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Engineering strategies to optimize plasmid stability and protein production in recombinant Saccharomyces cerevisiae fermentation

Cheng, Chinyuan, Ph.D.

The Ohio State University, 1992

UMI 300 N. ZeebRd. Ann Arbor, MI 48106 Engineering Strategies to Optimize Plasmid Stability and Protein

Production in Recombinant Saccharomyces cerevisiae Fermentation

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

Chinyuan Cheng, B.S., M.S.

The Ohio State University

1992

Dissertation Committee: Approved by Dr. S. T. Yang Dr. J. J. Charlmers Dr. J. F. Davis Adviser Department of Chemical Engineerings To My Parents ACKNOWLEDGMENT

I wish to express my appreciation to Dr. S. T. Yang for his support and insight throughout the research. I would also like to thank the other members of my advisory committee, Dr. Jeffrey J. Chalmers, Dr. Jim F. Davis and Dr. Jacques L. Zakin for their useful suggestions and comments. I also would like to acknowledge some friends who have been most helpful in various part of this study. Design engineer Mike Kukla and machinist Roy R. Renshaw helped me to set up the control system. Mr. Gary L. Kleman and Mr. Don E. Ordaz provided me technical assistance in using the computer-controlled glucose-stat. I sincerely thank for my friends who helped me get through my study, especially Dr. Jacques L. Zakin for his constant support and encouragement, C. H. Shu and J. W. Yen for their friendship and care, Mr. Raghavan V. Venkat for proofreading my dissertation. Finally, I appreciate my parents for their priceless love and support to make my education possible. VITA

October 29, 1960 ...... Bom in Tainan, Taiwan, Republic of China

June, 1983 B.S. Chemical Engineering Tunghai University Taichung, Taiwan, R.O.C.

1983-1985 ...... Military Service Chinese Navy

1986-1988 ...... M.S. Chemical Engineering The Ohio State University Columbus, OH

1988-Present ...... Graduate Research and Teaching Associate Department of Chemical Engineering, The Ohio State University Columbus, OH

FIELDS OF STUDY

Major Field : Chemical Engineering

Minor Field : Biochemical Engineering TABLE OF CONTENTS

ACKNOWLEDGMENTS------ii

VITA------iii

LIST OF TABLES------ix

LIST OF FIGURES.------xi

NOMENCLATURE------xvi

ABSTRACT------xviii

CHAPTER PAGE

I. INTRODUCTION ...... I

II. LITERATURE REVIEW------6

Introduction ...... —...... 6 High Cell Density Fermentation ...... 8 Factors Affecting Cell Density ...... 11 Control Strategy for High Cell Density Fermentation— 18 Plasmid Stability ...... 18 Genetic Function of Cells and Recombinant Plasmid — 19 Types of Plasmid Instability ------21 Intrinsic Factors Affecting Plasmid Stability ------22 Environmental Factors Affecting Plasmid Stability 23 (1) Effect of Growth Nutrients ...... 23 (2) Effect of Temperature ------24 (3) Effect of Growth (Dilution) Rate ------26 (4) Effect of Oxygen Tension ------26 Determination of Plasmid-Carrying Cells ------27 Strategies for Overcoming Plasmid Loss...... 31 (1) Genetic Method ------31 (a) Use of Genes Modulating ------31

iv (b) Incorporation into Chromosome 31 (c) Natural Immunity ------32 (d) Double Auxotrophic Mutant. ------33 (e) Secretion ------34 (2) Operation Strategies ------35 (a) Selective Pressure------35 (b) Cell Immobilization ------40 (c) Separation of Growth and Production Phases 41 (d) Recycling Plasmid-Carrying Cells — 44 (e) Cyclic Oscillation in Fermentation Conditions 45 Cloning Vectors for Saccharomyces cerevisiae ------49 Plasmid with a Partition Sequence ------50 Plasmid Based on the Yeast 2 Micron Circle ------50 The Characteristics of Yeast Used in This Study 51 (1) Construction of Plasmid pSXR 125 ------55 (2) The Characteristics of Auxotrophic Yeast— 57 References ------59

III. EFFECT OF TEMPERATURE ON BATCH FERMENTATION OF A RECOMBINANT YEAST STRAIN CONTAINING A TEMPERATURE- SENSITIVE PROMOTER...... 72

Abstract ------72 Introduction ...... 73 Materials and Methods ...... 75 Yeast and Plasmid ------75 Growth Media ------75 Fermentation ------76 Analytical Methods ...... 76 Results and Discussion ...... 81 Plasmid Stability in Flask ------81 Fermentation Kinetics ...... 82 (1) Specific Growth Rate ...... -...... 96 (2)Cell Yield...... -...... 100 (3) Product Yield ...... 104 (4) Specific Production- ...... 107 (5) Plasmid Stability ------109 Mathematical Model ...... 114 (1) Parameter Estimation ------116 Conclusion ------118 References ------122

V IV. DYNAMIC RESPONSES OF GENE EXPRESSION TO TEMPERATURE SWITCH DURING FERMENTATION------124

Abstract ------124 Introduction ------125 Materials and Methods ------127 Yeast and Plasmid ------127 Growth Media ------127 Fermentation ------127 Analytical Methods ------128 Results and Discussion ------129 Batch Fermentation ------129 Repeated Batch Fermentation ------132 (1) Turn-Off Action ------132 (2) Turn-On Action ------133 Continuous Fermentation ------140 (1) Turn-Off Action ------140 (2) Turn-On Action ------140 (3) Turn-Off Then Turn-On ------140 Mathematical Model ------145 (1) Parameter Estimation— ...... 149 Conclusions and Recommendation ------153 References ------157

V. EFFECT OF OSCILLATING GLUCOSE CONCENTRATION ON PLASMID STABILITY AND RECOMBINANT PROTEIN PRODUCTION IN REPEATED BATCH FERMENTATIONS------158

Abstract ------158 Introduction ------159 Materials and Methods ------161 Yeast and Plasmid ------161 Growth Media ------162 Fermentation ------162 Analytical Methods ------163 Results and Discussion ------163 Continuous Fermentation ------163 Batch Fermentation ------165 Repeated Batch Fermentation ------169 (1) Comparison of Various Fermentations 175 Conclusions and Recommendation ------176 References ------180

VI. CONCLUSION AND RECOMMENDATION

Conclusions ------183 Recommendations ------185

APPENDICES ------188

A. EFFECT OF CYCLIC ENVIRONMENTAL CONDITIONS ON RECOMBINANT YEAST FERMENTATION------189

Abstract ------189 Introduction ------190 Materials and Methods ------191 Yeast and Plasmid ------191 Growth Media ------191 Fermentation ------192 Analytical Methods ------193 Results and Discussion ...... 194 Oscillation in glucose— ...... 194 Oscillation in Temperature- ...... -...... 195 The Comparison of Specific Productivity and Plasmid Stability Between Cells Under Cyclic Oxygen Level and Cells With Fixed Oxygen Level in Chemostat ...... 201 Conclusions ------205 Recommendations ------206

B. COMPUTER-CONTROLLED BIOFLO II FERMENTOR 207

Installation ------207 Control Method...... 209 Feeding of Nutrient by On-Line Glucose Control System 209 Feeding of Nutrient by On-Line Measurement of Turbidty 213

C. THE ADAPTIVE COMPUTER CONTROL PROGRAM IN FED-BATCH FERMENTATION FOR BIO-FLO II BIOREACTOR------218 D. A COMPUTER PROGRAM FOR THE KINETIC MODEL IN BATCH FERMENTATION------249

LIST OF REFERENCES. 252 LIST OF TABLES

TABLE PAGE

2.1. The maximum IFN-q and cell concentrations in various induction methods ------10

2.2. The effects of glucose concentration on cell yield of baker's yeast and the production of ethanol under aerobic conditions — 12

2.3. The list of a saturation constant (k ) from different source - 13

2.4. The effect of glucose and ethanol concentration on oxidative and fermentative metabolism, maximum specific growth rate, cell yield rate, respiratory quotient (RQ) and ATP yield 17

2.5. The effect of plasmid copy number on m of Host (E, coli HB10G 20

2.6. Some controllable promoters for use in expression vectors . 48

2.7. p-Galactosidase activity at various temperature in yeast transformed with plasmid pSXR125 ------53

3.1. Estimated values for parameters in the proposed model for growth in the nonselective medium ...... 120

3.2. Estimated values for parameters in the proposed model for growth in the selective medium ------121

4.1. Estimated values for parameters in the proposed model — 155

5.1. Comparison of plasmid stability in various fermentations -- 178

ix 5.2. Comparison of cell dry weight, P-galactosidase production and specific production of P-galactosidase from various fermentations ------179

A. 1 Component of the HPLC ------193

A.2. The comparison of plasmid stability between cells experiencing the cyclic oscillation of oxygen level and cells without any oscillation ------204

A.3. The comparison of cell dry weight, P-galactosidase production and specific productivity between cells experiencing the cyclic oscillation of oxygen level and cells without any oscillation 204

B. 1. Comparison of maximum cell density, glucose cosumed, cell yield and product yield between the batch fermentation in the selective medium and the fed-batch fermentation ------216

X LIST OF FIGURES

FIGURE PAGE 2.1. A simplified metabolic map of Saccharomyces cerevisiae (Coppella and Dhurjati, 1989) ------14

2.2. The effect of ethanol concentration on the specific growth rate of various yeast strains (Bazua and Wilke, 1977) ------16

2.3. Graphic representation of yeast aerobic catabolism and substrate dependence ------16

2.4. Construction of plasmid pMA902 (Struhl et al. (1979) ------52

2.5. Construction of plasmid pJDB207 (Zakian et al., 1979) — 52

2.6. Construction of plasmid pSXR125 ------54

2.7. Representation of temperature-dependent regulation of hybridpromoters in pSXR125 ------54

3.1. The plot of optical density at A, = 420 nm versus the weight percentage of ONPG. ------79

3.2. Fraction of plasmid-containing cells in flask cultures with the selective medium. The arrows show when the flask culture was transferred to a fresh medium. ------83

3.3. Batch recombinant yeast fermentation with the selective medium (a) at 22 «C.------84 (b) at 24 °C. ------85 (c) at 25 °C ------86 (d) at 27 °C .------87 (e) at 28 <>C. ------88 (f) at 32 OC.------89

xi 3.4. Batch recombinant yeast fermentation with the nonselective medium (a) at 25 o c . ------90 (b) at 28 °C. ------91 (c) at 32 °C .------92

3.5. Batch fermentation kinetics for plasmid-free cells with the nonselective medium (a) at 25 °C ------93 (b) at 28 °C ------94 (c) at 32 °C ------95

3.6. The plot of ln(cell density) vs. time with the selective medium at various temperatures ------97

3.7. The plot of ln(cell density) vs. time with the nonselective medium at various temperatures ------98

3.8. Effect of temperature on the specific growth rate------99

3.9. The plot of cell concentration versus glucose concentration in the selective medium — ...... 101

3.10. The plot of cell concentration versus glucose concentration in the nonselective medium ------102

3.11. Effect of temperature on cell yield ...... -...... 103

3.12. The plot of P-galactosidase versus glucose concentration in the selective medium------105

3.13. Effect of temperature on product yield ...... 106

3.14. The specific production of P-galactosidase in the selective medium at various temperatures ------108

3.15. plasmid stability in batch fermentations with the selective medium------111

xii 3.16. kinetics of cell concentrations including total cells, plasmid- carrying cells and plasmid-free cells in a batch fermentation at 25 °C with the selective medium. ------112

3.17. plasmid stability in batch fermentations with the nonselective medium------113

4.1. Kinetics of batch fermentation with temperature switch from 30 °C to 24 OC- (a) time course data------130 (b) temperature switch at 15 hrs ------130 (c) specific production ------131

4.2. Dynamic responses of P-galactosidase production to temperature switch from 24 °C to 30 °C in a repeated batch fermentation - (a) time course data ------135 (b) temperature switch ------135 (c) specific production ------136

4.3. Dynamic responses of P-galactosidase production to temperature switch from 30 °C to 24 °C in a repeated batch fermentation - (a) time course data...... 137 (b) temperature switch ...... 137 (c) specific production ...... 138

4.4. The specific change of P-galactosidase ------139

4.5. Dynamic responses of the recombinant yeast to temperature- switch between 24 °C and 30 °C in continuous fermentation at 0.133 hr'l dilution rate. ------141

4.6. Dynamic responses of the recombinant yeast to temperature switch from 24 °C to 30 °C in a continuous fermentation at 0.1 hr"* dilution rate...... 142

4.7. Dynamic responses of the recombinant yeast to temperature switch from 30 °C to 24 °C in a continuous fermentation at 0.1 hr"l dilution rate. ------143

xiii Dynamic responses of the recombinant yeast to temperature switch from 30 °C to 24 °C in a continuous fermentation at 0.05 h r 1 dilution rate. ------144

Diagram of transfer function for the dynamic response of the change of recombinant protein concentration to temperature switch ------146

Dynamic responses of the concentration of P-galactosidase in the continuous reactor to temperature switch from 24 °C to 30 °C, (a) at 0.133 hr'l and (b) at 0.1 hr"l at dilution rate. Symbols show the data, and curves show model predictions ------150

Dynamic responses of the concentration of P-galactosidase in the continuous reactor to temperature switch from 30 °C to 24 °C, (a) at 0.1 hr-1 and (b) at 0.05 hr’l dilution rate. Symbols show the data, and curves show model predictions ------151

Effects of the dilution rate on gene response to (a) turn-off action and (b) turn-on action. ------152

Continuous fermentation with the nonselective medium at 25 °C. 164

Batch recombinant yeast fermentations at 25 °C. (a) selective medium------166 (b) nonselective medium ------167 (c) rich medium ...... 168

Repeated batch fermentation with the selective medium and followed by the addition of the selective medium at 25 °C. 170

Repeated batch fermentation with the nonselective medium and followed by the addition of the nonselective medium at 25 °C. 171

Repeated batch fermentation with the selective medium and followed by the addition of the nonselective medium at 25 °C. 173

Repeated batch fermentation with the selective medium and followed by the addition of the rich medium at 25 °C . ---- 174

xiv A.I. The kinetic of cell physiology and plasmid stability of recombinant yeast fermentation in glucose-stat at the setpoint of 1.0 g/L glucose concentration. ------196

A.2. Cyclic oscillation of glucose concentration between 1 g/L and 0 g/L with cycling time, 8 hours at 1 g/L and 4 hours at 0 g/L. 197

A.3. The experimental results of the kinetic behavior of recombinant yeast in glucose-stat in rich medium with temperature oscillation 200

A.4. The plot of cycling time, 8 hours, between 24 0 C and 30 0 C 200

A. 5. The physiology and plasmid stability in yeast continuous fermentation with rich medium at 80% of saturated dissolved oxygen level. ------202

A.6. The influence of the oscillation of dissolved oxygen level on the cell physiology and plasmid stability in the chemostat. — 203

B. 1. BioFlo II fermentor and its functions. ------211

B.2. The schematic diagram for computer-assisted on-line glucose close-loop fermentation system...... 212

B.3. The block diagram of on-line glucose adaptive plus feedback control system. ------213

B.4. The block diagram of on-line control by the measurement of the turbidity. ------215

B.5. Fermentation kinetics of on-line control by the measurement of the turbidity ------217

XV NOMENCLATURE a account for the growth rate of plasmid-carrying cells which can b expected to be lower when metabolite is not limiting

3 segregational instability i%iaPP maximum apparent specific growth rate in selective medium p + specific growth rate of plasmid-containing cells (1/hr)

M-" specific growth rate of plasmid-free cells (1/hr)

Pm+ maximum specific growth rate of plasmid-containing cells (1/hr)

Pm" maximum specific growth rate of plasmid-free cells (1/hr)

D dilution rate (1/hr)

F fraction of plasmid-carrying cells

Pave average of fraction of plasmid-carrying cells in selective medium

F0 initial fraction of plasmid-carrying cells

cell's affinity for the substrate

P production of P-galactosidase (g/L)

Po initial production of p-galactosidase (gP/L)

S substrate (glucose) concentration (g/L)

So initial substrate (glucose) concentration (g/L)

xvi t fermentation time (hr)

T temperature ( °C)

X+ concentration of plasmid-containing cells (g/L)

X- concentration of plasmid-free cells (g/L)

Xt total cell concentration (g/L)

Xto initial total cell concentration (g/L)

Y+p/S X+ production yield based on the consumption of glucose (gP/gS)

Y'P/S X" production yield based on the consumption of glucose

Y+X/S X+ cell yield based on the consumption of glucose

Y"X/S X' cell yield based on the consumption of glucose

xvii ABSTRACT

xix CHAPTER I INTRODUCTION

The bakers' yeast, Saccharomyces cerevisiae, is an attractive host for the production of recombinant proteins. It has no known pathogenic relationship with man. It lacks endotoxin and lytic viruses, and is generally recognized as safe. Saccharomyces cerevisiae has been used industrially for centuries in baking and brewing industries. Efficient large-scale propagation of yeast cell cultures to high cell density has also been extensively studied. The overall production of a recombinant protein mainly depends on three factors, cell density, plasmid stability and expression level. The major factors affecting cell growth rate and cell density are associated with medium formulation and control strategies for medium addition. The problems of plasmid maintenance and gene expression are not only dependent on the plasmid construction and the chosen host cell, but also are related to many operation strategies, medium formulation, bioreactor design and environmental conditions. A Saccharomyces cerevisiae strain with a temperature-regulated expression system for the production of a heterologous gene product, developed by Seldziewski et al.(1988), was used in this study. The plasmid pSXR125 was constructed to give Saccharomyces cerevisiae (host) the ability to grow in the medium without tryptophan (selective marker) and to produce P-galactosidase (heterologous gene product) in a temperature-regulated fashion.

1 In this research, various operation strategies to achieve high cell density and to enhance plasmid stability in recombinant yeast fermentations were studied. The content of each chapter in this thesis is as follows. In Chapter 2, important factors affecting the overall production of recombinant proteins are critically reviewed based on available literature. Operation strategies useful for achieving high cell density in fed-batch (or high cell density) fermentation are also reviewed. The factors affecting plasmid stability and various genetic and engineering methods for the maintenance of plasmid stability are reviewed. The construction of the plasmid pSXR125 and characteristics and functions of each gene on this recombinant plasmid are then discussed in detail. The metabolic pathway for the biosynthesis of tryptophan in yeast is also presented. This provides the information necessary to the understanding of the auxotrophic yeast used in the study. Temperature is one of the most important environmental factors affecting cell growth. Temperature, besides its general effect on reaction rate, can exert highly selective effects on metabolic pathways; by repression of particular protein synthesis for example. Thus, the culture as a whole may have varied and complex responses when temperature is altered. In addition to the specific growth rate and cell yield, temperature also affect productivity and plasmid stability when the recombinant yeast cell contains a temperature-sensitive promoter. Thus, the effects of temperature on the recombinant yeast containing the temperature-sensitive promoter in batch fermentations were studied first and the results are presented in Chapter 3. Also, a simple model was developed to describe cell growth, glucose consumption, product formation and plasmid stability in batch fermentations with selective and nonselective media. The computer program, written in FORTRAN language, used in developing the kinetic model is attached in Appendix D. The separation of growth phase and production phase has been proposed as an effective strategy to enhance plasmid stability and reactor productivity. In this case, the fermentation is conducted in two stages, with the restrictive temperature in the first stage and the permissive temperature in the second stage. In general, at the permissive temperature (< 28 °C for the yeast used in this study), a high level gene expression is allowed and plasmid stability is poor. On the other hand, at the restrictive temperature (>30 °C), low production but high plasmid stability are found. Therefore, a two-stage process would allow the plasmid-carrying cells to compete well with the plasmid-free cells in the first stage, thus reducing the competition instability and attaining a high density of plasmid-carrying cells before entering the second stage. The overall production thus would be much higher than a single-stage process. However, the cell response time to temperature change would be an important factor in considering the use of a two-stage fermentation process with the growth phase and production phase controlled by temperature. Cyclic oscillation of growth conditions, such as the specific growth rate and dissolved oxygen level, have also been proved as an effective method to favor the plasmid-carrying cells in competing with plasmid-free cells. It may be feasible to maintain the plasmid stability by forced oscillation in the specific growth rate by oscillating the reactor temperature. However, the cell response time to temperature oscillation is again a key factor to the use of this operation strategy. The dynamic responses of gene expression in the recombinant yeast cells to temperature shift-up (turn-off action) and shift-down (turn-on action) were studied in batch, fed-batch and continuous cultures, and the results are presented in Chapter 4. The information obtained here would be useful in determining if a two-stage process or a cyclic temperature oscillation system would be advantageous for the yeast cells studied. Similarly, cyclic oscillation of glucose concentration in the culture may have a positive effect in improving plasmid stability and reactor productivity. Repeated batch fermentations were conducted and are described in Chapter 5. In these experiments, new glucose was added to the batch cultures near glucose depletion several times to achieve the oscillation effect. It was found that higher productivity and better plasmid stability were achieved even though non-selective media were used. Therefore, the cyclic oscillation of other factors such as specific growth rate and dissolved oxygen also may effectively improve the problem of plasmid loss during fermentation. Three factors, glucose concentration, temperature and dissolved oxygen were tried. The influence of the cyclic glucose level between 0 g/L and 1 g/L on the plasmid stability and cell physiology was carried out in glucose-stat. Temperature oscillation between the permissive temperature, 24 °C, and the restrictive temperature, 30 °C, was executed in glucose-stat at the setpoint of 1 g/L glucose concentration. Oscillation of the dissolved oxygen level between 30% and 90% of the saturated dissolved oxygen was done in chemostat. The results from these experiments, however, were not positive or conclusive, and are included in Appendix A. The installation and control method of a computer-controlled BioFlo II fermentor is discussed in Appendix B. In this system, the turbidity of cell broth was determined by using an optical fiber device. The cell concentration was then calculated by the predetermined calibration curve between the reading from optical fiber and cell concentration. The control method for glucose feeding was based on the glucose demand calculated from the change of cell concentration during fermentation and a predetermined constant cell yield. This strategy seemed to work well for a trial run, which results are also included in this Appendix. The computer control program written in BASIC language for BioFlo II Bioreactor used in fed-batch fermentation is presented in Appendix C. Conclusion and recommendations for future studies are given in Chapter 6. CHAPTER H LITERATURE REVIEW

