explain its adaptation to industrial fermentation processes. Antonie Van Leeuwenhoek. 100(1), 99–107 (2011) Pita, W.B., Tiukova, I., Leite, F.C., Passoth, V., Simões, D.A., Morais Jr., M.A.: The influence of nitrate on the physiology of the yeast Dekkera bruxellensis grown under oxygen limitation. Yeast. 30(3), 111–117 (2013) Pita, W.B., Teles, G.H., Peña-Moreno, I.C., Silva, J.M., Ribeiro, K.C., Morais Jr., M.A.: The biotechnological potential of the yeast Dekkera bruxellensis. World J. Microbiol. Biotechnol. 35, 103 (2019) Polakovic, M., Handriková, G., Kosik, M.: Inhibitory effects of some phenolic compounds on enzymatic hydrolysis of sucrose. Biomass Bioenergy. 3(5), 369–371 (1992) Procházka, E., Poláková, S., Piskur, J., Sulo, P.: Mitochondrial genome from the facultative anaerobe and petite positive yeast Dekkera bruxellensis contains the NADH dehydrogenase subunit genes. FEMS Yeast Res. 10(5), 545–557 (2010) Pronk, J.T., Steensma, H.Y., van, Dijken, J.P.: Pyruvate metabolism in Saccharomyces cerevisiae. Yeast. 12(16), 1607–1633 (1996) Ratcliff, W.C., Travisano, M.: Experimental evolution of multicellular complexity in Saccharomyces cerevisiae. Bioscience. 64(5), 383–393 (2014) Ratcliff, W.C., Denison, R.F., Borello, M., Travisano, M.: Experimental evolution of multicellularity. Proc. Natl. Acad. U. S. A. 109(5), 1595–1600 (2012) Ratcliff, W.C., Fankhauser, J.D., Rogers, D.W., Greig, D., Travisano, M.: Origins of multicellular evolvability in snowflake yeast. Nat. Commun. 6, 6102 (2015) Reis, V.R., Bassi, A.P.G., Silva, J.C.G., Ceccato-Antonini, S.R.: Characteristics of Saccharomyces cerevisiae yeasts exhibiting rough colonies and pseudohyphal morphology with respect to alcoholic fermentation. Braz. J. Microbiol. 44, 1121–1131 (2013) Reis, V.R., Antonangelo, A.T.B.F., Bassi, A.P.G., Colombi, D., Ceccato-Antonini, S.R.: Bioethanol strains of Saccharomyces cerevisiae characterised by microsatellite and stress resistance. Braz. J. Microbiol. 48, 268–274 (2017) Reis, V.R., Bassi, A.P.G., Cerri, B.C., Almeida, A.R., Carvalho, I.G.B., Bastos, R.G., Ceccato-­ Antonini, S.R.: Effects of feedstock and co-culture of Lactobacillus fermentum and wild Saccharomyces cerevisiae strain during fuel ethanol fermentation by the industrial yeast strain PE-2. AMB Express. 8(23), 2–11 (2018)

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Chapter 4

Bacteria in Ethanol Fermentation

4.1 Introduction The large amount of nutrients available in fermenting musts and the fact that the fermentation process does not take place aseptically are conducive to bacterial contamination, which is responsible for significant losses in fermentation efficiency. The losses caused by contamination in alcoholic fermentation start in the field with the raw material. The bacteria come from the sugarcane, from the field or even from poorly cleaned equipment and utensils used in the fermentation process. Contamination may come not only from the cane but also from sources of contamination of the conveyor belts, mills, pipes and other equipment. Not all microorganisms are able to grow in the sugarcane juice, although it is a favourable medium. The quantity and types of microorganisms present will depend on the conditions of each stage of the fermentation process. Excessively contaminated sugarcane, besides the problems of efficiency in the treatment and cleaning of the juice, carries a large number of bacteria and products of their metabolism into the fermentative process. The contamination is considered an important factor due to the loss of sugars and brings harmful effects on the fermentative performance, such as low ethanol production, flocculation and low viability of yeast cells. Bacterial infections can reach 108–109 cells/mL and are often characterized by the accumulation of by-products such as lactic acid and acetic acid. These organic acids can inhibit the growth of starter yeasts (Bayrock and Ingledew 2004; Burtner et  al. 2009) causing a drop in yield and increased production costs by requiring downtime for cleaning and disinfection of the facilities (Narendranath et al. 1997; Bischoff et al. 2009; Beckner et al. 2011). For industrial fermentations, bacterial contaminations above 1.0 × 108 CFU/mL result in a decrease in the fermentation yield, making centrifugation operations more difficult due to the cell flocculation, and there is also an increase in the © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_4

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consumption of sulfuric acid and antibiotics (Cherubin 2003; Amorim et al. 2009; Basso et al. 2014). It is estimated that a contamination as high as 108 CFU/mL is capable of decreasing the production of 10,000–30,000 litres of ethanol per day in a distillery with a production capacity of 1,000,000  litres per day (Amorim et al. 2011). Although a diversity of bacterial genera and species is found in the fermentation process, the group of lactic acid bacteria is the most expressive in terms of abundance and effects caused, especially the genus Lactobacillus. The mechanisms by which bacteria affect fermentation are multivariate, involving the production of substances toxic to yeast, competition for nutrients, induction of flocculation and reprogramming of yeast genes, resulting in effects on fermentation parameters. It is noteworthy that successive fermentative cycles and non-aseptic conditions contribute to the establishment of bacterial communities that interact with yeast in different ways (Brexó and Sant’Ana 2017).

4.2 Diversity of Bacteria in the Fermentation Process The nature of the industrial process, the large volumes of substrate processed and the non-aseptic fermentation conditions contribute to the occurrence of bacterial contaminations. The bacteria that inhabit the fermentative environment originate mainly from sugarcane. A study addressing the composition of fungal and bacterial communities associated with roots, stems and leaves of sugarcane plants showed that the distribution of bacteria is more related to the plant organ. Roots showed 89 families of bacteria, 19 of which represented 44% of the total relative abundance (Souza et al. 2016). The study of bacterial diversity in industrial processes encounters limitations depending on the technique used to access diversity. Culture-independent methods have shown that the contaminating bacterial community is more diverse than that described in studies based on isolations from culture media plating (Rosales 1989; Gallo 1990; Lucena et al. 2010). Bacteria belonging to the phyla Actinobacteria, Aquificae, Bacteroidetes, Cyanobacteria, Deinococcus-Thermus, Firmicutes and Proteobacteria have been reported in works whose evaluation was performed by means of the 16S ribosomal DNA gene sequences (Costa et  al. 2015; Bonatelli et al. 2017). Bacteria of the genera Bacillus, Lactobacillus, Acetobacter, Clostridium and Leuconostoc are commonly found in the sugarcane juice. The genus Anaeosporobacter was first reported in the fermentative environment by Bonatelli et  al. (2017). Leuconostoc stands out as it is common in both sugar and ethanol production, causing problems due to the production of exopolysaccharides (gums). There are other gum-producing genera such as Klebsiella and Acetobacter, usually found in the conduction of juice in the mill (Caetano and Madaleno 2011). Although bacterial diversity is high in the fermentative environment, studies have shown that more than 98% of bacteria are Gram-positive, with a predominance

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of lactic acid bacteria of the genus Lactobacillus (Gallo 1990; Lucena et al. 2010; Caetano and Madaleno 2011; Bonatelli et al. 2017). The number of lactic acid bacteria ranged between 6.0 × 105 and 8.9 × 108 CFU/mL in the fermentation tanks of four Northeast distilleries in Brazil in the years 2007 and 2008, while the raw sugarcane juice showed between 7.4 × 105 and 6.0 × 108 CFU/mL (Lucena et al. 2010). The bacterial community in an industrial ethanol-producing unit was accessed by 16S rRNA gene sequencing from samples collected in various production steps. The species richness increased between decanter and must steps, with lower diversity at the fermentation step, with a predominance of Lactobacillus. Temperature was the main selection factor (Queiroz et al. 2020). Lactic acid bacteria are Gram-positive, facultative anaerobic, catalase-negative, without spore formation, morphology of rods and cocci, and according to the glucose fermentation mode can be classified into homofermentative and heterofermentative (Kandler 1983). Homofermentative species produce lactic acid as the main or only product of carbohydrate metabolism, while heterofermentative species produce not only lactic acid but also ethanol, acetic acid and CO2 (Fig. 4.1). Lactic acid bacteria include the following genera of the phylum Firmicutes, order Lactobacillales: Lactobacillus, Leuconostoc, Pediococcus, Streptococcus, Carnobacterium, Lactococcus, Enterococcus, Alloiococcus, Vagococcus, Oenococcus, Tetragenococcus, Symbiobacterium, Aerococcus and Weissella; the first four genera are the major ones among others (Novik et al. 2017). Although lactic acid bacteria have historically been regarded as facultative anaerobes and unable to synthesize respiratory chain components such as cytochromes

Fig. 4.1  Metabolism of homofermentative (a) and heterofermentative (b) lactic acid bacteria. (Source: From the author)

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and porphyrins, the literature has pointed out since the 1970s that heme (a red-­ coloured, redox-active, iron-containing macrocyclic compound) and menaquinones induce respiration in lactic acid bacteria, increasing the growth and survival of these bacteria and inducing the formation of cytochromes (Duwat et al. 2001; Brooijmans et  al. 2009). Respiratory metabolism in lactic acid bacteria provides important industrial applications as it is energetically more favourable and alleviates oxidative and acid stress during growth. Considering the availability of heme and menaquinones in natural environments and the survival advantages conferred by respiration, respiratory metabolism is considered to be part of the way of life of numerous lactic acid bacteria (Lechardeur et al. 2010). In heterofermentative species, with the conversion of acetyl phosphate to acetate instead of ethanol (Fig. 4.1), an additional ATP molecule is produced. The regeneration of the excess NAD+ is performed by means of an alternative electron acceptor, which can be oxygen under aerobic conditions (Condon 1987) or fructose under anaerobic or oxygen-limiting conditions (von Weymarn et al. 2002). In this case, fructose is reduced to mannitol. The presence of this polyol can be used as an indication of the presence of lactic acid bacteria in ethanolic fermentation, which will be discussed further. In the fermentative environment, despite the variety of species, the most frequent have been Lactobacillus fermentum and Lactobacillus vini, according to Lucena et al. (2010), who also highlighted the great intraspecific diversity in these two species and the tolerance up to 10% ethanol. By sequencing a strain of L. vini (JP7.8.9) isolated from the fermentative process for ethanol fuel, Lucena et al. (2012) reported the presence of important genes in the context of the fermentation such as genes linked to stress response. L. fermentum and Lactobacillus plantarum species were the most frequent in industrial and pilot-scale fermentation, respectively, while Lactobacillus casei was found in both fermentations in work by Dellias et al. (2018). L. fermentum is a rod-shaped bacterium, 0.5–0.9  μm wide, quite variable in length, isolated or in pairs, Gram-positive, non-sporulated and rarely mobile. The main physiological characteristics of these bacteria are facultative anaerobic, heterofermentative, catalase-negative, optimum temperature between 30 and 40 °C and optimum pH between 5.5 and 5.9 for growth (Oliveira et al. 1995). L. plantarum is a rod-shaped, Gram-positive bacterium found in silage and some food products. They are homofermentative bacteria and convert over 80% of fermentable sugars to lactate (McFall and Monteville 1989). L. vini is a facultative anaerobic, homofermentative, catalase-negative, Gram-­ positive bacterium with cells occurring singly, in pairs or short chains. They are non-spore-producing and motile rods capable of producing lactate exclusively as an end product from hexoses and pentoses. They do not produce mannitol from fructose (Rodas et al. 2006). Contamination can occur in different locations within the fuel ethanol production line, and lactobacilli can be found in locations after the heat exchanger, in saccharification tanks and in continuous yeast propagation systems. Due to their ability to produce biofilms (Dellias et al. 2018), the bacteria are protected in this structure that can act as reservoirs of cells that continuously reintroduce contaminants into

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the process (Skinner-Nemec et al. 2007; Khatibi et al. 2014). Thus, it is essential to study the characteristics of these bacteria and their importance in the fermentation environment so that preventive and corrective measures can be applied to reduce the adverse effects of bacterial contamination.

4.3 Effects of Bacterial Contamination on the Fermentation Process The effects that bacteria cause in the fermentation process are manifold and depend on the type of bacteria, the amount of bacterial cells, the type of fermentation mash, the fermentation system, the process conditions and the microbiota present in the fermentation vessels. The effects can be direct, affecting the viability of the yeast S. cerevisiae, but can also affect the fermentation yield by producing substances that divert sugar that would be converted to ethanol. The interaction between bacteria and yeast at different levels (physical, through cell-cell contact, and physiological, through the production of substances that interfere with each other’s metabolism), makes the evaluation of the effects of contamination not necessarily a simple task. Aggregation of yeast cells by the presence of the bacteria L. fermentum, L. plantarum and L. vini has been referred to in episodes of yeast flocculation (Yokoya and Oliva-Neto 1991; Tiukova et al. 2014). Flocculation in yeast is defined as a reversible, homotypic, non-sexual process of aggregation of cells into multicellular masses composed of thousands of cells called flocs, which sediment rapidly in the medium in which they are suspended (Stratford 1992). The most appropriate term for bacterial cell-induced flocculation of yeast is co-flocculation, also called mutual aggregation or mutual flocculation, which consists of a heterotypic process (whereas flocculation is homotypic) between two different strains of yeast or between yeast and bacteria (Stewart 2018). However, the most commonly used term for the aggregation of yeast cells induced by bacteria is flocculation itself. Figure 4.2 is a photomicrograph showing yeast and bacteria cells aggregated in a wine sample from an ethanol production unit. The contaminating bacteria are Gram-­ positive rods. The number of yeast and bacteria cells, presence of calcium, pH, temperature and composition of the medium are factors that affect flocculation (Ludwig et al. 2001; Soares 2010). Studies pointed out that the lowest concentration of L. fermentum bacteria that caused S. cerevisiae yeast cells to flocculate was 1.38  g/L dry biomass for a concentration of 65.4 g/L dry yeast biomass. Yeast deflocculation was only possible at pH less than 3.0, with a rapid reversion to flocculation occurring when the pH rose from 2.5 to 3.0 or 4.0 (Ludwig et al. 2001). The acid treatment to which the centrifuged cell mass is submitted after the fermentation cycle is able to perform the yeast deflocculation; however, when the cell mass returns to the vat for a new fermentation cycle, with input of new must, flocculation occurs again (Souza

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Fig. 4.2  Photomicrograph of a wine sample from an ethanol production unit showing yeasts and bacteria cells aggregated after Gram staining. Both the yeast and the rod-shaped bacteria are Gram-­ positive. Microscope magnification 400×. (Source: From the author)

and Mutton 2004), hence the need to use an alternative method to reduce the number of bacterial contaminants. Alcarde (2001) verified that the number of bacteria necessary to trigger flocculation was different between the two yeast S. cerevisiae strains studied (VR-1 and PE-2) and also differed between the bacteria tested. A number greater than 108 CFU/mL of L. fermentum, L. plantarum and Lactobacillus buchneri species were required to induce flocculation of the S. cerevisiae strain VR-1, while for L. fructivorans and L. fructosus, the numbers ranged from 1 to 5 × 107 CFU/mL. For S. cerevisiae strain PE-2, the number of bacteria required for flocculation was lower. Alcohol content (0–10%) and temperature (25–65 °C) significantly affected flocculation. The ratio of bacterial cell number/yeast cell number also varied widely among bacterial species, ranging from 0.2 to 3.0. Pretzer et al. (2005) evaluated the ability of fourteen L. plantarum strains to bind S. cerevisiae cells involving mannose, revealing the gene designated to encode the mannose-specific adhesin, the MSA gene. Analysis of the Mub domain of this gene showed homologies with adhesins from other bacterial species, for example, with a protein from Lactococcus lactis (hypothetical protein L39650) and with a surface protein from L. fermentum (Mlp). Co-aggregation of S. cerevisiae with L. plantarum depends on the structure of the main mannan chain of the yeast cell wall to which side chains containing one or more mannose residues are attached. Surface proteins of L. plantarum also contribute to co-aggregation with S. cerevisiae, indicating that these proteins would recognize mannose residues from the side chains on mannan as a lectin-like protein (Hirayama et al. 2012). Direct contact between S. cerevisiae and L. paracasei results in aggregation of bacterial and yeast cells, triggering the expression of genes related to the synthesis of extracellular polysaccharides, cell surface modification and transfer of

