27.Fermentation Microbiology and Biotechnology -2011.pdf

BIOLOGICAL SCIENCES & LIFE SCIENCES
Fermentation Microbiology and Biotechnology, Third
Edition explores and illustrates the diverse array of meta-
bolic pathways employed for the production of primary
and secondary metabolites as well as biopharmaceuticals.
This updated and expanded edition addresses the whole
spectrum of fermentation biotechnology, from fermenta-
tion kinetics and dynamics to protein and co-factor
engineering.
The third edition builds upon the fine pedigree of its earlier predecessors and extends
the spectrum of the book to reflect the multidisciplinary and buoyant nature of this
subject area. To that end, the book contains four new chapters:
• Functional Genomics
• Solid-State Fermentations
• Applications of Metabolomics to Microbial Cell Factories
• Current Trends in Culturing Complex Plant Tissues for the Production of
Metabolites and Elite Genotypes
Organized and written in a concise manner, the book’s accessibility is enhanced
by the inclusion of definition boxes in the margins explaining any new concept or
specific term. The text also contains a significant number of case studies that
illustrate current trends and their applications in the field.
With contributions from a global group of eminent academics and industry experts,
this book is certain to pave the way for new innovations in the exploitation of
microorganisms for the benefit of mankind.
Fermentation
Microbiology
and
Biotechnology
Edited by
E.M.T. El-Mansi • C.F.A. Bryce • B. Dahhou
S. Sanchez • A.L. Demain • A.R. Allman
Third Edition
Fermentation
Microbiology and
Biotechnology
Third Edition
Fermentation
Microbiology
and
Biotechnology
El-Mansi
K12604
ISBN: 978-1-4398-5579-9
9 781439 855799
9 0 0 0 0
Third
Edition
C
M
Y
CM
MY
CY
CMY
K
K12604_COVER_PRINT_REV.pdf 1 11/23/11 9:26 AM

Fermentation
Microbiology
and
Biotechnology
Third Edition

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CRC Press is an imprint of the
Taylor & Francis Group, an informa business
Boca Raton London NewYork
Fermentation
Microbiology
and
Biotechnology
Edited by
E.M.T. El-Mansi • C.F.A. Bryce • B. Dahhou
S. Sanchez • A.L. Demain • A.R. Allman
Third Edition

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A man lives not only his personal life as an individual, but also, consciously
or unconsciously, the life of his epoch and his contemporaries.
Thomas Mann
Professor Dr. Mahmoud Ismael Taha,
A chemist of exactitude and graceful humility (1924–1981)
This edition is dedicated with affection and gratitude to the memory of the late
Professor Dr. Mahmoud Ismael Taha, who ignited in me a lifelong passion
for biochemistry; he often reminded me that Louis Pasteur was a chemist.
E.M.T. El-Mansi
(Editor-in-Chief)

vii
Contents
Preface...............................................................................................................................................ix
Acknowledgments.............................................................................................................................xi
Editors............................................................................................................................................ xiii
Contributors ...................................................................................................................................xvii
Chapter 1 Fermentation Microbiology and Biotechnology: An Historical Perspective ...............1
E.M.T. El-Mansi, Charlie F.A. Bryce, Brian S. Hartley,
and Arnold L. Demain
Chapter 2 Microbiology of Industrial Fermentation: Central and Modern Concepts ..................9
E.M.T. El-Mansi, F. Bruce Ward, and Arun P. Chopra
Chapter 3 Fermentation Kinetics: Central and Modern Concepts..............................................37
Jens Nielsen
Chapter 4 Microbial Synthesis of Primary Metabolites: Current Trends and
Future Prospects .......................................................................................................77
Arnold L. Demain and Sergio Sanchez
Chapter 5 Microbial and Plant Cell Synthesis of Secondary Metabolites and
Strain Improvement.................................................................................................. 101
Wei Zhang, Iain S. Hunter, and Raymond Tham
Chapter 6 Applications of Metabolomics to Microbial “Cell Factories” for
Biomanufacturing: Current Trends and Future Prospects ....................................... 137
David M. Mousdale and Brian McNeil
Chapter 7 Flux Control Analysis and Stoichiometric Network Modeling:
Basic Principles and Industrial Applications ........................................................... 165
E.M.T. El-Mansi, Gregory Stephanopoulos, and Ross P. Carlson
Chapter 8 Enzyme and Cofactor Engineering: Current Trends and Future Prospects
in the Pharmaceutical and Fermentation Industries.................................................201
George N. Bennett and Ka-Yiu San

viii Contents
Chapter 9 Conversion of Renewable Resources to Biofuels and Fine Chemicals:
Current Trends and Future Prospects.......................................................................225
Aristos A. Aristidou, Namdar Baghaei-Yazdi, Muhammad Javed,
and Brian S. Hartley
Chapter 10 Functional Genomics: Current Trends, Tools, and Future Prospects in the
Fermentation and Pharmaceutical Industries...........................................................263
Surendra K. Chikara and Toral Joshi
Chapter 11 Beyond Cells: Culturing Complex Plant Tissues for the Production of
Metabolites and Elite Genotypes .............................................................................295
Pamela J. Weathers, Melissa J. Towler, and Barbara E. Wyslouzil
Chapter 12 Cell Immobilization and Its Applications in Biotechnology:
Current Trends and Future Prospects....................................................................... 313
Ronnie G. Willaert
Chapter 13 Biosensors in Bioprocess Monitoring and Control: Current Trends and
Future Prospects.......................................................................................................369
Chris E. French and Chris Gwenin
Chapter 14 Solid-State Fermentation: Current Trends and Future Prospects ............................403
Lalita Devi Gottumukkala, Kuniparambil Rajasree, Reeta Rani Singhania,
Carlos Ricardo Soccol, and Ashok Pandey
Chapter 15 Bioreactors: Design, Operation, and Applications................................................... 417
Anthony R. Allman
Chapter 16 Control of Industrial Fermentations: An Industrial Perspective.............................. 457
Craig J.L. Gershater and César Arturo Aceves-Lara
Chapter 17 Monitoring and Control Strategies for Ethanol Production in
Saccharomyces Cerevisiae.......................................................................................489
Gilles Roux, Zetao Li, and Boutaib Dahhou
Appendix: Suppliers List............................................................................................................. 519
Index.............................................................................................................................................. 521

ix
Preface
I beseech you to take interest in these sacred domains, so expressively called laboratories.
Ask that, there be more and that they be adorned for these are the temples of the future,
wealth and well being.
Louis Pasteur
Microorganisms, free-living and immobilized, are widely used industrially as catalysts in the
biotransformation of many chemical reactions, especially in the production of stereospecific iso-
mers. The high specificity, versatility, and the diverse array of microbial enzymes (proteomes) are
currently being exploited for the production of important primary metabolites including amino
acids, nucleotides, vitamins, solvents, and organic acids, as well as secondary metabolites such as
antibiotics, hypercholesterolemia agents, enzyme inhibitors, immunosuppressants, and antitumor
therapeutics.
Recent innovations in functional genomics, proteomics, metabolomics, bioinformatics, bio-
sensor technology, nanobiotechnology, cell and enzyme immobilization, and synthetic biology
and in silico research are currently being exploited in drug development programs to combat
disease and hospital-acquired infections as well as in the formulation of a new generation of
therapeutics.
The third edition builds upon the fine pedigree of its earlier predecessors and extends the spec-
trum of the book to reflect the multidisciplinary and buoyant nature of this subject area. To that end,
four new chapters have been commissioned:
• Functional Genomics
• Solid-State Fermentations
• Applications of Metabolomics to Microbial Cell Factories
• Current Trends in Culturing Complex Plant Tissues for the Production of Metabolites and
Elite Genotypes
More exciting advances and discoveries are yet to be unraveled, and the best is yet to come as we
enter a new era in which the exploitations of microorganisms continue to astonish the world com-
munity, especially the use of renewable resources and the generation of new therapeutics to combat
disease are recognized as an urgent need. To that end, Professor Brian S. Hartley predicts the emer-
gence of a new era in which “biorefineries” play a central role in climate control and the balance of
geochemical cycles in our ecosystem.
To aid learning and to make the text more lively and interactive, boxes highlighting the defini-
tions of new and central concepts are shown in the margin, a feature that is now synonymous with
our book.
We very much hope that the third edition will be assimilated and appreciated by those actively
engaged in the pursuit of advancing our field, and to that end, the editor-in-chief wishes to stress
his readiness to receive your feedback, including suggestions by authors who wish to add or
extend the knowledge base of our book, which is becoming increasingly global with every edition.

x Preface
In future editions, our endeavor to keep our readers abreast with recent innovations in this excit-
ing and buoyant field will continue unabatedly.
The Editorial Team
MATLAB® is a registered trademark of The MathWorks, Inc. For product information, please
contact:
The MathWorks, Inc.
3 Apple Hill Drive
Natick, MA 01760-2098, USA
Tel: 508 647 7000
Fax: 508 647 7001
E-mail: info@mathworks.com
Web: www.mathworks.com

xi
Acknowledgments
The third edition builds on the seminal work presented in earlier editions and owes much to the
original and innovative work of our peers and colleagues worldwide. I wish to thank my editorial
team and our distinguished authors for their sound contributions and for being very responsive
throughout; in particular, I wish to thank Brian S. Hartley, whose encouragement and stimulating
discussions across the Internet have been inspirational. It is also befitting to thank my two sons
Adam and Sammy, for their love and the happiness, which they continue to bring to my life.
On behalf of the editorial team and authors, I wish to thank Barbra Norwitz (executive editor)
and Albert Ebinesh (project manager) and their respective teams at CRC Taylor and Francis for
transforming our manuscripts, into a high quality book, which I hope meets with your expectations
as a reader.
The editorial team are only too conscious of mistakes and omissions, which may have crept in
unnoticed; the credit of producing this book is only partly hours, it is the blame that rests totally
with us.
Have a good read.
E.M.T. El-Mansi
Editor-in-Chief