Introduction

Fed-batch culture is an efficient technique to grow recombinant cells to high cell density and to attain high productivity of recombinant gene product and metabolites. To maximize the cell density and production of recombinant proteins is the major goal for a high cell density fermentation. The production of recombinant proteins is associated with the total number of cells. The optimal feeding strategy for the high cell density fermentation of Saccharomyces cerevisiae must be developed, because it is governed by product and substrate inhibited growth and product formation kinetics. In the past, three major types of control strategies for balance of feeding with demand were developed: the feeding rate of substrate based on the historical data, the indirect feedback control of substrate feed based on the measurement of non-substrate parameters, and the direct feedback control of substrate feeds based on the measurement of substrate concentration. The feeding rate of substrate based on the direct feedback control method is more accurate, since no assumption needs to be made about the metabolism of the organism. The other problem for the high cell density fermentation is the plasmid loss in the host cells during the course of fermentation. Plasmid loss not only affects the total production of recombinant proteins, which is called gene dosage effect, but also wastes a lot of nutrients utilized by the plasmid-free cells without any production. Factors affecting the stability of a plasmid include the genetic make-up of a plasmid, physiology of the host cells and environmental conditions such as temperature, medium formulation and dissolved oxygen. The methods used to overcome plasmid loss generally can be classified into two categories. The first one is to construct a stable plasmid for host cells by using a genetic method. Various strategies using genetic methods have been applied, including plasmids with even partition sequence, incorporation into chromosome, natural immunity and double auxotrophic mutant. The second way is to use better operation strategies by considering environmental factors to stabilize the plasmids. These strategies include selective pressure, cell immobilization, separation of growth and production phase, recycling the plasmid-carrying cells, and cyclic oscillation in fermentation conditions. In order to achieve high cell density and high production of the recombinant protein product in a high cell density fermentation, a feeding strategy for cell growth and methods for overcoming plasmid loss need to be developed. In the following sections, two major topics, one in high cell density fermentation and one on plasmid stability in recombinant cell fermentation, are discussed in detail. Factors affecting cell density and control strategies for achieving high cell density in fermentation are elucidated first. Then, various factors affecting plasmid stability and the genetic and engineering methods for the maintenance of plasmid stability during recombinant cell fermentations are reviewed. 8 High Cell Density Fermentation

Fed-batch culture is an efficient cultural technique to achieve high cell density and high production of recombinant gene product and metabolites. In high cell density fermentations, it is necessary to optimize the nutrient concentration to favor cell growth, and to maximize the production of the recombinant gene product. A control method for feeding the nutrients is thus essential to achieve this goal. The controlled fed-batch fermentation of baker's yeast for the production of ethanol have been studied extensively (Takamatsu, et al., 1985 and Hong, 1986). Recently, high cell density recombinant R coli fermentations have been also extensively studied (Tsai, et al., 1987, Fieschko and Ritch, 1986). Surprisingly, only a few articles about the high cell density fermentation of recombinant baker's yeast can be found in the literature. Hsieh et al. (1988) studied a controlled fed-batch fermentation of recombinant Saccharomyces cerevisiae producing hepatitis B surface antigen (HBsAg). In their experiments, a selective medium was added in the first 30 hours of fermentation to prevent plasmid loss, then the addition of a nonselective (rich) medium was followed. The medium adding rate was controlled to maintain a constant low glucose concentration in the reactor. For the YNN27/pDCB- S2 strain with GPD promoter, the highest cell concentration was approximately 35 g dry weight/L and the HBsAg expression level was 10 mg/L. No detailed information about the control strategy and plasmid stability during the process were presented. A growth-rate-control based on the glucose uptake rate in fed- batch culture of recombinant Saccharomyces cerevisiae producing hepatitis B surface antigen (HBsAg) with a selective medium was developed by Bitter et al. (1988), Gu et al. (1989) and Gu et al. (1991). According to the Bitter's experimental results, the cell density could reach as high as 100 g/L and the final concentration of recombinant HBsAg was 54 mg/L. From Gu's data, the highest cell density could only reach 31 g/L and the highest production of HBsAg was 20 mg/L. The difference between Bitter's and Gu's experimental results for the performance of recombinant yeast resulted from the different physiology of cells and the construction of the plasmid. They also concluded that the HBsAg formation was growth-associated. The fed- batch cultivation method based on the production kinetics of a batch culture enhanced HBsAg production ten times more than in the batch culture. The production yield in the fed-batch fermentation was two times higher than that in a batch fermentation. Fieschko, et al. (1987) studied the controlled expression and purification of human immune interferon (IFN-y) from high-cell-density fermentations of Saccharomyces cerevisiae. The expression of IFN-y in the hybrid yeast promoters (PGK and GPD(G)), in conjunction with various yeast strains (RH218-D, J 17-3 A and DM-1), were able to be turned off or turned on by employing glucose or galactose as the carbon source, respectively. The maintenance of plasmids by the separation of growth phase and production phase coupled with a feeding control strategy based on the respiratory quotient was applied in their experiments. As shown in Table 2.1, efficiently regulated expression vectors, combined with high cell density fermentation, resulted in the production of greater than 2.0 g interferon/L fermentation culture. The cell concentration reached as high as 100 g of cell dry weight/liter, with about 50% plasmid-carrying cells at the end of the fermentation. Three different methods of induction by galactose were used in three seperate experiments (1) separate 10 g/L shot addition of galactose to a culture that was continuously fed and growing under carbon limitation, ( 2) replacement of the glucose feed by a galactose feed so that galactose was the predominant carbon/energy source, and (3) a combination of method 1 followed by method 2.

Table 2.1. The maximum IFN-y and cell concentrations in various induction methods.

Experiment Promoter Induction Maximum Maximum Medium Host method cell IFN-y type conc.(g/l) conc.(u/l) 1 PGK constitutive* 15 1.5*108 minimal RH218-D 2 PGK constitutive* 19 2.2*108 enriched RH218-D 3 GPD(G) 1* 76 2.0* 109 enriched J17-3A 4 GPD(G) 2* 83 3.3* 10 9 enriched J17-3A 5 GPD(G) 3* 53 5.6* 10 9 enriched J17-3A 6 GPD(G) 1* 110 2.2* 1010 enriched DM-1 * : represent various methods of galactose induction of IFN-y expression

In the following sections, the discussions will be divided into two parts. The first part will discuss major factors affecting maximization of cell density. The second part will present factors affecting plasmid instability and various strategies for overcoming the plasmid loss. Factors Affecting Cell Density In a fed-batch fermentation, a high substrate concentration resulting from unbalanced feeding may cause the formation of inhibitory byproducts and inhibit cell growth and product formation. The effects of glucose and ethanol on cell growth and control strategies for high cell density fermentation are discussed in the following sections.

(1) Effect of Glucose Figure 2.1 shows a simplified metabolic map of Saccharomyces cerevisiae involving the glycolysis of sugar to the branch point pyruvate and its connection with either ethanol formation or the TCA cycle. Through the aerobic metabolism of Saccharomyces cerevisiae. glucose is converted to carbon dioxide, cell mass and ethanol. However, the amount of ethanol produced is dependent on the glucose concentration. The influence of the glucose concentration on the physiology of cells in a continuous culture has been studied by Brown and Johnson (1970). Table 2.2 shows the effects of glucose concentration in the vessel (i.e. outlet glucose concentration) on cell yield of Saccharomyces cerevisiae and ethanol production in the continuous fermentation under aerobic conditions. At low glucose concentration (below 0.5 g/1), cell yield and specific ethanol production were proportional to the glucose concentration. Glucose, at concentrations ranging from 0 to 0.5 g/1, is degraded predominantly by oxidative fermentation. When the glucose concentration was above 0.5 g/1, cell yield did not change with glucose concentration, but the amount of ethanol accumulated in the growth medium increased with an increase in the glucose concentration. This phenomenon is called Crabtree effect (Crabtree, 1929). An increase in the concentration of glucose results in a repression of the synthesis of oxidative 12 (respiratory) enzymes and is manifested by decreased oxygen uptake coupled with accumulation of intermediate such as ethanol.

Table 2.2. Effects of glucose concentration on cell yield of baker's yeast and the production of ethanol under aerobic conditions in continuous fermentation

Inlet Outlet Cell conc. Cell yield Ethanol (g/L) Ethanol glucose glucose (g/L) (g dry wt./ yield (g/g conc.(g/L) conc.(g/L) gglu. cell) consumed.) 1.0 0 0.05 0.05 25 500 2.0 0.5 0.18 0.12 136 960 5.0 1.62 0.44 0.13 590 1345 10.0 4.43 0.78 0.14 1440 1850 50.0 40.75 1.11 0.12 1800 2120

Brown and Johnson (1970) and Johnson et al. (1972) claimed that the metabolic change of Crabtree effect might be associated with a decrease in mitochondria components which led to a general decrease in total fatty acids, glycerophospholipids and sterol esters. Coppella and Dhurjati (1989) proved that the level of TCA enzyme activity decreased by about 90% of the maximum enzyme activity when the Crabtree effect occurred. An extremely high concentrated of glucose solution also may severely damage or even kill cells due to osmotic shock. Besides the glucose concentration, the Crabtree effect was also shown to be caused by the change of the specific growth rate of Saccharomyces cerevisiae. Meyenburg (1969) showed that above a specific growth rate of 0.2-0.25 h , ethanol would accumulate in the medium, and would lead to a transition from oxidative to fermentative metabolism. Table 2.3. The list of a saturation constant (ks ) from different sources 13 ks (g/L) Reference 0.2-0.4 Moo-Young (1985) 0.40 Ryder and DiBiasio(1984) 2.05 Abulesz and Lyberatos(1989) 0.00021 Satyagal and Agrawal (1989) 0.85 Davis and Parnham (1989) 0.22 Hong (1986) 0.5 Shields (1989)

Table 2.3 shows the values of the saturation constant ks in the Monod equation found in the literature. Apparently, the specific growth rate will be sensitive to the glucose concentration up to 2 g/L if ks value is about 0.2 g/L. This also implies that the Crabtree effect will be sensitive to the glucose concentration at least up to 2 g/L. This is consistent with the result shown in Table 2.2.

(2) Effect of Ethanol In the anaerobic pathway of Saccharomyces cerevisiae. glucose is converted to ethanol and carbon dioxide via glycolysis. However, too much ethanol present in the medium is toxic to yeast and will inhibit the cell growth. The effect of ethanol concentration on the specific growth rate of various yeast strains under aerobic (or anaerobic) conditions is shown in Figure 2.2 (Bazua and Wilke, 1977). This experimental result shows that ethanol inhibition is generally negligible at low ethanol concentration (less than 20 g/L) but increases rapidly at high concentration. The reason that ethanol causes the inhibition of yeast growth is directly related to the inhibition and denaturation of important glycolytic 14

G lu -lP - Poly X y - ATP saccharide; Ribulose-5P-^- Glu-6P

' KAT? * Fru-l,6diP Nucleic acids

Glyceraldehyde-3P Dihydroxy acetone-P MAD NADH CO o llf NADH _ l > v r 2 a t p Glycolysis Ethanol" —r*—^ Pyruv aldehyde

I * ' NADH Acetyle-CoA -► Fattv acids

Respiration

ADP ATP co TCA- cycle NADH NAD

Amini Proteins acids

Figure 2.1. A simplified metabolic map of Saccharomyces cerevisiae (Coppella andDhurjati, 1989) enzymes, as well as to the modification of cell membrane (Rose and Beavan, 1981 and Millar et al., 1982). Graphic representation of yeast catabolism and substrate dependence is shown in Figure 2.3 (Coppella and Dhurjati, 1989). The summary of the effect of glucose and ethanol concentration on oxidative and fermentative metabolism, maximum specific growth rate, cell yield rate, respiratory quotient (RQ) and ATP yield is presented in Table 2.4. 16

1.0

0.5

20 40 60 100 Ethanol Concentration (g/liter)

Figure 2.2. The effect of ethanol concentration on the specific growth rate of various yeast strains (Bazua and Wilke, 1977) (different symbols represent different strain)

3$ ro>— i Glucose o Fermentation / CJ 3 3 Glucose Tanol Oxidative dative [Ethanol] (g/I)

Figure 2.3. Graphic representation of yeast aerobic catabolism and substrate dependence 17 Table 2.4. effect of glucose and ethanol concentration on oxidative and fermentative metabolism, maximum specific growth rate, cell yield rate, respiratory quotient (RQ) and ATP yield

[Case 1]: Low glucose concentration ([glu] < 0.05-0.13 g/L)

c 6h 12°6+ 6 02 —> 6 H 2O + 6 CO2 (i.e. glucose is oxidized ) [Prnax] = 0.25 - 0.30 (1/hr) Yx/S = 0-5 ( g of cell dry weight / g of glucose consumed) R.Q. = 0.9- 1.0 ATP yield = 16 - 28 ( mole/glucose oxidized)

[Case 2]: High glucose concentration

c 6h 1206+ 6 O 2 —> 6 H2O + 6 CO2 (i.e. glucose is oxidized ) C6H12O6—> 2 C2H5OH + 2 CO2 (i.e. glucose is fermented) [l-hnax] = 0-40 - 0.45 (1/hr) Yx/S = 0.15 ( g of cell dry weight / g of glucose consumed) R.Q. > 1.0 ATP yield = 2 ( mole/glucose oxidized)

[Case 3]: No glucose, Ethanol accumulation

C2H5OH + 3 O2 —> 3 H2O + 2 CO2 (i.e. ethanol is oxidized ) [Umax] = 0.10-0.18 (1/hr) Yx/S = 0-5 ( g of cell dry weight / g of glucose consumed) R.Q. <0.9 ATP yield = 6 - 11 ( mole/ethanol oxidized) 18 Control Strategy for High Cell Density Fermentation In order to maintain the balance of substrate feed with demand, three approaches have been developed. First, feeding the substrate controlled by an open-loop control scheme based on historical data (Yamane and Shimizu, 1984; Strohl et al., 1986). Second, indirect feedback control of substrate feeds based on the measurement of non-substrate parameters such as pH (pH-stat; Susuki et al., 1987; 1988), product formation (e.g., ethanol, acetone, butanol; McLaughlin et al, 1985), calculated respiratory quotient (Spruytenburg et al., 1979), mass balance equations (Mou and Cooney, 1983), or offgas concentrations (Suzuki, 1986a). Third, direct feedback control of substrate feed based on an on-line measurement of limiting substrate using on-line analyzers (Suzuki et al., 1986b,c; Kole et al., 1986; Ghoul et al., 1986; Luli et al., 1987). This third strategy is by far the most desirable, since no assumptions need to be made about the metabolism of the organism. Kleman et al.(1991) developed a combined adaptive and feedback control algorithm with direct control methods for the substrate demand to provide constant glucose concentration in fed-batch fermentations. Their experimental results show that the glucose concentration in fed-batch fermentation can be maintained as tight as 0.49 + 0.04 g/1 during growth of E, coli.

Plasmid Stability

An important factor in the scale-up of a recombinant microbial fermentation is the plasmid employed. However it is not always easy to maintain the plasmid copy number per cell and the stability of the plasmid itself. Especially in continuous fermentations or high cell density fermentations, which require long fermentation time, the problem of plasmid loss becomes worse. 19 From the statistic viewpoint, the percentage of plasmid-free cells during cell division after one generation by random partition is as high as 16.67%. Freifielder (1986) studied the stability of wild-type plasmids. The loss rate of low-copy number could be as low as 10"? per cell division. A mechanism for the stability of wild-type plasmids must involve the control of replication and partition of the wild-type plasmid (Nordstrom and Austin, 1989). Unfortunately, recombinant plasmids are not as stable as wide-type plasmids, because recombinant plasmids lack the same ability for the control of replication and partition as wide-type plasmids. The stability of a wide range of host plasmid constructs have been studied by Futcher and Cox (1984). They concluded that considerable variation exists in both stability and copy number from plasmid to plasmid and from host to host. The factors causing plasmid instability can be classified into seven categories: segregational instability, structural instability, incompatibility, plasmid size, selection, copy number, host ploidy and daughter cell size effects.

Genetic Function of Cells and Recombinant Plasmid Jones et al. (1980) investigated the stability of five different types of plasmids in R coli. Plasmid Rpl, plasmid pds4101 and plasmid PDS1109 show very high stability in R coli, but plasmid PBR322 and plasmid PMB9 are not as stable. By using the same host cell, it has been demonstrated that plasmid instability depends on plasmid structure. Some plasmids can insert a partition sequence to increase its stability (Fitzgerald-Hayer, et al., 1982). The partition sequence carries information that codes for the even partition of the plasmid copies for all cell divisions. 20 Seo and Bailey (1985) studied the effect of a series of plasmid copy mutants on the same host cell. The experimental data are listed in Table 2.5. The results show that the copy number of plasmids can be varied either by changing the genetic make-up of plasmid or by employing different growth media. The specific growth rate (p.) depends not only on medium formulation but also on the copy number of plasmid. The cell with the highest copy number of plasmid has the lowest specific growth rate. Godwin and Slater (1979) proved that plasmid-free cells had a higher specific growth rate than that of plasmid-carrying cells if the cells are grown in a non-selective medium. Seo and Bailey (1985) claimed that the copy number and stability of a recombinant plasmid and expression of the desired protein were dependent on the genetic make-up of the hybrid plasmid.

Table 2.5. The effect of plasmid copy number on p of Host (R coli HB101)* plasmid copy # p in different media M9 LB PDM247 12 0.93 0.92 0.97 PDM246 24 0.88 0.91 0.94 RSF1050 60 0.88 0.87 0.88 PDM248 120 0.78 0.82 0.84 PFH118 408 0.68 0.77 0.82 * from Seo and Bailey (1985) 21 Types of Plasmid Instability m Segregational Instability Segregational instability refers to the loss of a complete plasmid due to defective partitioning during cell division (Tsunekawa, 1981). For the case of ARS plasmids, Newlon (1989) and Murray (1983) proposed that segregational instability could be caused by the preferential mother-cell bias due to affinity of the ARS sequence to specific nuclear components in the mother cells.

(2) Structural Instability Structural instability refers to the change in plasmid structure due to insertion, deletion or rearrangement of DNA, which can result in the loss of the desired gene function (Tsunekawa, 1981). Furthermore, integration of the selective markers into chromosome will result in loss of stability under selective conditions (Broach and Hicks, 1980).

(3) Incompatibility Plasmid incompatibility is one of the causes of plasmid instability . The phenomenon of plasmid incompatibility is related to the regulation of plasmid copy number. An incompatible group is defined as a set of plasmids whose members are unable to coexist in the same bacterial cells. The reason for their incompatibility is that they cannot be distinguished from one another at some stage that is essential for plasmid maintenance. DNA replication and segregation are stages at which this may apply. Examples for plasmid incompatibility have been given by Gerbaus and Guerineau (1980) and Jayaram et al. (1983). They found 22

that the coexistence of a 2jam-based episomal plasmid and the endogenous 2 jam plasmid was impossible in the copy number amplification and/or control system.

Intrinsic Factors Affecting Plasmid Stability

(1) Plasmid Size Plasmid size has also been shown to be a factor in affecting instability. In general, the larger the plasmid is, the lower is its apparent stability. Physical interactions during mitosis has been suggested as a possible reason (Volkert et al., 1989). According to this theory, the nucleus at mitosis is assumed to have a very complex 3-dimensional structure full of tubules and spindles. These represent physical barriers to the smooth passage of a plasmid from a mother cell to a daughter, the extent of passage inhibition being a function of plasmid size.