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metabolites in the bacteria. Most of the genes in lactic acid bacteria induced by direct contact with yeast have homologs among different Lactobacillus species, indicating that this phenomenon induced by direct contact with yeast cells is widely found in Lactobacillus. Lactic acid bacteria respond to direct contact with yeast by recognizing the mannan on the yeast cell surface (Yamasaki-Yashiki et al. 2017). The presence of the bacterium L. fermentum can result in modifications in yeast gene expression. Carvalho-Netto et al. (2015) analysed the molecular physiology of yeast strain PE-2 in two fermentation conditions: typical fermentation, when most of the yeast cells are in suspension, and fermentation with cell aggregates, with flocculated cells. The authors observed the transcription profile of this yeast by RNA-­ seq on an industrial scale in discontinuous fermentation with must feeding. Comparative analysis of the two conditions revealed differentiated transcription profiles mainly by a profound gene repression in the samples with aggregates. The expression of the SUC2 gene, related to sucrose hydrolysis, decreased sevenfold when the fermentation presented flocculation, causing a longer fermentation time due to the low availability of reducing sugars. The data also indicated that L. fermentum was the bacterial species responsible for the co-aggregation of yeast and the high levels of organic acids detected in the samples. A study with pure cultures of L. fermentum and L. plantarum and in coculture with S. cerevisiae (strain CAT-1) showed different behaviours between the bacteria regarding substrate consumption. In medium with equivalent proportions of glucose and fructose, L. plantarum consumed glucose faster than fructose, producing lactic acid exclusively. The rate of fructose consumption was higher than that of glucose for L. fermentum, which produced mannitol as the main metabolite, followed by lactic acid and acetic acid. In coculture in semisynthetic medium, when both yeast and bacteria were inoculated in equal numbers (107 cells/mL), the bacteria L. plantarum was more detrimental to fermentation than L. fermentum, causing a reduction in yeast viability, producing a higher amount of lactic acid and lower alcohol content in the must. Under conditions that simulate the industrial process, such as high yeast cell density, short fermentation time and cell recycle, the heterofermentative species – L. fermentum – was more detrimental to fermentation, showing increased population over the recycles, lower ethanol production and lower fermentative efficiency and higher glycerol production (Basso et al. 2014). Mannitol is a six-carbon polyol produced mainly by lactic bacteria with heterofermentative metabolism (Wisselink et al. 2002). The bacteria compete with yeast for substrate to produce mannitol instead of ethanol, causing a decrease in ethanol yield. Eggleston et al. (2007) observed a strong positive correlation between mannitol formation and bacterial numbers in fermentations with sugarcane juice and molasses. The species that presented the highest mannitol production was L. mesenteroides, a sugarcane juice spoilage bacterium. Among the contaminant bacteria in the fermentation process, the greatest producers of mannitol were L. fermentum and L. fructosus. Since it is not produced by yeast, mannitol can be used as an indicator of bacterial contamination. The authors developed a fast and simple enzymatic method to determine the concentration of mannitol, which can help to monitor bacterial contamination.

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The increase in the production of glycerol by the yeast in a situation of bacterial contamination has been related to the presence of the bacteria, which would explain the lower fermentative efficiency due to the deviation of sugar for glycerol production. However, there are situations described in the literature in which there was lower production of glycerol in the presence of the bacterial contaminant, either because the bacterium – L. plantarum – consumed glycerol (Basso et al. 2014) or because a metabolic imbalance occurred in the yeast able to affect the metabolic pathways for glycerol production in the presence of L. fermentum (Carvalho-Netto et al. 2015). Although glycerol production occurs at the expense of lower ethanol production, glycerol is important to maintain redox balance and provide osmoregulation (Nevoigt and Stahl 1997), protecting the cell from the stressful conditions that occur during industrial fermentation. In this situation of decreased glycerol production, the yeast can be more exposed to stresses and affect both its cell viability and metabolism. The influence of metabolic products of bacteria on S. cerevisiae is a controversial issue. Narendranath et al. (2001a) found that the minimum inhibitory concentration of acetic acid for the growth of two strains of S. cerevisiae was 0.6% (w/v) and for lactic acid was 2.5% (w/v) but concentrations much lower than those caused a reduction in growth rate, glucose consumption and ethanol production. At lactic acid concentration higher than 6  g/L and bacterial number higher than 1.2  ×  109 cells/mL, there was significant inhibition of fermentation efficiency after 15 cycles of fermentation (Oliva-Neto and Yokoya 1994). However, Nobre et al. (2007) found that in the absence of live bacterial cells, the presence of Lactobacillus and Bacillus cell metabolites did not affect the viability of S. cerevisiae. The production of lactic acid by L. paracasei was not responsible for the 83% reduction in S. cerevisiae viability, but rather competition for substrate nutrients (Bayrock and Ingledew 2004). The toxicity of organic acids is determined by their chemical properties and, in particular, by their hydrophobicity, volatility and pKa (dissociation constant). When the cells are in an environment with pH below the pKa value of the weak acid, the undissociated lipophilic form of the acid (RCOOH) predominates, permeating the plasma membrane by simple diffusion or facilitated diffusion, in the case of acetic acid. In the cytosol, at pH close to neutrality, dissociation of the acid occurs with the release of H protons+ and its respective counter-ion (RCOO−). These ions are not able to cross the hydrophobic bilayer of the plasma membrane and accumulate inside the cell. In order to maintain constant the intracellular pH, protons are transported across the membrane by the activity of ATPases. In addition to affecting the internal pH of the cell, weak acids affect the lipid organization and function of cell membranes due to their propensity to become more inhibitory as they become more hydrophobic, which demands ATP, leading to effects on the growth of the microorganism (Mira et al. 2010). Narendranath et al. (2001b) showed that acetic acid and lactic acid inhibit the growth of S. cerevisiae by different mechanisms. In the presence of 0.5% (w/v) lactic acid, a considerable reduction of two unsaturated membrane fatty acids (palmitoleic acid and oleic acid) occurred; however, the changes in membrane fatty acid composition were small in the presence of acetic acid. The acids had different effects on intracellular pH and ATPase activity.

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It is important to consider that the effect of organic acids on ethanolic fermentation depends on the concentration and type of acid produced, the pH of the fermentation medium, the number of yeast cells and the synergy of the acids with each other and with other fermentation products such as ethanol, for example. The inhibitory effect of acetic acid and lactic acid was significantly increased when both acids were present, showing synergistic effect (Narendranath et al. 2001a). Both ethanol (40 g/L) and n-butanol (8 g/L) severely affected the diffusion rate of acetic acid (at concentrations of 3 and 6 g/L) in S. cerevisiae, increasing it by about 65% in cells sampled during the exponential phase. The increase in the diffusion rate can be explained by the partition of alcohol in the polar end region (head) of the membrane lipid bilayer, causing considerable increase in the area per lipid molecule, besides reducing the thickness and order of lipids in the membrane, which is related to fluidity. The effect of ethanol was found to be synergistic while that of butanol was additive, which means that ethanol and acetic acid have the same targets inside the cell, while butanol has greater effect on membrane partitioning (Lindahl et al. 2018). The main effect of ethanol inside the cell is to reduce water activity (Hallsworth 1998), and in the presence of acetic acid, further reduction of water activity to below the critical level for cell growth occurs, according to the conclusion of Lindahl et al. (2018). Study by Guo and Olsson (2016) showed there is a relationship between the yeast initial cell density and the intensity of the acetic acid effect (at 300 mM or 18 g/L concentration), since at initial cell concentration of 1 g/L of yeast biomass occurred reduced lag phase and higher tolerance to acid stress when compared to initial cell density of 0.1 g/L of yeast biomass. Considering the high cell densities in the fermentation tanks (7–14% w/v), it is expected that the effect of acetic acid would be decreased. Glycolytic flux in yeast is increased in the presence of weak acids, either in glucose-limited or glucose-saturated cultures. With the entry of H ions+ into the cell due to the presence of weak acids, the cell needs ATP to pump these ions out in order to maintain the intracellular pH. Pampulha and Loureiro-Dias (2000) calculated that 1 mol of ATP is required per mol of acetic acid entering the cell to pump 1 mol of H ions+ out of the cell. Thus, glycolysis is activated by the low level of ATP, resulting in increased specific rate of ethanol production and decreased specific rate of glycerol production in the range of 0- to 170-mM acetic acid (0–10.2  g/L). Greetham (2014) found that at concentration of 20  mM (1.2  g/L) of acetic acid, there was less glycerol accumulation and increased ATP production, with consequent improvement in fermentative yield. The interactions between bacteria and yeasts present in the fermentation vessel are an important aspect to be considered in the context of contaminations. In industrial ethanol production processes with cell recirculation, the species L. vini was found on several occasions to be associated with Dekkera bruxellensis, an important yeast contaminant of ethanolic fermentation (Passoth et  al. 2007; Lucena et  al. 2010; Tiukova et  al. 2014). However, the nature of the interactions has not been elucidated. Passoth et  al. (2007) found that an industrial fuel ethanol production process was dominated by D. bruxellensis and L. vini, with a high number of lactic

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acid bacteria. There was no impairment to productivity and process stability, so the yeast-bacteria consortium was considered beneficial. Souza et  al. (2012) showed that the addition of L. vini to S. cerevisiae culture did not affect the yeast cells. When added to D. bruxellensis culture, there was a stimulus in the fermentative activity of the yeast with consequent increase in ethanol yield. Tiukova et al. (2014) attributed to the presence of L. vini the occurrence of flocculation when in the presence of S. cerevisiae or D. bruxellensis. With the former yeast, flocculation was more intense probably due to the higher mannose content in the cell wall of S. cerevisiae. The small flocs of L. vini associated with the elongated cells of D. bruxellensis provided an advantage in nutrient uptake and protection against stressful conditions. In this situation, there was a decrease in yeast number and ethanol production when compared to pure cultures. These results indicate that lactic bacteria can affect ethanol production not only due to the competition for substrate or lactic acid production but also due to the spatial structure of the population within the fermentation vessels.

4.4 Methods to Control Bacterial Growth The control of bacterial contamination is normally carried out during the yeast treatment step between fermentation cycles. The fermented must is centrifuged to separate the yeast cells from the wine, which goes to distillation to obtain ethanol. The cell mass, consisting of yeast cells and any microbial contaminants, is treated in an aqueous solution of sulfuric acid, pH 2.0–2.5 for 1–2 h, and then returns to the fermentation tanks for a new fermentation cycle (Lopes et al. 2016). This acid treatment promotes the deflocculation of the yeast caused or not by bacteria; however, as the pH of the must in the fermentation tanks is higher than the acid treatment, the cells flocculate again at the time they are added to the tanks for a new fermentation cycle. Increasing the residence time of the cells in the treatment and/or decreasing the pH can have an effect on the yeast metabolism, considering also that younger or older yeast cells are the least resistant to acid treatment (Silva et al. 2015). Sulfuric acid reduces the number of bacterial cells acting as a bactericide, but there are few studies showing the effect of acid treatment on the number of contaminating bacteria. Gallo (1990) showed a reduction of approximately 45% in the bacterial population in a distillery, while laboratory experiments showed a reduction of three log cycles (99.9%) in the number of L. fermentum using sulfuric acid treatment at pH 2.0 (Costa et al. 2018). The native bacterial microbiota of sugarcane juice was eliminated with acid treatment pH 2.0 (Silva-Neto et al. 2020). The reduction in the number of bacteria by acid treatment depends on the initial concentration of cells and the type of bacteria present, so it will not always be effective in controlling bacterial contamination in the fermentation process. The mechanisms by which bacteria resist to the acid treatment need to be more extensively studied in order to improve strategies to control the bacterial growth in industry. L. vini bacteria, for example, respond to acid stress (caused by weak acids or strong inorganic acids) by two complementary but independent mechanisms. To

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control the internal pH, the cell needs to neutralize excess protons in the cytoplasm, and since proton extrusion is an energy-demanding process, the stationary phase of growth is anticipated. As a result, there is a reduction in the deposition of cell wall components, with signalling for resorption, and consequent remodelling of the cell wall structure. These physiological changes increase the survival and competitiveness of the cell in stressful environments such as the industrial fermentative environment (Mendonça et al. 2019). The use of antibiotics dates back to the 1940s with the proposition of using tyrothricin and polymyxin B in fermentative processes (Gray and Kazin 1946; Case and Lyon 1956). In the milling and fermentation stages, the antibiotics penicillin, streptomycin, tetracycline, monensin and virginiamycin have been commonly used. Penicillin should be added at concentrations much higher than the minimum inhibitory concentrations for bacteria due to the following issues, instability at pH below 5 and inactivation at a temperature of 35  °C, conditions that occur frequently in ethanolic fermentation, in addition to the possibility of being enzymatically degraded (Ceccato-Antonini 2018). Virginiamycin has been a more attractive option (Muthaiyan et al. 2011); however, monensin has had wide application in ethanolic fermentation (Stroppa et al. 2000). A dosage of 0.3–3.0 mg/L is usually added to the fermentation broth (Miniac 1999). Monensin is a polyether ionophore antibiotic produced by Streptomyces cinnamonensis with antimicrobial activity against Gram-­ positive bacteria (Agtarap et al. 1967; Lowicki and Huczyński 2013), with the commercial preparation Kamoran® HJ being the best known. The use of antibiotics in the ethanolic fermentation industry runs into two points that deserve highlighted attention: (1) the emergence of antibiotic-resistant bacterial strains, requiring the use of increasing dosages of antibiotics, (2) the persistence of antibiotics in the dried yeast that is marketed for animal feed (Ceccato-Antonini 2018). Studies have isolated bacteria commonly found in the human gastrointestinal tract with high levels of resistance to antibiotics such as penicillin, erythromycin and virginiamycin, in the fermentative environment (Murphree et al. 2014), or even bacteria such as L. vini presenting tetracycline resistance gene (tet-m), acquired by transposon, with the risk of spreading this gene to human pathogens in the distillery surroundings (Mendonça et al. 2016). The search for nonconventional alternatives (that do not use sulfuric acid or antibiotics) has shown a range of natural and chemical products with efficiency in controlling bacterial contamination. Among the chemical products, chlorine dioxide is already a reality in the fermentation industry. With strong oxidant characteristics; antimicrobial properties against bacteria, viruses and algae; and efficiency in water treatment, chlorine dioxide avoids the problem of antibiotic resistance and the risks of handling with sulfuric acid, besides leaving no residues in the yeast and other fermentation by-products (Meneghin et al. 2008). In 2012, the commercialization of DuPont™ Fermasure® was approved in Brazil for use in ethanol fermentation. The product (stabilized chlorine dioxide as the active ingredient) has been used at a concentration of 30  mg/L and decreased sulfuric acid treatment by 40% (Furtado 2013). Table 4.1 lists some of the chemicals that have been studied for bactericidal and/ or bacteriostatic effect for potential use in the fuel ethanol industry.