xiii
Editors
Dr. Mansi El-Mansi is a graduate of the University of Assiut, El-Minya,
Egypt (BSc, First Hons and MSc Microbiology). He was intrigued and
fascinated by the versatility of microorganisms and soon realized that
understanding their physiology demanded a clear understanding of their
biochemistry. He made the conscious decision of undertaking his PhD
in the field of microbial biochemistry and was fortunate enough to carry
it out at UCW, Aberystwyth, United Kingdom, under the supervision of
David J. Hopper, whose meticulous approach to experimental design was
a towering influence. During the course of his PhD studies, he became
familiar with the work of Stanley Dagley, the father of microbial bio-
chemistry as we know it, and this in turn galvanized his resolve to further
his understanding of microorganisms at the molecular level.
Immediately after the completion of his PhD, Dr. El-Mansi joined Harry Holms at the Department
of Biochemistry, University of Glasgow, Scotland, and such a happy and stimulating association con-
tinued for the best part of a decade, during which their group was the first to clone and show that the
structural gene encoding the bifunctional regulatory enzyme ICDH kinase/phosphatase is indeed a
member of the glyoxylate bypass operon. Soon thereafter, Dr. El-Mansi became acquainted with flux
control analysis and its immense potential in the fermentation and pharmaceutical industries. His
interest in the application of flux control analysis was further stimulated by collaboration with Henrik
Kacser, the founder of metabolic control analysis (MCA) theory, at the University of Edinburgh.
During the course of his employment in Edinburgh, Dr. El-Mansi was the first to postulate and
unravel the role of HS-CoA in the partition of carbon flux among enzymes of central metabolism
during growth of Escherichia coli on acetate. He was also the first to provide evidence supporting
Dan Kosahland’s theory of “ultrasensitivity”. His research activities, which span the best part of
30 years, yielded an extensive list of publications of which four are single-author publications in
peer-reviewed journals.
After 27 years of intensive research and teaching in Scotland, Dr. El-Mansi felt that the time was
right to share his experience with others and to enrich him culturally. He is currently a professor of
biotechnology at Sharda University, Greater Noida, India.
Dr. Charlie Bryce has held posts as Head of the School of Life Sciences
and Dean of the Faculty of Sciences for over 20 years at Edinburgh
Napier University. For the last three years he focused on International
Development for the Faculty of Health, Life and Social Sciences and,
more recently, he extended this to work with the Vice Chancellor on
developing international research and technology transfer links for all
areas of the university. He now acts as an independent, international con-
sultant for program development, learning support material development
including e-learning, continuing professional development, and quality
assessment and audit at the departmental and institutional level.
In the last 30 years, he has published 100 refereed research publica-
tions and designed and produced approximately 30 teaching packages in a wide variety of media
formats. He has undertaken an international survey of the biochemistry curriculum for science
and medical students and a pan-European survey of curriculum content for programs in biotech-
nology and is currently developing programs in biomedical science for a partner in Singapore.
Dr. Bryce has served on national and international committees including U.K. Deans of Science

xiv Editors
(chairman), U.K. Interest Group on Education in Biotechnology (chairman), Education Group of
the Biochemical Society (chairman), vice president of the European Federation of Biotechnology
(EFB), EFB Task Group on Education and Mobility (chairman), EFB Task Group on Innovation
(chairman), secretary general of the Association for Higher Education in Biotechnology
(HEduBT, the body that oversees the operation of the Eurodoctorate in Biotechnology), specialist
adviser to several British Council and COSTED Projects, member of the Editorial Board of New
Biotechnology, and former executive editor of the journal Bioinformatics. He has acted as an audi-
tor and a subject reviewer for the Quality Assurance Agency (QAA) and for the Scottish Funding
Council (SFC) and has also undertaken audit/assessment work in Bangladesh and in Hong Kong.
He currently chairs accreditation panels for the Forensic Science Society and has also undertaken
research project evaluation for the Commission of the European Communities (CEC).
Dr. Arnold Demain, research fellow in microbial biochemistry at
the Charles A. Dana Research Institute for Scientists Emeriti of Drew
University in Madison, NJ, is an icon synonymous with excellence in the
fields of industrial microbiology and biotechnology. Born in Brooklyn,
New York City, in 1927, he was educated in the New York public school
system and received his BS and MS in bacteriology from Michigan State
University in 1949 and 1950, respectively. He obtained his PhD on pec-
tic enzymes in 1954 from the University of California, having divided
his time between the Berkeley and Davis campuses. In 1956, he joined
Merck Research Laboratories at Rahway, NJ, where he worked on fer-
mentation microbiology, β-lactam antibiotics, flavor nucleotides, and
microbial nutrition. In 1965, he founded the Fermentation Microbiology
DepartmentatMerckanddirectedresearchanddevelopmenton processesfor monosodiumglutamate,
vitamin B12, streptomycin, riboflavin, cephamycin, fosfomycin, and interferon inducers. In 1969, he
joined MIT, where he set up the Fermentation Microbiology Laboratory. Since then, he has pub-
lished extensively on enzyme fermentations, mutational biosynthesis, bioconversions, and metabolic
regulation of primary and secondary metabolism. His success is evident in a long list of publications
(over 530), 14 books of which he is co-editor or co-author, and 21 U.S. patents. His ability to “hybrid-
ize” basic studies and industrial applications was recognized by his election to the presidency of
the Society for Industrial Microbiology in 1990, membership in the National Academy of Sciences
in 1994, the Mexican Academy of Sciences in 1997, and in the Hungarian Academy of Science in
2002. In recognition of his outstanding contribution to our current understanding in fermentation
microbiology and biotechnology, he has been awarded honorary doctorates from the University of
Leon (Spain), Ghent University (Belgium), Technion University (Israel), Michigan State University
(United States), Muenster University (Germany), and Drew University (United States).
Dr. Anthony (Tony) R. Allman, a graduate of the University of
Liverpool (BSc, PhD), has been a member of the Institute of Biology
and the Society of General Microbiology for more than 25 years.
He began his career at Glaxo, where he spent six years carrying out
research into the development of subunit bacterial vaccines. During
that time, he became acquainted with fermentors and their applications.
Subsequently, he acted as a specialist in this area for the U.K. agent
of a major European fermentor manufacturer. When Infors U.K. was
established in 1987, Tony joined the new company as Product Manager
(later Technical Director) and in 2002, he became Fermentation
Product Manager for the Swiss parent company, Infors AG. His work
involves providing technical support, training, and application exper-
tise in-house and throughout the world.

Editors xv
Dr. Allman is well known among research and industrial communities for having a passion for
making fermentation accessible to the wider public. His “extracurricular activities” of devising
practical workshops and giving lectures on fermentation technology speak volumes about the active
pursuit of this aim.
Dr. Sergio Sanchez, born in Mexico City, Mexico, received his
MD in 1970 and his PhD in 1973, both from the National University
of Mexico. After two postdoctoral research fellowships at the U.S.
Department of Agriculture in Peoria, IL, and then at the MIT,
Cambridge, MA, Dr. Sanchez began his career as a researcher at the
Institute of Biomedical Research, National University of Mexico and
in 1984 he co-founded the first Biotechnology Department at the same
University. He has served several times as a head of that department
and more recently as technical secretary of the same institute.
As a professor of industrial microbiology, Dr. Sanchez published
extensively and his work is characterized by a sustained level of
important discoveries in several areas of industrial microbiology,
including research on the interrelation between the role of glutathione and the amino acid transport
systems and the production of penicillin in Penicillium chrysogenum. He also explored the regula-
tory relationships between primary and secondary metabolism in Streptomyces peucetius var. cae-
sius; he was the first to show that in addition to Glk, an adjacent gene (sco2127) participates in the
process of carbon catabolite repression in this organism.
He was elected as the first president to the Mexican Society for Biotechnology and Bioengineering
(MSBB), and in recognition of his contributions, the MSBB has established the Sergio Sanchez
award to recognize the best thesis research project for pre- and postgraduate students in biotech-
nology and bioengineering in Mexico. In 1986, he co-founded the Postgraduate Biotechnology
Programme at the National University of Mexico, being its first coordinator.
Currently, he is an editor on the editorial board of Applied Microbiology and Biotechnology and
the Editor-in-Chief of BioTecnología, an international journal published by the Mexican Society for
Biotechnology and Bioengineering.
Dr. Boutaib Dahhou, a graduate of (PhD 1980) of Paul
Sabatier University–Toulouse III, France, has been addressing
various issues of supervision, control, and modeling of linear
and nonlinear systems. In his studies, Dr. Dahhou adopted a
new strategy consisting of adding a road base or a block of
supervision in which one can exploit all of the available infor-
mation. He further developed this process by modifying the
layer immediately above than the adaptive loop, which is the
layer of supervision of the control; at that level, the signals
evolved from adaptation and feedback loops are used as signal identifiers to recognize spe-
cific physiological situations and to act on the parameters of the algorithms of control and
estimation.
He recognized that, in a given system, significant signals have to be identified to test its validity
on the basis of certain preset criteria. Violation of these criteria triggers the start of a second task
by the supervisor. For example, in biotechnological processes, these anomalies can be related to
specific biological reaction or ascribed to the operation of actuators or sensors.
Currently, the detection and isolation of faults in the dynamic of nonlinear systems is of par-
ticular interest. Addressing this aspect, Dr. Dahhou developed new algorithms on the basis of the
adaptive observers that made possible the instantaneous detection of any fault. On the other hand,

xvi Editors
the isolation of these faults demanded much time because of the procedure of parameter adaptation.
To resolve this problem, he is currently developing a new approach of isolation that is based on the
parameter intervals.
Dr. Dahhou has successfully supervised 18 PhD students and published more than 72 articles in
international journals and 130 communications in international congresses.