(2) Copy Number Copy number regulation is also a feature that the higher the copy number the more stable the plasmid will be. This is based mostly on a probability of a transfer function (Jayaram et al., 1983; Futcher and Cox, 1984)

(3) Host Ploidv Host ploidy has been shown to have an influence on stability (Mead et al., 1986). Some suggestions have been made that this might be associated with chromosomally located stability function (Kikuchi and Toh-e, 1986), enabling cells with higher ploidy to be more stable than those with lower polidy (Spalding andTuite, 1989). 23 (4) Daughter Cell Size Hjortsu et al. (1985) studied the correlation of plasmid stability under batch growth condition with physiology. He found that plasmid instability was highest during exponential growth on glucose where ca. 12% of the cells at birth were plasmid-free. Instability increased upon exhaustion of the glucose in the culture up to 25-28%. The mechanisms proposed to explain the phenomena are based on the fact that the size of the daughter cell is smaller following exhaustion of glucose in the culture fluid. This has led to the conclusion that more difficulties were encountered in getting sufficient copy number of the plasmid into daughter cells with decreased size (Coppella and Dhurjati, 1989b). The stability of a recombinant plasmid in the host is not the same as wild- type plasmid in the same host. Many factors such as the construction or the genetic structure of the plasmid vector and growth conditions may affect the stability of a recombinant plasmid.

Environmental Factors Affecting Plasmid Stability

(1) Effect of Growth Nutrients The effects of growth medium on plasmid stability in continuous fermentations have been studied by several researchers. Jones, et al.(1980) showed that a carbon-source-limited medium employed in the fermentation process decreased the stability of the plasmid. Compared with other media, a phosphate- limited medium presented the most unstable situation for a recombinant plasmid, whereas a nitrogen-limited medium showed the most stable recombinant plasmid in the host cell (Noack, et al., 1981 and Sterkenburg, et al., 1984). 24 (2) Effect of Temperature Temperature is a very important environmental factor affecting cell growth. Temperature, besides its general effect on reaction rates, can exert highly selective effects on metabolic pathways; by repression of particular protein synthesis, for example. The protein synthesis capacity of a cell is determined by its number of ribosomes and their activity. If protein synthesis is the rate-limiting step in cell replication, the growth rate can be varied by altering the activity of the existing ribosome via a change in the cultivation temperature, and by altering the size of the biosynthetic machinery by changing the RNA content.

(a) Effect of Temperature on the Specific Growth Rate and RNA Content

The influence of temperature, in the range 23-35 0 C, on the specific growth rate and RNA content of Saccharomyces cerevisiae was examined in batch and continuous fermentations by Parada and Acevedo (1983). The specific growth rate increased with increasing temperature when temperature was below 30 °C. A significant drop in the specific growth rate was found when temperature was higher than 30 °C. A linear relationship between the specific growth rate and the RNA content of Saccharomyces cerevisiae grown at four different temperatures, 23 °C, 28 °C, 32 °C and 35 °C in continuous fermentations was found. At a given dilution rate (or specific growth rate), the lower the temperature was, the higher the RNA content was found in the cells.

(b) Effect of Temperature on Plasmid Stability The effects of temperature on recombinant cells include changes in specific growth rate, plasmid stability, level of translation and transcription of intermediates for gene-product biosynthesis. In the past decade, the research mainly focused on the construction of a temperature-sensitive promoter on the plasmid to control the gene expression by varying temperature (Ryu and Siegel ,1986, Siegel and Ryu, 1985, Lee et al.,1988, Sledziewski, et al., 1988, and Silva and Bailey, 1989). Park (1988) studied the effect of temperature on plasmid-harboring cell fraction in continuous fermentations. This study used a recombinant R, coli with a temperature-sensitive promoter. He found that the plasmid is more stable at 41 °C, the repressed temperature, than at 35 °C, the derepressed temperature. He suggested that spending considerable amount of energy on plasmid maintenance and gene expression during growth always leads to high plasmid instability. On the other hand, the plasmid is more stable when the expression is turned off. This unified explanation can not generally be applied for every recombinant cells with the temperature-sensitive promoter. After all, plasmid maintenance in the case of recombinant cells with the temperature-sensitive promoter is associated with many other factors such as the host cells and the construction of plasmid. Aiba and Koizumi (1984) showed a high plasmid stability in B. stearothermophilus at temperatures under 50 °C, but plasmid stability became poor as temperature increased above 50 °C.

(c) Effect of Temperature on Gene Expression Rate According to Park's study (1988), a A,Pl promoter is controlled by the temperature-sensitive repressor (CI 857 ), and the gene expression is regulated by changing temperature. Acker et al. (1982) showed that the probability of repression of the A,Pr promoter can be quantitatively related to the change of repressor concentration. 26 (3) Effect of Growth ('Dilution) Rate The stability of a yeast plasmid also depends on the growth rate of the culture. The dilution rate determines the apparent or average specific growth rate of a heterogeneous population of plasmid-carrying and plasmid-free cells. The growth rate, or dilution rate, in turn, affects the plasmid content of the cell, plasmid stability and cellular metabolic rates for the translation and transcription. Impoolsup, et al. (1989b) found that the plasmid stability in a nonselective medium decreased with increasing growth rate of the cells. It is known that the specific growth rate generally is higher for plasmid-free cells than for plasmid- carrying cells. Therefore, plasmid- free cells will outgrow in the nonselective medium. Kleinman et al. (1986) found that the stability of plasmid pJDB248 in yeast in a nonselective medium increased with the growth rate of the yeast. They suggested that this increase might be due to the fact that cell division results in larger buds at fast growth rates. These large buds might increase the probability that a successful segregation of plasmids would occur at cell division. On the contrary, DiBiasio and Sardonini (1986) found the stability of the plasmid carrying a pBR322 segment, yeast 2-\i segment, trpl, pho5 and acid phosphatase genes in a selective medium increased with decreasing the growth rate of cells. f4) Effect of Oxygen Tension The impact of dissolved oxygen shock on the stability of plasmid has been studied by several researchers (Caunt, et al.,1989, Lee and Hassan, 1988 and Hopkins, et al., 1987). They found that plasmid loss became evident after dissolved oxygen shock. Caunts (1989) explained the loss of plasmid after the dissolved oxygen shock was due to the lack of enough energy for the replication of a multi-copy plasmid generated by cells anaerobically. Tolentino and San (1988) 27 investigated the stability and gene expression of a batch culture of R coli strain C600 carrying the plasmid pKN401 under both aerobic and anaerobic conditions. The plasmid was stable under both conditions and in the environment with alternate oxygen and nitrogen supplies . Hopkins, et. al (1987) studied the effect of dissolved oxygen shock on the stability of recombinant R coli strain AB 1157, containing plasmid pKN401. The results indicated that even under a selective pressure the appearance of plasmid-free cells after a dissolved oxygen shock occurred in the medium.

Determination of Plasmid-Carrying Cells It is known that the percentage of plasmid-carrying cells or plasmid stability in fermentation would strongly affect the total production of recombinant proteins. Therefore, accurate methods to determine the fraction of plasmid-carrying cells in the cell population present in a fermentation process is important. Plasmid instability can be assayed by determining the plasmid-loss frequency in a total population of microorganisms. Replica-plating method has been conventionally and widely used to determine the fraction of plasmid-carrying cells. Plasmid instability is usually determined by plating of cells after series dilution onto selective agars and replica plating onto nonselective agars. In order to be statistically sound, the number of colonies on each agar plate should be between 30 and 300. The percentage of plasmid-carrying cells is calculated by the ratio of the average number of colony-forming units on the selective agar plates to those on the nonselective plates. The replica-plating method is most widely and popularly used for the study of plasmid instability. However, there are several disadvantages for this method. First, this method is costly, because a lot of selective and nonselective agar plates need to be prepared and the number of colonies is restricted between 30 and 300. A spiral plate method would reduce significantly the costs involved in quantitative estimation of viable micro-organism was developed by Gilchrist et al. (1973). This spiral plate method was described for determining the number of microorganism in a solution by the use of a machine which deposited a known volume of sample on a rotating agar plate in an ever decreasing amount in the form of an Archimedes spiral. This system permits the estimation of cell concentrations over a range of about three orders of magnitude, e.g. 6* 10^ -6* 10^ or 10^ -10^ c.f.u m l'l , without recourse to serial dilution of the sample and using only a single agar plate for each sample. Jarvis et al. (1977) indicated that there were no differences between the surface spread plate method and spiral plate method at the 5% level although some isolated interactions occurred. The biggest problem with the spiral plate method is that it is very difficult to count the large number of colonies on the gar plate. Second, the error for the percentage of plasmid-carrying cells by using replica-plating method is in the range of 10% to 20% under careful analysis. The large error mainly comes from the sampling based on statistic analysis. The error may be reduced by either using more replica plates or counting more colonies on each agar plate. Third, it is very difficult to detect the low frequency of plasmid loss by using replica-plating method. The lower the frequency of plasmid loss is, the more the randomly chosen clones must be replica-plated. Furthermore, if the plasmid loss frequency is lower than 10-3, it is practically impossible to determine the frequency by replica-plating even with as many as several hundred clones. Mori et al. (1991) developed a new method which was able to do direct selection of plasmid-free segregants using mercury hypersensitivity as a phenotypic marker of 29 bacterial plasmids. The Hgss marker originated from the 4.8-kb EcoRI fragment H of the R-factor R100. Since the EcoRI fragment spans the majority of the mercury resistance operon (mer), but lacks the intact merA gene coding for the mercury reductase enzyme, this fragment conferred the Hg phenotype. The Hgss marker was introduced into high-copy-number plasmids pUC18, pBR322, and pHSG298. Segregational loss of the Hgss could allow direct selection of plasmid-free segregants on nutrient agars containing 1-2 pg HgCl 2 mLr*. Plasmid-loss segregants were estimated to appear at frequencies ranging from 10"3 to 10~7 for the tested high-copy-number plasmids. Fourth, the replica-plating method is laborious and time-consuming. Because the method requires several days' incubation period, it cannot rapidly determine the cell level during cultivation. Therefore, some rapid and simple methods for the determination of plasmid-carrying cells have been developed. Double-beam laser flow cytometry is a well known technique for the determination of biological parameters of cell size, protein, RNA and DNA content (Scheper et al., 1987). Several methods have been reported on the detection of recombinant cells using flow cytometry (Bruschi and Chuba, 1988, Scheper et al., 1984, Scheper et al., 1987, Srienc et al., 1986). Scheper et al. (1984 and 1987) have reported on the distribution of plasmid-containing and plasmid- free Escherichia coli cells using flow cytometry. The principle of this method is that the cell form changes, following the addition of antibiotic into the cell. Although these methods could distinguish between cell types, the operation of the device is complicated and required deep technical knowledge. Another direct method to calculate plasmid instability on-line is the use of culture fluorescence as a sensor for distinguishing the difference between the plasmid-carrying cells and plasmid-free cells. This method is based on the 30 difference of the level of intracellular NADH (Walker and Dhurjati, 1989). However, information regarding single cells was not obtained from this method. A further improvement for quick assay for the determination of the fraction of plasmid-carrying cells and the information regarding single cell was recently proposed by Endo et al. (1991). They developed an imaging sensor system to rapidly within 4 hours determine plasmid-carrying cells on-line. The pyrimidine analogy 5-fluoro-orotic acid (5-FOA) has been used for the selection of URA' yeast cells amid a population of URA+ yeast cells. This analog prevents the growth of URA3 mutation strains that contain a plasmid-bome URA3 gene (plasmid-carrying cells) and permits the growth of cells with a mutation in the URA3 gene (Plasmid-free cells). When 5-FOA is contained in a medium, the plasmid-carrying cells take up 5-FOA in place of orotidine-5 -phosphate decarboxylase activity. Therefore, the loss of membrane integrity of plasmid- carrying cells might be due to the inhibition of growth by 5-FOA. The basis of this method is that only plasmid-carrying cells fail to exclude specific fluorescent probe dyes because of the loss of their membrane integrity. Therefore, it can detect plasmid-carrying yeast cells possessing the URA3 gene as a selective marker in a population of plasmid-free yeast cells using 5-FOA fluorescent probes such as ethidium bromide (EB), and 4,6-diamidino-2-phenylindole (DAPI) and the imaging sensor system. Although, this imaging sensor system provides a rapid way to determine the plasmid carrying cells, it can not reflect the real percentage of plasmid-carrying cells in the growth medium. To decant the growth medium and then to regrow the cells in medium with 5-FOA are required before the use of this imaging system. The percentage of plasmid-carrying cells in the total population after regrowth of cell in the medium with 5-FOA will be different from that before regrow in the medium with 5-FOA. 31 Strategies for Overcoming Plasmid Loss

Cl) Genetic Method fa) Use of Genes Modulating Stable Maintenance of Plasmid In nature, very stable plasmid exist and certain mechanisms exist by which the stability of plasmids is maintained. It has been shown that the insertion of the par sequence into plasmid vectors stabilize the plasmids due to its equal partitioning function. The cer (ColEl resolution) function of the ColEl plasmid, which was identified by Meacock and Cohen (1980) and Summers and Sherratt (1984), also can stabilize the plasmid. The cer sequence makes monomer plasmids from multimers by multimer resolution at the time of cell division. fb) Incorporation into Chromosome Non-yeast DNA sequence have been successfully integrated into the chromosome of yeast by homologous recombination (Parent, et al., 1985 and Hinnen, et al. 1978). This results in a very stable transformant, but usually with only one copy number of the introduced DNA. Expression levels are not enhanced, so that plasmids are usually used to improve or alter existing yeast strains. A similar method uses a centromeric plasmid, which carries a centromere, whose functions in yeast leads to the plasmid to behave as a mini-chromosome. Such transformations also have high mitotic stability but normally have only one copy number. 32 (o') Natural Immunity Built-in Intracellular Selective Pressure — A built-in intracellular selection pressure uses the natural immunity to prevent the growth of plasmid-free cells. The use of X lysogen forms suicidal cells when the host cells lose plasmids (Rosteck and Herschberger, 1983). Streptomycin dependency is another intracellular selective pressure that has been used (Miwa et al., 1984). Porter et al. (1990) re-engineered an R coli strain by removing the ssb gene from the chromosome and place it on the plasmid. The gene encodes the SSB protein, which is required for DNA replication and cell viability. No cross-over effects between plasmid-carrying cells and plasmid-free cells will be occurred, because the SSB protein is an intracellular protein. Limited growth of plasmid-free cells due to the oversynthesis of the SSB protein by plasmid-carrying cells can prevent reactor takeover. They claimed that, by using this system, high level of recombinant (3-lactamase production in a continuous culture without using a selective pressure, such as the addition of antibiotic or the use of a selective medium, could be achieved. Built-in Extracellular Selective Pressure -- Built-in Extracellular selective pressure, the other type of natural immunity, refers to the secreted toxic proteins from killer strains which are lethal to certain sensitive strains. A killer system in yeast has been reviewed by Vondrejs (1987). This concept has been applied to r- DNA technology to maintain the plasmid-containing cells in the medium. A killer toxin chimeric plasmid was constructed, and then transferred into Saccharomyces cerevisiae which became the killer strain (Bostian, et al., 1984 and Skipper, et al., 1984). The killer strain was able to express and secrete a heterodimeric toxin to kill other sensitive nonkiller Saccharomyces species. 33 The effects of oxygen tension and dilution rate on expression and plasmid stability of killer yeast strain in a glucose-limited chemostat culture were investigated by Lee and Hassan (1987). They found that the change in oxygen tension affected not only the metabolism but also the expression and stability of the killer toxin recombinant DNA in the yeast culture. The stability and expression of the same killer strain in continuous fermentations at different dilution rates was studied by Lee and Hassan (1988). Their experimental results showed that the toxin expression depended on the dilution rate and also affected the degree of killing effect on the nonkiller strain. The advantage of this control strategy is the ability to use a low-cost, complex medium for the selection of recombinant cells. However, the adding cost in the downstream processes for the separation of the desired products and the toxin protein needs to be taken into consideration. Synthesis of the toxin also has a deleterious effect on the productive (plasmid-containing) cells. In addition, the degree of the selectivity of the recombinant cells depends on the toxin expression which is controlled by the environmental factors and the cell itself.

(d) Double Auxotrophic Mutant The inheritance of a plasmid in a Saccharomyces cerevisiae URA3 FUR1 double mutant in chemostat culture was investigated by Marquet, et al. (1987). The selection system was based on the biosynthetic pathways of uridine-5'- monophosphate (UMP). UMP can be produced either by the decarboxylation of orotidine-5'-monophosphate (OMP) or by the direct conversion of uracil. The decarboxylation activity is encoded by URA3 gene and the uracil phosphoribosyl- transferase by FUR1 gene. Yeast double mutant (ura3 furl) lacking both activities are either nonviableor at least severely handicapped. The gene URA3 contained on 34 the plasmid was transferred into the double mutant (ura3 furl). The furl mutation impedes the utilization of Uracil contained in the medium. The experimental results showed that yeast double mutant successfully maintained stable plasmids over a range of dilution rate between 0.1 hr-1 and 0.32 hr'l. There was no appearance of plasmid-free cells during the course of the fermentation, and the plasmid copy number remained constant at all time. Similar results was demonstrated by Marquet, et al. (1986). They showed that the plasmid in the yeast double mutant could be maintained for up to 150 generations at a constant dilution rate in a chemostat culture.

(el Secretion Secretion of heterologous proteins by S. cerevisiae has been proved to increase plasmid stability. Shaw et al. (1988) reported that by coupling secretion with the regulated expression of the heterologous gene, problems associated with plasmid instability and toxicity of the recombinant product may be minimized. Murine granulocyte-macrophage colony-stimulating factor (GM-CSF) was expressed in Saccharomyces cerevisiae using a novel regulated secretion system. This system involves the fusion of the GAL1 upstream regulatory region to the signal sequence of the alpha mating pheromone and the integration of this GALl:MFal prepro:MuGM-CSF construct into yeast chromosome. These constructs were very stable under both selective and nonselective conditions. No plasmid loss was observed after 30 generations of growth. There are other advantages to have the heterologous proteins to be secreted from S. cerevisiae (Schekman et al., 1982). First, the relatively low concentration of naturally-occurring proteins secreted by the yeast into the medium facilitates purification. Second, intramolecular disulfide bonds are formed during the 35 secretion process. Third, secreted proteins may be protected from intracellular proteases. Fourth, it is easy for the downstream process. Fifth, yeast has a secretion system similar to higher eucaryotes that can be manipulated for obtaining increased amount of secretion of foreign polypeptides. Factors which affect the efficiency of secretion of protein are promoter strength, gene dosage, plasmid maintenance, nature of the signal sequence and host mutation. The major disadvantage for this approach is that the secreted proteins are degraded by extracellular proteases. A cell recycle reactor is designed by Siegel and Brierley (1990) to solve the problem of degradation of secreted protein. The reactor is able to increase the production of a proteolysis-susceptible peptide secreted from recombinant S. cerevisiae. The reason for deducing degradation-associate loss of a secreted protein product by using the cell recycle mode of fermentation is to reduce the residence time of secreted products in the fermentor. The secretion of recombinant proteins may have a positive effect on plasmid stability, but it also will not completely solve the plasmid instability problem. The construction of the plasmid and the host cell itself are perhaps more important.

(2) Operation Strategies

(a) Selective Pressure The most common way to solve the problem of plasmid instability is the introduction of a selective environmental pressure to the system against the plasmid-free cells. 36 (T) Antibiotic. Drug or Heavy Metal Ion Resistance One method for the introduction of selective pressure is to use plasmids conferring resistance to an antibiotic or a certain chemical upon host cells and to incorporate that antibiotic into culture medium (Welmsley, et al., 1983). Antibiotic (such as penicillin, tetracycline, et.) selection, which is widely used in K coli. can be ineffective in large-scale fermentation. Pierce and Gutteridge (1985) find that all the antibiotic in the culture can be inactivated by a small fraction of plasmid- carrying cells which coexist and protect a much larger population of cells that have shed the plasmid. Furthermore, the other disadvantages for this method are the requirement of a significant amount of costly antibiotic and addition of downstream purification steps for the separation of the antibiotic and the desired product. Several plasmids conferring resistance to antibiotic, drug and heavy metal ion upon yeast cells have been constructed. These include selection for aminoglycodise G418 (antibiotic) resistance [encoded by Escherichia coli Tn601(903) aminoglycoside phosphotransferase gene] (Jimenez and Davies, 1980), copper (heavy metal ion) resistance [encoded by the yeast CUP1 gene] (Fogel and Welch, 1982), and methotrexate (drug) resistance [IT coli plasmid R388 or mouse DHFR gene] (Miyajima et al., 1984 and Zhu, et al., 1985).