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Table 4.1  Chemical agents searched for bactericidal and/or bacteriostatic effects to be employed in bioethanol industry Product Ethanol and sodium chloride

Ethanol and low pH

Fermentation medium Wood hydrolysate

Bacteria L. fermentum, L. buchneri, L. plantarum, Acetobacter tropicalis, Acetobacter syzygii Sugarcane juice L. fermentum

Performic acid

Sucrose medium

L. fermentum, L. paracasei, L. planetarium, L. mesenteroides

Sulphite and hydrogen peroxide

Glucose-based semisynthetic medium

L. fermentum and L. casei

3,4,4′-trichlorocarba-­ nilide (TCC)

Molasses

L. fermentum

TCC + benzethonium chloride or benzalkonium chloride

Man-Rogosa-­ Sharpe (MRS) and nutrient medium

L. fermentum

Main results (reference) The combined addition of NaCl (25 g/L) and ethanol (40 g/L) maintained the yeast viability and decreased the bacterial viability. There was no effect on the fermentative parameters (Albers et al. 2011) The addition of 5% of ethanol to the acid solution (pH 2.0) for yeast cell washing resulted in total loss of viability of the bacteria after the first fermentative cycle. No effect on the ethanol yield (Costa et al. 2018) The bacterial number decreased by four log cycles after 10 min in contact with performic acid (DesinFix TM 135). No negative effects on yeast growth and fermentation (Barth et al. 2014) L. casei was more susceptible to sulphite (100–300 mg/L). L. fermentum growth was controlled by hydrogen peroxide at the concentrations of 1–10 mM (Chang et al. 1997) TCC (1.8 g/L) entrapped in calcium alginate inhibited L. fermentum growth. A much lower concentration (0.075 g/L) combined with sodium dodecyl sulphate (1.67 mg/L) controlled bacterial growth for 19 fermentative cycles. Improvement in the ethanol efficiency was observed (Oliva-Neto and Yokoya 1998) TCC associated with other chemicals caused a much higher reduction in bacterial number when added to the sugarcane milling. No effect on S. cerevisiae was observed (Oliva-Neto et al. 2014) (continued)

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Table 4.1 (continued) Product Chlorine dioxide

Fermentation medium MRS and nutrient broth

Bacteria L. fermentum, L. plantarum, L. mesenteroides and Bacillus subtilis

Main results (reference) Lactobacillus species were more resistant to chlorine dioxide (75 and 125 ppm, respectively, for L. fermentum and L. plantarum) than B. subtilis (10 ppm) and L. mesenteroides (50 ppm). The effects were comparable to monensin (Kamoran®) (Meneghin et al. 2008)

Source: Ceccato-Antonini (2018), with permission from Springer

Among the natural products with antibacterial properties, hop (Humulus lupulus) extracts have been used in the bioethanol industry. Commercial preparations of α-acids (humulones) and β-acids (lupulones), under the names IsoStab®, LactoStab® and Betabio 45®, have been used at concentrations ranging from 10 to 50 mg/L both in fermentation tanks and during acid treatment, with no effect on yeast viability (Leite et al. 2013). Other natural compounds such as chitosan and propolis have shown action against bacteria contaminating the fermentation; however, the works have been restricted to laboratory scale without employment yet in industrial scale (Kalogeropoulos et al. 2009; Garg et al. 2010; Pan et al. 2011; Viégas 2011; Mutton et al. 2014; Tanganini et al. 2020). New antimicrobials should be explored for the alcoholic fermentation, especially considering that numerous antimicrobial compounds can be found in herbs, spices, fruits, seeds and leaves, especially agro-­ industrial wastes, which would offer a new and safer option against bacterial contamination in the bioethanol industry, reducing/eliminating the use of sulfuric acid and antibiotics due to their environmental, safety and health problems (Shirahigue and Ceccato-Antonini 2020). A new strategy that has been studied is based on the antagonistic effects against bacteria resulting from their interaction with other microorganisms. Bacteriophages are obligate parasites specific to bacteria, are low-cost and autocatalytic and can be isolated from environmental samples. In a work by Worley-Morse et al. (2015), the phage 8014-B2 caused a three-log cycle decrease of L. plantarum in coculture with S. cerevisiae (semisynthetic medium, 48 h of fermentation), increased ethanol content by 8% and maintained yeast viability. The efficiency of the phage system depended on the initial number of phages and bacteria. The inactivation of phages by heat during distillation can guarantee the safety of the system; however, the possibility of bacterial or phage gene transfer to the yeast and the emergence of bacteriophage resistant bacteria should be investigated. In medium consisting of corn liquor contaminated with L. fermentum, the use of two bacteriophages restored the ethanol yield and reduced the concentration of residual sugar and organic acids (Liu et al. 2015). With L. plantarum, the mixture of

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two phages was efficient in pH 4–6, reducing bacterial contamination by 99% and restoring ethanol yield (Bertozzi Silva and Sauvageau 2014). Bacteria can produce peptides or extracellular proteins with activity against other bacteria. Colicin and nisin are examples of compounds produced by Escherichia coli and Lactococcus lactis, respectively (Silva Sabo et al. 2014). Nisin has an effect against Gram-positive bacteria, controlling the growth of L. plantarum and L. brevis without affecting ethanol production and limiting lactic acid production (Peng et al. 2012). A formulation combining nisin and hop extract was tested against L. fermentum, L. mesenteroides and S. cerevisiae in fermentative tests, promoting reduction in the number of bacteria without severely affecting the process yeast (Maia et al. 2019). A secondary metabolite (called F4 fraction) produced by a strain of Pseudomonas aeruginosa had selective activity against Lactobacillus sp. without affecting yeast viability and fermentative parameters, reducing foaming and floc formation in fermentation with sugarcane juice and molasses (Góis et  al. 2013). Bacteria of the species B. subtilis and Bacillus cereus produce a lipopeptide with antibacterial action against L. fermentum, L. brevis, L. mucosae and L. amylovorus, which could be used in ethanol fermentation (Manitchotpisit et al. 2013). Rich et al. (2018) evaluated 516 bacterial strains that did not inhibit ethanol production by S. cerevisiae as potential beneficial strains to be tested against L. fermentum. The authors identified a group of beneficial strains that restored ethanol production to fermentation levels without L. fermentum contamination. This is undoubtedly a new strategy to be tested in the ethanol fermentation industry that could replace the use of acids, antibiotics or any other product. Lino et al. (2021) developed a synthetic consortium of bacteria such as L. amylovorus, L. fermentum, Lactobacillus helveticus, L. buchneri, Pediococcus claussenii and Zymomonas mobilis in addition to S. cerevisiae in order to study how each species interact with each other and with the yeast in all possible combinations of bacteria and yeast. L. amylovorus was considered a beneficial bacterium to the fuel ethanol fermentation, improving yeast growth and rate and ethanol yield by providing acetaldehyde. This substance acted as an alternative electron acceptor allowing NADH/NAD balance by distributing more carbon towards pyruvate and biomass production and with less glycerol production. It is noteworthy to say that the beneficial effect of L. amylovorus was observed when this species was co-cocultured with other bacterial species in multispecies consortia. This strategy could be a way to promote bioethanol production. S. cerevisiae yeasts can produce substances with antibacterial activity especially against lactic acid bacteria (Oliva-Neto et al. 2004; Meneghin et al. 2010), and this characteristic could be inserted as a criterion for the selection of yeast strains for ethanolic fermentation (Ceccato-Antonini 2018). Table 4.2 summarizes the different strategies to control bacterial contamination, their advantages and disadvantages. There is scientific evidence pointing to different compounds and strategies aiming at not only process economics but also a safer

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Table 4.2  Summary of the conventional and nonconventional approaches to control bacterial contamination, their advantages and disadvantages Conventional

Strategies Acid treatment

Antibiotics

Nonconventional Chlorine dioxide

Natural products (hops, propolis, chitosan and other plant extracts)

Bacteriophages

Beneficial bacteria

Bacteriocins

Advantages In appropriate conditions, no effect on yeast viability Generally effective to reduce bacterial contamination Efficient against Gram-positive bacteria, especially Lactobacillus

Disadvantages Health risks Disposal of the effluent

Emergence of drug-­ resistant strains Retention in yeast cell mass utilized for poultry and livestock feeds Replaces part of the acid Effect on yeast viability treatment with no depending on the residues in the yeast cell concentration mass Commercial Only small-scale studies preparations of hop are for propolis, chitosan available for bioethanol and other plant extracts industry so far No effects on yeast viability but effective against bacteria No residues in the yeast cell mass Systems are available Only small-scale studies for use in the bioethanol so far industry Effective against Lactobacillus Action against specific Only small-scale studies bacteria by production so far of peptides/proteins Nisin affects Only small-scale studies Lactobacillus so far

Source: Ceccato-Antonini (2018), with permission from Springer

and more environmentally friendly context when compared to the use of antibiotics and sulfuric acid. It is important to inform the industrial sector that there are many potential options and that they need to be tested in the industry so that any changes can be made for proper use.

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Silva-Neto, J.M., Covre, E.A., Rosa, B.C., Ceccato-Antonini, S.R.: Can ethanol replace partially or fully sulfuric acid in the acid wash step of bioethanol production to fight contamination by Lactobacillus fermentum? Braz. J. Chem. Eng. 37(2), 323–332 (2020) Skinner-Nemec, K.A., Nichols, N.N., Leathers, T.D.: Biofilm formation by bacterial contaminants of fuel ethanol production. Biotechnol. Lett. 29(3), 379–383 (2007) Soares, E.V.: Flocculation in Saccharomyces cerevisiae: a review. J.  Appl. Microbiol. 110(1), 1–18 (2010) Souza, M.A.C.E., Mutton, M.J.R.: Floculação de leveduras por Lactobacillus fermentum em processos industriais de fermentação alcoólica avaliada por técnica fotométrica. Ciência e Agrotecnologia. 28(4), 893–898 (2004) Souza, R.B., Santos, B.M., Souza, R.F.R., Silva, P.K.N., Lucena, B.T.L., Morais Jr., M.A.: The consequences of Lactobacillus vini and Dekkera bruxellensis as contaminants of the sugarcane-­ based ethanol fermentation. J. Ind. Microbiol. Biotechnol. 39(11), 1654–1650 (2012) Souza, R.S.C., Okura, V.K., Armanhi, J.S.L., Jorrin, B., Lozano, N., Silva, M.J., González-­ Guerrero, M., Araújo, L.M., Verza, N.C., Bagheri, H.C., Imperial, J., Arruda, P.: Unlocking the bacterial and fungal communities assemblages of sugarcane microbiome. Sci. Rep. 6, 28774 (2016) Stewart, G.G.: Yeast flocculation – sedimentation and flotation. Fermentation. 4(2), 28 (2018) Stratford, M.: Yeast flocculation: Reconciliation of physiological and genetic viewpoints. Yeast. 8(1), 25–38 (1992) Stroppa, C.T., Andrietta, M.G.S., Andrietta, S.R., Steckelberg, C., Serra, G.E.: Use of penicillin and monensin to control bacterial contamination of Brazilian alcohol fermentations. Int. Sugar J. 102(1214), 78–82 (2000) Tanganini, I.C., Shirahigue, L.D., Altenhofen da Silva, M., Francisco, K.R., Ceccato-Antonini, S.R.: Bioprocessing of shrimp wastes to obtain chitosan and its antimicrobial potential in the context of ethanolic fermentation against bacterial contamination. 3 Biotech. 10, 135 (2020) Tiukova, I., Eberhard, T., Passoth, V.: Interaction of Lactobacillus vini with the ethanol-producing yeasts Dekkera bruxellensis and Saccharomyces cerevisiae. Biotechnol. Appl. Biochem. 61(1), 40–44 (2014) Viegas, E.K.D.: Propriedade antibacteriana da própolis verde sobre bactérias contaminantes da fermentação etanólica. Dissertation, Escola Superior de Agricultura “Luiz de Queiroz”, Universidade de São Paulo (2011) von Weymarn, N., Hujanen, M., Leisola, M.: Production of D-mannitol by hetero-fermentative lactic acid bacteria. Process Biochem. 37, 1207–1213 (2002) Wisselink, H.W., Weusthuis, R.A., Eggink, G., Hugenholtz, J., Grobben, G.J.: Mannitol production by lactic acid bacteria: a review. Int. Dairy J. 12, 151–161 (2002) Worley-Morse, T.O., Deshusses, M.A., Gunsch, C.K.: Reduction of invasive bacteria in ethanol fermentations using bacteriophages. Biotechnol. Bioeng. 112, 1544–1553 (2015) Yamasaki-Yashiki, S., Sawada, H., Kino-Oka, M., Katakura, Y.: Analysis of gene expression profiles of Lactobacillus paracasei induced by direct contact with Saccharomyces cerevisiae through recognition of yeast mannan. Biosci. Microbiota Food Health. 36(1), 17–25 (2017) Yokoya, F., Oliva-Neto, P.: Características da floculação de leveduras por Lactobacillus fermentum. Rev. Microbiol. 22(1), 12–16 (1991)

Chapter 5

Methods for the Identification and Characterization of Yeasts from Ethanolic Fermentation

5.1 Introduction In a biotechnological process such as the fuel ethanol fermentation, the yeast introduced as the fermentation agent is the Saccharomyces cerevisiae species. As the fermentation process takes place under non-aseptic conditions, contamination by native non-Saccharomyces yeasts or even by native S. cerevisiae strains occurs. These can dominate the process and present desirable characteristics for selection for the next harvest. However, these native S. cerevisiae strains can be detrimental to the process. It is important that the microbiological monitoring uses techniques that allow the identification of the yeast as well as the comparison with others of the same species. Thus, to identify (determine the species) and characterize (compare with others of the same species) are activities that require the choice of methodologies and techniques to achieve one and/or another objective. Yeasts can be identified according to morphological, physiological and biochemical characteristics through fermentation and assimilation tests of various sources of sugars and nitrogen and morphology of the sexual and asexual states of yeasts. These tests present a certain degree of ambiguity, besides being time-consuming and requiring considerable knowledge for the interpretation of the results. Although these techniques can be used for yeast identification, they are not applied to the characterization of yeasts for differentiation at the intraspecific level, as is desirable in the fermentative environment. DNA-based methods of yeast identification and characterization are more discriminatory, sensitive and independent of gene expression and environmental conditions than the conventional system based on phenotypic characteristics. The transition from the conventional to the molecular system occurred with the determination of the genomic C + G content. Ascomycete species have genomic C + G content of 28–50% while basidiomycetes from 50% to 70%, and differences of 1% to 2% would indicate being from different species (Kurtzman; Fell, 2006). The © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_5

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quantification of genome similarity between strains has become possible with the development of DNA reassociation techniques, which allow measuring the extent of nucleotide sequence pairing between the single strands of the strains to be analysed. Strains that exhibit 70–80% complementarity in DNA reassociation techniques are considered to be of the same species. However, these techniques are only valid for closely related species (Kurtzman 2011). The advent and development of DNA sequencing techniques and the creation of a sequence database with which to compare the sequence to be evaluated have facilitated comparisons between gene sequences for identification purposes even with more distant species. Ribosomal genes have been used for yeast identification, comprising specific genes and intergenic and internal transcribed spacer regions. Karyotyping by pulsed-field electrophoresis is a technique extensively used for yeast identification, and because it reveals the polymorphisms resulting from chromosome rearrangements, it is also a method to characterize strains. Other important techniques for the evaluation of polymorphisms among strains are mitochondrial DNA restriction analysis and microsatellites. The industrial segment demands fast, reliable and simple methods for monitoring yeast populations in fermentation vats. Molecular methods can ensure better yield and process efficiency, as well as the selection of promising strains for use in subsequent seasons.

5.2 Uses and Limitations of Identification Methods Based on Phenotypic Characteristics The classical taxonomy of yeast dates back to the nineteenth century, when Cagniard-Latour, Kutzing and Schwann showed that yeast was a living organism, more specifically a fungus. In 1838, Meyen assigned the name Saccharomyces (the Latin form for Zuckerpilz, sugar fungus) to a genus of fermenting yeasts comprising three species, S. cerevisiae, S. pomorum and S. vini, isolated from beer, fermented apple juice and wine, respectively. Classical taxonomy was based primarily on macroscopic and microscopic characteristics, including sexual spore production, but rapidly evolved to other tests (Barnett et al. 2000). Criteria for yeast classification include (a) cell size and shape; (b) cell wall structure; (c) modes of vegetative reproduction; (d) type of sexual reproduction, if present; and (e) ability to utilize exogenous compounds (Barnett 2004). The conventional procedures that identify yeasts based on their morphological and physiological characteristics are labour-intensive, time-consuming and not fully conclusive. However, some of the taxonomic characteristics evaluated in the conventional identification process have implications in the fermentative process, such as sexual spore production, assimilation of carbon and nitrogen sources and sugar fermentation.