xvii
Contributors
César Arturo Aceves-Lara
Université de Toulouse; UPS, INSA, INP,
LISBP; Toulouse, France and INRA
UMR792, Ingénierie des Systèmes
Biologiques et des Procédés
Toulouse, France
Anthony R. Allman
Infors U.K., Ltd.
Rigate, England, United Kingdom
Aristos A. Aristidou
Bioprocess Development
Centennial, Colorado
Namdar Baghaei-Yazdi
Biocaldol, Ltd., The London Bioscience
Innovation Centre
London, England, United Kingdom
George N. Bennett
Department of Biochemistry and Cell Biology
Rice University
Houston, Texas
Charlie F.A. Bryce
Edinburgh Napier University
Edinburgh, Scotland, United Kingdom
Ross P. Carlson
Department of Chemical and Biological
Engineering
Center for Biofilm Engineering
Montana State University
Bozeman, Montna
Surendra K. Chikara
Xcelrislabs, Ltd.
Ahmedabad, India
Arun P. Chopra
Department of Biotechnology
Hindustan College of Science and Technology
Farha, Mathura, India
Boutaib Dahhou
Centre National de la Recherche Scientifique
Laboratoire d’Analyse et d’Architecture des
Systèmes
Université de Toulouse
Toulouse, France
Lalitha Devi Gottumukkala
Biotechnology Division
National Institute for Interdisciplinary Science
and Technology
Council of Scientific and Industrial Research
Trivandrum, India
Arnold L. Demain
Research Institute for Scientists Emeriti
Drew University
Madison, New Jersey
E.M.T. El-Mansi
Department of Biotechnology, School of
Medical Sciences and Research
Sharda University
Greater Noida, Uttar Pradesh, India
Chris E. French
Institute of Cell Biology
University of Edinburgh
Craig J.L. Gershater
Institute of Continuing Education
University of Cambridge
Cambridge, England, United Kingdom
Chris Gwenin
School of Chemistry
Bangor University
Wales, United Kingdom
Brian S. Hartley
Grove Cottage
Cambridge, England, United Kingdom
Iain S. Hunter
Department of Pharmaceutical Sciences
University of Strathclyde
Glasgow, Scotland, United Kingdom

xviii Contributors
Muhammad Javed
Biocaldol, Ltd.
The London Bioscience Innovation Centre
London, England, United Kingdom
Toral Joshi
Xcelrislabs, Ltd.
Ahmedabad, India
Zetao Li
Electrical Engineering College
Guizhou University
Guiyang, Guizhou, People’s Republic of China
Brian McNeil
Institute of Pharmacy and Biomedical Sciences
Royal College
Strathclyde University
David M. Mousdale
beÒcarta Ltd.
Royal College Building
Jens Nielsen
Chalmers University of Technology
Department of Chemical and Biological
Engineering
Gothenburg, Sweden
Ashok Pandey
and Technology, Council of Scientific and
Industrial Research
Trivandrum, India
Kuniparambil Rajasree
and Technology, Council of Scientific and
Industrial Research
Trivandrum, India
Gilles Roux
Centre National de la Recherche Scientifique
Laboratoire d’Analyse et d’Architecture des
Systèmes
Université de Toulouse
Toulouse, France
Ka-Yiu San
Department of Bioengineering
Rice University
Houston, Texas
Sergio Sanchez
Departamento de Biología Molecular y
Biotecnología, Instituto de Investigaciones
Biomédicas, Universidad Nacional
Autónoma de México
México City, México
Gregory Stephanopoulos
Department of Chemical Engineering
Massachusetts Institute of Technology
Cambridge, Massachusetts
Reeta Rani Singhania
Laboratoire de Genie Chimique
et Biochimique
Universite Blaise Pascal
Clermont Ferrand, France
Carlos Ricardo Soccol
Federal University of Parana
Curitiba, Brazil
Raymond Tham
Flinders Centre for Marine
Bioprocessing and Bioproducts,
School of Medicine
Flinders University
Adelaide, Australia
Melissa J. Towler
Department of Biology and
Biotechnology
Worcester Polytechnic Institute
Worcester, Massachusetts
F. Bruce Ward
Institute of Cell Biology
University of Edinburgh,
Darwin Building

Contributors xix
Pamela J. Weathers
Department of Biology and Biotechnology
Worcester Polytechnic Institute
Worcester, Massachusetts
Ronnie G. Willaert
Department of Structural Biology,
Flanders Institute for Biotechnology
Vrije Universiteit Brussel
Brussels, Belgium
Barbara E. Wyslouzil
William G. Lowrie Department of Chemical
and Biomolecular Engineering
Ohio State University
Columbus, Ohio
Wei Zhang
Flinders Centre for Marine Bioprocessing and
Bioproducts, School of Medicine
Flinders University
Adelaide, Australia

1
1 Fermentation Microbiology
and Biotechnology: An
Historical Perspective
E.M.T. El-Mansi, Charlie F.A. Bryce,
Brian S. Hartley, and Arnold L. Demain
“Dans le champ de l’observation, le hasard ne favorise que les esprits préparés.”
Louis Pasteur, 1854
1.1 FERMENTATION: AN ANCIENT TRADITION
Fermentation has been known and practiced by humankind since prehistoric times, long before
the underlying scientific principles were understood. That such a useful technology should arise
by accident will come as no surprise to those people who live in tropical and subtropical regions,
where, as Marjory Stephenson put it, “every sandstorm is followed by a spate of fermentation in
the cooking pot” (Stephenson 1949). For example, the productions of bread, beer, vinegar, yogurt,
cheese, and wine were well-established technologies in ancient Egypt (Figures 1.1 and 1.2). It is an
interesting fact that archaeological studies have revealed that bread and beer, in that order, were the
two most abundant components in the diet of ancient Egyptians. Everyone, from the pharaoh to the
peasant, drank beer for social as well as ritual reasons. Archaeological evidence has also revealed
that ancient Egyptians were fully aware not only of the need to malt the barley or the emmer wheat
but also of the need for starter cultures, which at the time may have contained lactic acid bacteria
in addition to yeast.
1.2 THE RISE OF FERMENTATION MICROBIOLOGY
With the advent of the science of microbiology, and in particular fermentation microbiology, we
can now shed light on these ancient and traditional activities. Consider, for example, the age-old
CONTENTS
1.1 Fermentation: An Ancient Tradition.........................................................................................1
1.2 The Rise of Fermentation Microbiology ..................................................................................1
1.3 Developments in Metabolic and Biochemical Engineering .....................................................3
1.4 Discovery of Antibiotics and Genetic Engineering..................................................................5
1.5 The Rise and Fall of Single-Cell Protein .................................................................................5
1.6 Fermentation Biotechnology and the Production of Amino Acids ..........................................6
1.7 Biofuels and the “Evolution” of Biorefineries ..........................................................................6
1.8 Impact of Functional Genomics, Proteomics, Metabolomics, and Bio-Informatics on
the Scope and Future Prospects of Fermentation Microbiology and Biotechnology...............7
References..........................................................................................................................................8

2 Fermentation Microbiology and Biotechnology, Third Edition
technology of wine making, which relies upon crushing grapes (Figure 1.2) and letting nature take
its course (i.e., fermentation). Many microorganisms can grow on grape sugars more readily and
efficiently than yeasts, but few can withstand the osmotic pressure arising from the high sugar
concentrations. Also, as sugar is fermented, the alcohol concentration rises to a level at which only
osmotolerant, alcohol-tolerant cells can survive. Hence inhabitants of ancient civilizations did not
need to be skilled microbiologists in order to enjoy the fruits of this popular branch of fermentation
microbiology.
In fact, the scientific understanding of fermentation microbiology and, in turn, biotechnology
only began in the 1850s, after Louis Pasteur had succeeded in isolating two different forms of
amyl alcohol, of which one was optically active (L, or laevorotatory) while the other was not.
Rather unexpectedly, the optically inactive form resisted all of Pasteur’s attempts to resolve it
into its two main isomers, the laevorotatory (L) and the dextrorotatory (D) forms. It was this
FIGuRE 1.1 Bread making as depicted on the wall of an ancient Egyptian tomb dated c. 1400 bc. (Reprinted
with the kind permission of the Fitzwilliam Museum, Cambridge, England.)
FIGuRE 1.2 Grape treading and wine making as depicted on the walls of Nakhte’s tomb, Thebes, c. 1400 bc.
(Reprinted with the kind permission of AKG, London, England/Erich Lessing.)

Fermentation Microbiology and Biotechnology: An Historical Perspective 3
observation that led Pasteur into the study of fermentation, in the hope of unraveling the underly-
ing reasons behind his observation, which was contrary to stereochemistry and crystallography
understandings at the time.
In 1857, Pasteur published the results of his studies and concluded that fermentation is associated
with the life and structural integrity of the yeast cells rather than with their death and decay. He reit-
erated the view that the yeast cell is a living organism and that the fermentation process is essential
for the reproduction and survival of the cell. In his paper, the words cell and ferment are used inter-
changeably (i.e., the yeast cell is the ferment). The publication of this classic paper marks the birth
of fermentation microbiology and biotechnology as a new scientific discipline. Guided by his criti-
cal and unbiased approach to experimental design, Pasteur was able to confidently challenge and
reject Liebig’s perception that fermentation occurs as a result of contact with decaying matter. He
also ignored the well-documented view that fermentation occurs as a result of “contact catalysis,”
although it is possible that this concept was not suspect in his view. The term “contact catalysis”
probably implied that fermentation is brought about by a chain of enzyme-catalyzed reactions. In
1878, Wilhelm Kühne (1837–1900) was the first to use the term enzyme, which is derived from the
Greek word ενζυμον (“in leaven”) to describe this process. The word enzyme was used later to refer
to nonliving substances such as pepsin, and the word ferment used to refer to chemical activity
produced by living organisms.
Although Pasteur’s interpretations were essentially physiological rather than biochemical, they
were pragmatically correct. During the course of his further studies, Pasteur was also able to estab-
lish not only that alcohol was produced by yeast through fermentation but also that souring was a
consequence of contamination with bacteria that were capable of converting alcohol to acetic acid.
Souring could be avoided by heat treatment at a certain temperature for a given length of time. This
eliminated the bacteria without adversely affecting the organoleptic qualities of beer or wine, a
process we now know as pasteurization.
A second stage in the development of fermentation microbiology and biotechnology began in
1877, when Moritz Traube proposed the theory that fermentation and other chemical reactions are
catalyzed by protein-like substances and that, in his view, these substances remain unchanged at
the end of the reactions. Furthermore, he described fermentation as a sequence of events in which
oxygen is transferred from one part of the sugar molecule to another, culminating in the formation
of a highly oxidized product (i.e., CO2
) and a highly reduced product (i.e., alcohol). Considering the
limited knowledge of biochemistry in general and enzymology in particular at the time, Traube’s
remarkable vision was to prove 50 years ahead of its time.
In 1897 Eduard Buchner, two years after Pasteur died, discovered that sucrose could be fer-
mented to alcohol by yeast cell-free extracts and coined the term “zymase” to describe the enzyme
that catalyses this conversion. The term “zymase” Is derived from the Greek word “zymosis”, which
means fermentation. In 1907, he received the Nobel Prize in Chemistry for his biochemical research
and his discovery of cell-free fermentation. In the early 1900s, the views of Pasteur were modified
and extended to stress the idea that fermentation is a function of a living, but not necessarily mul-
tiplying, cell and that fermentation is not a single step but rather a chain of events, each of which is
probably catalyzed by a different enzyme.
1.3 DEVELOPMENTS IN METABOLIC AND
BIOCHEMICAL ENGINEERING
The outbreak of the First World War provided an impetus and a challenge to produce certain chemi-
cals that, for one reason or another, could not be manufactured by conventional means. For example,
there was a need for glycerol, an essential component in the manufacture of ammunition, because
no vegetable oils could be imported due to the naval blockade. German biochemists and engineers
were able to adapt yeast fermentation, turning sugars into glycerol rather than alcohol. Although