(ii) Selective Medium Without Key Metabolite Another method is to use an auxotrophic mutant as the host cell, which has lost the capability to metabolize a key nutrient, and to restore this metabolic capability with the plasmid. The cloned TRP1, LEU2, HIS3, and URA3 genes are commonly used as selective markers and numerous auxotrophic strains exist with 37 mutations in the appropriate chromosomal gene. Medium lacking tryptophan, leucine, histidine, or uracil is used to select cells containing the plasmid. Sardonini and DiBiasio (1986) studied the relationship between dilution rate and plasmid stability in tryptophan auxotrophic yeast under the selective pressure, i.e. with a selective medium, in batch to continuous fermentations. They found the selective pressure was inefficient for the recombinant plasmid in auxotrophic yeast. They claimed that the plasmid stability decreased with decreasing the dilution rate in the selective medium. At 0.2 hr“l dilution rate, the fraction of plasmid-carrying cells in the total cell population was as low as 70%. The following mechanisms have been proposed to explain this phenomena. As pointed out by Lauffenburger (1987), one potential problem in using the nutrient-selection method is the uncertainty surrounding the ability to match normal cell enzyme levels using a gene present on a plasmid instead of on the host chromosome. However, Satyagal and Agrawal (1989) elucidated that the persistence of plasmid-encoded enzyme from the mother cell to daughter cells was not the major cause for the appearance of plasmid-free cells under selective pressure because of the self-regulation system for the production of enzyme in cells. The major reason that the selective medium is ineffective in this method. It is very likely that medium-deficient nutrient would be oversynthesized by the plasmid-carrying cells and is then either secreted into the medium (Satyagal and Agrawal, 1989) or passed onto the daughter cells to support the growth of plasmid- free cells (Murray and Szostak, 1983; Srienc et al., 1986; Bailey et al., 1986; Wittrup and Bailey, 1988). Although a daughter cell may lack the plasmids needed for survival, it may retain a residual level of the metabolite from its mother cell or it can obtain the metabolite from the medium. Pedigree analysis of plasmid 33 segregation in auxotrophic yeast has been conducted by Murray and Szostak (1983). They found that the cells without the plasmid also reproduced and in many cases, microcolonies of 2 to 250 cells were found when plates were scored for growth. The ability of plasmid-free cells to divide in a selective medium after plasmid loss was due to the persistence of the metabolite from the mother cell to a daughter cell. The number of divisions occurring after plasmid loss depended on the copy number of the plasmid, the amount of oversynthesized metabolite and the residual level of the necessary enzyme. The phenomenon of tryptophan secretion by yeast mutants have been shown by Fantes, et al. (1976) and Schurch, et al. (1974). DiBasico and Sardonini (1986) proposed that the inefficiency of the selective pressure for the recombinant plasmid in auxotrophic yeast was mainly caused by the secretion of the overproduced tryptophan by plasmid-carrying cells. The secreted tryptophan was then subsequently used by plasmid-free cells. However, they failed to detect any secreted tryptophan in the supernatant of the medium. Satygal and Agrawal (1989) considered the oversynthesized tryptophan passing onto the daughter cells from the plasmid-carrying cells was the major key factor to support the appearance of plasmid-free cells. For this reason, Satyagal and Agrawal (1989) later suggested that the inefficiency of the selection of the plasmid in auxotrophic yeast should result from the persistence of metabolite from mother cell to daughter cell, not from the secretion of oversynthesized tryptophan. Another possibility for the inefficiency of the selective pressure is the release of cellular contents from lysed cells into the medium. The released plasmid and complementary product from the lysed cells in the medium can then be taken up by the cells. Therefore, the plasmid-free cells can survive under this condition. This process is known as cryptic growth (Mason and Hamer, 1987). For efficient 39 production of recombinant products both the extent to which plasmid free cells arise and the lysis rate of the plasmid containing cells must be minimized. The major disadvantages of using a selective medium are the cost of the defined medium without the corresponding metabolite and the inefficiency of the selective pressure for the recombinant plasmid in auxotrophic mutant. When the selective pressure is employed to the system, the cost of antibiotic or selective medium and its efficiency is always a big problem for industrial applications. An ideal industrial system for the growth of recombinant cells and stabilization of plasmid should include the following two requirements. First, to exclude cross over effects wherein plasmid-containing cells support the growth of plasmid-free cells. Second, to allow recombinant cells grow in inexpensive and complex media. On the other hand, the maintenance of plasmid-carrying cells without applying a selective pressure to the system may is desired.

(liij Substrate Level Dependence Substrate level dependence for the selectivity of plasmid-carrying cells is regarded as the third type of selective pressure. However, this has been applied to methylotrophic species only. Generally, Methylotrophs are sensitive to metabolite inhibition of growth. The carbon source, such as methanol, can be utilized as the energy source by methylotrophic species at very low concentration. However, a high concentration of carbon source will inhibit its growth. A plasmid system successfully constructed has been for a methylotrophic species of soil bacteria which is able to be effectively tolerant or defect the growth inhibitor (Basdasarian and Timmis, 1982, Windass, et al., 1980, Stahl and Esser, 1982). The maintained certain amount of metabolite in the system will attenuate the growth rate of plasmid-free cells, but have no effect on the growth rate of plasmid-carrying cells. 40 This naturally attenuation of growth rate due to metabolite inhibition could be utilized as a selective pressure to enhance plasmid stability. Therefore, it is very important to maintain the substrate concentration at a suitable level during the fermentation process. An operational strategy for unstable recombinant DNA cultures had been proposed by Ryder and DiBiasio in 1984. They presented a kinetic model based on the characteristics of substrate inhibited growth in fed-batch fermentation. It is noted that due to the resulting steady-state instability of the coexistence state, feedback control was required to maintain at the certain level of substrate. Chemostat or glucose-stat with the constant level of substrate can also be used in this system.

(TO Cell Immobilization The immobilization of living cells possesses a number of advantages over traditional fermentation methods (Karel, et al., 1985). Cell immobilization allows continuous metabolite or protein production, high cell densities, prevention of cell wash-out and an increase in productivity and operational stability. Cell immobilization also provides environmental protection to keep the living cells from the mechanical stress or damage (Barbotin, et al., 1989). The advantages of immobilization of recombinant cells include high plasmid stability even under nutrient limitation, the maintenance of high plasmid copy number, high productivity of heterologous protein and prevention of cell wash-out (Sayadi, et al., 1989). 41 (c) Separation of Growth and Production Phases

(i) Theoretical Background Spending considerable amount of energy on plasmid maintenance and gene expression during growth always leads to high plasmid instability. On the other hand, the plasmid is more stable when the expression is turned off. Therefore, in order to obtain high expression level and high productivity, it is better to separate the growth phase and production phase. Some controllable promoters for use in expression vectors are listed in Table 2.6.

(ii) Application in Batch Fermentation A typical strategy in batch fermentations is cultivation of the K coli cells to high density and then initiation of high level cloned gene expression by induction of a strong promoter, copy number amplification, or both (Caulcott and Rhodes, 1986 and Fieschko, et al., 1987). Furthermore, in the case of recombinant yeast, a temperature-sensitive strain of Saccharomyces cerevisiae was constructed which, in conjunction with plasmid promoters controlled by yeast galactose regulatory circuit, allowed induction of cloned gene product synthesis by temperature-shift (Silva and Bailey, 1989). The comparison of the induction methods for the performance of the production of recombinant P-galactosidase in batch fermentation at 35 °C between galactose addition and temperature-shift was done. They found that the levels of product protein produced by temperature-shift induction were better than those produced by galactose induction. However, higher levels were formed by galactose induction at the preferred growth temperature of 30 °C. In continuous 42 fermentations, induction by galactose addition at 30 °C was superior, indicating the importance of temperature for cell growth and cloned gene expression.

(nf Application in Continuous Fermentation An analogous strategy in continuous fermentations is the use of a mutistage system, with uninduced cells in the first vessel and cloned gene product synthesis in the second vessel. A two-stage culture by using a temperature-sensitive expression K coli mutant have been reported by Ryu and Siegel (1986), Siegel and Ryu (1985) and Lee et al. (1988). The results showed that a two-stage system allowed higher productivity of gene product over a prolonged period when compared to a single-stage or batch culture. Two important operational parameters that affect the gene-product yield of a continuous fermentation system are the dilution rate and temperature. The dilution rate determines the apparent or average specific growth rate of a heterogeneous population of plasmid-carrying and plasmid-free cells. The growth rate, or dilution rate, in turn, affects the plasmid content of the cell, plasmid stability and cellular metabolic rates for the translation and transcription necessary for both stages. The optimal conditions for the two-stage fermentation process must be set to achieve the highest gene-production. The kinetic model based on the dilution rate for the optimization of a two-stage recombinant K coli fermentation has been proposed by Hortacsu and Ryu (1991). Simulation results for the plasmid maintenance in the first stage without gene expression suggested that, for a longer fermentation period, plasmid stability was better at a higher dilution rate. The optimal apparent specific growth rate for maximum productivity in the second stage was found to be 0.4 hr"l. 43 For the case of recombinant yeast in continuous fermentations, the influence of dilution rate and induction of cloned gene expression on the production of recombinant protein and plasmid stability was proposed by Silva and Bailey (1991). P-Galactosidase production was be induced by galactose addition. They found that in all dilution rates, 0.1 hr"l, 0.2 hr'l and 0.26 hr"l, plasmid stability decreased with induction of lacZ gene expression. Specific P- galactosidase, concentration of biomass and overall productivity increased as the dilution rate decreased.

(iv) Application in Fed-batch Fermentation A two-stage process by using galactose as an inducer for the control of the human immune interferon expression in high-cell density fermentations of Saccharomyces cerevisiae was studied by Fieschko, et al. in (1987). In the fist stage, the recombinant yeasts grew on glucose as the major substract in order to reach a high cell density. It also resulted in high stability of plasmid due to no expression of recombinant products. In the second stage, the substract was switched from glucose to galactose to induce the expression of human immune interferon. This operational strategy, combined with high-cell-density fermentations, resulted in higher specific production of interferon as compared to fermentation with only one type of substract, galactose or glucose. Although this strategy improved productivity and lowered plasmid loss during the course of the fermentation, the problem for plasmid instability still remained unsolved. 44 Cd') Recycling Plasmid-Carrying Cells

(T) Theoretical Background Due to the instability of plasmids and the relatively low growth rate of plasmid-carrying cells as compared with plasmid-free cells, a plasmid-carrying culture is gradually diluted by plasmid-free cells. For a long fermentation time, bioreactor takeover by plasmid-free cells becomes a severe problem. The selective recycle for the plasmid-carrying cells only, regardless of the growth-competition between plasmid-carrying and plasmid-free cells, is a solution to solve the problem for bioreactor takeover by plasmid-free cells. A kinetic model for the selective cell recycle to enhance the desired cells in a fermentor has been proposed by Ollis (1982). The concept to separate plasmid- carrying cells from plasmid-free cells in a selective cell recycle is based on differences in shape, density, size or other physical properties. However, it would be very difficult and might even be impractical in a large-scale fermentation to adapt this selective cell recycle scheme. Some auxiliary characteristics, which are to be added into the recombinant cells, would be required to separate plasmid- carrying cells from plasmid-free cells more efficiently.

(ii) Selection by Charge and Hvdrophobicitv LaMarca, et al. (1990) used charge and hydrophobicity related property differences of antibiotic-resistance recombinant cells and their antibiotic-sensitive hosts to separate plasmid-carrying cells and plasmid-free cells in an aqueous two- phase system. 45 (nil Selection by Flocculation The characteristics of forming aggregation by Saccharomyces cerevisiae cells has long been exploited in the brewing industry. The yeast strain with flocculation capacity aggregates spontaneously and forms floes which sediment rapidly in the culture medium (Stewart et al., 1975, 1976). The ability for aggregation is controlled by genes located on the chromosome (Stewart et al., 1976; Stewart and Russel, 1986, Esser et al., 1987). These genes have been isolated from the chromosome and inserted on plasmids (Davis and Pamham, 1989). The aggregation ability is deprived from the host yeast and the transmitted back into the yeast with the plasmid. A continuous fermentation with selective flocculation and recycle has been developed by Davis and Pamham (1989). An inclined settler was used to selectively separate and recycle a slower-growing flocculent strain of yeast to a continuous stirred bioreactor and thereby maintain the species as dominant in spite of competition from a faster-growing nonflocculent strain. The potential problem for flocculation is the formation of floes inside the fermentor which drastically reduce the amount of cells in contact with the growth medium. Consequently, the fermentation slows down, and the process can terminate abruptly. Flocculation can also restrict the use of spectrophotometric analysis for cell density estimation by turbidity.

(e) Cyclic Oscillation in Fermentation Conditions The fluctuation in fermentation conditions such as temperature, pH, nutrient concentration and other operating conditions has significant effects on culture behaviors, productivity and plasmid instability. 46 (T) Substrate Concentration The use of cyclic oscillation in the substrate level to stabilize the recombinant organism has been studied theoretically by Stephens and Lyberatos (1988). In their work, cells experienced cyclic changes between substrate limited and unlimited conditions. Because of their extra metabolic burden, it was proposed that plasmid containing cells are slower to adapt to changes in substrate concentration than plasmid free cells. During the periods of substrate limitation, plasmid free cells are growing at a sub-maximal growth rate and therefore have a lower mean growth rate. By manipulating the cycling times and amplitudes, the normal growth differences between plasmid free and plasmid containing cells would be removed or even reversed.

(ii) Dilution Rate or Specific Growth Rate Weber and San (1987) found that plasmid-carrying and plasmid-free cells behaved differently in transient environments. The transients induced by forced oscillation in the dilution rate were advantageous to plasmid-carrying cells in competing with plasmid-free cells. (Weber and San, 1988). Two possible mechanisms were proposed. First, the recombinant cells under transient conditions became more adaptive to the environmental changes than the plasmid-free cells. Second, they claimed that under transient conditions the cells intended to retain a high copy number of plasmid. No experimental results were presented to support this hypothesis. Stephens and Lyberatos (1988) showed theoretically that cyclic changes in substrate concentration could be used to obtain coexistence of plasmid-containing and plasmid-free cells. In an experimental study, cyclic growth rate changes in a nonselective medium in continuous fermentation showed a stabilizing effect on the 47 recombinant yeast culture studied (Impoolsup, et al., 1989a). The fraction of plasmid-carrying cells and gene expression could remain high even without optimization. fin) Dissolved Oxygen Level Cyclic dissolved oxygen levels with a cycle time of a few minutes also has a stabilizing effect on the recombinant yeast (Caunt et al., 1990). The plasmid-free cells adapted quickly to changes in DOT (Dissolved Oxygen Tension), and switched to a more incomplete oxidative metabolism and had reduced energy levels with each down cycle. Therefore, these cells had a lower average growth rate. In contrast, plasmid containing cells were already under a metabolism burden and normally had reduced growth rates. Plasmid containing cells were less able to respond to changes in the DOT level than plasmid-free cells, and the growth rate of such cells were less affected by cycling. Under the influence of cycling, growth rate differences between plasmid containing and plasmid free cells were reduced or reversed, resulting in plasmid stabilization. fiv) Cyclic Induction-Noninduction Peretti and Bailey (1987) proposed a kinetic model for transient response simulations of recombinant microbial populations. From the simulated results, they found that the calculated responses for recombinant populations subjected to constant promoter induction or cyclic induction-noniduction lead to the conclusion that inducible systems give greater productivity than those with fixed promoter strength. 48 Table 2.6. Some controllable promoters for use in expression vectors

Promoter Source Operational Control Off On E. coli A.pL, Leftward and 30 oc > 37 OC (in X pR rightward early cI875 host) promoters of X E. coli lac R coli lac operon IPTG in medium E. coli fiE R coli trp operon Tryptophan Indoleacetic in medium acid in medium • * E. coli tac trp-35 region IPTG in lac-10 region medium hybrid E. coli phoA E. coli alkaline Excess Phosphate phosphatase operon phosphate limited in medium medium E. coli rec A R coli recA gene Mitomycin C in medium E. coli tet TnlO tetracycline- Tetracylines resistance gene in medium B. subtilis bla Bacillus P-lactams licheniformis P- in medium lactamase gene B. subtilis cat Bacillus pumilis Chloram chloramphenicol phenicol in acetyl tmsferase medium Streptomvces* gyl Streptomvces Glucose in Glycerol in coelicolor glycerol medium medium operon S. cerevisiae 1 tpi 1 yeast MAT a gene 35 °C 25 OC S. cerevisiae^ gpd hybrid yeast gal 10-1 Galactose intergenic region in medium *: from the handout of microbial physiology course in OSU 1 : from Sledziewski, et al. (1988) 2: from Silva and Bailey (1989) 49 Cloning Vectors for Saccharomyces cerevisiae

As discussed before, the copy number and stability of a plasmid are dependent on the genetic structure. Therefore, to construct a suitable recombinant plasmid is an important issue. An ideal plasmid expression system should posses the following characteristics (Smith, 1987): - high copy number - copy number control system - stable vector (structural and segregational stability) - high transcriptional efficiency (RNA polymerase) - choice of strong constitutive or regulated promoters - stable messenger RNA - high translational efficiency (ribosome binding site, codon usage) - stability of protein to host proteases - possibility of cytoplasmic expression or secretion - availability of signal sequences for addressing proteins - post translational modifications, e.g. S-S bridge formation, correct folding, glycosylation - suitability for high biomass process development - compatibility with downstream operations such as cell separation, cell breakage, removal of endotoxins - acceptability by registration authorities 50 Two major types of plasmid vector are commonly used in S. cerevisiae. The first type is the plasmid vector with even partition function to stabilize the plasmid, but usually the copy number is very low. The second type is the plasmid vector with 2 micron sequence. This type possesses high stability and high copy number too.

Plasmid with a Partition Sequence A vector, plasmid YRp7, constructed by Struhl et al. (1979), is composed of an origin for replication and genes coding for ampicillin and tetracycline resistance for R coli. the yeast TRP 1 gene for selection and ARS 1 to permit autonomous replication in yeast. This plasmid can be replicated not only in yeast but also in EL coli. This plasmid usually is presented in the range of 20 to 50 copy number per cell, depending on the conditions for cell growth. The proportion of plasmid- carrying cells in the population growth without a selective pressure is in the range of 5% to 20%. A new plasmid, pMA902, was constructed by inserting the CEN3 gene from the centromere region of the yeast chromosome into plasmid YRp7. This plasmid is shown in Figure 2.4. The CEN sequence reduces the plasmid copy number from 20 to one, but the plasmid is maintained in about 90% of the plasmid-carrying cells during mitotic growth without a selective pressure.

Plasmid Based on the Yeast 2 Micron Circle A native plasmid, 2 micron plasmid, has been extracted from S. cerevisiae for use in recombinant plasmids. The major characteristics of this native plasmid is that it is stable and possesses copy number from 20 to 100 per cell (Zakian et al., 1979). Plasmid pJDB207, shown in Figure 2.5, was constructed by incorporating 2 micron plasmid sequences to the E. coli pBR322 plasmid with LEU2 as the 51 selective marker. This plasmid is maintained at a high copy number around 20 to 100 per cell. The fraction of plasmid-carrying cells can be maintained as high as 90% during cell growth without the selective pressure.

The Characteristics of Recombinant Yeast Used in This Study A Saccharomyces cerevisiae strain containing the plasmid pSXR125 obtained from Zymogenetics, Inc. (Seattle, WA) was be used in this research. The plasmid, shown in Figure 2.6, contained the yeast trpl gene that allows for selection of yeast cells containing the plasmid in auxotrophic trpl strains. This plasmid also contained genes for temperature-regulated expression of a heterologous gene product, (3-galactosidase, by using the MATa2 repression system (Sledziewski, et al., 1988). This regulation system is shown in Figure 2.7. At the permissive temperature (25 °C), the MATa2 repressor is not synthesized by HMLa2 and P-galactosidase is produced at high level. At the restrictive temperature (35 °C), MATa2 repressor is made and represses transcription of lac Z. The gene expression at various temperature in yeast transformed with plasmid pSXR125 is shown in Table 2.7. The results show p-galactosidase activity at 25 °C, the derepressed temperature, is 115 times higher than that at 35 °C, the repressed temperature. P-galactosidase activity at 30 °C is only two times higher than that at 35 °C. The change of P-galactosidase activity in temperature shift experiments is also showm in the same table. Recombinant cells with plasmid pSXR125 were first grown at the repressed temperature (35 °C) to the early stationary phase. Example pM A902 Dobson and Bowen

Hind III

Bglll TRP1

EcoRI EcoRI •Hindll -Bam

ORI

TRP1 selectable marker ORI pBr 322 origin of replication A R S1 autonomously replicating sequence AMPR antibiotic resistance genes CEN3 chromosomal centromere TETR Figure 2.4. Construction of plasmid pMA902 (Struhl et al., 1979)

Example pJDB207

EcoRI

LEU 2 EcoRI ■■find

Bam

ORI

LEU 2 selectable marker AMPR aritit:iotic resistance genes TETR 2/x yeast 2/x sequences (incomplete)

ORI pBr 322 origin of replication The 2/i circle tsolf is n *5.01:1) plasmid present at 2C -100 copies per cell

Figure 2.5. Construction of plasmid pJDB207 (Zakian et al., 1979) The cells were then transferred to a fresh medium and grown at various temperatures, 35 °C, 30 °C and 25 °C, for 24 hours. P-galactosidase activity within 24 hours of being shifted to 25 °C only reached about one-fourth of the activity at the fully derepressed level.