5.2  Uses and Limitations of Identification Methods Based on Phenotypic Characteristics

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Fig. 5.1  Life cycle of the yeast S. cerevisiae. Haploid and diploid generations alternate, producing sexual spores (ascospores) under nutrient depletion conditions. (Source: From the author)

The life cycle of the yeast S. cerevisiae is depicted in Fig.  5.1. Haploid cells divide by budding, producing a daughter cell identical to the mother cell. Before the bud is detached, segregation of each chromosome occurs by mitosis. A haploid cell, carrying one copy of each chromosome, can be of mating type a or α. A cell of one type produces a pheromone that stimulates fertilization by attracting a cell of the opposite mating type. The cells emit projections towards each other to form structures called shmoos. When two haploid cells of opposite mating types (a + α) fuse, a diploid a/α cell is formed, which divides mitotically to generate diploid cells by budding. When the diploid cells are in nutrient-deficient conditions, they undergo meiosis and generate four haploid spores called ascospores (two a and two α), which are contained in a saclike structure called ascus. The spores, when released from the ascus, either divide by mitosis and generate new haploid cells or fuse with a cell of opposite mating type and form a new diploid (Mell and Burgess 2002). The production of sexual spores is an important taxonomic characteristic in the identification of yeasts at a genus level. The industrial yeast strains PE-2, CAT-1, VR-1 and BG-1 are heterothallic, that is, haploid cells are not able to reverse the mating type due to mutations in the HO gene, which encodes an endonuclease that stimulates the mating-type change in homothallic strains (Herskowitz 1988). These strains are diploid and sporulate well

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and rapidly, producing asci with two, three or four spores. Crossings can occur between spores of the same ascus when the number of spores in the ascus is even; if there are three spores in the ascus, one of them can fuse with spore of opposite mating type from another ascus or even from another yeast strain, increasing the heterozygosity of the populations. With these events, new combinations of genes and new variant strains can arise, which can present better adaptability to the fermentative environment or undesirable characteristics. The fact that the yeast enters a cycle of meiosis affects the original balance of genes in these superior strains, which can result in the loss of the original genetic characteristics of the selected strain (Lopes et al. 2015). For yeast identification at species level, biochemical and physiological studies are more relevant than morphological and sexual characteristics, which are more useful in genus determination. The differences that yeasts present in fermentation and assimilation of carbon compounds are important criteria in yeast identification. Yeast grows in media containing carbon sources in the presence and absence of oxygen. When a yeast uses a carbon source fermentatively, it also uses it respiratorily, but the reverse is not true. The ability to ferment carbohydrates to ethanol and carbon dioxide is thus a very important characteristic to differentiate between yeast species. For example, Saccharomyces exhibits vigorous fermentation, while yeasts of the genera Rhodotorula and Lipomyces are strictly non-fermentative (Phale 2018). Yeasts can be classified in relation to the type of energy-generating process involved in sugar metabolism as non-fermentative, facultative fermentative or obligatory fermentative (van Dijken and Scheffers 1986). Most yeasts, including S. cerevisiae, exhibit facultative fermentative metabolism, and depending on the environmental conditions, the type and concentration of sugar and the availability of oxygen, they can utilize the full respiratory or fermentative metabolism or a mixture of them. In this context, the sugar composition of the medium and oxygen availability is the two main environmental conditions that have a profound impact on yeast physiology. In view of this, four different effects associated with the type of energy-generating process involved in sugar metabolism and oxygen availability are observed: Pasteur, Crabtree, Custer and Kluyver effects (Rodrigues et al. 2006). The Pasteur effect refers to the activation of glycolysis in anaerobic conditions in order to meet the demand for ATP, i.e. in the absence of oxygen, there is a faster consumption of sugar to compensate for the lower ATP efficiency of fermentation compared with respiration. Conversely, in the presence of oxygen, there is inhibition of fermentative metabolism. The use of fermentative metabolism even in the presence of oxygen when glucose concentrations are high is known as the Crabtree effect, and yeasts exhibiting this characteristic are known as Crabtree positive. The species S. cerevisiae exhibits both the Pasteur and Crabtree effect and is considered Crabtree positive. The Custer effect, defined as the inhibition of alcoholic fermentation in the absence of oxygen, occurs in the yeast Dekkera bruxellensis, an important contaminant of ethanolic fermentation. Fermentation is stimulated by the presence of oxygen or the addition of H+ acceptors, since yeasts exhibiting this effect are unable to close the redox balance by producing glycerol or other highly reduced compounds. The Kluyver effect is exhibited by yeasts that are able to utilize

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disaccharides under aerobic conditions but not under anaerobic conditions, despite being able to utilize one or more of the hexose components of these disaccharides under anaerobic conditions (Fukuhara 2003; Barnett and Entian 2005; Rodrigues et al. 2006; Pfeiffer and Morley 2014). The Kluyver effect can be presented by yeast for some carbohydrates and not for others, as it is the case for the metabolism of trehalose (disaccharide constituted of two glucose units) in S. cerevisiae, which can be assimilated by respiration but cannot be fermented, in contrast to glucose or maltose (Malluta et al. 2000). Sugar assimilation and fermentation tests performed for yeast identification are usually qualitative, and it is not possible to clearly distinguish fermentation with growth from fermentation without growth, i.e. to check whether growth is coupled with fermentation. These tests contribute more to the identification of non-­ Saccharomyces yeasts but add little when it comes to differentiating between S. cerevisiae strains. The intimate relationship among sugar metabolism-energy generation process-oxygen availability is of substantial relevance to industrial fermentation and deserves prominent attention to investigate the costs and benefits associated with metabolic characteristics. The nitrogen source assimilation test reveals a distinctive feature between S. cerevisiae and non-Saccharomyces yeasts, which is the inability of S. cerevisiae to assimilate nitrate and lysine as nitrogen sources (Barnett et al. 2000). Analysing not only from the taxonomic point of view, the characteristics that are distinctive in the comparison between Saccharomyces and non-Saccharomyces yeasts are used in the elaboration of culture media that allow the selective isolation of yeasts from the industrial fermentative environment. The differential and selective culture media used in the isolation and quantification of contaminant yeasts are based on physiological characteristics common to native yeasts but absent in S. cerevisiae yeasts, such as assimilation of lysine as nitrogen source, growth inhibition in the presence of actidione and differential absorption of dyes. In these media, the growth of the process yeast S. cerevisiae is inhibited, allowing the growth of contaminant yeasts, even those present in low concentrations in the fermentation medium. The Wallerstein Laboratory Nutrient Medium (WLN) contains a pH indicator, bromocresol green, which colours the colonies differentially as a result of the variable degrees of affinity between the microorganisms and the dye. This medium is differential, and because it is not selective, it allows the development of any yeast species, although it can show yeast diversity (Oliveira and Pagnocca 1988; Castro 1995). Non-Saccharomyces cerevisiae strains are detected in media with crystal violet in their formulations, such as Lin’s Wild Yeast Medium (LWYM). To differentiate non-Saccharomyces yeasts, Lysine Agar medium is widely used in fermentative processes because it contains lysine as the only source of nitrogen, which prevents the growth of most Saccharomyces species, which cannot assimilate lysine as a nitrogen source. The WLD medium (WLN + actidione) is also indicated for detection of non-Saccharomyces wild yeasts, since this species is sensitive to concentrations of actidione (also known as cycloheximide), an antifungal agent. All three

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Fig. 5.2  Petri dishes inoculated with samples of the yeast cream (after centrifugation of the fermented broth) onto the general counting medium (A-WLN, dilution 10−10) and on the selective media (B-WLD, C-LWYM and D-Lysine Agar, undiluted). (Source: From the author)

media are considered selective and, together with the WLN medium, are used in the brewing industry for detection of contaminating yeasts. The applicability of these media in the context of fermentation for bioethanol production was studied by Oliveira and Pagnocca (1988). Figure 5.2 shows the above media used for isolation of yeasts from an industrial unit. Tosta and Ceccato-Antonini (2005) analysed the efficiency of the selective media Lysine Agar, LWYM and WLD in the isolation of wild yeasts in comparison with the results of classical taxonomy tests and the amplification of rDNA ITS region by PCR (polymerase chain reaction). Strains isolated from wine and yeast cream using the selective media belonged exclusively to non-Saccharomyces genera, with sizes of the ITS region ranging from 420 to 550 bp. S. cerevisiae strains isolated exclusively from WLN presented ITS size above 800 bp, characteristic of this and other species of the Saccharomyces sensu stricto group. The selective media allowed the distinction between wild yeast strains and S. cerevisiae.

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5.3 Electrophoretic Karyotyping The determination of the complete set of chromosomes (karyotype) of a cell or organism is an important parameter in species identification. Cytological analyses to determine the karyotype are not applicable to fungi because fungal chromosomes are too small to be observed by microscopy. Agarose gel electrophoresis is the most widespread technique for the separation of DNA molecules in relation to their size. The matrix formed by the agarose is acting as a molecular filter, by means of which the DNA molecules are passing through the pores in direction of the opposite pole to their charge, by application of an electric field. As the DNA molecules present a negative charge, they migrate towards the positive pole. As the difficulty of transposing the agarose matrix towards the positive pole is inversely proportional to the size of the molecule, there is a separation of smaller molecules, which migrate more rapidly, from larger molecules, which have a longer migration time (Magalhães et al. 2005). The definition of the agarose concentration to be used in electrophoresis depends on the size of the DNA fragments to be evaluated. An agarose gel in the concentration of 0.8% (w/v) is indicated for separation of fragments in the range of 0.5 to 20–30  kb, approximately. Fragments smaller than 0.5  kb are separated in higher concentrations of agarose (2.5–3%), while for fragments up to 50 kb, the indicated concentration of agarose is 0.5%, which results in a fragile gel and extremely long run time (Magalhães et al. 2005). The yeast S. cerevisiae presents chromosomes in the range of 225–1900 kb (Fig. 5.3a), which makes the karyotype determination by conventional agarose gel electrophoresis unfeasible. A new type of agarose gel electrophoresis was proposed in the mid-1980s by Schwartz and Cantor (1984), which consists in the application of alternating, perpendicularly oriented electrical pulses of sufficient duration to allow the separation of DNA molecules from 30 to 2000 kb. This technique, called pulsed-field gel electrophoresis (PFGE), has greatly facilitated the evaluation of the yeast karyotype. In the 1990s, through a collaboration with the Institut National de la Recherche Agronomique (INRA), in Montpelier, France, a Brazilian Professor (Luiz Carlos Basso, from the University of São Paulo) started to apply the pulsed-field electrophoresis technique to monitor and identify yeast strains from Brazilian industrial fermentations in partnership with the company Fermentec (Piracicaba, São Paulo State, Brazil). The use of this technique meant a great advance in the understanding of the microbiology of fermentation in the sense of showing that the baker’s yeast and the selected strains of other fermentations did not survive more than 2–3 weeks into the fermentation tanks and were replaced by wild yeasts with better fermentative performance and adaptation to the stresses of the process. Moreover, with the monitoring through karyotyping, it was possible to establish a selection program for new yeast strains, which resulted in the isolation of the industrial strains PE-2 (1994), CAT-1 (1998), FT858L (2007) and Fermel (2014), among others (Lopes et al. 2015).

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Fig. 5.3  Pulsed-field gel electrophoresis of yeasts. In (a) karyotype of S. cerevisiae strain YP80 showing the 16 chromosomes with sizes ranging from 225 to 1900 kb, with emphasis on the two chromosomes whose bands are indistinguishable in the range 1100–1120 kb and 1640–1900 kb. The numbers in parentheses next to the chromosome size, in kilobases, refer to the chromosome number. In (b), karyotyping of different yeast species, being S. cerevisiae in wells 1–8 and non-­ Saccharomyces in wells 9–11. (Sources: (a) New England Biolabs®, (b) Lopes et al. 2015, with permission from Fermentec)

Karyotyping easily allows the distinction between S. cerevisiae yeasts and non-­ Saccharomyces contaminants due to the fact that they present distinct chromosome patterns, either in size or in number (Fig. 5.3b). Another advantage of pulsed-field gel electrophoresis is that it allows the evaluation of differences in chromosome size between S. cerevisiae strains, i.e. it allows the evaluation of intraspecific polymorphisms (Fig.  5.4). These polymorphisms can be the result of chromosome rearrangements that occurred post-meiosis or post-mitosis. Codon et al. (1997) analysed the genomic constitution of two baker’s yeasts and their sexual spores and verified the presence of chromosomal bands absent in the parents and the disappearance of bands present in the parents in the spores. The authors attributed the occurrence of these events to two phenomena in particular: (1) the presence of multiple transposable elements Ty1 and Ty2 that may have undergone interchromosomal translocation and amplification, giving rise to differences in chromosome size, and (2) the presence of multiple subtelomeric regions Y', giving rise to asymmetric homologous recombination and consequently differences in chromosome size between the parents and their spores. Chromosome reorganization occurs with very high frequency during meiosis. Industrial yeasts have reduced the number of Ty transposable elements (Stambuk et al. 2009; Babrzadeh et al. 2012); however, they sporulate easily, especially the strain PE-2. Lopes (2000) found that a single cycle of meiosis and sporulation generated several chromosomal rearrangements such as size change, gain and loss of

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Fig. 5.4  Karyotyping profile of the industrial yeast PE-2 isolated from industrial fermentations (a, c, e and g) showing chromosomal rearrangements (indicated by arrows) compared to the original profile of the strain without rearrangements (b, d, f and h). (Source: Lopes et al. 2015, with permission from Fermentec)

chromosomes, which were also observed in strains isolated from ten distilleries where strain PE-2 was introduced during three consecutive harvests, i.e. variants of PE-2. After four chromosomal rearrangements, it became difficult to distinguish between the PE-2 variant strains and the contaminant S. cerevisiae strains. Chromosomal rearrangements allow the amplification of genes involved in responses to environmental stresses and are associated with telomeric sequences, since the centromeric region is more conserved. Through pulsed-field electrophoresis karyotyping, strains with very similar profiles to PE-2 have been identified, i.e. derived from the PE-2 strain by pressure of the specific fermentation conditions, showing greater tolerance and adaptation to the industrial fermentative environment (Lopes et al. 2015). Meiotic recombination can be a source of adaptive mechanism that generates chromosomal arrangements with higher adaptability to industrial environment. For strains that do not sporulate easily in the industrial environment, mitotic recombination may be the main source of chromosomal rearrangements. Yeasts cultivated in successive batches under stressful conditions showed a heterogeneous pattern of chromosome variation depending on the strain and the culture conditions. Variations in chromosome number and length were observed along cell generations of three industrial S. cerevisiae strains (JP-1, IA1238 and MF1(1), isolated from a

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distillery in the State of Paraíba, Brazil), mainly in small- and medium-size chromosomes, using pulsed-field electrophoresis. Chromosomal polymorphisms were evident both in aerobiosis and anaerobiosis, and for two of the strains, the variants emerging replaced the parental strain along the process. The larger chromosomes (12, 4, 7 and 15) showed no instability, and the presence of an extra set of chromosomes was also detected compared to the standard yeast. These additional chromosomes resulted from unequal recombination events, such as non-reciprocal translocations (Lucena et al. 2007). In the above work, three main points concerning the occurrence of chromosome rearrangements are discussed: (1) When a new chromosome rearrangement occurs, the cell acquires a new genetic conformation that leads to different future rearrangement patterns. (2) Convergent chromosome rearrangements can come from different genomic backgrounds. (3) All the variants showed a decrease in the number of chromosomes, showing that mitotic chromosome rearrangements lead to a simplification of the karyotype. Thus, mitotic recombination can be a primary source of chromosomal rearrangements, which can be induced in the laboratory under simulated industrial fermentation conditions with cell recycling. Chromosomal rearrangements may be one of the factors involved in the adaptation of the yeast cell to the industrial environment. If this is a common occurrence in the industrial fermentative environment and if the parental strain can disappear along the cycles and be replaced by the variants arising from the chromosomal rearrangements, the karyotyping may have its applicability impaired in the context of ethanolic fermentation due to the imprecision and interpretation of the results in the definition as to be a contaminant strain or a derivative of the introduced strain (Lucena et  al. 2007). Thus, it becomes necessary and important to use another technique to assist in the task of characterization of fermentation yeasts.

5.4 Mitochondrial DNA Mitochondrial DNA (mtDNA) represents a small fraction of the yeast genome, approximately 15% of the total (Williamson 2002). Around 50–200 copies of mtDNA are estimated in the haploid cell of S. cerevisiae, but this number can vary with the strain and culture conditions (Moraes 2001; Solieri 2010). The yeasts of the Saccharomyces sensu stricto group contain mtDNA of sizes ranging from 64 to 85 kb, containing a high number of restriction sites recognized by HaeIII and Msp1 enzymes (Piskur et al. 1998). The yeasts of the Saccharomyces sensu stricto group comprise the species S. cerevisiae, Saccharomyces paradoxus, Saccharomyces cariocanus, Saccharomyces mikatae, Saccharomyces arboricolus, Saccharomyces kudriavzevii, Saccharomyces eubayanus and Saccharomyces uvarum, with S. cerevisiae being the most prominent member of this complex due to its close relationship with industrial activities (Borneman and Pretorius 2015). Saccharomyces zygotes result from the fusion of two parental cells, each possessing its own mtDNA.  After hybridization, the hybrids possess both parental

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mtDNA, but after about 20 generations, cells with only one parental mtDNA are found (Nunnari et al. 1997; Solieri 2010). The mtDNA is considered one of the most popular molecular markers for the study of molecular diversity. It presents a high rate of nucleotide substitution (Johnson et al. 2003), and due to the fast rate of mtDNA evolution in relation to nuclear DNA, the application of restriction enzymes to mtDNA can reveal a genetic profile (fingerprinting) that allows the differentiation between yeast strains (Lee and Knudsen 1985). Restriction fragment length polymorphism-mtDNA (RFLP-mtDNA) has been extensively used to differentiate industrial strains of S. cerevisiae in wine, cachaça and ethanol fermentations (Querol et  al. 1992; Vezinhet et  al. 1992; Fernández-­ Espinar et al. 2001; Schuller et al. 2004; Araujo et al. 2007; Lopes 2010; Lopes et al. 2015). Restriction enzymes HinfI, HaeIII and RsaI are the most widely used to differentiate S. cerevisiae strains (Querol et al. 1992; Guillamón et al. 1994; Fernández-­ Espinar et al. 2001). It is considered a simple, reliable and fast method that allows differentiating and monitoring the persistence and dominance of specific strains during the fermentation process. For the RFLP-mtDNA analysis, it is not necessary to isolate the mtDNA, and it can be performed from the total DNA by means of a method developed by Querol et al. (1992). After extracting the total DNA from the yeast, restriction enzymes that recognize a large number of regions in the nuclear DNA, but few regions in the mtDNA, are used. Yeast mtDNA is rich in regions with AT bases and has low percentage of regions with GC bases (Evans 1983). If restriction enzymes rich in GC bases are used, the nuclear DNA will be broken into many small fragments due to the greater number of GC restriction sites in the nuclear DNA, with difficult visualization by agarose gel electrophoresis. This will allow visualization of the clear and defined bands of mtDNA, which in smaller numbers overlaps the shadow generated by the large number of restriction fragments in nuclear DNA (Fernández-Espinar et al. 2006). Araujo et al. (2007) used RFLP-mtDNA (with the restriction enzyme HinfI) to study the dynamics of S. cerevisiae populations in cachaça production, which allowed the observation of a high diversity of strains, monitoring the predominance of specific strains in the vats and correlating the morphological types with a specific RFLP-mtDNA pattern. Lopes (2010) used RFLP-mtDNA and karyotyping (PFGE) to monitor yeast strains from a fuel ethanol production process and verified that the RFLP-mtDNA technique allowed the distinction of yeasts that could not be obtained with karyotyping, with which they presented nonspecific profiles. Figure 5.5 shows comparative RFLP-mtDNA patterns between S. cerevisiae strains from culture collection and industrial strains, showing that it is possible to distinguish even between industrial strains PE-2, CAT-1, BG-1 and SA-1. In the industrial context of fermentation for ethanol production, the RFLP-­ mtDNA technique has been used together with karyotyping for monitoring yeast during the sugarcane harvest. The chromosomes follow the Mendelian laws of independent segregation, different from the mtDNA, which is more conserved. Thus,

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Fig. 5.5  Agarose gel electrophoresis (a) showing the patterns generated by RFLP-mtDNA using the restriction enzyme HinfI in S. cerevisiae strains from culture collection (1 and 2) and from industry (3–6) in comparison with the Saccharomyces boulardii species (7). In (b), schematic representation of the electrophoretic bands referring to the agarose gel in (a). (M) refers to the λHindIII molecular weight standard. (Source: Lopes 2010)

using both techniques, it is possible to distinguish between strains related to the selected strain and native strains with no kinship (Lopes et al. 2015). Schuller et al. (2004) evaluated the discriminatory power of different methods, including RFLP-mtDNA (with HinfI enzyme) and karyotyping for 23 commercial wine yeast strains. Only karyotyping allowed the discrimination of one of the three commercial strains indistinguishable by other methods, indicating the importance of using complementary methods for the evaluation of yeast diversity.