this process enabled the Germans to produce in excess of 100 tons of glycerol per month, it was
abandoned as soon as the war was over because glycerol could be made very cheaply as a by-product
of the soap industry. There was also, of course, a dramatic drop in the level of manufacture of explo-
sives and, in turn, the need for glycerol.
The diversion of carbon flow from alcohol production to glycerol formation was achieved by add-
ing sodium bisulfite, which reacts with acetaldehyde to give an adduct that cannot be converted to
alcohol (Figure 1.3). Consequently, NADH accumulates intracellularly, thus perturbing the steady-
state redox balance (NAD+:NADH ratio) of the cell. The drop in the intracellular level of NAD+ is
accompanied by a sharp drop in the flux through glyceraldehyde-3-phosphate dehydrogenase,
which in turn allows the accumulation of the two isomeric forms of triose phosphate (i.e., glyceral-
dehyde-3-phosphate and dihydroxyacetone-3-phosphate). Accumulations of the latter together with
high intracellular levels of NADH trigger the expression of glycerol-3-phosphate dehydrogenase,
which in turn leads to the diversion of carbon flux from ethanol production to glycerol formation,
thus restoring the redox balance within the cells by regenerating NAD+ (Figure 1.3). Although this
explanation is with the hindsight of modern biochemistry, the process can be viewed as an early
example of metabolic engineering.
Following the First World War, research into yeast fermentation was largely influenced by
the work of Carl Neuberg and his proposed scheme (biochemical pathway) for the conversion of
sugars to alcohol (alcohol fermentation). Although Neuberg’s scheme was far from perfect and
proved erroneous in many ways, it provided the impetus and framework for many scientists at
the Delft Institute, who vigorously pursued research into oxidation/reduction mechanisms and
the kinetics of product formation in a wide range of enzyme-catalyzed reactions. Such studies
were to prove important in the development of modern biochemistry as well as fermentation
biotechnology.
Glucose Fructose 1,6-
bisphosphate
2 Glyeraldehyde
3-phosphate
Dihydroxyacetone
3-phosphate
Glycerol
2 Alcohol
Bisulphite
×
2 NADH, H+
2 NAD+
2 Acetaldehyde
2 Phosphoenol-
pyruvate
2 Pyruvate
2 ATP
2 ADP
Bisulphite
adduct
Glycerol, 3-phosphate
1
2
NADH, H+
NAD+
2 ATP 2 ADP
FIGuRE 1.3 Diversion of carbon flux from alcohol production to glycerol formation in the yeast
Saccharomyces cerevisiae. Note that the functional role of bisulfite is to arrest acetaldehyde molecules, thus
preventing the regeneration of NAD+ as a consequence of making alcohol dehydrogenase redundant. To
redress the redox balance (i.e., the NAD+:NADH ratio), S. cerevisiae diverts carbon flow (dashed route) toward
the reduction of dihydroxyacetone-3-phosphate to glycerol-3-phosphate, thus regenerating the much-needed
NAD+. The glycerol-3-phosphate thus generated is then dephosphorylated to glycerol.

While glycerol fermentation was abandoned immediately after the First World War, the acetone-
butanol fermentation process, catalyzed by Clostridium acetobutylicum, flourished. Production
lines were modified to accommodate the new approach of “Fill and Spill” (see Box 1.1), which
permitted substantial savings in fuels without adversely affecting the output of solvent production
during the course of the Second World War. However, as soon as the production of organic solvents
as a by-product of the petrochemical industry became economically viable, the acetone-butanol
fermentation process was discontinued.
1.4 DISCOVERY OF ANTIBIOTICS AND GENETIC ENGINEERING
The discoveries of penicillin in the late 1920s and its antibacterial properties in the early 1940s
represent a landmark in the development of modern fermentation biotechnology. This discovery,
to a country at war, was both sensational and invaluable. However, Penicillium notatum, the pro-
ducing organism, was found to be susceptible to contamination by other organisms, and therefore
aseptic conditions were called for. Such a need led to the introduction of so-called stirred tank
bioreactors, which minimize contamination with unwanted organisms. The demand for penicillin
prompted a worldwide screen for alternative penicillin-producing strains, leading to the isola-
tion of Penicillium chrysogenum, which produced more penicillin than the original isolate P.
notatum. P. chrysogenum was then subjected to a very intensive program of random mutagen-
esis and screening. Mutants that showed high levels of penicillin production were selected and
subjected to further rounds of mutagenesis, and so on. This approach was successful, as indi-
cated by the massive increase in production from less than 1 g l−1 to slightly more than 20 g l−1
of culture.
Once the antibacterial spectrum of penicillin was determined and found to be far from universal,
pharmaceutical companies began the search for other substances with antibacterial activity. These
screening programs led to the discovery of many antibacterial agents produced by various mem-
bers of the actinomycetes. Although the search for new antibiotics is never over, intensive research
programs involving the use of genetic and metabolic engineering were initiated with the aim of
increasing the productivity and potency of current antibiotics. For example, the use of genetic and
metabolic engineering has increased the yield of penicillin manyfold.
1.5 THE RISE AND FALL OF SINGLE-CELL PROTEIN
The latter part of the 1960s saw the rise and fall of single-cell protein (SCP) production from petro-
leum or natural gas. A large market for SCP was forecast, as the population in the third world, the
so-called underdeveloped countries, continued to increase despite a considerable shortfall in food
supply. However, the development of SCP died in its infancy, largely due to the sharp rise in the
price of oil, which made it economically nonviable. Furthermore, improvements in the quality and
yields of traditional crops decreased demand for SCP production.
Box 1.1 “FILL AND SPILL”
This pattern of fermentation is essentially a “batch fermentation” or “fed-batch fermentation”
process in which the organism is allowed to grow, and once product formation has reached
the maximum level, the fermentation pot is harvested, leaving some 10% of the total volume
as an inoculum for the next batch. This process is repeated until the level of contamination
becomes unacceptably high.

1.6 FERMENTATION BIOTECHNOLOGY AND
THE PRODuCTION OF AMINO ACIDS
The next stage in the development of fermentation biotechnology was dominated by success in the
use of regulatory control mechanisms for the production of amino acids. The first breakthrough
was the discovery of glutamic acid overproduction by Corynebacterium glutamicum in the late
1950s and early 1960s, when a number of Japanese researchers discovered that regulatory mutants,
isolated by virtue of their ability to resist amino acid analogs, were capable of overproducing amino
acids. The exploitation of such a discovery, however, was hampered by the induction of degradative
enzymes once the extracellular concentration of the amino acid increased beyond a certain level;
for example, accumulation of tryptophan induced the production of tryptophanase, thus initiating
the breakdown of the amino acid. This problem was resolved by the use of penicillin, which, with
tryptophan as the sole source of carbon in the medium, eliminated the growing cells (i.e., those
capable of metabolizing tryptophan, but not those that were quiescent). Following the addition of
penicillin, the mutants that had survived the treatment (3 × 10−4) were further tested. Enzymic anal-
ysis revealed that one mutant was totally devoid of tryptophanase activity. This approach was soon
extended to cover the production of other amino acids, particularly those not found in sufficient
quantities in plant proteins. The successful use of regulatory mutants stimulated interest in the use
of auxotrophic mutants for the production of other chemicals. The rationale is that auxotrophic
mutants will negate feedback inhibition mechanisms and in turn allow the accumulation of the
desired end product. For example, an arginine-auxotroph was successfully used in the production of
ornithine, while a homoserine-auxotroph was used for the production of lysine.
1.7 BIOFuELS AND THE “EVOLuTION” OF BIOREFINERIES
In the last decade, fermentation biotechnology has taken a leap forward in consequence of the rising
price of oil and international concern about global warming. Brazil was a pioneer since the 1970s
in developing bioethanol production from its huge sugarcane industry and alongside it an expanding
industry for production of ethanol-utilizing cars; as a result, today about 80% of Brazilian vehicles
are fueled by > 20% bioethanol–gasoline mixtures.
The United States, the largest consumer of gasoline, has expanded its program and increased
its bioethanol production from corn by some sixfold over the last decade, thus superseding Brazil’s
production from sugarcane. However, this is still only a fraction of U.S. gasoline consumption.
Ethanol production from corn is much less efficient than from sugarcane, so subsidies are required
to market it as a 15% ethanol–gasoline blend, which can be used in conventional car engines without
modification. Nevertheless, the rocketing price of oil is close to making unsubsidized corn bioetha-
nol competitive with gasoline. Corn prices are also rising, but the increasing animal feed value of
the fermentation residues (distillers’ dried grains, or DDGs) almost compensates.
There is therefore a worldwide trend to increase conventional bioethanol production, even if
subsidies or tariffs are required and although the carbon footprint of the fuel is only marginally
better than that of gasoline. The production of bioethanol or the capacity to make it appears to have
a buffering capacity against further increases in oil prices. There are many situations in which
bioethanol production represents a logical alternative to farming subsidies, such as wheat produc-
tion in the European Union. There is, however, valid opposition to “first-generation” bioethanol as
a sustainable biofuel on grounds of minimal reduction of global warming and competition with
food supply. Fortunately, fermentation biotechnology has an answer. We harvest at best 20% of
what farmers grow and eat only a fraction of that. Agricultural residues such as corn stover, cereal
straws, and palm oil wastes are lignocellulosic biomass that could dwarf current bioethanol produc-
tion. Harvested factory residues, such as sugarcane bagasse, corn cobs, wheat bran, palm oilcake,
and so on represent an immediate opportunity. Lignocellulosic residues alone could yield sufficient
bioethanol to fuel all the cars in the world.