Table 2.7. P-galactosidase activity at various temperatures in yeast transformed with plasmid pSXR125 (Sledziewski, et al., 1988).

Growth Conditions P-galactosidase (units) 35 oc 30 oc 25 ©C Constant Temperature 1 2 115 Pregrown at 35 °C 0 2 31 54

MATa2 Operator TCATGT ACTTAC CCA ATTAGG AAA ACAJGG Bam HI Bui TPI I promoter TATA

Bam HI

Hind CEN 3 Eco Rl^

A RS I

TRP 1 Eco RI

ORI AMP

Figure 2.6. Construction of plasmid pSXR125 (Sledziewski, et al., 1988)

no functional 3IR3 protein

KML a

luneiionul SIR3 repression of silent locus

< noMATaj repressor function

MATa; ; c e r r c c r (1 - eaiactosidase activity

Figure 2.7. Representation of temperature-dependent regulation of hybrid promoters in pSXR125 (Sledziewski, et al., 1988). 55 (T) Construction of Plasmid pSXR125 Figure 2.6 shows the construction of plasmid pSXR125. Four synthetic MATa2 operator sequences were inserted in the strong yeast promoter TPI1 upstream of the putative TATA box. This variant promoter was fused into lacZ gene, the R coli gene encoding P-galactosidase, and inserted into the centrometric plasmid pDBC3Tl. This new plasmid was then inserted into S. cerevisiae C2 carrying the MATa and sir 3-8 loci. The sir 3-8 mutation renders the SIR3 protein inactive at 35 °C. More detail information about vector, genes and restriction sites are described below.

(a) PBR322 (Tetr . Ampf ) Shutter Vector - a hybrid plasmid from R coli including AMPr , TETr and ORI genes - TEV and AMPr gene is responsible for the resistance to tetracycline and ampicillin, respectively - ORI gene is the gene responsible for the origin of replication - copy number is about 20 in E. coh - contain origin of replication - not self-transmissible

Of) TRP1 Gene - serves as a selective marker and allows plasmid-carrying cells to growth in the tryptophan-free medium - The yeast TRP1 gene was isolated from the yeast-R coli shuttle vector YRP7 by EcoRI digestion and ligated into the EcoRI site of CE7V3-PBR322 vector after treatment of EcoRI-cut plasmid with calf intestine alkaline phosphatase. - encode N(5'-phosphoribosyl) anthranilate isomerase

(c) ARS1 ('Autonomously Replication Sequence') Gene - is chromosomal origin of replication allows the plasmid to replicate in S. cerevisiae - present at a high copy number about 20-50 copies per cell

(d) CEN3 Gene - from the centromere region of the yeast chromosome - major functions: (i) control copy number (ii) participate segregation of plasmids ( means that it possesses the partition function) - evidences: (i) plasmid PDBC3T1 without CEN3 gene : - copy number : 20-50 (high copy number) - stability : very low (ii) plasmid PDBC3T1 with CEN3 gene : - copy number : 1-2 (low copy number) - stability : > 90% - ARS plasmids are highly unstable; in the absence of selection about 20% of the cell loss plasmid per generation - The maintenance of ARS-based plasmids can be stabilized by the addition of CEN3 gene - CEN3 gene allows the plasmid to function as a chromosome, both mitotically and meiotically. 57

(e) TPI1 Promoter - a strong yeast promoter

ffl MATa2 operator - a temperature-sensitive promoter - 4 copies of MATa2 operator - At low temperatures (e.g. 25 °C), no MATa2 repressor would be produced from HMLa gene. Therefore, no repressor would bind with MATa2 gene. - At high temperatures (e.g. 35 °C), MATa2 repressor would be produced.

(g) lacZ Gene - encode for the enzyme (3-galactosidase, which splits the substrate lactose into two simple sugars, glucose and galactose.

(h) Eco RL Hindlll and BamHI restriction sites - the location of EcoRI, Hindlll and BamHI restriction sites can be cleaved by the corresponding restriction enzymes, EcoRI, Hindlll and BamHI restriction enzymes.

12) The Characteristics of Auxotrophic Yeast Any mutant microorganism possessing a nutrient requirement possessed by the parent is known as auxotrophic. An auxotrophic trpl strain is lacking in an enzyme, called N(5'-phosphoribosyl) anthranilate isomerase, needed for synthesizing a particular amino acid, tryptophan, and therefore requires tryptophan 58 as a growth factor in its nutrient medium. The tryptophan biosynthetic pathway of in Sf cerevisiae is illustrated in the following figure (Miozzari, et al., 1978):

phenylalanine " tyrosine ^ . EnZl EnZ2 EnZ3 EnZ4 x x chorismate x anthranllate X P R A x CDRP

EnZ5 >> tryptophan ) indole glycerol phosphate

> indole

Figure 2.8. Tryptophan biosynthetic pathway in Sf cerevisiae where: Enzl: anthranilate synthase encoded by genes trp2 and trp3 Enz2: anthranilate phosphoribosyl transferase encoded by gene trp4 Enz3: phosphoribosyl anthranilate isomerase encoded by gene trpl Enz4: indole glycerol phosphate synthase encoded by gene trp3 Enz5: tryptophan synthase encoded by gene trp5 59 References

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Abstract

The kinetics of cell growth, (3-galactosidase production and plasmid stability in batch recombinant yeast fermentations with selective and nonselective media at temperatures ranging from 22 °C to 32 °C were studied. The production of the recombinant product was regulated by the growth temperature. At permissive temperatures (< 25 °C), (3-galactosidase was produced at high level, whereas at restrictive temperatures (>30 °C), no p-galactosidase was produced. When yeast cells were grown in the nonselective medium, greater plasmid stability was found at the restrictive temperature (30 °C) than at the permissive temperature (25 °C). Mathematical models for these batch recombinant yeast fermentations were developed. The Imanaka and Aiba mechanism was assumed to account for the loss of plasmid during cell growth. Monod model was used for cell growth. The models also include equations for substrate consumption and recombinant protein production associated with both plasmid-free cells and plasmid-containing cells. The production of the recombinant protein was found to be growth- associated. The developed kinetic model simulates the experimental data very well. 72 73 Introduction

Recombinant DNA (rDNA) technology has advanced tremendously in recent years. Some recent examples in the pharmaceutical industry include the production of human insulin and human interferon. Obtaining the desired gene product is associated with scaling up the production so that enough protein may be recovered. An important factor in batch cultivation of the recombinant cells is the stability of the plasmid employed. Temperature is one of the most important environmental factors affecting cell growth. Temperature, besides its general effect on reaction rates, can exert highly selective effects on metabolic pathways; by repression of particular protein synthesis, for example. Thus, the culture as a whole may have varied and complex responses when its temperature is altered. For recombinant cells, the growth temperature would affect not only the specific growth rate, but also plasmid stability, the level of translation and transcription of intermediates for gene- product biosynthesis. To assess the stability of plasmid in host cells, Imanaka and Aiba (1981) proposed a scheme to represent the fraction of plasmid-containing cells in a population growing in a nonselective medium for exponential cell growth. Ollis (1982) and Chang and Oills (1982) included substrate consumption and product formation for batch recombinant cell fermentation kinetics. Leudekin-Piret equation, including the terms for the growth associated and non-growth associated, was used for protein formation. A better model representation for the formation of a recombinant protein was proposed by Lee et al. (1988). They suggested that the formation of recombinant proteins would depend on the gene expression, intracellular concentration of plasmid DNA, and decay constant of proteins. A kinetic model for the growth of Saccharomvces cerevisiae (tip-) cells containing a recombinant plasmid in continuous fermentation with selective media was reported by DiBiasio and Sardonini (1986) and Sardonini and DiBiasio (1987). Their model assumed that the growth of plasmid-free cells was sustained by the secretion of the oversynthesized tryptophan from plasmid-carrying cells. Satyagal and Agrawal (1988) proposed that the appearance of plasmid-free cells under the selective pressure should result from their retaining of the oversynthesized tryptophan from the plasmid-carrying cells and developed an intracellular model to explain the insufficiency of the selective pressure. The Saccharomvces cerevisiae strain containing the plasmid pSXR125 with a temperature-sensitive promoter (Sledziewski, et al., 1988) was used in this study. The kinetics of plasmid instability and the production of (3-galactosidase in batch fermentations with selective and nonselective media at various temperatures were studied. Six different temperatures, 22 °C, 24 °C, 25 °C, 27 °C, 28 °C and 32 °C were used for batch cultivation in the selective medium. Three different temperatures, 25 °C, 28 °C and 32 °C, were used for batch growth of the mixture of plasmid-free and plasmid-carrying cells and plasmid-free cells only in a nonselective medium. The kinetics and modeling of temperature effects on these recombinant yeast fermentations were also studied. The model developed is able to describe cell growth, glucose consumption, product formation and plasmid stability kinetics. 15 Materials and Methods

Yeast and Plasmid The Saccharomvces cerevisiae strain containing the plasmid pSXR125 obtained from Zymogenetics, Inc. (Seattle, WA) was used. The plasmid contained the yeast trpl gene that allowed for selection of yeast cells containing the plasmid in auxotrophic trpl strains. This plasmid contained genes for the temperature- regulated expression of a heterologous gene product, p-galactosidase, by using the MATa2 repression system (Murray and Szostak, 1983). At a permissive temperature (25 °C), the MATa2 repressor was not synthesized by HMLa2 and P-galactosidase was produced at high level. At a restrictive temperature (35 °C), MATa2 repressor was made and repressed the transcription of lac Z. Detailed descriptions of the plasmid construction and gene function have been given in the previous chapter.

Growth Media The selective medium used in fermentation contained 0.4% (wt/vol) yeast nitrogen base without amino acids (Difco), 0.4% (wt/vol) glucose, and 0.0675% (wt/vol) casamino acid (Difco). The use of acid-hydrolyzed casamino acid provided a tryptophan-free amino acid source. The nonselective medium had the same composition as the selective medium but also contained 0.005% tryptophan. The medium composition used in agar plates was as follows: 2.0% glucose, 0.67% yeast nitrogen base w/o amino acids, 0.56% casamino acid and 2% agar (Bacto) for the selective agar plate and with additional 0.004% tryptophan for the nonselective agar plate. 76 Fermentations Several 5-L fermentors were used in this work. Three Marubshi (MD-300) and one BioFlo II fermentor (New Brunswick) were used. For each batch fermentation, the reactor temperature was controlled at a constant value in the temperature range studied. Except for the temperature, conditions for all fermentations were the same for all fermentations- the pH at 5.5, aeration rate at 3 L/min, and agitation speed at 400 rpm. The dissolved oxygen level was generally maintained at 85% saturation. The medium was prepared in two parts. A glucose solution was prepared by adding 12 g glucose in 300 ml of distilled water in a flask. The rest of the medium components were dissolved in 2650 ml of distilled water in the fermentor. They were then autoclaved for 30 minutes at 121 °C, 15 psig. After sterilization, the medium in the fermentors was allowed to cool down to the selected experiment temperature. The glucose solution and 50 ml inoculum were then added to the fermentor. The total liquid volume in the fermentor was 3 liters. After inoculation, liquid samples were taken at regular time intervals. Measurement of broth optical density (O.D.) and cell plate count were conducted immediately. Additional liquid samples were frozen for future analysis of glucose and P-galactosidase concentrations.

Analytical Methods

(1) Cell Concentration The cell concentration was determined by measuring the optical density at

660 nm (OD 660) of the culture broth in a polystyrene cuvette (light path length 10 mm) with a spectrophotometer (Sequoia-Tumer Model 340). The cell dry weight 77 was determined by centrifuging 20 ml cell broth at 10,000xg for 10 minutes. After removing the supernatant, the resulting pellet was washed twice with distilled water. The washed cell pellet was resuspended in distilled water and then poured into a pre-weighed aluminum pan. The pan was dried at 80 °C for 24 hours and then weighed to determine the cell dried weight. A linear correlation between ODggo and cell concentration (g dry wt/L) was found as follows: Cell density (g/L) = 0.51 * ODggo This correlation was good for ODggo smaller than 0.5. The broth samples were diluted, if necessary, to ensure ODggo was lower than 0.5 in all measurements.

(2) Glucose Concentration The glucose concentration in the culture supernatant was measured by using a YSI Model 2000 glucose analyzer.

(3)B-Galactosidase Concentration The method of Miller (1972) was used in determining the P- galactosidase concentration. Frozen samples were thawed and vortexed. One milliliter of each sample solution was then centrifuged for 3 minutes in a microcentrifuge (Fisher, Model 235C). The supernatant was removed and the pelleted cells were resuspended in 1 ml Z-buffer solution with 0.27% P-mercaptoethanol (Sigma), 100 ml chloroform and 50 pi 1% sodium dodecylsulfate solution were added, and the mixture were then vortexed for 10 seconds to break the cells. The Z-buffer was composed of 16.1 g/L Na 2HP0 4 (7H20), 5.5 g/L NaH2P04 (H20), 0.76 g/L

KCL , and 0.246 g/L MgSC>4(7H20 ), and had a pH value around 5.5. To each 78 sample, 0.2 ml of a 0.4% o-nitrophenyl-3-D-galactopyranoside (ONPG) in Z-

buffer solution was then added, and the sample was incubated at 30 °C for 20

minutes. The reaction was stopped by adding 0.5 ml of 1.0 M Na 2C0 3 . The

sample was then centrifuged, and the optical density at 420 nm (OD 420) of the supernatant was measured by using a spectrophotometer. Using a commercial Aspergillus niger P-galactosidase enzyme as a reference, a linear correlation between the concentration of P-galactosidase and the optical density was found and followed the the following equation (Shields, 1989):

P-galactosidase (mg/L) = 200.5 * OD 420 A plot of optical density at 420 nm versus the weight percentage of ONPG is shown in Figure 3.1. The data shown in this figure were obtained by completing reaction of various concentrations of ONPG at pH 5.5, temperature 30 °C and 0.05

mg/ml of P-galactosidase. Thus, one unit of OD 420 was equivalent to 3.2 mmole

ONP in the solution., or in the enzyme assay, one unit of OD 420 was equivalent to 160 enzyme units.

P-galactosidase (unit) = 160 * OD 420 For R coli P-galactosidase, one enzyme unit is defined as that will hydrolyze 1.0 pinole of o-nitrophenyl P-D-galactopyranoside to o-nitrophenol and D-galactose per min at the specified pH and temperature (SIGMA, 1992). The P- galactosidase from Aspergillus orvzae had approximately 4 units per mg solid using lactose as substrate and pH 4.5 at 30 °C (o-nitrophenyl P-D- galactopyranoside is hydrolyzed at approximately the same rate). Figure 3.1. The plot of optical density at density optical of plot The 3.1. Figure OD (at 420 n m)

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 . 50 00 50 00 25.0 20.0 15.0 10.0 5.0 0.0 ONPG used initially for the enzymereaction. the for initially used ONPG Conditions: eprtr a 30 at Temperature [Beta —gal.] pH 5.5 [ONPG] (mmole/L)

.5 g/L 0.05 lp 0.312605 slope

X = 420 nm versus the concentration of of concentration the versus nm 420 = 79 80 Plasmid Stability The fraction of plasmid-containing cells in the total cell population was determined by plating cells after series dilution onto five nonselective medium agar plates and replica plating onto five selective medium agar plates. These agar plates were then incubated at 30 °C for several days. The number of colonies on each agar plate should be between 30 and 300. The ratio of the average number of colony-forming units on the selective agar plates to that of the nonselective plates provided the percentage of cells containing the plasmid. The fraction of plasmid- carrying cells was estimated as follows:

F = (SCCselective(i))/(SCCNonseiective(i)) The error in the determination of the fraction of plasmid-carrying cells by this spread plate method was calculated by using the following equation:

^ £ (CCSelec!ivet CCSekctiv^ ) Error= + CCnonselective.

Where: N : number of samples CCselective(i) : the colony count on an individual selective plate c c Selective(av.) and c c Nonselective(av.) : the average colony counts on the five selective and nonselective plates, respectively In all experiments, the error was found to be within 15%. 81 Results and Discussion

Plasmid Stability in Flask Culture The preparation of seed cultures used to inoculate batch fermentations was prepared in 50 ml selective medium in 500-mL flasks at 24 °C without pH control. The selective medium was used to maintain plasmid stability. The seed culture retrieved from 5 ml of inoculum was transferred to 45 ml of fresh selective medium and grown overnight. Without pH control in the flask, the pH values changed from 5.8 at the beginning to 4.0 at the end of fermentation. The low pH value at the end of the fermentation resulted from the accumulation of acetic acid. The fraction of plasmid-carrying cells in the flask culture was usually in the range of 85% to 95%. In order to check if the recombinant cells could be stably maintained before used for inoculation, the flask culture was transferred to a fresh medium for several times. The fraction of plasmid-carrying cells in the flask culture were checked during the whole process and was found to remain in the range of 71.6% and 95.5% (Figure 3.2). This indicated that the fraction of plasmid-carrying cells could be stably maintained in the selective medium, even after a series of transfer. The reasons for the selective medium failed to maintain 100% plasmid-carrying cells have been discussed before. However, under no circumstances one should expect to get the same colony count from the selective and nonselective agar plates even though the selective medium was 100% effective. The selective medium can only prevent the growth and reproduction of plasmid-free cells, but not the appearance of plasmid-free cells due to segregational instability. Therefore, unless the plasmid-free cells died immediately after their birth, they would grow and show up in the plate count once they were 82 transferred to the nonselective agar plate. Clearly, the plasmid-free cells could survive long enough in the selective medium used in this study.

Fermentation Kinetics

Six batch fermentations with the selective medium in the range of 22 °C to 32 °C are shown in Figures 3.3.a to 3.3.f. Figures 3.4.a to 3.4.c show three batch fermentations (at 25 °C, 28 °C and 32 °C) with the nonselective medium. The curves through the data points for the figures at 25 °C, 28 °C and 32 °C in the selective and nonselective media were generated from model simulations, which will be discussed latter in this chapter. Figures 3.5.a to 3.5.c show batch fermentations with plasmid-free cells in the nonselective medium at 25 °C, 28 °C and 32 °C, respectively. Figure 3.2: Fraction of plasmid-containing cells in flask cultures with the selective the with cultures flask in cellsplasmid-containing of Fraction 3.2:Figure Fraction (%)

20. 40. 60. ao. ioo. . 5 5. 5 10 15 10 15 200. 175. 150. 125. 100. 75. 50. 25. O. medium. The arrows show when the flask culture was transferred to a to transferred was culture flask the when show arrows The medium. fresh medium. fresh ie (hr)Time 5 C 25 Selective 83 iue .. Bthrcmiatyatfretto ih h slciemdu at medium selective the with fermentation yeast recombinant Batch : 3.3. Figure Concentration bjO cn N w co 'O'n 1 o. - - . - r ) - --- 1 1 A 22 °C. 22 9 Glucose A A A —1—i-i— -1— i , H Cell( *5 ) 5. 9 , 5 20. 15. 1 0 □ A 1 ■i rr i r r r ... □ A | I | -T I 1 ( , , "| r me (hr) ) r h ( e im T n □ A (a) at (a) , l , V 22 Selective □ A 22 c oq o □ V A Fraction. Q 1 ° ° □ C7 A n § o A V , T ' 5 0 3 30. 25. □ A 1

Beta — A V , “ I 1 A 1 A1 □ V » gal □ V J 1 , r-—i *rS 3 □ 1 1 1 A (*io_ '« ---- i 1 — . - - - - » o I o N o o CO o o CO N o 84 Fraction (%) Concentration. Figure 3.3. Continuous 3.3.Figure w ci 10

1 ----- □ V 1 ----- A- —a-a A a) - a j— -A -A O □ 1 ----- 1 ----- eagl (*10)Beta—gal □ £ □□□ 1 ----- 1 ----- V 1 V 1 LAH ----- 1 ----- r- 30. 1 I I I I 35.

o 20. 40. 60. 80. lOO. 120. 85 Concentration (g/L) Fraction (%) o

1- 2. 3. 4. 5. 6. 60. 80. lOO. 120. Continuous 3.3. Figure o. el (Cell *5 ) Glucose 5 Seletive 5 C 25 10 . c t2 oc o at25 (c) Time (hr) 15. 20 Beta —gal (*10) . . 5 2 30. 35. 86 Concentration (g/1) Continuous 3.3. Figure N 03 10 CD o . . 0 1. 0 2. 0 35. 30. 25. 20. 15. 10. 5. O. A A A A el*) □ Cell(*5) e s o c u l G a T C 2T Selective

o (d) at 27 oc. at 27 (d) ie (hr)Time

a □ o o V □a eagl (*10) Beta—gal v Fraction □ 7 V 0

Cd O o o CD o O CD Cd o O

Fraction (%) 87 Concentration (g/L) Fraction (%) iue33 Continuous 3.3. Figure o 1- 2. 3. 4. 5. 6. 60. 80. lOO. 120. o. Glucose CeLl (*5) Seletive 8 C 28 .15. 5. 10 . Time (h.r) (e) at 28 at 28 (e) oq 20 . Beta — ( gal * 10 ) 5 30. 25. 35. Concentration (g/L) Fraction (%) O

1 - 2- 3- 4. 5. 6. 60. 80. lOO. 120. o. ‘ c. iue33 Continuous 3.3. Figure Glucose e l (Cell *5 ) Seletive 2 C 32 5 10 . Time (h.r) (f) at 32 °C. at 32 (f) 15. Beta —gal (*10) 20 . 25. 30. 35. 89 Concentration (g/L)

20. 40. 60. 80. lOO. 120.