5.5 Microsatellites Microsatellites are DNA regions composed of small sequences of 1–6 nucleotides repeated in tandem and that are spread in the genome of prokaryotes and eukaryotes (Buschiazzo and Gemmell 2006). Also known as SSR (simple sequence repeats) or STR (short-tandem repeats), they have higher mutation rates than the rest of the genome and are flanked by unique and conserved sequences, which allows amplification by PCR and constitute excellent molecular markers (Antonangelo 2012).

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Microsatellites are hypervariable in length and may have arisen due to DNA replication errors, exhibiting a high level of polymorphism among individuals of the same species. In S. cerevisiae, microsatellites are non-uniformly distributed in abundance along chromosomes and in mitochondrial DNA and thus may have an important application in characterization and discrimination among strains of this yeast (Hennequin et al. 2001; Jubany et al. 2008; Richards et al. 2009; Antonangelo et al. 2013). Although microsatellites have been used for genotyping S. cerevisiae strains in wine fermentation for at least two decades (González-Techera et al. 2001; Legras et al. 2005; Jubany et al. 2008), the application of this technique to discriminate between S. cerevisiae strains from ethanolic fermentation for fuel ethanol production is much more recent (Silva-Filho et al. 2005; Antonangelo 2012; Antonangelo et al. 2013; Reis et al. 2017). The first report of the use of microsatellite molecular markers in ethanol production is by Silva-Filho et al. (2005), who used the oligonucleotide (GTG)5 to characterize S. cerevisiae yeast populations during the fermentation process in six distilleries. Basilio et al. (2008) also used (GTG)5 associated with DNA sequencing and rDNA restriction analysis to characterize S. cerevisiae yeasts from ethanol fermentation with a high level of reliability. Souza-Liberal et  al. (2007) distinguished two main patterns of bands using (GTG)5, which they named Sc (S. cerevisiae) and Db (D. bruxellensis). The authors found that for the Sc pattern, there was a set of conserved bands that could be used for S. cerevisiae species recognition and a set of polymorphic bands used for intraspecific discrimination. The Db pattern corresponded to isolates of D. bruxellensis, an important fermentation contaminant yeast, indicating that the two species could be distinguished by typing using the microsatellite (GTG)5. For D. bruxellensis, the bands generated by the microsatellite also allowed intraspecific discrimination. A study conducted by Antonangelo (2012) used a set of microsatellite markers to evaluate the genetic diversity and population structure of S. cerevisiae strains from ethanol-producing units. Initially, 11 pairs of oligonucleotides flanking, 11 microsatellite loci were used in the genome of S. cerevisiae using 4 industrial strains, BG-1, CAT-1, PE-2 and SA-1. Four polymorphic loci were found, which were named A, C, F and H, meaning that the strains showed distinct electrophoretic bands when the oligonucleotides A, C, F and H were used. These polymorphic loci were then used for microbiological monitoring in an industrial unit, collecting samples weekly in 2008. The São Manoel Distillery (Botucatu, State of São Paulo, Brazil) started the fermentation process with a mixture of 50% of the PE-2 strain and 50% of the CAT-1 strain, but after 30 days, the emergence of strains with a genetic profile distinct from CAT-1 and PE-2 was observed, concomitantly with a decrease in the percentage of PE-2 and increase in the CAT-1 concentration. At the end of the season, even the CAT-1 strain represented approximately 18% of the total population of the introduced yeasts, and it was possible to observe 13 different microsatellite profiles. Then, 13 new pairs of oligonucleotides were tested in addition to the 4 mentioned above, and the tests were performed with strains isolated from different distilleries, localities and sugarcane harvests, to evaluate both diversity and population

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Fig. 5.6  Amplification analysis of microsatellite loci P3 (in a) and H (in b) in industrial strains BG-1, CAT-1, PE-2 and SA-1 (wells 1–4) and native S. cerevisiae strains (wells 5–29), in 3% agarose gel containing molecular weight standard (PM) 100 bp. (Source: Antonangelo 2012)

structure. Figure 5.6 shows the electrophoresis pattern of the P3 and H microsatellite loci, where it can be observed that the native strains 11, 16, 21, 25, 26, 27 and 28,and 11, 15, 16, 17, 18, 23, 27 and 29 showed different patterns from the selected strains, respectively, for the P3 and H loci. Among the 24 microsatellite loci studied, 12 of them were polymorphic and able to differentiate between selected and native strains of S. cerevisiae. The results of the microsatellite multiple loci were examined by the Bayesian method of individual grouping, which showed the presence of great diversity among the strains, which were grouped according to the place of origin and year of sampling. For example, the population isolated from the Rio Pardo unit in 2010 showed great genotypic variation compared to 2011, but with low intrapopulational variation, and the individuals were genetically similar. The same can be observed for the São Manoel unit when comparing the 2008 and 2009 harvests, but the intrapopulational variation was large (Antonangelo 2012). The analysis of the population structure revealed genotypic differences between populations, which could be combined with fermentative performance, enabling the selection of native strains with desirable industrial characteristics.

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5.6 Other Molecular Methods for Yeast Identification and Characterization of Ethanolic Fermentation Although the most recommended methods for the characterization of yeasts from ethanol fermentation are karyotyping, RFLP-mtDNA and microsatellites, other molecular methods can be used because they allow obtaining unique patterns for the isolated strains. Minisatellites, which are composed of sequences of 10–100 nucleotides, can also be useful for monitoring yeast communities. Carvalho-Netto et al. (2013) compared the genome-coding sequences of the selected strain PE-2 (JAY270) with the sequences of the laboratory strain S. cerevisiae S288c in order to detect genes containing insertion or deletion polymorphisms larger than 24 bp. The authors designed oligonucleotides that flanked nine of these sites and amplified them by PCR, compared the electrophoretic banding patterns of the selected major strains with native strains and found good discriminatory power by this molecular approach. These molecular markers enabled the monitoring of yeast populations in six bioethanol distilleries. The developed method could be applied with economy and efficiency in industrial laboratories. Costa-Silva et al. (2010) used the Intron Splice Site EI-1 oligonucleotide to discriminate between different Saccharomyces and non-Saccharomyces species, with specific banding patterns for the yeasts analysed; however, the EI-1 oligonucleotide was not discriminatory at the intraspecific level. The discovery that rDNA (ribosomal DNA) is highly conserved but contains certain variable segments among yeast species led to the use of rDNA sequencing for phylogeny and taxonomic purposes. The genes encoding rDNA (or rRNA) are the most abundant in the eukaryotic genome. In S. cerevisiae, they are presented in a single cluster occupying about 60% of chromosome 12 and 10% of the total genome, comprising approximately 150 repetitive units (copies) of the gene blocks. The rDNA encodes the ribosomal RNAs that form the structure of ribosomes, being transcribed into a 35S unit that is then processed to form three mature rRNAs named 18S, 5.8S and 26S. A small rRNA, 5S, is transcribed independently and, together with 35S, forms the structure of the ribosome. This is a protein-RNA complex that translates the messenger RNA into protein and is abundant in the cells. To meet this biosynthetic demand, eukaryotic cells contain hundreds of copies of ribosomal genes organized in clusters (Kobayashi 2011). Figure  5.7 shows a representative scheme of the rDNA arrangement in yeasts. Each repetitive unit is composed of the 26S (LSU, large subunit), 18S (SSU, small subunit), 5.8S and 5S genes, in addition to the internal transcribed spacer regions ITS1 and ITS2, the intergenic spacer regions IGS1 and IGS2 and the external transcribed spacer regions (ETS) located at the 18S and 26S ends (James et al. 2009; Matos-Perdomo and Machín 2019) (Fig. 5.7). The ITS regions constitute internal transcribed sequences that are not translated into rRNA subunits and can be amplified by specific primers. They are located between small (18S) and large (26S) subunits and separated by the 5.8S gene. The

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Fig. 5.7  Representative schematic of the rDNA arrangement in yeasts. (a) Location of the single rDNA cluster on chromosome 12. (b) Representation of the copies (repetitive units), approximately 150 in number in tandem along the chromosome. (c) Representation of a basic unit, of size 9.1 kb, showing the transcription unit (35S) represented by the 18S (small subunit, SSU), 5.8S and 26S (large subunit, LSU) genes, separated by internal transcribed spacer regions (ITS1 and ITS2), in addition to external transcribed spacer regions (ETS) located at the 18S and 26S ends. The 35S transcription unit and the 5S gene are separated by intergenic spacer regions (IGS1 and IGS2). The D1/D2 domain comprises a region of about 600 nucleotides within the 26S large subunit. (Source: From the author)

D1/D2 domain sequences within the large subunit are also used for the same purpose (Fig.  5.7). This domain has approximately 600 nucleotides, and in general, strains from the same species do not show differences of more than three nucleotides (0–0.5%). Strains with six or more non-contiguous substitutions (1%) belong to different species. Usually, ITS sequences do not offer higher resolution than sequences obtained by D1/D2 domain sequences. For closely related species, it is advisable to sequence both the D1/D2 domain and the ITS region. The smaller subunit (18S) and the IGS region do not allow good separation of the species (Kurtzman and Fell 2006). The ribosomal genes present a highly conserved region, allowing the design of specific primers, alternating with variable regions and demonstrating low intraspecific polymorphism and high interspecific polymorphism. After amplification by PCR, the sequencing of ribosomal genes allows the identification of yeasts at species level by comparison with the sequences deposited in databases such as GenBank, EMBL or DDBJ (Beh et al. 2006). In addition, the evaluation of the size of the PCR product of the ITS1 and ITS2 regions also allows the identification of the yeast species in defined contexts. Souza-­ Liberal et al. (2005) developed a rapid DNA extraction protocol from mixed cultures that allows the amplification of the ITS region and evaluation of the electrophoretic bands in 8 h. The determination of the ITS region size in the electrophoresis gel enables distinguishing between the process yeast and contaminant yeast, since S. cerevisiae presents this PCR product with about 800–850 bp, while non-Saccharomyces contaminants from 400 to 700  bp. This method does not identify the yeasts, but provides information about the presence of contaminants in

References

99

Fig. 5.8  Agarose gel electrophoresis (1.5%) of the PCR products of the ITS region (including the 5.8S gene) of S. cerevisiae (in rectangles) and non-Saccharomyces (the other strains) yeast strains. The numbers and letters over the wells refer to the yeast codes, except for M1 (50-bp molecular weight marker) and M2 (100-bp molecular weight marker). (Source: Meneghin 2007)

the process, and thus identification and characterization techniques need to be associated. Figure 5.8 illustrates an agarose gel of the ITS region of S. cerevisiae yeasts with PCR product of about 800 bp compared to non-Saccharomyces strains with lower PCR product size. The employment of restriction enzymes to the PCR product obtained from the amplification of the internal transcribed spacer regions ITS1 and ITS2 including the 5.8S rDNA gene results in unique patterns for yeast species, allowing the identification of yeasts. Esteve-Zarzoso et al. (1999) identified a total of 132 yeast species belonging to 25 different genera using the restriction patterns obtained with the enzymes CfoI, HaeIII and HinfI in the ITS region including the 5.8S gene. Basilio et al. (2008) used the enzymes DraI, MspI and HaeIII + HinfI in the ITS region and obtained specific length patterns of the restriction fragments, which were coincident with the different typing patterns generated by using the microsatellite (GTG)5. Any technique has advantages and limitations, which stimulate the search for new markers with high discrimination power that meet the criteria of low cost, easy experimental conduct and rapid execution.

References Antonangelo, A.T.B.F.: Genotipagem de leveduras presentes no processo industrial de produção de álcool combustível e estudo do polimorfismo de genes envolvidos no processo fermentativo em Saccharomyces cerevisiae. Thesis, Universidade Estadual Paulista Julio de Mesquita Filho (2012) Antonangelo, A.T.B.F., Alonso, D.P., Ribolla, P.E.M., Colombi, D.: Microsatellite marker-based assessment of the biodiversity of native bioethanol yeast strains. Yeast. 30, 307–317 (2013)

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Araujo, R.A.C., Gomes, F.C.O., Moreira, E.S.A., Cisalpino, P.S., Rosa, C.A.: Monitoring Saccharomyces cerevisiae populations by mtDNA restriction analysis and other molecular typing methods during spontaneous fermentation for production of the artisanal cachaça. Braz. J. Microbiol. 38, 217–223 (2007) Babrzadeh, F., Jalili, R., Wang, C., Shokralla, S., Pierce, S., Stambuk, B.U.: Whole-genome sequencing of the efficient industrial fuel-ethanol fermentative Saccharomyces cerevisiae strain CAT-1. Mol. Gen. Genomics. 287, 485–494 (2012) Barnett, J.A.: A history of research on yeasts 8: taxonomy. Yeast. 21, 1141–1193 (2004) Barnett, J.A., Entian, K.D.: A history of research on yeasts 9: regulation of sugar metabolism. Yeast. 22, 835–894 (2005) Barnett, J.A., Payne, R.W., Yarrow, D.: Yeasts: Characteristics and Identification, p.  1139p. Cambridge University Press, Cambridge (2000) Basilio, A.C.M., Araujo, P.R.L., Morais, J.O.F., Silva-Filho, E., Morais Jr., M.A., Simões, D.A.: Detection and identification of wild yeast contaminants of the industrial fuel ethanol fermentation process. Curr. Microbiol. 56, 322–326 (2008) Beh, A.L., Fleet, G.H., Prakichaiwattana, C., Heard, G.M.: Evaluation of molecular methods for the analysis of yeasts. In: Hocking, A.D., Pitt, J.I., Samson, R.A., Thrane, U. (eds.) Advances in Food Mycology, pp. 69–106. Springer, New York (2006) Borneman, A.R., Pretorius, I.S.: Genomic insights into the Saccharomyces sensu stricto complex. Genetics. 199, 281–291 (2015) Buschiazzo, E., Gemmell, N.J.: The rise, fall and renaissance of microsatellites in eukaryotic genomes. BioEssays. 28, 1040–1050 (2006) Carvalho-Netto, O.V., Carazolle, M.F., Rodrigues, A., Bragança, W.O., Costa, G.G.L., Argueso, J.L., Pereira, G.A.G.: A simple and effective set of PCR-based molecular markers for the monitoring of the Saccharomyces cerevisiae cell population during bioethanol fermentation. J. Biotechnol. 168(4), 701–709 (2013) Castro, M.M.S.: Leveduras contaminantes do processo de fermentação alcoólica: diversidade taxonômica e metabólica. Dissertation, Universidade Estadual de Campinas (1995) Codon, A.C., Benitez, T., Korhola, M.: Chromosomal reorganization during meiosis of Saccharomyces cerevisiae baker’s yeasts. Curr. Genet. 32(4), 247–259 (1997) Costa-Silva, R.B., Melo Jr., M.R., Morais Jr., M.A.: Utilização do intron splice site primer EI-1 na discriminação de leveduras contaminantes do processo de fermentação alcoólica. Cienc. Tecnol. Aliment. 30(3), 761–765 (2010) Esteve-Zarzoso, B., Belloch, C., Uruburu, F., Querol, A.: Identification of yeasts by RFLP analysis of the 5.8S rRNA gene and two ribosomal internal transcribed spacers. Int. J. Syst. Bacteriol. 49, 329–337 (1999) Evans, I.H.: Molecular genetic aspects of yeast mitochondria. In: Spencer, J.F.T., Spencer, D.M., Smith, A. (eds.) Yeast Genetics – Fundamental and Applied Aspects, pp. 269–370. Springer, New York (1983) Fernández-Espinar, M.T., López, V., Ramón, D., Bartra, E., Querol, A.: Study of the authenticity of commercial wine yeast strains by molecular techniques. Int. J.  Food Microbiol. 70(1-2), 1–10 (2001) Fernández-Espinar, M.T., Martorell, P., de Lannos, R., Querol, A.: Molecular methods to identify and characterize yeasts in foods and beverages. In: Querol, A., Fleet, G. (eds.) Yeasts in Food and Beverages, pp. 55–82. Springer, Berlin (2006) Fukuhara, H.: The Kluyver effect revisited. FEMS Yeast Res. 3, 327–331 (2003) González-Techera, A., Jubany, S., Carrau, F.M., Gaggero, C.: Differentiation of industrial wine yeast strains using microsatellite markers. Lett. Appl. Microbiol. 33, 71–75 (2001) Guillamón, J.M., Barrio, E., Huert, T., Querol, A.: Rapid characterization of four species of the Saccharomyces sensu stricto complex according to mitochondrial DNA patterns. Int. J. Bacteriol. 44, 708–714 (1994) Hennequin, C., Thierry, A., Richard, G.F., Lecointre, G., Nguyen, H.V., Gaillardin, C., Dujon, B.: Microsatellite typing as a new tool for identification of Saccharomyces cerevisiae strains. J. Clin. Microbiol. 39(2), 551–559 (2001)