As we will be discussing in Chapter 9, these residues are composed mostly of bundles of long
cellulose fibers (40–50% dry weight) waterproofed by a coat of lignin (15–25%) and embedded in a
loose matrix of hemicelluloses (25–35%). Most R&D has been directed to cellulose utilization since
it can be hydrolyzed to glucose and fermented by yeasts. However, this is a slow and/or energy-
intensive process, so cellulosic ethanol is not competitive with corn or wheat bioethanol, let alone
cane bioethanol. In contrast, hemicelluloses are easily hydrolyzed to a mixture of C5 and C6 sugars,
most of which cannot be fermented by yeasts. Many microorganisms can ferment these sugars, but
produce lactic acid rather than ethanol. Therefore, much effort has gone into genetic manipulation
to divert carbon flux from lactate production to bioethanol formation.
Notable among such microorganisms are thermophilic Geobacilli found naturally in compost
heaps and/or silage. They can be engineered to produce ethanol from hemicellulosic sugars with
yields equivalent to those from yeast fermentations of starch sugars. They have the additional advan-
tages of extremely rapid continuous fermentations at high temperatures in which ethanol vapor can
be removed continuously from the broth. Hence, although such fermentations have not yet been
commercialized, calculations indicate that the production cost will be well below that of cane bio-
ethanol or gasoline, so the scene is set for the evolution of biorefineries.
By analogy with the emergence of petrochemicals from processing the by-products of oil
refineries, new biochemicals will emerge from the processing of biomass in biorefineries.
Sugarcane, for example, could yield sugar or ethanol from the juice, ethanol from the hemicel-
lulosic pith, waxes from the external rind, plus heat and electricity from efficient combustion of
the lignocellulosic fibers (KTC-Tilby 2011). Alternatively, the fibers could be used directly for
packaging or building board or for paper production after ethanol extraction of the lignin. The
lignin extract could make an efficient biodiesel or give rise to a new range of bioaromatics to
compete with those currently derived from oil. The residual stillage from ethanol distillation has
high animal feed value.
Another advantage of such biorefineries is that they would be self-contained units built close to
existing food-processing plants, such as sugar refineries, flour mills, or oil-processing plants. Since
rape seed or palm oils are already used for biodiesel production, an intriguing proposal to use the
by-product glycerol together with hemicellulosic sugars for high-yield bioethanol production would
produce biorefineries to rival oil refineries in producing both fuels from a single raw material. The
scene is therefore set for the evolution of biorefineries.
1.8 IMPACT OF FuNCTIONAL GENOMICS, PROTEOMICS,
METABOLOMICS, AND BIO-INFORMATICS ON THE
SCOPE AND FuTuRE PROSPECTS OF FERMENTATION
MICROBIOLOGY AND BIOTECHNOLOGY
Modern biotechnology, a consequence of innovations in molecular cloning and overexpression in
the early 1970s, has started in earnest in the early 1980s after the manufacture of insulin, with the
firstwaveofproductshittingthemarketintheearly1990s.Duringthisearlyperiod,thebiotechnology
companies focused their efforts on specific genes/proteins (natural proteins) that were of well-
known therapeutic value and typically produced in very small quantities in normal tissues. Later,
monoclonal antibodies became the main products of the biopharmaceutical industry.
In the mid-1980s, Thomas Roderick coined the term genomics
to describe the discipline of mapping, sequencing, and analyzing
genomic DNA with the view to answering biological, medical, or
industrial questions (Jones 2000). Recent advances in functional
genomics, stimulated by the Human Genome Project and com-
puter software technology, led many biotechnologists to venture
from the traditional in vivo and in vitro research into the in silico
Functional genomics is a discipline of biotech-
nology that attempts to exploit the vast wealth
of data produced by genome-sequencing
projects. A key feature of functional genomics
is their genome-wide approach, which invari-
ably involves the use of a high-throughput
approach.

approach, thus establishing a new science in the shape of bio-informatics. In this approach, micro-
biologists employ computers to store, retrieve, analyze, and compare a given sequence of DNA or
protein with those stored in data banks from other organisms. Microbial biotechnologists were
quick to realize that the key to successful commercialization of a
given sequence relied on the development of an innovative meth-
odology (bio-informatics) that facilitates the transformation of a
given sequence into a diagnostic tool and/or a therapeutic drug,
thus bridging the gap between academic research and commer-
cialization.
The new innovations in functional genomics—proteomics,
metabolomics, and bio-informatics—will certainly play a major
role in transforming our world in an unparalleled way, despite
political and ethical controversies.
In this book, we have addressed the multidisciplinary nature
of this subject and highlighted its many fascinating aspects in
the hope that we are providing a stepping stone in its progress.
As we enter a new era in which the use of renewable resources
for the production of desirable end products is recognized as an
urgent need, fermentation microbiology and biotechnology have
a central role to play.
REFERENCES
Jones, P.B.C. 2000. The commercialisation of bioinformatics. EJB Electronic Journal of Biotechnology 3(2):
33–34.
KTC-Tilby. 2011. Sweet sorghum and sugar cane separation technology. www.youtube.com/watch?v 
=YbQT7Yfmn7s
Stephenson, M. 1949. Bacterial Metabolism. London: Longmans, Green.
Proteomics is a new discipline that focuses
on the study and exploitation of proteomes.
A proteome is the complete set of proteins
expressed by a given organism under certain
conditions.
Metabolomics is a new discipline that focuses
on the study and exploitation of metabo-
lomes. A metabolome refers to the complete
set of primary and secondary metabolites as
well as activators, inhibitors, and hormones
that are produced by a given organism under
certain conditions. It is noteworthy, however,
that it is not currently possible to analyze the
entire range of metabolites by a single ana-
lytical method.

9
2 Microbiology of Industrial
Fermentation: Central
and Modern Concepts
E.M.T. El-Mansi, F. Bruce Ward, and Arun P. Chopra
CONTENTS
2.1 Introduction ............................................................................................................................10
2.2 Chemical Synthesis of Bacterial Protoplasm or Biomass ...................................................... 11
2.2.1 Central and Intermediary Metabolism ....................................................................... 11
2.2.2 Anaplerotic Pathways .................................................................................................12
2.2.3 Polymerization and Assembly ....................................................................................13
2.2.4 Biomass Formations ...................................................................................................13
2.2.5 Logarithms.................................................................................................................. 14
2.2.5.1 Use of Semilogarithmic Graph Paper.......................................................... 14
2.3 Growth Cycle.......................................................................................................................... 14
2.3.1 Lag Phase.................................................................................................................... 16
2.3.2 Exponential Phase....................................................................................................... 17
2.3.2.1 Metabolic Interrelationship between Nutrient Limitations
and Specific Growth Rate (μ) ......................................................................19
2.3.3 Stationary Phase and Cell Death................................................................................ 21
2.3.4 Maintenance and Survival..........................................................................................22
2.4 Diauxic Growth ......................................................................................................................24
2.5 Growth Yield in Relation to Carbon and Energy Contents of Growth Substrates.................24
2.6 Fermentation Balances ...........................................................................................................26
2.6.1 Carbon Balance ..........................................................................................................26
2.6.2 Redox Balance............................................................................................................26
2.7 Efficiency of Central Metabolism...........................................................................................26
2.7.1 Impact of Futile Cycling on the Efficiency of Central Metabolism ...........................26
2.7.2 Impact of Metabolite Excretion on the Efficiency of Central Metabolism ................27
2.8 Continuous Cultivation of Microorganisms ...........................................................................28
2.8.1 Types of Continuous Cultures ....................................................................................29
2.8.2 Principles and Theory of Continuous Cultures ..........................................................29
2.8.2.1 Microbial Growth Kinetics in Continuous Cultures....................................29
2.8.2.2 Interrelationship between Growth Rate (µ) and Dilution Rate (D) .............30
2.8.2.3 Efficiency and Productivity of Fermentation Processes.............................. 31
2.9 Current Trends in the Fermentation and Pharmaceutical Industry........................................ 31
2.9.1 “Quiescent Cell Factory”: A Novel Approach............................................................32
2.9.2 Applications of Batch-Fed Two-Stage Fermentation in the Production of
Biopharmaceuticals: A Robust Approach...................................................................32

“..et le rêve de toute cellule: devenir deux cellules”.
Jacques Monod, 1970
2.1 INTRODuCTION
Microorganisms play a central role in the production of a wide range of primary and secondary
metabolites, industrial chemicals, enzymes, and antibiotics. The diversity of fermentation processes
may be attributed to many factors, including the high surface-to-volume ratio and the ability to
utilize a wide spectrum of carbon and nitrogen sources. The high surface-to-volume ratio supports
a very high rate of metabolic turnover: for example, the yeast Saccharomyces cerevisiae has been
reported to be able to synthesize protein by several orders of magnitudes faster than plants. On the
other hand, the ability of microorganisms to adapt to different metabolic environments makes them
capable of utilizing inexpensive renewable resources such as wastes and by-products of the farming
and petrochemical industries as the primary carbon source. Industrially important microorganisms
include bacteria, yeasts, molds, and actinomycetes.
While the metabolic route through which glucose is converted to pyruvate, glycolysis, is uni-
versally conserved among all organisms, microorganisms differ from eukaryotes in their ability
to process pyruvate through a diverse array of routes (Figure 2.1), giving rise to a multitude of
2.10 Microbial Fermentations and The Production of Biopharmaceuticals...................................33
2.10.1 Production of Insulin: A Case Study..........................................................................33
2.10.1.1 History and Background..............................................................................33
2.10.1.2 Cloning and Commercial Production of Insulin..........................................33
2.10.2 Protein Engineering of Insulin ...................................................................................34
2.10.2.1 Fast-Acting Insulin Analogs ........................................................................34
2.10.2.2 Long-Acting Insulin Analogs ......................................................................34
Summary..........................................................................................................................................35
References........................................................................................................................................35
Glucose
Glycolysis
H3C
Alcoholic
fermentation
B
u
t
y
r
i
c
-
b
u
t
y
l
i
c
M
i
x
e
d
-
a
c
i
d
f
e
r
m
e
n
t
a
t
i
o
n
P
r
o
p
l
o
n
i
c
f
e
r
m
e
n
t
a
t
i
o
n
f
e
r
m
e
n
t
a
t
i
o
n
fermentation
Ethyl alcohol
and CO2
Butyric acid butanol,
isopropyl alcohol,
acetone, and CO2
Acetic acid, succinic acid,
ethyl alcohol, CO2, and H2
Propionic acid,
acetic acid, and CO2
Butanediol and CO2
B
u
t
a
n
e
d
i
o
l
f
e
r
m
e
n
t
a
t
i
o
n
Lactic acid
OH Homolactic-acid
O
Pyruvic acid
O
FIGuRE 2.1 Diversity of fermentation pathways among microorganisms.