Fraction (%) 90 Concentration (g/L) Continuous 3.4. Figure O. Glucose Nonselective 8 C 28 lO. 5 ie (hr)Time (b) at 28 oC. at 28 (b) 15. 20 el (*5)Cell Beta (*10)—gal Fraction . 25. 30. 35.

20. 40. 60. 80. lOO. 120.

Fraction 91 Concentration (g/L) W CO 10 (0 iue34 Continuous 3.4. Figure O. Glucose Nonselective 2 C 32 5 lO. ie (h.r)Time (c) at 32 oc. at32 (c) 15. 20 . el (*5) Cell Beta (*10)—gal Fraction 25. 0 35. 30. O C\! o O CD o co Cl o o

F r a c t i o n 92 iue .. Bth emnain ieis o pamdfe cls ih the with cells plasmid-free for kinetics fermentation Batch : 3.5. Figure \ Concentration bfl W CD . . 0 1. 20. 15. 10. 5. O. “ I I 1 | I f i J J i f I | 1 I I “ i I i I i i i Cell(*5) Glucose n n nonselective medium at 25 °C at 25medium nonselective d a . A A □ t l 1 l I j I l 1 j i r l j 1 I ie (larTime ) (a) at 25 °C at 25(a) i 4, i J 5 C 25 lsi fe Cls only Plasmid Cells—free Nonselective □ a □ SJ . . I . .I.. ------I ------I ------.__ « I « t.1___« - I ------30. j ------t r 35. 93 Concentration (g/1) iue35 Continuous 3.5. Figure N CO 10 CD O. 1 ” ------el*) O Cell(*5) e s o c u l G D □ A A 1 ------1 ------I 5. [ ------□ I I I L. L I I I I I I I 1 _ 1 ------1 ------

1 ------0 1. 20. 15. 10. 1 ------1 ------1 ------ie (h.r)Time I ------(b) at 28 oc at 28(b) 1 ------lsi fe Cls only CellsPlasmid —free 8 C 28 Nonselective 1 ------A A A Af 'A A - * - □ a a a □ □ D I ------1 ------—T f— ------1 ------1 1 ------25. 1 ------1 ------1 ------■ I _ ------30. I 1 ------1 ------1 35. Concentration, (g/l) w CO 10 to Figure 3.5. Continuous 3.5. Figure i a (i . . 0 1. 0 25. 20. 15. 10. 5. O. Glucose - J 1 J « I I “ Cell( ------□ 1 ------1 ------J ------1 ------1 ------i e (hr)Time 1 ------(c) at 32 0C at32 (c) J ------2 C 32 lsi fe Cls only Plasmid Cells—free Nonselective 1 ------□ □ □ □□ 1 ------1 ------j ------1 ------1 ------1 ------J ------1 ------\ ------1 ------0 35. 30. J ------95 96 The effects of temperature on these recombinant yeast fermentations are discussed below.

Cl) Specific Growth Rate The plots of ln(cell dry weight) versus time at various temperatures, 22 °C, 24 °C, 25 °C, 27 °C, 28 °C and 32 °C, shown in Figure 3.6, were used to determine the maximum apparent growth rate for growth in the selective medium. The specific growth rates of plasmid-free cells in the nonselective medium at three different temperatures, 25 °C, 28 °C and 32 °C were determined from the plots shown in Figure 3.7. The slopes of the linear portions of these plots are the maximum apparent specific growth rate for the corresponding growth conditions. Figure 3.8 shows that the effect of temperature on the maximum apparent specific growth rate for growth in the selective medium and the maximum specific growth rate of plasmid-free cells grown in the nonselective medium. The specific growth rate increased with temperature in the range of 22 °C to 32 °C for both cases. Since the plasmid-carrying cells could have extra burdens in synthesis of plasmid and recombinant protein, they would grow slower than plasmid-free cells at the same temperature. The apparent specific growth rate in the selective medium was thus lower than the specific growth rate of plasmid-free cells grown in the nonselective medium. iue .: h po o l(el est) s tm wt te eetv mdu at medium selective the with time vs. density) ln(cell of plot The 3.6: Figure l J C3 c\i (Cell) i I 1 O. various temperatures various . 0 5 20. 15. 10. 5. ie (hr)Time Selective 5 C 25 . 30. 5. 35. 97 iue .: h po fl(el est) s tm wt te oslcie eim at medium nonselective the with time vs. density) ln(cell of plot The 3.7: Figure Ln( Cell) . . 0 1. 0 2. 0 35. 30. 25. 20. 15. 10. 5. 0. various temperatures various (Plasmid-free cells ) cells (Plasmid-free ie (h.r)Time Nonselective 98 Figure 3.8: Effect of temperature on the specific growth rategrowth specific temperaturetheon of Effect 3.8: Figure Speofic growth, rate ( jj ) (1/h.r)

0.0 0.1 0.2 0.3 0.4 20 . Apparent □ for plasmid plasmid cells —freefor eprtr (°C) Temperature 25. n slcie medium selective in. 30. 35. 99 100 (2) Cell Yield In Figure 3.9, the apparent cell yields at various temperatures were obtained from the slope of the linear plot of cell concentration versus glucose concentration in the selective medium. Figure 3.10 shows the determination of cell yields for plasmid-free cells grown in the nonselective medium at three different temperatures, 25 °C, 28 °C and 32 °C. The relationship between the cell yield and temperature in the selective medium and the nonselective medium with plasmid- free cells is shown in Figure 3.11. From this figure, the cell yield is seen to be nearly constant at all temperatures for both cases. However, a significant higher cell yield was found for plasmid-free cells grown in the nonselective medium when it is compared with the cell yield in the selective medium. 101

Selective

CO 22 C d 24 C hJ 25 C \ bfl 27 C pH pH

o o

o. 1. 2. 3. 4. Glucose (g/l)

Figure 3.9: The plot of cell concentration versus glucose concentration in the selective medium iue .0 Te lt f el ocnrto vru guoe ocnrto i the in concentration glucose versus concentration cell of plot The 3.10: Figure Cell (g/L) N O o ® H o co O o N o o o. □ v \ nonselective medium nonselective . . 3. 2. 1. (Plasmid —free only) cells lcs (g/l) Glucose 2 C 25 □ 2 C 28 A v 2 C 32 Nonselective

□y e # b. 4. 102 Figure 3.11: Effect of cellonyield of temperature Effect 3.11:Figure Cell Yield, (g of CDW/ g of glucose)

0.0 0.1 0.2 0.3 0.4 0 2. 0 35. 30. 25. 20. Aprn cl yed n eetv medium selective in yield cell Apparent □ cl yed o pamd—re el only plasmid cells —free for yield cell A eprtr (°C) Temperature 104 (3) Product Yield The plot of P-galactosidase versus glucose concentration with the selective medium at various temperatures is presented in Figure 3.12. The apparent product yield was obtained from the slope of the curve at each temperature. The effect of temperature on the apparent product yield is shown in Figure 3.13. In the selective medium, the highest product yield was found at 25 °C and lower temperatures. There was no product from plasmid-free cells. The product yields from growth in the nonselective medium was generally lower than those found in the nonselective medium at corresponding temperature. The lower product yield from nonselective medium can be attributed to plasmid loss. iue .2 Te lt f -aatsds vru guoe ocnrto i the in concentration glucose versus P-galactosidase of plot The 3.12: Figure Beta galaetosidase (g/L)

00 01 0-2 0.3 0.4 c o. -A selective medium selective 1 lcs (g/1) Glucose 2 Selective 105 Figure 3.13: Effect of on product yield of temperature Effect 3.13:Figure Product Yield (g/g)

0.0 0.1 0.2 0.3 0.4 20 a paet rd yed n eetv medium selective in yield prod, Apparent - a . A rd yed o pamd—re el only plasmid cells—free for yield Prod, eprtr (°C) Temperature 5 0 35. 30. 25. 107 (4) Specific Production The plot of the specific production versus fermentation time at various temperatures with the selective medium is shown in Figure 3.14. The specific production can be considered as an indicator of the degree of gene expression in cells. This temperature-regulated promoter on the plasmid was controlled by the level of MATa2 repressor. At the restrictive temperature (> 30 °C), high concentration of repressor would efficiently bind with the MATa2 operator and completely shut off the expression of the product gene. Therefore, a low production of P-galactosidase or even no production was detected. On the contrary, P-galactosidase was produced at a high level owing to the lack of the synthesis of MATa2 repressor at the permissive temperature (< 25 °C). It is thus clear that the specific production is a function of temperature. The highest gene expression was found at 25 °C. The gene expression decreased with increasing the temperature in the range between 25 °C and 32 °C. Also, the specific production increased gradually with fermentation time before it reached a constant value near the stationary phase. Apparently, gene expression and P-galactosidase production laged behind cell growth, although the product formation was generally growth- associated.. Figure 3.14: The specific production of ( of production specific The 3.14: Figure (Beta. —gal/Cell) (g/g)

0.0 0.1 0.2 0.3 0.4 0.5 o to O. [> 28 32 O 27 O Selective various temperatures various 5 10 . ie (h.r)Time 15. 3 -galactosidase in the selective medium at medium selective the in -galactosidase 20 . . 5 2 30. 35. 108 109 (5) Plasmid Stability The effect of temperature on plasmid stability in batch fermentations with the. selective medium are also presented in Figures 3.3.a to 3.3.f. Insufficient selective pressure was discovered in these fermentations and the fraction of plasmid-carrying cells averaged between 80% to 90% at all temperatures. Several researchers have pointed out that the inefficiency of the selective pressure for the recombinant plasmid in auxotrophic yeast. Four types of explanation for the appearance of plasmid-free cells under the selective environment have been proposed. First, the persistence of plasmid-encoded enzyme from the mother cells to daughter cells may help in the survival of plasmid-free cells (Lauffenburger, 1987 and Satyagal and Agrawal, 1989). However, this may not be the major cause for the appearance of plasmid-free cells due to the self-regulation system for the production of enzymes in cells (Satyagal and Agrawal, 1989). Second, the oversynthesized metabolite from the plasmid-carrying cells may be passed onto the daughter cells, and the persistent metabolite may be enough to help the cells lacking the plasmid to grow from 1 to 8 generations (Murray and Szostak, 1983). Third, the oversynthesized metabolites may be secreted from the plasmid-carrying cells to the medium and then be taken up by the plasmid-free cells (DiBiasio and Sardonini, 1986 and Sardonini and DiBiasio, 1987). Fourth, the release of cellular contents, plasmid and complementary products, from lysed dead cells into the medium may support the growth and existence of plasmid-free cells (Mason, 1991 and Mason and Hamer, 1987). As shown in Figure 3.15, when the data from all temperature are plotted together, a clear pattern can be recognized for plasmid instability in the selective medium. The fraction of plasmid-carrying cells dropped gradually during the exponential phase, but this trend was revered in the stationary phase. As discussed earlier, it is not surprised to observe a decrease in the fraction of plasmid-carrying cells in the selective medium. However, the come-back phenomena (increase in the fraction of plasmid-carrying cells) is interesting and has not been reported in the literature. The come-back of the fraction of plasmid-carrying cells might be simply resulted from the difference in the survival ability for the plasmid-carrying and plasmid-free cells in the selective medium. Under nutrient-limited (glucose depletion) conditions, plasmid-carrying cells would adapt to the environment better than the plasmid-free cells. Also, it is less likely for any tryptophan to be made available to the plasmid-free cells under this condition. Therefore, plasmid- free cells could not maintain their metabolism and would die fast in the stationary phase, as shown in Figure 3.16. The quick death of plasmid-free cells would then result in an increase in the fraction of plasmid-carrying cells. This come-back phenomena was not observed for cultures grown in the nonselective medium . The effect of temperature on plasmid stability in batch fermentation with the nonselective medium is shown in Figure 3.17. As shown in this figure, the drop of the fraction of plasmid-carrying cells was around 30% for all three cases. The temperature effect on plasmid stability will be discussed further in the following modeling section. Fraction Figure 3.15: plasmid stability in batch fermentations with the selective medium selective the with fermentationsbatchin stability plasmid 3.15: Figure O N O O CD o cn o o o a o . . 0 1. 0 2. 0 35. 30. 25. 20. 15. 10. 5. O. Seletive 5 C 25 2 C 22 ie (h.r)Time 111 Figure 3.16: kinetics of cell concentrations including total cells, plasmid-carrying plasmid-carrying cells, total including concentrations cell of kinetics 3.16: Figure

Concentration (g/L)

0.0 0.2 0.4 0.6 o.a o . . O 1. 0 2. 0 35. 30. 25. 20. 15. lO. 5. O. A - Cells ' Total □ selectivemedium. the with °C 25at fermentation batch a in cellsand plasmid-free cells Plasmid —free cells v Plasmid —carrying cells ie (h.r)Time 112 Figure 3.17: plasmid stability in batch fermentations with the nonselective medium nonselective the with fermentations batch in stability plasmid 3.17: Figure

O 20. 40. 60. 80. 1O0. 120. . 50 00 50 00 50 30.0 25.0 20.0 15.0 10.0 5.0 0.0 oslcie Medium Nonselective Time (hr) t j r L 35.0 113 114 Mathematical Model

Imanaka and Aiba (1981) proposed that the loss of plasmid during cell growth was resulted from the segregational instability and could be represented by the following mechanism.

+ j- M- v j. X ------:------? (2-p)X+p.X

X ------> 2 X Where X+ and X" are the concentration of plasmid-containing cells and plasmid-free cells, respectively. P is the probability of plasmid loss from each cell division. For cells growing in a nonselective medium, P is between zero and one and can be determined by fitting the kinetic model to experimental results. For cells growing in a selective medium, P should have the same value as that in a nonselective medium. This proposed mechanism is suitable for batch fermentations with selective and nonselective media at all temperatures. 115 The kinetic model is as follows:

^-=/>SX'+(.fl--kd)x- at dX _ dX + | dX~ dt dt dt dS 1 + „ + 1 _ v_ = ju+X++ u X Uldt Ix/s Y *x/sY~ dP _Yp/s + y+ dt Yx/S

ks+S If =~p^—u~S ks+S

F = -x++x~ r - —

Where S is the substrate (glucose) concentration and P is the product (3- galactosidase) concentration. As already seen in Figures 3.3 and Figure 3.4, the p- galactosidase concentration increased with cell growth and then remained constant or slightly decreased after cells entered the stationary phase. Therefore, the production of this recombinant product should be growth associated, not non growth associated. p+ and p~ are the specific growth rates of the plasmid- containing and plasmid-free cells, respectively. k(j is the death rate for plasmid- free cells. The growth rate of cells follows the Monod model, which depends on the concentration of substrate, glucose. ks is the cell affinity for the substrate. Y+x/S and Y"x/S are the cell yield for plasmid-carrying cells and plasmid-free cells, respectively. Y+p/s is the product yield for plasmid-carrying cells. F is the fraction of plasmid-carrying cells. These equations can be solved numerically, and 116 the best values for the parameters in this model can be either determined from experimental data or found by fitting the model to the data. This is discussed in the following section. As already shown in Figure 3.3 and 3.4, the model simulates the data quite well.

(1) Parameter Estimation

The parameter values used in the model simulation are listed in Table 3.1 and 3.2 for growth in selective and nonselective media, respectively.

(a) Cell Yield - Y+ y /s , V y/g Best values for Y~x/S were determined from the slope in the plot of cell concentration versus glucose concentration (Figure 3.10) This slope was used in the model for growth in the nonselective medium. The cell yields for plasmid- carrying cells and plasmid-free cells in the selective medium and the cell yield for plasmid-carrying cells in the nonselective medium were estimated by best fitting the model with suitable parameter values to match with the experimental data.

(b) Product Yield - Y+p/§ This parameter was determined in a similar way, by plotting p - galactosidase concentration against glucose concentration in the selective medium (Figure 3.12). Product yield for the plasmid-free cells should be zero and thus is not considered in the kinetic model. 117 (c) Max. specific growth rate- um+ . um~ The maximum apparent specific growth rates, determined from Figure 3.6, were used as the maximum specific growth rate of plasmid-carrying cells. The maximum specific growth rates for plasmid-free cells grown in the nonselective medium was determined from Figure 3.7. It was assumed that the values were the same in both selective and nonselective media in model simulation.

(d) Segregational Instability - B The value for the segregational instability, P, was evaluated from model fitting by using the plasmid instability data from batch fermentations with the nonselective medium. From the simulation results, the segregational instability , at the permissive temperature (P=0.08), is higher than segregational instability, at the restrictive temperature (p=0.03). The plasmid is less stable at lower (or permissive or 25 °C) temperatures than at higher (or restrictive or 32 °C) temperature. Spending considerable amount of energy on plasmid maintenance and gene expression during growth usually leads to high plasmid instability. On the other hand, the plasmid is more stable when the expression is turned off (Lee et al., 1988). In the selective medium, an assumption was made that the segregational stability is identical to that in the nonselective medium. The mechanism for the plasmid loss is strongly associated with the genetic structure and host cells. The probability of plasmid loss during cell division should not be affected by the tryptophan concentration. 118 (V) Substrate Affinity - ks The Monod model was suggested as the kinetic model for recombinant cell growth. Cell's affinity for the substrate (ks) affects the specific growth rate of recombinant cells. The larger ks is, the slower the growth rate of cells is. The optimized ks value was obtained from curve fitting and was found to be 0.1 g/L. It is noted that ks was found to be the same for all cases studied.

ffl Death Rate of Plasmid-free Cells - kj The death rate of plasmid-free cells in the selective medium was estimated by matching the curve of plasmid stability. No death rate of plasmid-free cells was considered in the nonselective medium.

Conclusion

The appearance of plasmid-free cells was discovered even under the employment of the selective pressure (i.e. in the selective medium) at all temperatures studied. The appearance of plasmid-free cells indicates the insufficiency of the selective pressure. During the course of fermentation, the fraction of plasmid-carrying cells first dropped to the lowest value at the middle of log phase and then came back to a higher value after entering the stationary phase. This come-back phenomena can be attributed to the fast death of plasmid-free cells under the selective environment. In the nonselective medium, the plasmid was more unstable at the permissive temperature than at the restrictive temperature. At the same temperature, the apparent specific growth rate in the selective medium was lower than the specific growth rate of plasmid-free cells in the nonselective medium. This indicates that the plasmid-free cells grow faster than the plasmid-carrying cells. Also, a higher cell yield was found for plasmid-free cells grown, in the nonselective medium as compared to the apparent cell yield in the selective medium. The highest product yield was found at 25 °C in the selective medium. There were no products in plasmid-free cells. The gene expression decreased with increasing temperature from 25 °C to 32 °C. The level of repressor was high enough to shut off the expression completely when temperature was above 30 °C. The product formation was growth-associated. 120 Table 3.1. Estimated values for parameters in the proposed model for growth in the nonselective medium

25 oc 28 OC 32 OC M-+m 0.240 0.266 0.300 P"m 0.260 0.321 0.363 P 0.08 0.04 0.03 ^s 0.1 0.1 0.1 Y+X/S 0.225 0.221 0.190 Y'X/S 0.295 0.260 0.262 Y+p/S 0.135 0.004859 0.00149 Y’P/S 0 0 0 *lag 5.0 2.5 5.0 kd 0.0 0.0 0.0 Initial Conditions at 0 hr x to 0.02295 0.02244 0.02346 So 3.75 3.98 3.98 Po 0 0 0 Fo 0.83 0.88 0.83

where:

The values of 3, ks, Y+x/S an<3 t|ag were obtained from model fitting The value of p+m was obtained from Figure 3.6 The value of p"m was obtained from Figure 3.7 The value of Y"x/S was obtained from Figure 3.10 The value of Y+p/§ was obtained from Figure 3.12 121 Table 3.2. Estimated values for parameters in the proposed model for growth in the selective medium

22 OC 24 oc 25 °C 27 oc 28 oc 32 oc P^m 0.183 0.236 0.240 0.260 0.266 0.300 M-"m 0.260 0.321 0.363 P 0.08 0.04 0.03 ^s 0.1 0.1 0.1 Y+X/S 0.201 0.199 0.265 0.206 0.23 0.180 Y'X/S 0.265 0.260 0.222 Y+P/S 0.135 0.135 0.135 0.0369 0.004859 0.00149 Y"P/S 0 0 0 0 0 0 tlag (hr) 2.50 1.75 2.25 tiag for P(hr) 8 0 0 kd 0.1 0.1 0.05 Initial Conditions at 0 hr Xtf) 0.0194 0.0175 0.0204 So 3.55 3.93 3.95 Po 0 0 0 F0 0.90 0.85 0.80 Where: The values of p, ks, Y+x/S> Y"X/S> tjag for P, tiag and were obtained from model fitting The value of p+m was obtained from Figure 3.6 The value of p“m was obtained from Figure 3.7 The value of Y+p/§ was obtained from Figure 3.12 122 References

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Miller, J. Experiments in Molecular Genetics. Cold Spring Harbor Laboratory, 352-355 (1972).