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Herskowitz, I.: Life cycle of the budding yeast Saccharomyces cerevisiae. Microbiol. Rev. 52, 536–553 (1988) James, S.A., O’Kelly, M.J.T., Carter, D.M., Davey, R.P., van Oudenaarden, A., Roberts, I.N.: Repetitive sequence variation and dynamics in the ribosomal DNA array of Saccharomyces cerevisiae as revealed by whole-genome resequencing. Genome Res. 19, 626–635 (2009) Johnson, J.A., Toepfer, J.E., Dunn, P.O.: Contrasting patterns of mitochondrial and microsatellite population structure in fragmented populations of greater prairie-chickens. Mol. Ecol. 12, 3335–3347 (2003) Jubany, S., Tomasco, I., Ponce de Leon, I., Carrau, F., Arrambide, N., Naya, H., Gaggero, C.: Toward a global database for the molecular typing of Saccharomyces cerevisiae strains. FEMS Yeast Res. 8, 472–484 (2008) Kobayashi, T.: Regulation of ribosomal RNA gene copy number and its role in modulating genome integrity and evolutionary adaptability in yeast. Cell. Mol. Life Sci. 68, 1395–1403 (2011) Kurtzman, C.P.: Recognition of yeast species from gene sequence comparisons. Open Appl. Inf. J. 5, 20–29 (2011) Kurtzman, C.P., Fell, J.W.: Yeast systematics and phylogeny  – implications of molecular identification methods for studies in ecology. In: Rosa, C.A., Gábor, P. (eds.) Biodiversity and Ecophysiology of Yeasts, pp. 11–30. Springer, Berlin (2006) Lee, S.Y., Knudsen, F.B.: Differentiation of brewery yeast strains by restriction endonuclease analysis of their mitochondrial DNA. J. Inst. Brew. 91, 169–173 (1985) Legras, J.L., Ruh, O., Merdinoglu, D., Karst, F.: Selection of hypervariable microsatellite loci for the characterization of Saccharomyces cerevisiae strains. Int. J.  Food Microbiol. 102, 73–83 (2005) Lopes, M.L.: Estudo do polimorfismo cromossômico em S. cerevisiae (linhagem PE-2) utilizada no processo industrial de produção de etanol. Thesis, Universidade Estadual Paulista Julio de Mesquita Filho (2000) Lopes, D.D.: Estudo molecular e morfológico de leveduras de processos fermentativos de produção de etanol. Dissertation, Universidade Estadual de Londrina (2010) Lopes, M.L., Paulillo, S.C.P., Cherubin, R.A., Godoy, A., Amorim Neto, H.B., Amorim, H.V.: Tailored Yeast strains for Ethanol Production: The Process-Driven Selection. Fermentec, Piracicaba (2015) 41p Lucena, B.T.L., Silva-Filho, E.A., Coimbra, M.R.M., Morais, J.O.F., Simões, D.A., Morais Jr., M.A.: Chromosome instability in industrial strains of Saccharomyces cerevisiae batch cultivated under laboratory condition. Genet. Mol. Res. 6(4), 1072–1084 (2007) Magalhães, V.D., Ferreira, J.C., Barelli, C., Darini, A.L.C.: Eletroforese em campo pulsante em bacteriologia – uma revisão técnica. Revista Instituto Adolfo Lutz. 64(2), 155–161 (2005) Malluta, E.F., Decker, P., Stambuk, B.U.: The Kluyver effect for trehalose in Saccharomyces cerevisiae. J. Basic Microbiol. 40(3), 199–205 (2000) Matos-Perdomo, E., Machín, F.: Nucleolar and ribosomal DNA structure under stress: yeast lessons for aging and cancer. Cell. 8, 779 (2019) Mell, J.C., Burgess, S.M.: Yeast as a model genetic organism. In: Encyclopedia of Life Sciences, pp. 1–7. Wiley, Hoboken (2002) Meneghin, M.C.: Caracterização e comportamento fermentativo de linhagens de Dekkera contaminantes da fermentação alcoólica. Dissertation, Escola Superior de Agricultura “Luiz de Queiroz” – Universidade de São Paulo (2007) Moraes, C.T.: What regulates mitochondrial DNA copy number in animal cells. Trends Genet. 17, 199–205 (2001) New England BioLabs: Yeast Chromosome PFG Marker. Disponível em: https://www.neb. com/products/n0345-­yeast-­chromosome-­pfg-­marker#Product%20Information. Accessed 31 Mar 2020. Nunnari, J., Marshall, W.F., Straight, A., Murray, A., Sedat, J.W., Walter, P.: Mitochondrial transmission during mating in Saccharomyces cerevisiae is determined by mitochondrial fusion and

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fission and the intramitochondrial segregation of mitochondrial DNA. Mol. Biol. Cell. 8(7), 1233–1242 (1997) Oliveira, M.C.F.L., Pagnocca, F.C.: Aplicabilidade de meios seletivos empregados na indústria cervejeira para detecção de leveduras selvagens em unidades sucroalcooleiras. Anais do VIII Simpósio Nacional de Fermentação, 78–81 (1988) Pfeiffer, T., Morley, A.: An evolutionary perspective on the Crabtree effect. Front. Mol. Biosci. 1, 17 (2014) Phale, S.: Yeast: characteristics and economic significance. J.  Bioprocess. Biotechniq. 8(5), 1000337 (2018) Piskur, J., Smole, S., Groth, C., Petersen, R.F., Pedersen, M.B.: Structure and genetic stability of mitochondrial genomes vary among yeasts of the genus Saccharomyces. Int. J. Syst. Bacteriol. 48, 1015–1024 (1998) Querol, A., Barrio, E., Huerta, T., Ramon, D.: Molecular monitoring of wine fermentations conducted by active dry yeast strains. Appl. Environ. Microbiol. 58(9), 2948–2953 (1992) Reis, V.R., Antonangelo, A.T.B.F., Bassi, A.P.G., Colombi, D., Ceccato-Antonini, S.R.: Bioethanol strains of Saccharomyces cerevisiae characterised by microsatellite and stress resistance. Braz. J. Microbiol. 48, 268–274 (2017) Richards, K.D., Goddard, M.R., Gardner, R.C.: A database of microsatellite genotypes for Saccharomyces cerevisiae. Antonie Van Leeuwenhoek. 96, 355–359 (2009) Rodrigues, F., Ludovico, P., Leão, C.: Sugar metabolism in yeasts: an overview of aerobic and anaerobic glucose catabolism. In: Rosa, C.A., Gábor, P. (eds.) Biodiversity and Ecophysiology of Yeasts, pp. 101–122. Springer, Berlin (2006) Schuller, D., Valero, E., Dequin, S., Casal, M.: Survey of molecular methods for the typing of wine yeast strains. FEMS Microbiol. Lett. 231, 19–26 (2004) Schwartz, D.C., Cantor, C.F.: Separation of yeast chromosome-sized DNAs by pulsed field gradient gel electrophoresis. Cell. 37, 67–75 (1984) Silva-Filho, E.A., Santos, S.K.B., Resende, A.M., Morais, J.O.F., Morais Jr., M.A., Simões, D.A.: Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR fingerprinting. Antonie Van Leeuwenhoek. 88, 13–23 (2005) Solieri, L.: Mitochondrial inheritance in budding yeasts: towards an integrated understanding. Trends Microbiol. 18, 521–530 (2010) Souza-Liberal, A.T., Silva-Filho, E.A., Morais, J.O.F., Simões, D.A., Morais Jr., M.A.: Contaminant yeast detection in industrial ethanol fermentation must by rDNA-PCR.  Lett. Appl. Microbiol. 40, 19–23 (2005) Souza-Liberal, A.T., Basílio, A.C.M., Monte Resende, A., Brasileiro, B.T.V., Silva-Filho, E.A., Moraes, J.O.F., Simões, D.A., Morais Jr., M.A.: Identification of Dekkera bruxellensis as a major contaminant yeast in continuous fuel etanol fermentation. J.  Appl. Microbiol. 102(2), 538–547 (2007) Stambuk, B.U., Dunn, B., Alves, J.S.L., Duval, E.H., Sherlock, G.: Industrial fuel ethanol yeasts contain adaptive copy number changes in genes involved in vitamin B1 and B6 biosynthesis. Genome Res. 19, 2271–2278 (2009) Tosta, C.D., Ceccato-Antonini, S.R.: Eficiência de meios seletivos no monitoramento de leveduras na fermentação alcoólica atestada por PCR.  Anais do XV Simpósio Nacional de Bioprocessos. (2005) van Dijken, J.P., Scheffers, W.A.: Redox balances in the metabolism of sugars by yeasts. FEMS Microbiol. Rev. 32, 199–224 (1986) Vezinhet, F., Hallet, J.N., Valade, M., Poulard, A.: Ecological survey of wine yeast strains by molecular methods of identification. Am. J. Enol. Vitic. 43, 83–86 (1992) Williamson, D.: The curious history of yeast mitochondrial DNA. Nat. Rev. Genet. 3, 1–7 (2002)

Chapter 6

Microbiological Techniques and Methods for the Assessment of Microbial Contamination

6.1 Introduction The permanent microbiological monitoring and the improvement of its methods allow the follow-up of yeast quality and the detection of native yeasts, i.e. the differentiation between process yeast and contaminant yeast, which is not always easy. The differential or selective culture media for isolation and quantification of contaminant yeast populations are based on physiological characteristics common to native yeasts but absent in process yeasts, initiators of fermentation. Among these, nutritional characteristics (variations in the carbon and nitrogen sources and in the growth factors) and resistance to certain compounds such as antibiotics and dyes stand out. However, a single medium is not totally satisfactory for the evaluation of all the yeasts present; therefore, it is necessary the use of several types of media when it is intended to detect most of the yeasts present. In general, the selective or differential media can be classified into media for the detection of non-Saccharomyces contaminant yeasts and media for the detection of contaminant yeasts of the Saccharomyces genus, and in the first case, we can mention the Lysine Agar and WLN + actidione (WLD) media and, in the second case, the LWYM (Lin’s Wild Yeast Medium) medium. The determination of the bacterial number present in the various stages of the industrial process is important to evaluate the efficiency of the treatment of the sugarcane juice and the points of recontamination. In the case of contamination, the use of antimicrobial agents reduces the damage caused by contaminants, but there is a need to determine which is the most correct antimicrobial and dosage, aiming at the rational application of these products. The choice of the microbiological monitoring method will depend on how easy it is to implement at the industrial unit. It is very important to train the analysts/laborators in the proper performance of the techniques in the off-season period, in

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7_6

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addition to constant supervision by specialists during the harvest. Besides that, the work should be done during the whole harvest, evaluating since the starter ferment.

6.2 Techniques for Assessing Yeast Viability in the Fermentation Process Direct Counting Under a Microscope There is no absolute method for determining the cell viability of a population of yeast cells. To estimate the proportion of viable cells in a culture or fermentation process, methods based on plating or microscopic observation have been used. Direct counting methods are fast and simple, require minimal equipment and allow cell morphology to be observed simultaneously. Cell viability is extremely important because the tolerance of yeast to its fermentation product, ethanol, is very significant in relation to the efficiency of alcohol production in industrial-scale fermentations. It has also been verified that the presence of higher alcohols (n-butanol, isoamyl), fatty acids and their esters even at low concentrations, together with ethanol, acts in a synergistic manner intoxicating the yeast cell, leading it to death and consequently reducing cell viability. In the monitoring of yeast cell viability, the staining of the cells with methylene blue or erythrosine has been extensively employed because of the ease and speed of analysis. The methylene blue staining technique (Lee et al. 1981) consists in mixing equal parts of the properly diluted yeast suspension (sample) and the staining solution (methylene blue). Cells with high physiological activity are not stained, while inactive (dead) cells will be stained blue (Fig. 6.1). The percentage or number of viable cells is determined by transferring the sample with the aid of a pipette into the Neubauer chamber. This is a special slide, precisely divided in squares of 1 mm2

Fig. 6.1  Determination of yeast cell viability with methylene blue. The blue-stained cells are dead cells, while the colourless ones are viable cells. 400× magnification under optical microscope. (Source: From the author)

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Fig. 6.2  Neubauer chamber. (a) External appearance. (b) Counting grid, with the circle indicating the approximate area (central square split in 25 small squares) covered by the 100-fold microscope magnification (10× ocular and 10× objective) of a standard counting chamber. (c) Appearance of a small square as seen at 400× microscope magnification, with the rectangle indicating a reticle. (Sources: (a) and (c) From the author, (b): https://www.emsdiasum.com/microscopy/technical/ datasheet/68052-­14.aspx)

of area (Fig. 6.2); the slide is covered with a glass cover that leaves a volume of 10−4 cm3 or 0.1 mm3 on each square (equivalent to 0.0001 mL or 10−4 mL). Analytical Procedure 1. Homogenize the sample in a tube shaker. If it is flocculated, add papain (5 mg), and allow to stand for 5 min. 2. Make convenient dilution in a test tube with distilled water. 3. After dilution, transfer 1 mL to a test tube, and add 1 mL of the methylene blue sodium citrate solution. Wait for 5 min. 4. Homogenize the mixture in a tube shaker. 5. Place the coverslip in the Neubauer chamber, and using a Pasteur pipette, transfer a small volume of the sample prepared with the dye. 6. Under the optical microscope and with a 40× objective, count the cells in the central square in one of the following ways: five small squares in the second column and five small squares in the fourth column (total of ten squares), or four central reticules in each of the 25 small squares (total of 100 reticules), or five small squares, one in each corner and one central. Choose 2 limits in each square where the cells found on top of the limits will be discarded. For example, count the cells that are on the upper and left side limits of the grid, and discard those on the lower- and right-side limits.

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7. Write down the number of viable cells (cells that do not stain with methylene blue), non-viable cells (cells stained intense blue) and viable budding cells. 8. Cell viability indicates the percentage of active cells in the yeast population of the sample considered and can be calculated as follows: Viability ( % ) = ( Number of live cells / Number of live cells + non − viable cells ) × 100





9. The budding cell count indicates the percentage of active yeasts that are multiplying and is thus calculated: Budding ( % ) = ( Total viable cells in budding / Total viable cells ) ×100





10. The yeast population of the sample considered is calculated as follows:

No.of viable cells / mL = ( Total viable cells × 4000 / Total number of reticles counted ) × 103 × dilution



or

No.of viable cells / mL = Total of .viable cells in 10 small squares × 2.5 × dilution × 104



or

No.of viable cells / mL = ( Total viable cells in 5 small squares / 5 ) × 25 × dilution × 104



Comments 1. There must be no formation of bubbles in the Neubauer chamber under the glass cover after placing the sample. 2. Dilution is carried out so that the number of cells is adequate for the highest accuracy range of the methodology, i.e. between 300 and 500 cells should be counted per chamber, and not less than 80 reticles should be counted. The dilution of the sample must be such that around 60 cells per small square or 3 cells per reticle are counted. 3. Consider the dilution of the sample with the dye, i.e. a dilution factor of 2 (1 part sample/1 part dye) in the calculations. This factor should be multiplied by the dilution factor of the sample initially in distilled water. For example, a dilution in the ratio of 1-mL sample to 9-mL distilled water (factor 10) × dilution of the sample with dye (factor 2) → total dilution: 20.