Microbiology of Industrial Fermentation: Central and Modern Concepts 11
different end products. Such diversity has been fully exploited by fermentation technologists for the
production of fine chemicals, organic solvents, and dairy products.
Prokaryotic organisms differ from yeast and fungi as well as other eukaryotes in a number
of ways, including cell structure and growth cycle. For example, while DNA is compartmental-
ized within the nucleus in eukaryotes, it is neatly folded within the cytoplasm in prokaryotes. The
site of oxidative phosphorylation represents yet another example; while oxidative phosphorylation
is associated with mitochondria in eukaryotic organisms, oxidative phosphorylation in prokaryotes
is associated with cytoplasmic membranes. Furthermore, the newly synthesized DNA molecules in
prokaryotes need no special assembly to form a chromosome, as the DNA is already attached to the
bacterial membrane, thus ensuring its successful segregations into two daughter cells. Any treat-
ment that dislodges the DNA or compromises the attachment of DNA to the cytoplasmic membrane
may lead to failure in segregation of DNA. This was the scientific bases on which sodium dode-
cyle sulphate (SDS) was used to cure large endogenous plasmids from Klebsiella pneumoniae and
Pseudomonas putida (El-Mansi et al. 2001).
2.2 CHEMICAL SYNTHESIS OF BACTERIAL PROTOPLASM OR BIOMASS
In addition to carbon, nitrogen, phosphate, potassium, sulfur,
irons, and magnesium, the chemical input required for growth
also include trace elements. The necessity for such a multitude of
inputs is paramount as it is required for enzymic activities. The
contribution of each additive to biomass and product formation
can be assessed quantitatively.
2.2.1 Central and IntermedIary metabolIsm
Throughout Section 2.2, we will be addressing the function of enzymes of central and intermediary
metabolism (Figure 2.2) with respect to their role in bacterial growth, and as such it would be help-
ful if we were to appreciate the functional role of each.
During growth on a glucose minimal medium under aerobic conditions, Escherichia coli
catabolizes glucose through glycolysis and the Krebs cycle (Figure 2.2) to bring about its trans-
formation to biosynthetic precursors; there are 12 in total, over half of which are phosphorylated
adenosine-5’-triphosphate (ATP) and reducing powers in the shape of NADH, NADPH, and FADH2
as well as esterified CoA derivatives (e.g., succinyl CoA and malonyl CoA). In this process a whole
host of different reactions, the fueling reactions (Figure 2.3) are coordinated in a precise manner
to ensure successful adaptation and survival of the organism. Once the biosynthetic precursors,
ATP, and reducing powers are generated, the organism employs anabolic enzymes to convert those
biosynthetic precursors into monomers (building blocks) in the shape of various sugars, amino acids,
and nucleotides. The monomers are then polymerized into polymers (macromolecules), which, in
turn, are assembled into different structures or organelles and thence to biomass (Figure 2.3). The
central metabolic pathways (glycolysis, the pentose phosphate pathway, and the Krebs cycle) fulfill
both catabolic (from cata, a Greek word for breakdown) and anabolic (from ana, a Greek word for
buildup) functions and as such may be referred to as amphibolic pathways.
Although the central metabolic pathways are highly conserved in all organisms, microorganisms
display a great deal of diversity even within a single species such as E. coli in response to growth
conditions. As can be seen from Figure 2.2, microorganisms are capable of utilizing a wide range
of substrates and afford a different entry point for each into central metabolism. As the point of
entry into the central metabolic pathways of the Krebs cycle vary from one substrate to another,
the makeup of the enzymic machinery necessary for metabolism changes accordingly (Guest and
Russell 1992). For example, during growth on acetate or fatty acids, E. coli expresses uniquely the
anaplerotic sequence of glyoxylate bypass (Cozzone 1998).
While central metabolism (glycolysis, the
pentose phosphate pathway, and the Krebs
cycle) is concerned with the breakdown of
growth substrates and their conversion to the
12 biosynthetic precursors, ATP, and reduc-
ing powers, intermediary metabolism focuses
on the conversion of those biosynthetic pre-
cursors to monomers and their subsequent
polymerization and assembly into polymers.

2.2.2 anaplerotIC pathways
During growth on glucose or other acetogenic substrates (i.e., those that support flux to acetate
excretion), metabolites of the Krebs cycle, namely, α-ketoglutarate, succinyl CoA, and oxaloac-
etate (Figure 2.2), are constantly being withdrawn for biosynthesis. It follows, therefore, that such
intermediates must be replenished; otherwise, the cycle will grind to a halt. The reactions that fulfill
such a function are known as anaplerotic, a Greek word for replenishing, pathways. The makeup
Fructose 6-
phosphate
Glucose 6-
phosphate
Pentose 4-
phosphate
Serine,
glycine,
cystine
3-Phosphoglycerate
Aromatic
amino acids
Fructose 1,6-bisphosphate
ADP
ATP
Glucose
PEP Pyruvate
Phosphoenol-
pyruvate
Pyruvate
Acetyl-CoA
Valine,
leucine,
alanine
Lactate
Fatty acids
Acetate
Aromatic &
branched amino acids
Oxaloacetate
Malate
Acetyl-CoA
Glyoxylate
Isocitrate
CO2
Fumarate
Succinate
Methionine,
valine,
isoleucine
Porphyrins
Histidine
α-Keto-
glutarate
Glutamate,
glutamine,
proline,
arginine
Succinyl-
CoA
CO2
Tyrosine,
phenylalanine
Aspartate,
asparagine,
threonine,
isoleucine,
methionine,
lysine
Citrate
ADP
ATP
8
7
3
2
10
4
9
1
5
6
FIGuRE 2.2 An overview of the metabolic pathways of central and intermediary metabolism employed by
E. coli for the conversion of glucose and other substrates to biosynthetic precursors; indicated by heavy-dotted
arrows, ATP, and reducing powers. Entry of substrates other than glucose into central metabolism is indicated
by dashed arrows. Key enzymes are as follows: 1, glucose–phosphoenolpyruvate (PEP) phosphotransferase
system; 2, the pentose phosphate pathway; 3, pyruvate kinase; 4, PEP carboxylase; 5, PEP carboxytranspho-
sphorylase; 6, pyruvate carboxylase; 7, isocitrate lyase; 8, malate synthase; 9, malic enzyme; and 10, PEP
carboxykinase.

of the anaplerotic enzymes differs from one phenotype to another, in other words, it is substrate
dependent. For example, during growth on glucose, phosphoenolpyruvate carboxylase, pyruvate
carboxylase, and phosphoenolpyruvate carboxytransphosphorylase (Figure 2.2) represent the full
complement of anaplerotic enzymes that may be used in full or in part depending on the organism
under investigation. During growth on acetate, however, E. coli employs the glyoxylate bypass operon
enzymes, namely, isocitrate lyase and malate synthase, as an anaplerotic sequence. Interestingly,
however, while the enzymes of the glyoxylate bypass in E. coli form an operon and include the
bifunctional regulatory enzyme isocitrate dehydrogenase kinase/phosphatase, these enzymes are
not organized in the same way in Corynebacterium glutamicum.
2.2.3 polymerIzatIon and assembly
Following transcription through the activity of RNA polymerase, mRNA is translated into protein
by ribosomes. In this process, ribosomes attach to mRNA together with co-factors, enzymes, and
complementary tRNA, thus forming a polysome and, in turn, initiating the synthesis of polypep-
tides. Polysomes are one of the most abundant organelles in growing cells; each polysome contains
approximately 20 subunits of ribosomal RNA (Ingraham et al. 1983).
2.2.4 bIomass FormatIons
The rate of product formation in a given industrial process, a significant parameter, is directly related
to the rate of biomass formation, which, in turn, is influenced directly or indirectly by a whole host
of different environmental factors (e.g., oxygen supply, pH, temperature, and accumulation of inhib-
itory intermediates). It is, therefore, important that we are able to describe growth and production in
quantitative terms. The study of growth kinetics and growth dynamics involves the formulation and
Lipid
Inclusion
bodies
Cell
envelope
Flagella
Pili
Poly-
ribosomes
Biomass
Cytosol
Lipopolysaccharide
Glycogen
Peptidoglycan
Protein
RNA
DNA
Amino acids
(20)
Nucleotides
(8)
Glucose
Pi
Glucose 6-P
Fructose 6-P
Pentose 5-P
Erythrose 4-P
3 P-Glycerate
P-Enopyruvate
Pyruvate
Acetyl-CoA
α-Ketogluterate
Succinyl-CoA
Oxaloacetate
ATP
Biosynthetic
precursers
Monomers
(building blocks)
Polymers
(macromolecules)
Assembly of cell
organelles
NAD (P)H,
FADH2
SO4
NH4
ATP
Fueling
reactions
Biosynthetic
reactions
Nucleotide
Sugars
(25)
Fatty acids
(8)
Assembly
reactions
Polymerisations
FIGuRE 2.3 A diagrammatic representation of the reactions involved in the conversion of glucose and
simple salts to biomass of E. coli. (This figure is a slight modification of Ingraham, J.L., Neidhardt, F.C., and
Schaechter, M., A Molecular Approach, Sinauer Associates, Inc., Sunderland, MA, 1990, reproduced with the
kind permission of Sinauer Associates, Inc., Sunderland, MA, 1990.)