Murray, A. W. and Szostak, J. W., Pedigree analysis of plasmid segregation in yeast, Cell, 34, 961, 1983.

Noach, D., Roth, M., Geuther, R., Muller, G., Undisz, K., Hoffmeier, C. and Gaspar, S., Maintenance and genetic stability of vector plasmids pBR322 and pBR325 in E. coli K12 in a chemostat, Mol. Gen. Genet., 184, 121, 1981. 123

Nordstrom, K. and Austin, S. J., Mechanisms that contribute to the stable segregation of plasmids, Annu. Rev. Genet., 23, 37, 1989.

Ollis, D. F., Industrial fermentations with (unstable) recumbinant cultures, Philos. Trans. R. Soc. (london), 297, 617, 1982.

Sardonini, C. A. and DiBiasio, D., A model for growth of Saccharomvces cerevisiae containing a recombinant plasmid in selective medium, Biotechnol. Bioeng., 29, 469, 1987.

Satyagal, V. N. and Agrawal, P., On the effectiveness of selection pressure through use of a complementing product, Biotechnol. Bioeng., 34, 273, 1989.

Seo, J. H. and Bailey, J. E., Effects of recombinant plasmid content on growth properties and cloned gene product formation in Escherichia coli. Biotechnol. Bioeng., 27, 1668, 1985.

Sledziewski, A. Z., Bell, A., Kelsay, K. and Mackay, V. L., Construction of temperature-regulated yeast promoters using the MATa2 repression system, Bio/Technol., 6, 413, 1988.

Sterkenburg, A., Prozee, G. A. P., Leegwater, P. A. J. and Wouters, J. T. M., Expression and loss of the pBR322 plasmid in Klebsiella aero genes NCTC 418 grown in chemostat culture, Antonie van Leewenhoek, 50, 397, 1984.

Tsunsekawa, H., Tateishi, M., Imanake, T., Aiba, S., TnA-directed deletion of the trp operon from RSF2124-trp in Escherichia coli. J. Gen. Micro., 127, 93, 1981.

Walmsley, R., Gardner, D. and Oliver, S. G., Stability of a cloned gene in yeast growth in chemostat culture, Mol. Gen. Genet., 192, 361, 1983.

Weber, A.E. and San K. Y., Bioprocess Engineering Colloquium, ASME Winter Annual Meeting, Boston, MA, p. 75-78, Dean, R. C., Jr. and Nerem, R. M. (Eds), 1987. CHAPTER IV DYNAMIC RESPONSES OF GENE EXPRESSION TO TEMPERATURE SWITCH DURING FERMENTATION

Abstract

The separation of growth phase and production phase has been proposed to be an effective strategy in recombinant DNA fermentations to enhance plasmid stability and reactor productivity. The response time for tum-on of gene expression is a major factor for the design of separation of growth phase and production phase in a two-stage process. Cyclic oscillation of environmental conditions such as the specific growth rate and dissolved oxygen level has also been proved to be able to improve the plasmid stability and reactor productivity. It is feasible to apply cyclic oscillation of the specific growth rate regulated by temperature to the fermentation system. However, the response time for tum-on and turn-off gene expression must be studied. In this study, the dynamic responses of expression level of the protein product to temperature switch in batch, repeated batch and continuous fermentations were investigated in a selective medium. In the batch fermentation, the fermentation time was too short to turn on gene completely. In the repeated batch fermentations, this recombinant yeast showed that the cell response for gene turn-off took place slowly, but response for gene tum-on was quicker. In the continuous fermentations, the higher the dilution rate was, the longer the reactor and gene response times were. A kinetic model for the dynamic response of the 124 125 concentration of recombinant protein to temperature switch during the continuous fermentation was proposed. Cell response to temperature switch can be simulated by using a first order plus dead time model. A first order model was used to account for the effect of dilution rate on the change of protein concentration. The developed process model simulates the experimental data very well.

Introduction

Temperature is one of the most important environmental factors affecting cell growth. Temperature, besides its general effect on reaction rates, can exert highly selective effects on metabolic pathways; repression of particular protein synthesis is an example. Thus, the culture as a whole may have varied and complex responses when its temperature is altered. The protein synthesis capacity of a cell is determined by its number of ribosomes and their activity. If protein synthesis is the rate-limiting step in cell replication, the growth rate can be varied by altering the activity of the existing ribosome via a change in the cultivation temperature, and by altering the size of the biosynthetic machinery by changing the RNA content. The influence of temperature, in the range 23-35 °C, on the specific growth rate and RNA content of Saccharomyces cerevisiae w as examined in batch and continuous fermentations by Parada and Acevedo (1983). The specific growth rate increased with increasing temperature when the temperature was below 30 °C. A significant drop in the specific growth rate was found when the temperature was higher than 30 °C. They also found a linear relationship between the specific growth rate and the RNA content in Saccharomyces cerevisiae grown at 4 different temperatures, 25 °C, 28 °C, 32 °C and 35 °C, in continuous fermentation. At a 126 given dilution rate (or specific growth rate), the lower the temperature was, the higher the RNA content was. The effects of temperature on recombinant cells include not only the specific growth rate and RNA content, but also plasmid stability, level of translation and transcription of intermediates for gene-product biosynthesis. Park (1988) studied the effect of temperature on recombinant R coli with a temperature-sensitive promoter. The gene expression was regulated by changing temperature, because the A.Pl promoter was controlled by the temperature- sensitive repressor (clg 57) (Park, 1988). Acker et al. (1982) showed that the probability of repression of the AJPl promoter can be quantitatively related to the change of repressor concentration. Park (1988) also concluded that spending considerable amount of energy on plasmid maintenance and gene expression during growth always led to high plasmid instability. Therefore, in order to obtain high expression level and high production, it is better to separate the growth phase and production phase. A two-stage culture by using a temperature-sensitive expression E. coli mutant has been reported by Ryu and Siegel (1986), Siegel and Ryu (1985) and Lee et al. (1988). The results showed that a two-stage system allowed higher production of gene product over a prolonged period when compared to a single-stage or batch culture. In this study, the control of gene expression by temperature-switch in batch, repeated batch and continuous fermentations were studied. In order to prevent plasmid loss during the process, all fermentations were carried out in a selective medium. There were two purposes in studying the dynamic response of gene expression to temperature switch during fermentation. First, for the design of a two-stage fermentation process, the response time from the restrictive temperature at which cells possess high plasmid stability and low production, to the permissive 127 temperature at which cells possess low plasmid stability and high production, is a key factor. This response time is important in determining the suitable dilution rate in each stage. Second, Weber and San (1987) found that plasmid-carrying and plasmid-free cells behaved differently in transient environments. The transients induced by forced oscillation in the dilution rate (or specific growth rate) were advantageous to plasmid-carrying cells in competing with plasmid-free cells (Weber and San, 1988). It may be possible to maintain the plasmid stability by forced oscillation in the specific growth rate by oscillating the growth temperature in a glucose-stat. The glucose concentration is maintained at the setpoint, therefore, the specific growth rate can be regulated by the temperature. The response times for gene tum-on and turn-off actions are also very important for the design of temperature oscillation to stabilize plasmid, .

Materials and Methods

Yeast and Plasmid The yeast and plasmid used in this study have been described in chapter 3.

Growth Media In order to prevent plasmid loss during the course of fermentation, only the selective medium described hi chapter 3 was used in this study.

Fermentations The conditions for all fermentations were the same - the pH at 5.5, aeration rate at 3 L/min, agitation speed at 400 ipm and the dissolved oxygen level at 85% saturation. Fermentations were carried out with the selective medium. For repeated batch fermentations, the glucose concentration at the beginning was 4 g/L. When the glucose had been fermented and its concentration was close to 0 g/L, a concentrated glucose solution with corresponding nutrients was added to the medium to bring the glucose level back to 4 g/L. This was repeated for four times. During the course of fermentation, the gene tum-on experiment was conducted by changing the fermentation temperature from 30 °C to 24 °C. The gene turn-off experiment was carried out by changing the temperature from 24 °C to 30 °C. It generally took only 5 minutes for the fermentor to reach a new constant temperature after the switch. For continuous fermentations, the gene tum-on experiments were carried out at 0.1 and 0.05 hr'l dilution rate. The gene turn-off experiments were carried out at 0.133 and 0.1 hr'l dilution rate. For the gene turn-off experiment, the initial batch growth temperature was 24 °C. After 20 hours, a continuous feed was turned on and the fermentor was operated at continuous mode. The fermentor temperature was changed from 24 °C to 30 °C after reaching steady state. Similar procedures were followed for the gene tum-on experiments, except that the temperature setting was 30 °C initially and changed to 24 °C.

Analytical Methods The same analytical methods described in chapter 3 were used in this study. 129 Results and Discussion

Batch Fermentation Figure 4.l.a shows a batch fermentation with temperature switch from 30 °C to 24 °C. In this experiment, the temperature was initially maintained at 30 °C and then switched to 24 °C during the exponential phase. As expected, almost no 3-galactosidase was found during the first stage. After temperature switch, the production of p-galactosidase gradually increased with time. As indicated by the specific production (concentration of P-galactosidase / cell concentration) shown in Figure 4.1.c, gene expression is quite sensitive to temperature switch. Immediately following the temperature switch, the specific production of P- galactosidase (which equals to the slope in the linear plot) increased sharply. However, the production level and the specific production were still very low, far below the level if the fermentation were at 24 °C throughout (see Figure 3.3.b). This was because glucose depletion occurred shortly after the temperature switch and the fermentation time was too short to allow gene expression to be fully turned on. In order to extend the fermentation time, repeated batch and continuous fermentation were performed to further examine cell responses to temperature switch. 130 (a)

O IN « I I I I I I I I I I I I ------1 1------'------'------1------1------1------r- Batcti fermentation O NO co □ cell * (g/L) A glucose (g/L) 7 B —gal (g/L)* O O Specific productivity^ & Fraction. o

0.0 5.0 10.0 15.0 20.0 25.0 30.0 T i m e (hr*)

(b)

o o n

0.0 5.0 10.0 L3.0 20.0 25.0 Tim e ( Ur )

Figure 4.1: Kinetics of batch fermentation with temperature switch from 30 °C to 24 °C- (a) time course data, (b) temperature switch at 15 hrs Figure 4.1: Kinetics of batch fermentation with temperature switch from 30 °C to °C 30 from switch temperature with fermentation batch of Kinetics 4.1: Figure Figure 4.1. Continuous 4.1. Figure B B — galac tosidase (g/L)

0.000 0.005 0.010 0.015 0.020 0.0 Bth fretto, ih eprtr switch temperature with -Batch, fermentation, 24 °C- (c) specific production specific (c) °C- 24 0.2 (c) specific production specific (c) e l (g/L)Cell 0.4 / / 0.6 131 132 Repeated batch Fermentations The dynamic responses of the expression of the recombinant protein to temperature switch between 24 °C and 30 °C in repeated batch fermentations are shown in Figures 4.2 and 4.3 for turn-off action and tum-on action, respectively.

(T) Turn-Off Action As shown in Figure 4.2.a, before temperature switch, there was parallel production of P-galactosidase with cell growth. However, when glucose was exhausted, cells entered stationary phase and P-galactosidase decreased slightly. The growth and production were resumed when new glucose was added. The specific production of P-galactosidase reached the highest value, 0.74 (g/g cell) at 23 hours. It then went down to 0.50 at the point where temperature was switched. After temperature was changed from the permissive temperature, 24 °C, to the restrictive temperature, 30 °C, the recombinant cells did not respond to the temperature change immediately. There was a time lag before P-galactosidase production was turned off by the higher temperature. This turn-off response can be seen from the change in the slope in the linear plot shown in Figure 4.2.c. It is noted that the slope was only slightly higher than zero, indicating that the gene expression was turn off almost completely at 30 °C. The gene expression should be an inverse function of the repressor concentration. Therefore, the production of repressors in cells after the temperature switch should gradually increase and eventually reached a high level to inhibit or stop the gene expression. During this transition, the cells spend considerable time for the preparation of precursors and metabolites for the syntheses of repressors. This would explain the observed time delay in gene turn 133 off action. Also, as shown in this study, the already produced P-galactosidase would stay in the cells unless cells were dead and lyzed due to starvation.

(2) Turn-On Action Figure 4.3. shows the kinetics of the repeated batch fermentation with temperature switch from 30 °C to 24 °C. As shown in Figure 4.3.a, no production of P-galactosidase was observed in the first stage at 30 °C. After temperature was changed to 24 °C at 47.42 hours, it took several hours before significant amount of P-galactosidase were produced in the culture. As shown in the plot of P- galactosidase versus cell concentration, a sharp slope change took place, but not immediately, after the temperature switch. It took about 29 hours after the temperature switch to reach a maximum specific production (Figure 4.3.a). After that, the specific production decreased slightly, perhaps due to the long starvation periods between glucose addition. In principle, the specific production should remain at a constant value. The maximum specific production reached in this gene tum-on experiment was significantly lower than those found in the previous turn- off and batch fermentations. This indicated that the old cells, those formed before temperature switch, could not be effectively turned on. There would be no production of recombinant proteins from old cells even after the temperature- switch. This is mainly because that the p-galactosidase production is growth- associated. Therefore, there would be no production if there is no new cell growth. Also, the repressors in old cells had been synthesized before temperature-switch and would be retained for some time and perhaps even passed onto new (daughter) cells. This may explain why the specific production was so low comparing to growth at 25 °C throughout. No immediate full turn-on of gene expression right after temperature change from 30 °C to 24 °C was found. Therefore, there exists a lag time for gene expression in tum-on action during the transition period. This delay in response may be resulted from two sources. One is the oversynthesized repressors from the old cells may be passed to the new cells. Therefore, partial gene expression would occur in the new cells, since the level of gene expression is dependent on the amount of repressors. However, the passed repressors would be gradually diluted generation by generation. That probably take about 28.8 hours before the full expression is proceeded. The other possibility is that some precursors for the production of repressors may also pass onto new cells. Therefore, the first few generations of new cells after temperature-switch may retain partial ability to synthesize the repressor. To further examine the cell response to temperature switch and to eliminate the old cells effects discussed before, the specific change of p-galactosidase was plotted and shown in Figure 4.4. The specific changes, Ap- gal/AX, were calculated from every two adjacent data points from the entire period of repeated batch fermentations. As shown in Figure 4.4, asymptotes can be found after temperature switch for both turn-off and tum-on experiments. The large noise in these plots were caused by the irregular addition of glucose in the experiments and the approximation method used in calculating the specific change in P-galactosidase production. 135 (a)

■O cell (g/L)A glucose (g/L) v B-gal (g/L)*5 o o 6 . O Specific production *5 ► Fraction w o o o o

o o 4 03 r* oa) ^ — I 0 w o * j CO 0 0 c 01 o wo a o o.o 50.0 100.0 L50.0 T i m e (h.r)

(b)

0 0 o M n 3 d s> ^ vO m N hD

o 0.0 50.0 100.0 150.0 T i m e (U r )

Figure 4.2: Dynamic responses of P-galactosidase production to temperature switch from 24 °C to 30 °C in a repeated batch fermentation - (a) time course data (b) temperature switch Figure 4.2. Continuous 4.2. Figure B B — galactosidase (g/L)

0.0 0.2 0.4 0.6 o.a . 10 . 30 . 5. 4.0 3.0 2.0 1.0 0.0 Fed fermentation —batch ih eprtr switch temperature with rm 4 t 3 C 30 to C 24 from (c) specific production specific (c) e l (g/L))Cell 137 (a)

□ cell (g/L) A glucose (g/L) ^ B —gal (g/L)*5 o • ^ ^ mt- > Fraction (0 O Specific production. *5 o d

4 a 0) / o w

o a yia^ i i iia a ■ i r t v ' o* 0.0 50.0 100.0 150.0 T i m e (h.r)

(b)

£ 1,1 £"j :i b

wo o.o 5 0 . 0 1 0 0 . 0 1 5 0 . 0 Time ( h.r)

Figure 4.3: Dynamic responses of P-galactosidase production to temperature switch from 30 °C to 24 °C in a repeated batch fermentation - (a) time course data (b) temperature switch Figure 4.3. Continuous 4.3. Figure B B — galactosidase (g/L)

o.o 0.2 0.4 0.6 o.a o 0.0 Fed.—batch, fermentation ih eprtr switch temperature with 0 (c) specific production specific (c) Cell (g/L)) 2.0 3.0 4.0 K 5. 139

(a) O N Fed — batch fermentation O with, temperature switch from 24 C to 30

o o’

0 c1 i 0.0 50.0 100.0 150.0 T i m e ( h r )

(b)

Fed —batch fermentation with temperature switch

1 0.0 50.0 100.0 150.0 T i m e ( h r )

Figure 4.4 dynamic changes in the specific production of -galactosidase. -(a) turn off (b) tum-on 140 Continuous Fermentations

(1) Tum-0£f Action The dynamic responses of gene expression to turn-off action in continuous fermentations with 0.133 hr* and 0.1 hr"! dilution rates are shown in Figure 4.5 and Figure 4.6, respectively. In these fermentations, the temperature was at 24 °C initially and was changed to 30 °C after reaching steady state. Based on the observed specific production, the reactor response times for reaching 63.2% of complete gene turn-off at dilution rate 0.133 and 0.1 hr_l were 42 hr and 26 hr, respectively. The reactor response time in the turn-off action was longer at the higher dilution rate.

(D Turn-On Action The dynamic response of gene expression to tum-on action in continuous fermentations with 0.1 hr"l and 0.05 hr-* dilution rates are shown in Figure 4.7 and Figure 4.8, respectively. The temperature was changed from 30 °C to 24 °C after reaching steady state. Based on the observed specific production, the reactor response times for reaching 63.2% of complete gene tum-on at dilution rate 0.1 and 0.05 hr"l were about 47 hr and 29 hr, respectively. The reactor response time in the tum-on action was also longer at the higher dilution rate.

(3) Turn-Off Then Turn-On As also shown in Figure 4.5, when the fermentation temperature was first changed from 24 °C to 30 °C and then switched back to 24 °C, the gene expression was turned off and then turn on, following the temperature switches, However, as can be seen this figure, the specific production decreased slowly 141

o I ■ 1 1 I ■ 1' rH 1 1 1 I o Continuous Fermentation (D = 0.133 1 / h r) O d □ cell (g/L) a glucose (g/L) 7 B —gal (g/L)*5 w

O Specific production '* 5 Fraction

o C3 £ ocd 0 CO O

o o 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 T i m e (h.r)

Continuous Fermentation (D 0.133 1/ hr)

a no

o Cl 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 T im e < h.r )

Figure 4.5: Dynamic responses of the recombinant yeast to temperature-switch between 24 °C and 30 °C in continuous fermentation at 0.133 hr'l dilution rate. iue . Dnmc epne o h rcmiat es t tmeaue switch temperature to yeast recombinant the of responses Dynamic 4.6 Figure

Temperature (C) Scale 20.0 25.0 30.0 35.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 . 2. 4. 6. 8. 100.0 80.0120.0 140.0 60.0 160.0 180.0 40.0 20.0 0.0 . 2. 4. 6. 8. LOO.O 80.0 60.0 40.0120.0 110.0 20.0 1GO." 0.0 IHO.O Q el gLA lc-- gL Bgl (g/L)*5 B-gal gluco-=- (g/L) (g/L)A■Q v cell ■ - ■ I ' ' I ■ ■ ' I ■ 1 ' I ■ ■ I ■ 1 ' '"T I ' 1 I ' ' ' ' " otnos emnain (D Fermentation Continuous pcfc rdcin 5 Fraction > *5 production Specific rm 4 C o 0 C n cniuu fretto a 01 hr-! 0.1 at fermentation continuous a in °C 30 rate. dilution to °C 24 from otnos emnain D 01 1/hr) 0.1 (D= Fermentation Continuous ) r h ( e m i T ) r (h e m i T 0 w o d (0 o 'f CO 6 o 0 9-4 N o H o *4 s; lu 0 c 6 0 142 143

o O co □ cell (g/L) a glucose (g/L) v B —gal (g/L)*5 OJ o O Specific production "5 o Fraction. o o o o o 4 a a ycd 0 CO 0 o ua N Cl.

o o • O 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 T i m e ( h r )

o d co Continuous Fermentation (D 0.1 1/Ur)

O 6 CO

o d

o cw 0.0 20.0 40.0 60.0 80.0 100.0 120.0140.0 160.0180,0 T i m e ( h r )

Figure 4.7: Dynamic responses of the recombinant yeast to temperature switch from 30 °C to 24 °C in a continuous fermentation at 0.1 hr"! dilution rate. 144

o o • ■ ■ ~ i - ■ ■ i ■ . ■ i ■ ■ ■ | ■ ■ ■ | i ■ i i— ■ ■11 j » ' ■ i ' "■ ■ f Continuous Fermentation (D = 0.05 1/hr) o O 6 O cell (g/L) a glucose (g/L) 7 B —gal (g/L)*5 W O Specific production *5 ,> Fraction ao

ao ao

□ □ — a — sm s -b -h OJo

iy=S--r^~ i

0.0 20.0 40.0 60.0 00.0 100.0 120.0 140.0 160.0 180.0 T i m e (H r)

Continuous Fermentation (D

O 6a

a a\xi

o 0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 T i m e (lir )

Figure 4.8: Dynamic responses of the recombinant yeast to temperature switch from 30 °C to 24 °C in a continuous fermentation at 0.05 hr'l dilution rate. 145 following turn-off action, but it came back quickly when the temperature was switched back to 24 °C. This indicates that the partially turn-off culture could be quickly recovered by temperature switch.