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Serial Dilution and Plating on Culture Media Plate-based colony-counting methods are based on the principle that each colony is considered to originate from a single viable cell. The number of viable cells present in a suspension is generically referred to as colony-forming units (CFU). The quantification of CFU necessarily involves the aseptic preparation of a suspension of cells, which is then serially diluted, and an aliquot of each dilution is spread on the Petri dish. After incubation, the number of colonies is counted, always assuming that each colony is originated from a single cell (Fig. 6.3). Plate seeding or plating reveals the number of cells capable of multiplying and forming colonies on appropriate culture media and under appropriate incubation conditions. For best accuracy of the analysis, only plates with a number of colonies between 30 and 300 should be counted. The sample should be diluted before mixing with the culture medium. The drop plate method can be used as an alternative to streak plating. The advantages of using the drop plate is that less time and effort are required to dispense drops onto the surface of the culture medium compared to spreading the inoculum. Thus, colony counts can be performed more quickly and accurately. In addition, two plates are used for four dilutions, while in spread plating, a total of eight plates are used for four dilutions (Herigstad et al. 2001). The advantage of plate counting is that only viable cells are counted, allowing isolation of colonies which can be subcultured into pure cultures, facilitating study and identification. However, some disadvantages are presented: (1) there is no medium that allows growth of all microorganisms, (2) proper incubation is required to allow colony development, (3) a lot of glassware is used and it is relatively

Fig. 6.3  Scheme of the serial dilution and plating by spreading of the inoculum. (Source: Madigan et al. 2004, modified)

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labour-­intensive, and (4) a lot of manipulation is required, which can lead to erroneous counts due to dilution and/or plating errors. Selective and differential media have been developed for the purpose of selecting and differentiating yeasts from fermentative processes. The Wallerstein Laboratory Nutrient Medium (WLN) contains a pH indicator, bromocresol green, which stains the colonies differentially as a result of the variable degrees of affinity between the microorganisms and the dye. However, this medium, being non-selective, allows the development of any yeast species. The differentiation between process yeast and contaminant yeast is not easy, and the presence of contaminant yeast can be detected by using selective media, i.e. the employed media should allow the development of contaminant yeast only. However, a single medium is not completely satisfactory for the evaluation of all the yeasts present, so it is necessary to use several types of media when one wants to detect, if not all, but most of the contaminant yeasts present. The selective media for isolation and quantification of contaminant yeast populations are based on physiological characteristics common to wild yeasts but absent in strains used in fermentative processes for alcohol production. Among these characteristics, nutritional ones (variations in carbon and nitrogen sources and in essential growth factors) and resistance to certain compounds such as antibiotics, dyes, etc. stand out. Among the media proposed for the detection of contaminant yeasts, Saccharomyces or non-Saccharomyces, the WLD, LWYM and Lysine Agar stand out. The efficiency of the differential and selective culture media in the isolation of yeasts from ethanolic fermentation is presented in Table 6.1. Analytical Procedure 1. Centrifuge 10 mL of the sample at 4000 rpm for 5 min. 2. Discard the supernatant, add distilled water or sterile saline solution (NaCl 0.85%), homogenize and centrifuge again under the same conditions. 3. Resuspend the cells to 10 mL with sterile water or saline. 4. Transfer 1 mL of the centrifuged sample to a culture tube with 9 mL of water or sterile saline solution (1:10 dilution or 10−1). 5. Homogenize in a tube shaker.

Table 6.1  Efficiency of differential/selective culture media in the isolation of yeasts from alcoholic fermentation Means WLN WLD LWYM Lysine Agar

Saccharomyces cerevisiae (+) (−) (−) (−)

Other Saccharomyces (+) (−) (+) (-)

Non- Saccharomyces (+) (+) (+) (+)

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6. Pipette 1 mL of the previous dilution into another tube with 9 mL of water or sterile saline solution, and a 1:100 or 10−2 dilution will be obtained. Higher dilutions may be obtained by taking 1 mL of each successive dilution and placing into tubes with 9 mL of water or saline solution until the desired dilution is reached. 7. Seed in Petri dishes by pipetting 1 mL of each dilution, and add the appropriate culture medium liquefied and cooled to a temperature of 45–46 °C. Shake the plate with horizontal movements to distribute the cells evenly (deep plating or also called pour-plating). Seed at least two plates for each of the three dilutions chosen. The procedures are illustrated in Fig. 6.3. 8. An alternative is to initially place the culture medium in the Petri dishes, wait for solidification and then pipette 0.1  mL spreading the inoculum with a Drigalsky loop (surface plating). Fig. 6.4 shows the techniques used for surface and deep plating (pour plate). 9. Incubate the inverted plates at 30–32 °C for 48–72 h. 10. Count the colonies on each plate, and to estimate the number of CFU, choose the dilution that presents from 30 to 300 colonies. Take the average of the number of colonies of the plates in duplicate. Table 6.2 provides the guidelines for interpreting and reporting the plate count. The yeast count is expressed as follows: Pour plate:



No.CFU yeast / mL = Average of the number of colonies / dilution

Fig. 6.4  Pour-plating technique (a) and surface plating technique (b). (Source: Tortora et al. 2003, modified)

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Table 6.2  Guidelines for interpreting the plating results (1-mL sample/plate) and reporting the count in CFU/mL Interpretation 1. Two plates of the same dilution have between 30 and 300 colonies

Example Dilution 10−2 Plate 1 = 180 Plate 2 = 140 2. At the same dilution, 1 plate has Dilution 10−2 between 30 and 300 colonies and the Plate 1 = 70 other < 30 or > 300. Count the two Plate 2 = 26 plates 1.3. Plates of two consecutive (a) Mean dilutions have between 30 and 300 dilution 10−3 colonies. Count all four plates = 35 Mean dilution 10−2 = 250 (b) Mean dilution 10−3 = 38 Mean dilution 10−2 = 150 4. No colonies on plates of the most Dilution 10−1 concentrated suspension (of the Plate 1 = < 1 lowest dilution) Plate 2 = < 1 1.5. Two plates of the highest (a) dilution dilution have more than 300 10−3 colonies. Split the plates radially (2, Plate 1 = 4, 8), and count the number of 180 on 1/4 colonies per section of plate Plate 2 = 160 on 1/4 of plate (b) Dilution 10−3 More than 200 on 1/8 of the plate 6. Presence of scattered colonies in Dilution 10−2 an area smaller than half the plate. Plate 1 = Count the other half (half) = 60 ×2 Plate 2 = 180 Source: Gaviria (1978), modified

Calculation Arithmetic mean Mean = 160

Arithmetic mean Mean = 48

How to report Standard plate count: 1.6 × 104

Standard plate count: 4.8 × 103

Ratio 10−3/10−2 = Standard 35,000/25,000= 1.4 plate count: If the ratio is < 2, take the 3.0 × 104 average of the two dilutions

Ratio 10−3/10−2 = 38,000/15,000 = 2.5 If the ratio is >2, use the dilution result with the highest number of colonies counted Mean = < 1

Arithmetic mean Plate 1 =180 × 4= 720 Plate 2 =160 × 4= 640 Mean = 680

Standard plate count: 1.5 × 104

Estimated plate count: < 1.0 × 10 Estimated plate count: 6.8 × 105

>200 on 8 = 1600

Estimated plate count: >1.6 × 106

Arithmetic mean Mean = 150

Presence of scattered colonies: 1.5 × 104

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Surface plating:

No.CFU yeast / mL = ( Average number of colonies / dilution ) ×10



11. Alternatively, plating can be done by the drop plate method. Sample dilutions are made as described in the previous sub-items. The Petri dishes containing the culture medium should be divided in four parts, so that each quadrant is reserved for a dilution of the series. Transfer three to five portions (drops) of 10 μL of each of the four selected dilutions to one of the quadrants, carefully, taking care not to disperse the drop and maintaining distance between each of the portions deposited on the plate. Plate in duplicates. After the drops have dried, the Petri dishes are inverted and incubated at the appropriate temperature. Count the colonies, and choose the dilution that originates between 3 and 30 colonies per 10 μL of volume dispensed (Fig. 6.5). Average the number of colonies from the drops and the duplicate plates of the selected dilution. The yeast count is expressed as follows:

No.CFU yeast / mL = ( Average number of colonies / dilution ) ×100



Comments 1. The choice of the dilutions to be plated depends on the sample considered and the number of yeasts it contains. Generally speaking, for wine samples, the following dilutions are used for each medium, in surface plating: WLN, 10−5, 10−6 and 10−7, and WLD, Lysine Agar and LWYM, direct (without dilution), 10−1 and Fig. 6.5  Result of plating a yeast inoculum sample using the drop plate method. In each quadrant of the plate, three drops of 10 μL of the sample from each dilution (10−1, 10−2, 10−3 and 10−4 ) were deposited. The dilution that presents between 3 and 30 colonies is the 10−4 (the number in parentheses refers to the number of colonies in each drop). The number of yeasts can be expressed as 5.3 × 106 CFU/mL. (Source: From the author)

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10−2. For juice or must samples, use the same dilutions for WLD, Lysine Agar and LWYM, but for WLN, plate the dilutions 10−3, 10−4 and 10−5. For yeast cream samples, use the dilutions of 10−5, 10−6 and 10−7 for WLN and the same dilutions as above for the selective media. 2. Centrifugation of the samples before serial dilution is important due to the selective media, because cell washing removes residues from the sample that may interfere with yeast growth, leading to erroneous results. 3. It is common the growth of very small colonies on the plates with Lysine Agar originated from S. cerevisiae cells that grew due to cell reserves or traces of impurities in the culture medium, since these yeasts cannot assimilate the lysine present in the medium as the only source of nitrogen.

6.3 Techniques for Assessing the Viability of Bacteria in the Fermentation Process Direct Counting Under a Microscope Direct microscopic counting of bacteria has great applicability for quantification of rods in primary and mixed juice and wine samples. For clarified juice and must where the population is normally less than 104–105 rods/mL, this technique is less accurate. Greater precision and reproducibility are achieved when the number of rods/mL of the sample is between 106 and 107. The sample should be conveniently diluted so that no more than three to five rods are found per microscope field. Staining of bacterial cells with Nile blue + methylene blue is performed so that viable cells will appear colourless, while non-viable cells will be stained blue (Oliveira et al. 1996). Analytical Procedure 1. For primary or mixed juice samples, initially perform homogenization. 2. If necessary, filter the sample through cotton wool to remove suspended solid impurities. 3. Dilute the sample with distilled water (dilution is performed so that the number of bacterial cells is no greater than three to five per microscope field) if necessary. 4. Transfer 1 mL of filtered and diluted sample into a test tube. 5. Transfer 1 mL of the staining solution (Nile blue + methylene blue) into the test tube containing 1 mL of the filtered sample. 6. Homogenize in a tube shaker.

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7. Transfer 2 μL (20 × 20-mm glass cover), or 3 μL (22 × 22-mm glass cover), or 4 μL (24 × 24-mm glass cover) of the stained sample to a glass slide. 8. Place the glass cover over the preparation, taking care not forming bubbles. 9. Count the number of uncoloured rods present in 70 fields, uniformly distributed throughout the glass cover area, using the immersion objective (100×). 10. If a raw wine sample shows flocculation, papain must be added to the sample. Allow to stand for 5 min before diluting. 11. The number of rods/mL can be calculated as follows:

No.rods / mL = FM × (1 / sample volume ) × M × D



FM = microscope factor (will depend on the type of microscope used for counting: for polychromatic microscopes, it is 15,000, while for monochromatic, it is 20,000). M = total number of uncoloured rods/number of counted fields D = final dilution (consider the 2× dilution with dye, which should be multiplied by the dilution factor in distilled water)

Serial Dilution and Plating on Culture Media To avoid errors in bacteria counting, the use of low-carbohydrate culture media is recommended, so that there is no great production of capsule and eventual adherence of cells to each other. One of the most commonly used media for cultivating bacteria is Nutrient Agar, consisting of peptone, meat extract and agar. This simple formulation provides the nutrients necessary for cultivating a large number of bacteria that are not very nutritionally demanding. The meat extract contains water-­ soluble substances, including carbohydrates, vitamins, organic nitrogen compounds and salts. Peptones are the main source of organic nitrogen (amino acids and long-­ chain peptides), and agar is the solidifying agent. Another medium widely used for the cultivation of bacteria is Plate Count Agar, consisting of tryptone, yeast extract vitamins and glucose, which favours the growth of most bacteria. Analytical Procedure Proceed as described in Sect. 6.2 (starting at sub-item 4), but there is no need to centrifuge the sample initially. Dilutions can be made directly from the sample. The culture media used are Plate Count Agar or Nutrient Agar, in dilutions ranging from 10−2 to 10−7, depending on the sample (primary juice, mixed juice, must, wine, yeast cream, etc.). Both spread plating and drop plate plating can be used.

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6.4 Gram Staining Gram staining is a method widely used in the identification of bacteria. It is a differential staining method that uses a primary dye (crystal violet) and a counterstain (safranin). After using crystal violet, a lugol solution is applied, which is called a mordant because it combines with the dye to form an insoluble coloured compound. After decolourization with alcohol, the safranin counterstain is applied. Cells that resist decolourization and retain the crystal violet-iodine complex are purple and are called Gram-positive. Those cells that display no colour and lose the crystal violet-­ iodine complex are stained by safranin and turn red. They are the Gram-negative bacteria. The scheme of the Gram staining procedure is shown in Fig. 6.6. Most living cells, including animal tissues, are Gram-negative. It is the Gram-­ positive characteristic that is distinctive. Some bacteria, yeasts and some filamentous fungi are Gram-positive. Gram staining is not performed routinely but when contamination problems are detected. In addition to determining the Gram stain, this technique also allows the morphology of the cells (coccus, rod, presence of spores, etc.) to be assessed more easily. Fig. 6.6  Gram staining. (a) Procedure. (b) Photomicrograph of Gram-negative bacteria. (c) Photomicrograph of Gram-positive bacteria. The photos were taken under immersion objective (1000× magnification). (Source: From the author)

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Analytical Procedure 1. Place a drop of water on a glass slide, previously cleaned with alcohol for degreasing. 2. With the platinum loop, aseptically remove a small portion of the bacterial culture, and emulsify it in the drop to obtain a uniform suspension. Spread it sufficiently to obtain a thin smear. Do not forget to write down on the slide the origin of the smear. 3. Dry the preparation in the air or on the flame of the gas nozzle. 4. Fix the smear by passing the slide three times directly into the flame. 5. Before staining, allow the slide to cool completely. 6. For staining, cover the smear with the crystal violet solution. Wait for 1 min. 7. Carefully wash off the excess dye with distilled water. 8. Cover the smear with lugol solution. Wait for 1 min. 9. Remove the dye by washing the slide with cold water. 10. Cover the smear with absolute ethanol for 10 s. 11. Rinse thoroughly with cold water. 12. Cover the smear with safranin solution. Wait for 1 min. 13. Remove the excess dye with cold water. 14. Hold the preparation to dry at room temperature, or dry the slide carefully (without rubbing) between two sheets of absorbent paper. 15. Examine under the optical microscope using the objective for immersion (100×), dripping a drop of immersion oil on the slide, without placing the glass cover. 16. Check the staining of the bacteria, whether blue-violet (Gram-positive) or red (Gram-negative). Comments 1. Bacterial cultures with 18–24 h of culture should be used, because young cells have a higher affinity for dyes than old cells. 2. Depending on the stage of development, bacteria can show variable Gram reaction.

6.5 Tests of Susceptibility to Antimicrobials with Bacteria Antimicrobial susceptibility testing can be performed both to select the most efficient product to inhibit microbial growth and to define the lowest concentration of the antimicrobial agent (minimum inhibitory concentration (MIC)) that under defined conditions inhibits the growth of the bacteria being investigated. The MIC values are used to determine the susceptibility of bacteria to drugs and also to evaluate the activity of new antimicrobial agents. The test can be performed in solid medium, where different concentrations of the antimicrobial substance are incorporated into the culture medium, followed by the application of a standard number of

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cells on the surface of the culture medium. In liquid medium, bacteria are inoculated into the growth broth in the presence of different concentrations of the antimicrobial agent. Growth is determined after incubation for a given period of time (16–20 h), and the MIC value is checked. The action of antimicrobials can be performed through the spectrophotometric reading of the optical density (absorbance) of a microbial suspension inoculated with or without the test product. The higher the bacterial development, the higher will be the turbidity of the medium, and consequently the higher will be the absorbance reading. Therefore, the greater the antimicrobial effect of the product tested, the lower the turbidity, and the lower the absorbance reading.