use of differential equations (for more details, see Chapter 3). While the mathematical derivation
of these equations is beyond the scope of this chapter, it is important that we understand how such
equations can be used to further our understanding of microbial growth in general and its impact on
product formation (yield) in particular.
In microbiology we generally deal with very large numbers, and for convenience we express
these numbers as multiples of 10 raised to an appropriate power; for example, 1 million (1,000,000)
is written as 1 × 106.
2.2.5 logarIthms
Logarithms, otherwise known as logs, are very useful mathematical functions in both microbiology
and biochemistry, especially in measuring important parameters such as growth, death, and enzyme
kinetics.
The logarithm of a number is the exponent to which we must raise a base to obtain that number.
The exponent is also known as the index or the power. For example, consider the number 1000 and
the base 10; the number 10 is raised to the power 3 to obtain 1000; it follows that the logarithm to the
base 10 of 1000 is 3. The base of a logarithm is conventionally written as a subscript. For example,
the logarithm to the base 10 is written as log10 and the logarithm to the base e is written as loge. If a
log is given without a subscript, it denotes a logarithm to the base 10. Logarithms to the base e (loge)
are also called natural logarithms, which may also be written as In.
2.2.5.1 use of Semilogarithmic Graph Paper
A semilogarithmic (semilog) graph paper is a graph paper that has an arithmetic scale on one axis
and a logarithmic scale on the other. Although, it may appear very strange, it is user friendly and
is very useful as it allows you to plot your data directly without having to calculate logs. On the
logarithmic scale, there are a number of cycles. Each cycle represents a change in data of an order
of magnitude, a factor of 10; any set of factors of 10 can be used, but remember that there is no zero
on the log scale.
In plotting your data on semilog paper, the independent variable is plotted on the x-axis (abscissa),
while the dependent variable is plotted on the y-axis (ordinate) of the graph. For example, in deter-
mining the mean generation time (T) of a given organism under certain conditions, time is the
independent variable and is plotted on the x-axis, while the number of cells, which increases expo-
nentially during the course of the logarithmic phase of growth, is plotted on the y-axis. However,
it is noteworthy to remember that in determining the minimum inhibitory concentration (MIC)
of antibiotics, the drug dosage increases in an exponential fashion and as such the log scale here
becomes the x-axis.
2.3 GROWTH CYCLE
Now let us consider the basic equation used to describe microbial growth:
dx
dt
ax
b
= (2.1)
Equation 2.1 implies that the rate of biomass (x) formation
changes as a function of time (t) and that the rate of change is
directly proportional to the concentration of a particular factor
(a) such as growth substrate or temperature but is inversely pro-
portional to the concentration of another factor (b) such as inhibi-
tors. In Equation 2.1, both a and b are independent of time t, and
While growth kinetics focuses on the mea-
surement of growth rates during the course
of fermentation, growth dynamics relates the
changes in population (biomass) to changes
in growth rate and other parameters (e.g., pH
and temperature). To unravel such intricate
interrelationships, the description of growth
kinetics and growth dynamics relies on the
use of differential equations.

the proportionality factor in Equation 2.1 can in effect be ignored. In the early stages of any fermen-
tation process, the increase in biomass is unrestricted, and, as such, the pattern of growth follows an
autocatalytic first-order reaction (autocatalytic growth) up to a
point where either side of Equation 2.1 becomes negative, result-
ing in autocatalytic death.
During batch fermentation, a typical pattern of growth curve,
otherwise known as the growth cycle, is observed (Figure 2.4).
Clearly, a number of different phases of the growth cycle can be
differentiated. These are
1. Lag phase
2. Acceleration phase
3. Exponential (logarithmic) phase
4. Deceleration phase
5. Stationary phase
6. Accelerated death phase
7. Exponential death phase
8. Death or survival phase
The changes in the specific growth rate (μ) as the organism progresses through the growth cycle can
also be seen in Figure 2.4.
We shall now describe the metabolic events and their implications in as far as growth, sur-
vival, and productivity are concerned. Naturally, the scenario begins with the first phase of the
growth cycle.
The term autocatalytic growth is generally
used to indicate that the rate of increase in
biomass formation in a given fermentation
is proportional to the original number of cells
present at the beginning of the process, thus
reflecting the positive nature of growth.
The term growth cycle is used to describe
the overall pattern displayed by microorgan-
isms during growth in batch cultures. It is
noteworthy that such a cycle is by no means
a fundamental property of the bacterial cell,
but rather a consequence of the progressive
decrease in food supply or accumulation of
inhibitory intermediates in a closed system
to which no further additions or removals
are made.
0.8
0.4
0.0
Specific
growth
rate
h
–1
(µ)
Optical
density
(OD)
I II III IV V VI VII VIII
1.0
0.8
0.6
0.4
0.2
0 2 4 6 8
Time (hours)
24 26 28
FIGuRE 2.4 Typical pattern of growth cycle during the growth of microorganisms in batch cultures; the
vertical dotted lines and the roman numerals indicate the changes in specific growth rate (μ) throughout
the cycle.

2.3.1 lag phase
In this phase, the organism is simply faced with the challenge of adapting to the new environment.
While adaptation to glucose as a sole source of carbon appears to be relatively simple, competition
with other carbon sources, although complex, is resolved in favor of glucose through the operation
of two different mechanisms, namely, catabolite inhibition and catabolite repression.
Adaptation to other carbon sources, however, may require the induction of a particular set of
enzymes that are specifically required to catalyze transport and hydrolysis of the substrate (e.g.,
adaptation to lactose) or to fulfill anaplerotic as well as regulatory functions, as is the case in adap-
tation to acetate as the sole source of carbon and energy. Irrespective of the mechanisms employed
for adaptation, the net outcome at the end of the lag phase is a cell that is biochemically vibrant (i.e.,
capable of transforming chemicals to biomass).
Entering a lag phase during the course of industrial fermentation is not desirable as it is very
costly and as such should be avoided. The question of whether a particular organism has entered a
lag phase in a given fermentation process can be determined graphically by simply plotting log n
(biomass) as a function of time, as shown in Figure 2.5.
Note that the transition from the lag phase to the exponential phase involves another phase: the
acceleration phase, as described in Figure 2.4. This difficulty can be easily overcome by extrapolat-
ing the lag phase sideways and the exponential phase downward as shown, with the point of inter-
ception (L) taken as the time at which the lag phase ended. What is also interesting about the graph
5.0
4.0
3.0
2.0
1.0
0.8
0.6
0.4
Optical
density
(OD)
0.2
0.1
0.05
0.04
0.02
0.01
log n – log n0
log n
L
t
0 2 4 6
Time (hours)
8 10
log n0
FIGuRE 2.5 Graphical determination of the lag phase and the number of viable cells at the onset of batch
fermentation; as the exponential phase is extrapolated downward, it intercepts the extrapolated line of the lag
phase and the ordinate, respectively (see text for details).

in Figure 2.5 is that if one continues to extrapolate the exponential phase downward, then the point
at which the ordinate is intersected gives the number of cells that were viable and metabolically
active at the point of inoculation.
The question of whether a lag (L) has occurred during the course of the fermentation process and
for how long can be easily determined by
log log log
n n
t L T
−
−
=
0 2
(2.2)
where n is the total number of cells after a given time (t) since the start of fermentation, n0 is the
number of cells at the beginning of fermentation, and T is the organism’s mean generation time
(doubling time). Equation 2.2 describes the exponential growth, taking into consideration a lag
phase in the process. In Section 2.3.2, we shall describe the exponential phase in general and the
derivation of Equation 2.2 in particular.
2.3.2 exponentIal phase
In this phase, each cell increases in size, and providing that conditions are favorable, it divides
into two, which, in turn, grow and divide; and the cycle continues. During this phase, the cells are
capable of transforming the primary carbon source into biosyn-
thetic precursors, reducing power and energy, which is generally
trapped in the form of ATP, phosphoenolpyruvate (PEP), and
proton gradients. The biosynthetic precursors thus generated are
then channeled through various biosynthetic pathways for the biosynthesis of various monomers
(amino acids, nucleotides, fatty acids, and sugars) that, in turn, are polymerized to give the required
polymers (proteins, nucleic acids, ribonucleic acids, and lipids). Finally, these polymers are assem-
bled in a precise way, and the cell divides to give the new biomass characteristic of each organism
(Figure 2.3). The time span of each cycle (cell division) is known as generation time or doubling
time, but because we generally deal with many millions of cells in bacterial cultures, the term mean
generation time (T) is more widely used to reflect the average generation times of all cells in the
culture. Such a rate, providing conditions are favorable, is fairly constant.
If a given number of cells (n0) is inoculated into a suitable medium and the organism was allowed
to grow exponentially, then the number of cells after one generation is 2n0; at the end of two gen-
erations, the number of cells becomes 4n0 (or 22n0). It follows, therefore, that at the end of a certain
number of generations (Z), the total number of cells equals 2Zn0. If the total number of cells, or its
log value, at the end of Z generations is known, then
n = n02Z (2.3)
log n = log n0 + Z log 2 (2.4)
To determine the number of cell divisions, that is, the number of generations (Z) that have taken
place during fermentation, Equation 2.4 can be modified to give
Z
n n
=
−
log log
log
0
2
(2.5)
If T is the mean generation time required for the cells to double in number and t is the time span over
which the population has increased exponentially from n0 to n, then
Z
t
T
n n
= =
−
log log
log
0
2
(2.6)
Doubling time or mean generation time (T) is
the time required for a given population (N0)
to double in number (2N0).

If during the course of a particular fermentation, a lag time has been demonstrated, Equation 2.6
can be modified to take account of this observation. The modified equation is
Z
t L
T
n n
=
−
=
−
log log
log
0
2
(2.7)
Equations 2.6 and 2.7 can be rearranged to give the familiar equations governing the determination
of T as follows:
log log log
n n
t T
−
=
0 2
(2.8)
log log log
n n
t L T
−
−
=
0 2
(2.9)
While Equation 2.8 describes the exponential phase of growth in pure terms, Equation 2.9, however,
takes into consideration the existence of a lag phase in the process.
The exponential scale (i.e., 2, 4, 8, 16, and so on) demonstrated in Figure 2.6 obeys Equations 2.8
for logarithmic growth. Note the different position of log n0 to that cited in Figure 2.5.
Although the use of log to the base 2 has the added advantage of being able to determine the
number of generations relatively easily, because an increase of one unit in log 2n corresponds to one
generation, the majority of researchers continue to use log to the base 10. In this case, the slope of
the line (Figure 2.6) equals μ/2.303. The relationship between T and the specific growth rate (μ) can
be described mathematically by
ln 2 = μT (2.10)
1.0
20
40
60
0.8
0.6
0.4
Optical
density
(OD)
0.2
0.1
10
8
6
4
2
Time (hours) t
0
log n0
log n
log n – log n0
FIGuRE 2.6 Graphical determination of the mean generation time (T) during batch fermentation; note the
different position of log n0 with respect to that in Figure 2.2.