Analytical Procedure Preparation of the Inoculum 1. Collect a sample of wine from the vats at the end of fermentation, must or yeast cream, and homogenize. 2. Transfer 5 mL of the sample to culture tube and add papain (approximately 5 mg). 3. Homogenize in a tube shaker and wait for 5 min. 4. Transfer 1  mL of the sample to test tube containing 15  mL of sterile culture medium. 5. Transfer 0.15 mL of the actidione stock solution, and incubate the tube at 35 °C for approximately 12 h. 6. Add papain and homogenize in tube shaker. Test Performance 1. Transfer with pipette 0.15 mL of the actidione stock solution to each tube with 13.2 mL of the sterile culture medium. 2. Transfer 1.5 mL of the stock solution of the 10× concentrated antimicrobial. For example, if the concentration of the antimicrobial to be tested is 5  mg/L, the stock solution should be prepared at 50 mg/L. 3. Transfer 0.15 mL of the prepared inoculum and homogenize in a tube shaker. The final volume of the tube will be 15 mL. 4. Aseptically remove a sample from each tube, and take the (initial) absorbance reading of the control sample (without addition of the antimicrobial by placing the same volume of distilled water) and of the treatments (several concentrations of the same antimicrobial or different antimicrobials at defined concentrations) in the spectrophotometer at 540 nm immediately after homogenization. 5. Transfer the tubes with the control and treatment samples to an incubator at 35 °C for 6 h. The tubes should be capped with cotton wool.

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6. Remove the tubes from the incubator and homogenize in a tube shaker. 7. Take the (final) absorbance reading in the control and treatment tubes immediately after homogenization. 8. The efficiency of the product tested by this methodology can be evaluated by the variation in absorbance (ΔABS), as follows, considering that the lower the variation in absorbance, the more efficient the product is in controlling the bacterial microbiota present in the sample tested:

∆ABS = ( ABSfinal − ABSinitial ) ×100





9. To perform an MIC test for a specific antimicrobial, proceed as described in Table 6.3 for the preparation of the control tubes and treatments. Then, proceed as described in the previous sub-items. As an example, the antimicrobial will be tested in concentrations from 2 to 10 mg/L. The MIC will be the concentration in which ΔABS will be the lowest. If necessary, repeat the procedures with higher concentrations of the antimicrobial in order to have ΔABS close to zero. Comments 1. If the test is performed with pure cultures of bacteria and not with the industrial samples, leave the bacterial culture to grow in the culture medium (inoculum) for about 12 h before transferring it to the tubes with the antimicrobials. There is no need to add papain and actidione, since these products are used to deflocculate the sample and inhibit the development of process yeasts, respectively. 2. It is recommended to use three repetitions for each treatment and work with the averages for each treatment and the control. 3. The spectrophotometer shall be calibrated for zero absorbance with the culture medium used, without inoculum and antimicrobials. 4. The cuvette of the spectrophotometer must be washed with the sample to be read, to avoid dilution effect when using distilled water washing. 5. There are several culture media that can be used, such as Nutrient Broth, GLT and MRS (the latter for lactic bacteria). Table 6.3  Test preparation for determining the minimum inhibitory concentration (MIC) of a specific antimicrobial in the range of 2–10 mg/L Volume (mL) Concentration of the antimicrobial (mg/L) 0 2 4 6 8 10

Culture medium 13.2 13.2 13.2 13.2 13.2 13.2

Actidione solution 0.15 0.15 0.15 0.15 0.15 0.15

Stock solution of Inoculum the antimicrobiala 0.15 0 0.15 0.3 0.15 0.6 0.15 0.9 0.15 1.2 0.15 1.5

Sterile distilled water 1.5 1.2 0.9 0.6 0.3 0

Prepare a stock solution at a concentration of 100 mg/L, following the instructions as to the best way to solubilize the product a

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6.6 Composition of Culture Media and Solutions Methylene Blue + Sodium Citrate Solution Weigh 0.01-g methylene blue, dissolve in a small quantity of sterile distilled water, add 2-g sodium citrate, homogenize and make up to 1000 mL with sterile distilled water. Store preferably in a clean, dark flask. Saline Solution Weigh 8.5 g of sodium chloride, dissolve in distilled water, make up to 1 l, dispense into tubes or flasks and sterilize at 120 °C, 1 atm, for 15 min. Nile Blue + Methylene Blue Solution Solution A: 2% Nile blue sulphate – weigh 2 g of Nile blue sulphate, and dissolve in 100 mL of sterile distilled water. Solution B: 0.2% methylene blue – weigh 0.2 g of methylene blue, and dissolve in 100 mL of sterile distilled water. Working solution: Mix equal parts of solutions A and B, leave to stand for 24 h, and filter through filter paper. This solution can be stored for 12 months in a closed bottle, but if microbial contamination is detected, it must be discarded immediately. Crystal Violet Solution Solution A: Weigh 2 g of crystal violet and add 20 mL of 95% alcohol. Solution B: Weigh 0.8 g of ammonium oxalate, and dissolve in 80 mL of sterile distilled water. Mix the two solutions and store in a clean dark bottle. Lugol Solution Dissolve 2  g of potassium iodide in a small portion of sterile water, add 1  g of iodine, and make up to 300 mL of sterile distilled water. Store in clean, dark bottle. Safranin Solution Dissolve 2.5 g of safranin in 100 mL of 95% ethanol. Dilute 10 mL of this solution to 100 mL with sterile distilled water. Store in clean, dark bottle. Actidione (Cycloheximide) Solution Weigh 0.1 g of actidione, transfer to a 100 mL volumetric flask, dissolve in a portion of sterile distilled water, and complete the volume to 100 mL with sterile distilled water. Store in refrigerator for a maximum of 30 days. The concentration of this solution is 1 g/L (1000 mg/L). Stock Solution of the Antimicrobial Weigh 0.01 g of the antimicrobial, transfer to a 100 mL volumetric flask, add a few drops of ethanol to solubilize, if necessary (check the manufacturer’s recommendations for product solubilization), dissolve with sterile distilled water, and complete the volume to 100 mL. The solution should be prepared on the day the test will be performed or at most 1 day before and stored under refrigeration. After use, discard

6.6  Composition of Culture Media and Solutions

119

the solution. This stock solution has a concentration of 100 mg/L. Prepare the stock solution with a concentration 10× higher than the highest concentration to be tested. Culture Medium GLT Weigh 2.5-g yeast extract, 5-g tryptone and 1-g dextrose (glucose), dissolve completely, and make up to 1000-mL distilled water. Transfer the required volume to test tubes and cover with cotton wool. Sterilize the tubes in the autoclave at 121 °C, 1  atm, for 15  min. To prepare the solid medium, add 20  g agar to 1000  mL of medium before sterilization. Nutrient Broth Medium or Nutrient Agar Weigh 5-g peptone, 3-g meat extract and 1-g sodium chloride, dissolve completely, and make up to 1000-mL distilled water. Transfer the required volume into test tubes and cover with cotton wool. Sterilize the tubes in the autoclave at 121 °C, 1 atm, for 15 min. To prepare the solid medium (Nutrient Agar), add 20 g of agar to 1000 mL of medium before sterilization. Man-Rogosa-Sharpe (MRS) Medium Weigh 10-g peptone, 10-g meat extract, 5-g yeast extract, 20-g glucose, 1-mL Tween 80, 2-g potassium monoacid phosphate, 5-g sodium acetate, 2-g diammonium citrate, 0.2-g magnesium sulphate and 50-mg manganese sulphate, dissolve completely, and make up to 1000 mL. Transfer the required volume to test tubes and seal with cotton wool. Sterilize the tubes in the autoclave at 121  °C, 1  atm, for 15  min. To prepare solid medium, add 20  g agar to 1000  mL of medium before sterilization. Plate Count Agar Medium Weigh 5-g casein peptone, 2.5-g yeast extract and 1-g glucose, dissolve completely, add 20-g agar, and make up to 1000 mL. Sterilize in the autoclave at 121 °C, 1 atm, for 15 min. WLN Medium (Wallerstein Laboratory Nutrient Medium) According to Green and Gray (1950) Modified by Oliveira and Pagnocca (1988) Weigh 4-g yeast extract, 5-g hydrolysed casein, 50-g glucose, 0.55-g monopotassium phosphate*, 0.425-g potassium chloride*, 0.125-g calcium chloride bihydrate*, 0.125-g magnesium sulphate heptahydrate*, 2.5-g ferric chloride hexahydrate*, 2.5-g manganese sulphate tetrahydrate* and 22-mg bromocresol green*, dissolve completely, and make up to 1000 mL of distilled water. Add 20 g of agar, the antibiotics ampicillin* and nalidixic acid* at a final concentration of 5 mg/L, and sterilize in the autoclave at 121 °C, 1 atm, for 15 min. Reagents indicated with * must be added in the form of solutions prepared as follows: 1. Monopotassium phosphate solution – 5.5 g/100 mL; use 10 mL for 1000 mL of medium. 2. Ferric chloride hexahydrate solution – 4.25 g/100 mL; use 10 mL for 1000 mL of medium.

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3. Calcium chloride bihydrate solution – 1.25 g/100 mL; use 10 mL for 1000 mL of medium. 4. Magnesium sulphate heptahydrate solution  – 1.25  g/100 mL; use 10  mL for 1000 mL of medium. 5. Ferric chloride hexahydrate solution  – 0.5  g/200  mL; use 1  mL for 1000  mL of medium. 6. Manganese sulphate tetrahydrate solution – 0.5 g/200 mL; use 1 mL for 1000 mL of medium. 7. Bromocresol Green solution  – 0.2  g/100 mL; dissolve in 5-mL alcohol, and make up to 100 mL with water. Use 10 mL for 1000 mL of medium. 8. Nalidixic acid solution – grind one 500 mg tablet of pharmaceutical nalidixic acid in a mortar. Dissolve in 0.05-M NaOH solution, making up to 100 mL. Keep in refrigerator. Use 10 mL for each 1000 mL of medium to obtain 50 mg/L. The nalidixic acid solution is autoclavable and can be added to the medium before sterilization. Use 1 mL of this solution for 1000 mL of culture medium. 9. Ampicillin solution  – grind one 500-mg ampicillin pharmaceutical tablet in a mortar. Dissolve in distilled water, making up the volume to 100 mL. Use 10 mL for 1000 mL of medium, in order to obtain the final concentration of 50 mg/L. It can be autoclaved. WLD Medium According to Walters and Thiselton (1953) Modified by Morris and Eddy (1957) Add actidione in solution form to the WLN medium to a final concentration of 5 mg/L. The actidione solution should be prepared as follows: Stock solution – weigh 0.2 g and dissolve in 1-mL acetone. Add 9 mL of water, and sterilize by filtration through Millipore membrane of porosity 0.22 μ. This solution will have a concentration of 20 mg/mL. Store in refrigerator. Working solution – transfer 5 mL of the stock solution to a flask, and add 95 mL of sterile distilled water. The working solution will have the concentration of 1 mg/ mL. Use 5 mL for 1000 mL of already sterilized and liquefied medium. Store the solution in refrigerator. Lysine Agar Medium According to Walters and Thiselton (1953) Modified by Morris and Eddy (1957) This culture medium has the following composition: 11.7-g Yeast Carbon Base (YCB), 1-g lysine, 20-g agar, 50-mg ampicillin and 50-mg nalidixic acid; complete for 1000 mL of distilled water. The preparation of the medium should be done as follows: 10× concentrated YCB solution – dissolve 11.7 g of YCB in 100 mL of warm distilled water. Sterilize in Millipore membrane of porosity 0.22 μ. Use 100 mL for 1000 mL of medium. Solid medium preparation – dissolve 20-g agar and 1-g lysine to 880-mL distilled water in a water bath. Add 10 mL of ampicillin solution and 10 mL of nalidixic acid solution as previously described, autoclaving for 10  min at 1  atm and

References

121

121  °C.  After autoclaving, aseptically add 100  mL of 10× concentrated YCB solution. Lin’s Wild Yeast Medium (LWYM) According to Lin (1975) Modified by Longley et al. (1978) Weigh 2-g malt extract, 4-g yeast extract, 2-g peptone, 10-g glucose, 1-g potassium phosphate bibasic, 0.5-g ammonium chloride, 6-mg crystal violet* and 0.1-g fuchsin-­sulphite mixture, and dissolve completely in 1000-mL distilled water. Add 20 g of agar, and sterilize in the autoclave at 121 °C, 1 atm, for 15 min. Before distributing the culture medium on the plates, liquefy, cool to 55 °C, and add the antibiotics ampicillin and nalidixic acid at a final concentration of 50 mg/L each in the culture medium. The reagent indicated with * should be added in the form of a solution prepared as follows: weigh 0.6-g crystal violet, and dissolve in 100-mL distilled water. Use 1 mL of this solution for 1000 mL of culture medium. The fuchsin-sulphite mixture is composed of 1 part dextrin, 4 parts basic fuchsin and 25 parts anhydrous sodium sulphite (in weight).

References Gaviria, C.: Standards for interpreting and reporting “standard” plate counts. Available at: https:// document.onl/documents/normas-­para-­interpretacao-­de-­contagem-­em-­placa.html. Accessed 1 Apr 2020 Green, J.R., Gray, P.P.: A differential procedure applicable to bacteriological investigation in brewing. Wallerstein Lab. Comments. 13(43), 357–368 (1950) Herigstad, B., Hamilton, M., Heersink, J.: How to optimize the drop plate method for enumerating bacteria. J. Microbiol. Methods. 44, 121–129 (2001) Lee, S.S., Robinson, F.M., Wong, H.Y.: Rapid determination of yeast viability. Biotechnol. Bioeng. Symp. 11, 641–649 (1981) Lin, Y.: Detection of wild yeasts in the brewery. Efficiency of differential media. J. Inst. Brew. 81, 410–417 (1975) Longley, R.P., Dennis, R.R., Heyer, M.S., Wren, J.J.: Selective Saccharomyces media containing ergosterol and Tween 80. J. Inst. Brew. 84, 341–345 (1978) Madigan, M.T., Martinko, J.M., Parker, J.: Brock’s Microbiology, p.  608p. Prentice-Hall, São Paulo (2004) Morris, E.O., Eddy, A.A.: Method for the measurement of wild yeast infection in pitching yeast. J. Inst. Brew. 63, 34–35 (1957) Oliveira, M.C.F. L., Pagnocca, F.C.: Aplicabilidade de meios seletivos empregados na indústria cervejeira para detecção de leveduras selvagens em unidades sucroalcooleiras. Proceedings of the VIII National Symposium on Fermentations (1988), pp.78–81. Oliveira, A.J., Gallo, C.R., Alcarde, V.E., Godoy, A., Garcia, C.E.: Curso de treinamento em microbiologia. Fermentec, Piracicaba (1996). 37p Tortora, G.J., Funke, B.R., Case, C.L.: Microbiologia. Artmed, Porto Alegre (2003). 827p Walters, L.S., Thiselton, M.R.: Utilization of lysine by yeasts. J. Inst. Brew. 59, 401 (1953)

Index

A Acid treatment, 3, 11–15, 24, 25, 35, 56, 67, 72, 73, 75, 77 B Bacterial susceptibility tests to antimicrobial, 115–117 Bacterial viability determination, 104 Baker’s yeast, 21–23, 25, 26, 28–30, 89, 90 Biochemistry of fermentation, 4–8 Brazilian fermentation process, 3, 4 C Candida tropicalis, 44, 45, 56 Cell recycling, 4, 22, 43, 92 Contaminant yeasts, 44–46, 52, 55–57, 87, 95, 98, 103, 108 D Dekkera bruxellensis, 15, 44–50, 55, 56, 71, 72, 86, 95 E Electrophoretic karyotyping, 21–23, 89–92

F Factors affecting fermentation, 17 Flocculation, 10, 11, 14, 24, 25, 28, 33, 34, 49, 52–54, 63, 64, 67–69, 72, 113 G Genetically modified (GM) yeast, 37–38 H Heterofermentative bacteria, 65, 66, 69 Homofermentative bacteria, 66 I Industrial yeasts, 22, 24, 29, 33, 35, 36, 48, 52, 85, 90, 91 L Lactic acid bacteria, 15, 50, 64–66, 69, 71–72, 76 M Microbiological monitoring, 83, 95, 103 Microsatellites, 53, 84, 94–97, 99 Mitochondrial DNA, 24, 33, 53, 84, 92, 95

© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 S. R. Ceccato-Antonini, Microbiology of Ethanol Fermentation in Sugarcane Biofuels, https://doi.org/10.1007/978-3-031-12292-7

123

124 P Process-driven selection, 25, 84 R rDNA sequencing, 97 S Selected yeasts, 21, 22, 24–26, 28, 29, 31, 33, 35, 54

Index Selective media, 88, 108, 112 Snowflake yeasts, 52 Sugarcane biofuel, 1 Y Yeast-bacteria interactions, 72 Yeast characterization, 14 Yeast identification, 83, 84, 86, 87 Yeast stress resistance, 30 Yeast viability determination, 14