or
μ = ln 2/T (2.11)
Because ln 2 = 0.693, either Equation 2.10 or Equation 2.11 can be rearranged to give
T =
0 693
.
µ
(2.12)
During the course of exponential growth, the culture reaches a steady state. As such, the intracel-
lular concentrations of all enzymes, cofactors, and substrates are considered to be constant. During
this phase, one can therefore safely assume that all bacterial cells are identical and that the dou-
bling time is constant with no loss in cell numbers due to cell death. The rate of growth of a given
population (N) represents, therefore, the rate of growth of each individual cell in the population
multiplied by the total number of cells. Such a rate can be described mathematically by this dif-
ferential equation:
dN
dt
N
= µ (2.13)
This equation implies that the rate of new biomass formation is directly proportional to the spe-
cific growth rate (μ) of the organism under investigation and the number of cells (N). This pattern
of growth may be referred to as autocatalytic, a term described in this chapter. If Equation 2.13
describes the exponential phase correctly, then a straight line should be obtained when ln N is
plotted as a function of time (t). During the exponential phase, it is generally assumed that all cells
are identical, and as such the specific growth rate (μ) of individual cells equals that of the whole
population. Equation 2.13 can therefore be rearranged to take account of the fact that dN/dt is pro-
portional to the number of cells (N) and that the specific growth rate (μ) is a proportionality factor
to give
µ =
1
N
dN
dt
(2.14)
The specific growth rate (μ) is usually expressed in terms of units per hour (h–1).
Although Equations 2.9 and 2.10 describe the exponential phase satisfactorily, in some fermenta-
tions, as is the case during growth of E. coli on sodium acetate (El-Mansi unpublished results), the
organism fails to maintain a steady state for any length of time and so μ falls progressively with time
until the organism reaches the stationary phase. Such a drop in growth rate (μ) can be accounted for
by a whole host of different factors, including nutrient limitations, accumulation of inhibitors, and/
or the crowding factor (i.e., as the population increases in number, μ decreases).
2.3.2.1 Metabolic Interrelationship between Nutrient
Limitations and Specific Growth Rate (μ)
To account for the effect of nutrient limitations on growth rate (μ), Monod modified Equation 2.14
so that the effect of substrate concentration (limitations) on μ could be assessed quantitatively.
Monod’s equation is
µ
µ
=
+
m
S
S
K S
(2.15)

where S is the concentration of the limiting substrate, μm is the maximum specific growth rate, and
KS is the saturation constant (i.e., when S = KS, then μ = μm/2), as illustrated in Figure 2.7.
During growth in a steady state, Equations 2.16 and 2.17 may be used to describe growth using
biomass (X) rather than the number of cells (N) as a measure of growth:
dX
dt
X
= µ (2.16)
dS
dt
X
Y
= −µ (2.17)
where X is the biomass concentration and Y is the growth yield (e.g., biomass generated per gram of
substrate utilized). It is noteworthy, however, that during steady-state growth (i.e., in a chemostat or
a turbidostat), the terms used to describe the bacterial numbers (N) and biomass (X) in Equations
2.16 and 2.17 are identical. This is not necessarily the case in batch cultures because the size and
shape of bacterial cells vary from one stage of growth to another.
While Equation 2.16 addresses the relative change in biomass (the first variable) with respect
to time, Equation 2.17 addresses the relative change in substrate concentration (the second vari-
able) as a function of time. Note that following the exhaustion of substrate, dX/dt = dS/dt = 0.
While Equations 2.16 and 2.17 can surely predict the deceleration and stationary phases of growth,
respectively, it should be remembered that nutrient limitation is not the only reason for the decel-
eration of growth and subsequent entry into the stationary phase. In addition to environmental
factors, crowding is reported to have an adverse effect on growth rate (μ), that is, growth rate
diminishes as the size of the population increases. Although the equation describing the effect
of crowding on growth rate (the Verhulst–Pearl logistic equation) predicts a sigmoidal pattern of
growth and fits rather well with the growth curve for populations of higher organisms, yeasts, and
bacteria, it will not be further discussed in this chapter as it overlooks the effect of other environ-
mental factors on growth.
0
50%
µmax
Specific
growth
rate
(µ)
µmax
Ks
Substrate concentration [S] (g l–1)
FIGuRE 2.7 Graphical determination of specific growth rate (μ) and saturation constant (KS) during batch
fermentations; note that this graph was constructed without taking maintenance energy into consideration.
With maintenance in mind, the curve should slide sideways to the right in direct proportion to the fraction of
carbon diverted toward maintenance.

2.3.3 statIonary phase and Cell death
As the exponential phase draws to an end, the organism enters the stationary phase and thence the
death phase. If we assume that the kinetics of death are similar to that of growth, then the specific
rate of cell death (λ) can be described mathematically by
dN
dt
N
= −
( )
µ λ (2.18)
Equation 2.18 clearly indicates that if μ is greater than λ, then the organism will grow at a rate
equal to μ − λ. If, on the other hand, μ is less than λ, then the population dies at a rate equal
to λ − μ. Under conditions where μ equals λ, neither growth nor death is observed, a situation
thought to prevail throughout the course of the stationary phase. As the energy supply continues
to fall, the equilibrium between λ and μ will finally shift in favor of λ, and consequently cell
death begins.
Microorganisms respond differently to nutrient limitations during the stationary phase. For
example, while Bacillus subtilis and other Gram-positive, spore-forming organisms respond by
sporulation, E. coli and other Gram-negative, non-spore-forming bacteria cannot respond in the
same way, and as such other mechanisms must have evolved. Although a fraction of the bacterial
population dies during this phase of growth, a relatively large number remain viable for a long time
despite starvation. The ability of cells to remain viable despite prolonged periods of starvation is
advantageous, as most microorganisms in nature are subject to nutrient limitations in one form or
another. Our understanding of the molecular mechanisms employed by microorganisms for survival
during this phase of growth is rather limited. However, contrary to the notion that microorganisms
enter a logarithmic death phase soon after the onset of the stationary phase, some microorganisms
such as S. cerevisiae and E. coli adapt well to starvation, presumably through mutations and induc-
tion mechanisms, and do not readily enter a logarithmic phase of death.
The ability of some cells to survive prolonged starvation inspired some researchers to pursue the
question of whether such cells are biochemically distinguishable from their predecessors, which
were actively growing or had just entered the stationary phase. In the case of S. cerevisiae, analysis
of mRNAs, which are specifically expressed following the onset of the stationary phase, revealed
the presence of a new family of genes. This family is referred to as SNZ (short for snooze); sequence
analysis revealed that they are highly conserved. The functional role of each member of this family,
however, remains to be determined. It is interesting that some researchers use the term viable but
nonculturable (VBNC) to describe cells in the stationary phase. However, as colony-forming ability
is our only means of assessing whether a particular cell is alive or not, other microbiologists argue
the case for reversibility, that is, the cell’s ability to transform from being dormant to being meta-
bolically active. Recent investigations have revealed that resuscitation of stationary phase cells may
be aided by the excretion of pheromones as has been demonstrated in Micrococcus luteus.
In the case of E. coli, an attempt was made to identify the genes that are uniquely turned on in the
stationary phase in response to starvation, that is, not expressed during the exponential phase, with
the aid of random transposon mutagenesis. A number of mutants unable to survive in the station-
ary phase were isolated and subsequently designated as survival negative mutants (Sur–). As such,
the genes involved were designated as sur genes. While some genes, such as surA, are required for
survival during “famine” (starvation), others such as surB enable the organism to exit the stationary
phase as conditions change from “famine” to “feast.” Recent studies have also revealed that starva-
tion induces the production of a stationary phase-specific transcriptional activator (sigma factor)
that is essential for the transcription of sur genes by RNA polymerase. The physiological function
of the sur gene products is to downshift the metabolic demands made on central and intermediary
metabolism for maintenance of energy.

2.3.4 maIntenanCe and survIval
Maintenance can be defined as the minimal rate of energy supply required to maintain the viability
of a particular organism without contributing to biosynthesis. The fraction of carbon oxidized in
this way is, therefore, expected to end up in the form of carbon dioxide (CO2). The need for main-
tenance energy is obvious as the “living state” of any organism, including ourselves, is remote
from equilibrium and as such demands energy expenditure. Moreover, in addition to the carbon
processed for maintenance, another fraction of the carbon source may be wasted through excretion
(e.g., acetate, α-ketoglutarate, succinate, or lactate). In this context, excretion of metabolites ought
to be seen as an accidental consequence of central metabolism rather than by design to fulfill certain
metabolic functions. The fraction of carbon required for maintenance differs from one organism to
another and from one substrate to another. For example, maintenance requirements for the lactose
phenotype of E. coli are greater than those observed for the glucose phenotype as the lac-permease
is much more difficult to maintain than the uptake system employed for the transport of glucose,
that is, the phosphotransferase system (PTS).
The metabolic interrelationship between maintenance and growth was first described by Pirt
(1965). In his theoretical treatment of this aspect, he formulated a maintenance coefficient (m)
based on the earlier work of Monod and defined the coefficient as the amount of substrate con-
sumed per unit mass of organism per unit time (e.g., g substrate per g biomass per h). If s rep-
resents the energy source (substrate), then the rate of substrate consumption for maintenance is
governed by
–
ds
dt
mX
( ) =
M
(2.19)
where m is the maintenance coefficient. The yield can therefore be related to maintenance by
Y
x
s s
=
( ) ( )
D
D D
G M
(2.20)
where Y is the growth yield, Δx is the amount of biomass generated, (Δs)G is the amount of substrate
consumed in biosynthesis, and (Δs)M is the amount of substrate consumed for maintenance of cell
viability.
If maintenance energy (Δs)M was determined and found to be zero, then Equation 2.20
reduces to
Y
x
s
G
G
=
( )
D
D
(2.21)
Equation 2.21 clearly means that growth yield (Y) is a direct function of the amount of substrate
utilized. The growth yield (Y, gram dry weight per gram substrate) obtained in this case may be
referred to as the true growth yield to distinguish it from the YG where maintenance (Δs)M is involved.
However, if a specific fraction of carbon is diverted toward maintenance energy or survival, then
one might conclude that the slower the growth rate (μ), the higher the percentage of carbon that is
diverted toward maintenance, and the less the growth yield.
On the other hand, during unrestricted growth (i.e., no substrate limitation), the interrelationship
between substrate concentration and maintenance can be determined by (Pirt 1965)
ds/dt = (ds/dt)M + (ds/dt)G (2.22)

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