Mathematical Model

The cell concentration in the continuous fermentation remained almost unchanged by the temperature switch. Therefore, the concentration of (3- galactosidase in these continuous fermentations can be used to determine the cell response time to the temperature change. For this purpose, only transient data are required. A model needs to be developed before the cell (or gene) response can be evaluated. Since the reactor was a CSTR, the glucose in the feed would be converted to the product P immediately in the reactor. The yield would be dependent on the reactor temperature or gene expression level. Also, as always discussed in the repeated batch experiments, only the new growth would be contributing to the production. Therefore, one can imagine that the reactor was operated with a feed containing Pq at a concentration depending on the temperature or gene expression level. A step change in the reactor temperature thus would cause changes in Po to the reactor. The change in Po would be dependent on the cell response in gene expression. The whole process can be represented by the following block diagram (Figure 4.9). The dynamic change (process response) in the recombinant protein concentration (P 2) is dependent on the reactor dilution rate and the gene expression level, which depends on the cell response to the reactor temperature. 146

o o

Cell Response Reactor Response

-0s P,(s) i P,(s) T(s_)_^ Pmax - Pmin V s\ e \ ...... - ) - ...... ; T -T x ^ s + 1 x 2 s + 1 > 2 1 Figure 4.9 Diagram of transfer function for the dynamic response of the change of recombinant protein concentration to temperature switch

Where: {T2-Tx) T(s) = P - P G0(s)= max mm T2-T, e~°s G,(s) = r,5 + l

G2(j)= 1 t2+ 1 1 = — 2 D R. T.= 9+ r, 147 There are three transfer functions in the above block diagram. The constant transfer function (Go(s)) is used to translate from a transform, T(s), of a step change of temperature of magnitude (T 2 - Tj) to the transform, Po(s), of a step change of recombinant protein concentr ation of magnitude (Pmax -Pmin)- Tj is the temperature before temperature switch. T 2 is the temperature after temperature switch. Pmax and Pmin 316 the maximum and minimum values of the recombinant protein concentrations found at steady state. The transfer function Gi(s) corresponds to the cell response in its gene expression to the temperature change. A first-order plus dead time model is assumed. 0 is the time delay and xj is the time constant for this transfer function. Pl(s) is the transform of response by gene expression. The cell response time (R.T.) for reaching 63.2% of complete gene turn-off or tum-on is equal to 0 + xi R.T. can be used as a reference of the quickness of gene response to temperature change.

The transfer function G 2(s) corresponds to the reactor response to a change in the feed concentration. From a simple mass balance, this reactor response should follow a first order model with a time constant, X 2, equal to the inverse of the dilution rate. P 2(s) is a transform of the reactor response of the protein concentration. The overall transfer function for cell response, G(s), obtained by multiplying G q(s) and Gi(s) is given below.

G\s) = G0(s)*G,(s) and G (s) = T(s) 148

The overall transfer function for process response, G"(s), obtained by multiplying G q( s), G i ( s) and G 2(s) is given below.

G'(s) = G0(s)*G 1(s)*G 2(s) and i£) G' (s) = Px T(s) The responses of tum-on or tum-off action to a step temperature change thus can be easily obtained from the inverse of above overall transfer functions.

For Tum-on Action:

f 0-«n 1- e r' + *u(t-0) + Pmin v J - -

r f U-e) \ ( A (0 = 0^ - ^ ) * 1------* e r‘ + 1------* Q r 2 *u(t-0) + Pmin ( *i - r2) U - r2)

For Tum-off Action:

P\(*) = P«m -(Pm* ~ Pmin ) * 1- e r‘ + *u(i - 6)

r f (,-0) \ (,-0) \ r\ i Px(t) = PM-(P„*-Pn*)* 1- + 2 * e * 2) ( T\ - *2 ) 149 These equations can be used to simulate the cell response (in the gene expression level) to and the reactor output (in the P-galactosidase concentration) resulting from a step change in the reactor temperature.

(T) Parameter Estimation The dynamic changes of p-galactosidase concentration in the continuous reactor due to temperature switch from 24 °C to 30 °C in the continuous fermentations at 0.133 hr"! and 0.1 hr" 1 dilution rates are shown in Figures 4.10.a and 4. lO.b. The dynamic changes of p-galactosidase concentration in the reactor due to temperature switch from 30 °C to 24 °C in the continuous fermentations at 0.1 hr'l and 0.05 hrldilution rates are shown in Figures 4.11.a and 4.11.b. These transient data were used to estimate the parameter values in the proposed model. Table 4.1 lists the best values found for the parameters in the proposed model. The optimized values for time delay, 9, and q were obtained from curve fitting. %2 was obtained from the inverse of the dilution rate. Pmax or Pmin > maximum or minimum of recombinant protein concentration, were found from the steady state data shown in the previous figures from the same experiments. As also shown in these figures, the model predictions simulate the data very well. Figures 4.12.a and 4.12.b show the effect of the dilution rate on gene responses to the tum- off and tum-on actions. For both tum-on and tum-off actions, the gene response was slower at a higher dilution rate. Also, at the same dilution rate (0.1 hr* ), the gene response to tum-on action was much slower than to tum-off action. As shown in Table 4.1, the gene response time was 11 hours for tum-off action but 30 hours for tum-on action at the same 0.1 hr_l dilution rate. This indicates that the already formed responses would remain in the cells and be passed onto daughter cells for many generations before the repressor effects diminished. 150 (a) O

CO Continuous Fermentation o 0.133 1/hr)

o O. 15. 30. 45. 60. 75. T i m e (h.r)

(b) O

CO Continuous Fermentation o 0.1 1/hr) co o

o O. 15. 30. 45. 60. T i m e ( h.r )

Figure 4.10: Dynamic responses of the concentration of p-galactosidase in the continuous reactor to temperature switch from 24 °C to 30 °C, (a) at 0.133 hr"l and (b) at 0.1 hr -1 at dilution rate. Symbols show the data, and curves show model predictions 151 (a)

00 Continuous Fermentation o (D 0.1 1/hr)

\ <0 SO o

PQ w o

o o o 15 30. 60. r 5 . T i m e * r) (b)

Con.tirxu.ous Fermentation CO o (D 0.05 1/hr)

\fcD Q CO « * O N o o o O. 15 30. 45. 60. T 5 . T i m e ( h r )

Figure 4.11: Dynamic responses of the concentration of P-galactosidase in the continuous reactor to temperature switch from 30 °C to 24 °C, (a) at 0.1 hr'l and (b) at 0.05 hr'l dilution rate. Symbols show the data, and curves show model predictions Figure 4.12: Effects of the dilution rate on gene response to (a) tum-off action and action tum-off (a) to generesponse on rate dilution the of Effects 4.12:Figure (a)

B — gal (g/L )

o.o 0.2 0.4 o.e o.a l.o B — gal ( g / L ) O. o W o * o © O «0 O H (b) tum-on action. (b)tum-on 0. otnos Fermentation Continuous 15. otnos Fermentation Continuous 30. me' ) r h ( ' e im T 30. hr) r (h e m i T . 1 0.1/hr .5 1/hr 0.05 4-5. .3 1/hr 0.133 . 1/hr 0.1 60. 60. 5 152 153 Conclusions and Recommendations

The dynamic responses of gene expression of a recombinant yeast strain containing temperature-sensitive promoter to temperature switch during fermentation were investigated in batch, repeated batch and continuous fermentations in the selective medium. It was found that the gene expression was sensitive to the temperature and could be turned on or off by temperature switch. However, there was always a time delay for cells to respond to the change. In the batch fermentation, the fermentation time was too short to allow complete gene tum-on. From the repeated batch fermentations, it was found that temperature switch was effective only to the new growth because the production of the recombinant protein was growth-^jociated. This implies that the two-stage fermentation with temperature switch may not be effective in improving the production if batch or fed-batch fermentation is employed. In continuous fermentations, the larger the dilution rate was, the longer the reactor and gene response times to gene tum-on or tum-off are. The proposed kinetic model, including the first order plus dead time model for gene response and the first order model for the effect of dilution rate, simulates the experimental data very well. For a two-stage continuous process, the restrictive temperature, 30 °C, is usually used in the first stage to obtain high plasinid stability due to low expression, high specific growth rate, and high cell mass. In the second stage, the permissive temperature, 24 °C, is then used to turn on the gene expression. The plasmid stability and specific growth rate become lower in the second stage. In our case, the low dilution rate may be chosen for the application of a two-stage process because of short reactor and gene response time. However, the cell response time is so long that it may impose severe limitation on the use of a two- 154 stage fermentation process, which separates growth phase and production phase by controlling the reactor temperature. Since a partially turned off expression system could be quickly turned on by temperature switch, it is feasible to apply cyclic oscillation of temperature to improve the plasmid stability and maintain high specific production. A combination of temperature and dilution rate change may be necessary to achieve slow turn-off and quick turn-on. The effect of cyclic oscillation in temperature on recombinant yeast with a rich medium in glucose-stat has been tried. The theoretical background and the experimental results are shown in the appendix. Table 4.1 Estimated values for parameters in the proposed model

Temperature switch D(hr-l) 0 (hr) xi (hr) R.T. (hr) x2 (hr) From 24 °C to 30 °C 0.133 14.0 20.0 34.0 7.52

From 24 °C to 30 °C 0.1 6.0 5.0 11.0 10

From 30 °C to 24 °C 0.1 13.0 17.0 30.0 10

From 30 °C to 24 °C 0.05 4.0 5.0 9.0 20

Temperature switch D (hr-1) Pmin (g/L) Pmax (g/L) From 24 °C to 30 °C 0.133 0.0188 0.711 From 24 °C to 30 °C 0.1 0.0188 0.748 From 30 OC to 24 °C 0.1 0.02 0.71 From 30 °C to 24 0.05 0.07358 0.76358 156 Notations:

Ti: temperature before temperature switch (°C) T2: temperature after temperature switch (°C) Pmax : maximum protein concentration (g/L) Pm in : minimum protein concentration (g/L) T(s): step change of temperature in s domain Go(s): constant transfer function between T(s) and Po (s) Po(s): step change of protein concentration in s domain Gi(s) : transfer function of first order plus dead time model for the response of gene expression in cells due to tum-on or turn-off action Pi (s): output protein concentration from the cell in s domain

G2(s) : transfer function of first order model for the reactor response to a step change in Pi P2 (s) : output protein concentration from the reactor in s domain xi : time constant in Gi(s) (hr)

%2 : time constant in G 2(s) (hr) 0 : dead time for gene expression (hr) D : dilution rate (1/hr) R.T. : gene response time for reaching 63.2% of complete gene tum-on or turn off (hr) 157 References

Acker, G. K., Johnson, A. D., Shea, M. A., Quantitative model for gene regulation by X phage repressor, Proc. Natl. Acad. Sci. USA, 79, 1129, 1982.

Park, S. H., Ph.D. Thesis, University of California at Davis, 1988.

Ryu, D. D. Y. and Siegel, R., Scale-up of fermentation processes using recombinant microorganisms, Ann. Acad. Sci., 469, 73, 1986.

Ryu, D. D. Y., Kim, J. Y., Lee, S. B., Bioprocess Kinetics and Modeling of Recombinant Fermentation" m the book, Biotechnology, Rehm, H. J., Reed, G., Puhler, A. and Stadicr, P., 2e<^, 486, 1991.

Parada, G., Acevedo, F., On the Relation of Temperature and RNA Content to the Specific Growth Rate in Saccharomyces cerevisiae, Biotechnol. Bioeng., 25, 2785, 1983.

Siegel, R. and Ryu, D. D. Y., Kinetic study of instability of recombinant plasmid pPLc23trpAI in E. coli using two stage continuous culture system, Biotechnol. Bioeng., 27, 28, 1985.

Weber, A.E. and San K. Y., Bioprocess Engineering Colloquium, ASME Winter Annual Meeting, Boston, MA, p. 75-78, Dean, R. C., Jr. and Nerem, R. M. (Eds), 1987.

Weber, A. E. and San K. Y., Enhanced plasmid maintenance in a CSTR upon square-wave oscillations in the dilution rate, Biotechnol. Lett., 8 , 531, 1988. CHAPTER V EFFECTS OF OSCILLATING GLUCOSE CONCENTRATION ON PLASMID STABILITY AND RECOMBINANT PROTEIN PRODUCTION IN REPEATED BATCH FERMENTATIONS

Abstract

A repeated batch fermentation strategy using low-cost media to achieve high plasmid stability and high cell w^nsity was developed for a recombinant yeast fermentation. The recombinant protein product was produced in an auxotrophic yeast initially growing in a selective medium, followed by pulse additions of nutrient to extend the fermnetation and production. The selective medium, which favors the growth of plasmid-carrying cells, was used to initiate the fermentation to achieve the initial maintenance of plasmid stability. In subsequent fermentation, pulse additions of new media were conducted to restore the glucose concentration from 0 g/1 to 1 g/1. This media addition method reduced the plasmid loss significantly. The experimental results for the repeated batch fermentation using the selective medium for batch growth and then followed with pulse additions of the nonselective or low-cost rich medium showed that this fermentation method was able to enhance the plasmid stability and increased the cell yield, product yield and specific production, as compared to the conventional batch fermentation.

1 5 8 159 Introduction

The bakers' yeast, Saccharomvces cerevisiae. is an attractive host for the production of recombinant proteins. It has no known pathogenic relationship with man. It lacks endotoxin and lytic viruses, and is generally recognized as safe. Saccharomvces cerevisiae has been used industrially for centuries in the baking and brewing industries, and the efficient large-scale propagation of this yeast to high cell densities has therefore been well developed. Fed-batch culture is an efficient technique to grow recombinant cells to high cell density and to attain high productivity of recombinant gene product and metabolites. One problem for recombinant yeast fermentations is the loss of plasmid from host cells during the course of . ;rmentation. Since the plasmid-free cells are more competitive than the plasmid-carrying cells, they tend to outgrow plasmid- carrying cells quickly and dominate the fermentation within several generation times. Consequently, total production of the recombinant protein product is dramatically reduced, and significant amounts of substrate utilized by non production plasmid-free cells are wasted. The factors known to affect plasmid stability include the genetic make-up of a plasmid(Seo and Bailey, 1985), physiology of host cells and environmental conditions such as temperature (Parada and Acevedo, 1983), medium formulation (Jones, et al.. 1980, Noach, et al., 1981 and Sterkenburg, et al., 1984) and dissolved oxygen (Caunt, et al., 1989, Lee and Hassan, 1988 and Hopkins, et al., 1987). One common way to solve the problem of plasmid instability of a recombinant auxotrophic yeast is to introduce a selective pressure to the system by using a growth medium lacking in a specific metabolite, which is essential to the growth of the auxotrophic cells (Walmsley, et al., 1983). However, several researchers have found that the use of a selective (nutrient deficient) medium for growing recombinant auxotrophic yeasts might not be effective in avoiding plasmid instability problems. A significant fraction of the cell population was found to be plasmid-free cells in many recombinant auxotrophs cultivated in selective media. (Walmsley, et al., 1983, Lauffenburger, 1987, Satyagal and Agrawal, 1989, Murray and Szostak, 1983, DiBasic and Sardonini, 1986 and Sardonini and DiBiasio, 1987). Several hypothesis have been proposed to account for the appearance of plasmid-free cells under the selective environment. The plasmid-encoded enzyme might be passed from the plasmid-carrying mother cells to plasmid-free daughter cells and thus help the survival of plasmid-free cells (Lauffenburger, 1987 and Satyagal and Agrawal, 1989). Similarly, the metabolite synthesized from the plasmid-cany .-ig mother cells might be passed onto the plasmid-free daughter cells (Satyagal and Agrawal, 1989). In addition, the essential metabolite might be secreted from plasmid-carrying cells to the medium to support the growth of plasmid-free cells (Dibiasio and Sardonini, 1986 and Sardonini and Dibiasio, 1987). Also, the essential metabolite might be from plasmid-carrying cells upon their death and lysis (Mason, 1991 and mason, 1987). However, no direct proof of any of these hypothesis can be found due to the difficulty in detecting the metabolite at trace levels. Another way to remedy the plasmid instability problem is to make use of the difference between plasmid-carrying and plasmid-free cells in their ability to respond to environmental changes. Plasmid-carrying cells with extra metabolic burden are slower to respond to environmental changes than plasmid-free cells. In other words, plasmid-carrying cells could be insensitive to the environmental change, and this would work to their advantage under oscillating conditions. It has been shown that plasmid stability could be maintained without the use of a I

161 selective pressure when cells were grown in an oscillating environment. The fluctuation or oscillation in fermentation conditions, such as growth rate (Impoolsup, et al., 1989a, Impoolsup, et al., 1989b), dilution rate (Weber and San, 1987 and Weber and San, 1988), dissolved oxygen level (Cault, et al., 1989), and substrate concentration (Stephens and Lyberatos, 1988) all have been shown to have significant effects on culture behaviors, productivity and plasmid stability. With proper cyclic oscillation in growth conditions, the net growth rate difference between plasmid-containing cells and plasmid-fiee cells can be reduced or even reversed to result in plasmid stabilization. In this study, a novel fermentation strategy by using the combination of a selective pressure and oscillation of glucose level was studied to its effects in reducing the plasmid loss and ^.creasing the specific production of the recombinant P-galactosidase. The plasmid stability in flask, batch and continuous cultures were studied with a selective medium to check if the selective medium was effective in preventing plasmid loss during fermentation. The growth in a nonselective medium or rich medium was then studied to examine the kinetic behavior of plasmid loss under nonselective environmental conditions. Repeated batch fermentation, batch fermentation followed by pulse additions of new media, were then studied. The glucose level during the process was maintained between 0 g/L and 1 g/L to avoid the Crabtree effect (Crabtree ,1929).

Materials and Methods

Yeast and Plasmid The yeast and plasmid used in this study have been described in detail in chapter 3. 162

Growth Media The selective and nonselective media used in this study were identical to those described in chapter 3. The compositions of the rich medium were 0.4% yeast extract, 0.4% glucose, and 0.0675% casamino acid.

Fermentations All fermentations were carried out in 5-L fermentors, which have been described in detail in chapter 3. The procedures for batch fermentations also have been described in chapter 3. Batch fermentations were carried out with the selective, nonselective and rich media at 25 °C, pH 5.5. The plasmid instability un^er the selective pressure in the selective medium was studied in a continuous fermentation. The procedures for the preparation of the selective medium in the fermentor was the same as those used in the batch fermentation. The fermentation was initiated as a batch culture and a continuous feed was turned on after 20 hours. The dilution rate was set at 0.1 hr*. For the repeated batch fermentations, the initial glucose concentration was 4 g/L. A concentrated glucose solution (60 g/L) with corresponding nutrients was then added to the medium when glucose concentration was close to 0 g/L and the glucose level was brought back to 1 g/L. For each addition, only 50 ml concentrated medium were added. Thus, the liquid volume in the fermentation was not affected significantly by the medium addition. The medium addition was repeated for four times. Four different combinations in the media were used in these repeated batch fermentations. These were selective medium followed by selective medium, nonselective medium followed by nonselective medium, 163 selective medium followed by nonselective medium and selective medium followed by rich medium.

Analytical Methods All sample analyses followed the same procedures described in chapter 3.

Results and Discussion

In this section, plasmid stabilities in continuous, batch and repeated batch fermentations are presented separately. All experimental results concerning the plasmid stability are then compared and summarized in Table 5.1. Then, the cell dry weight, P-galactosidase producuon, specific production of P-galactosidase, cell yield and product yield from various fermentation conditions are compared and summarized in Table 5.2.

Continuous Fermentation The ineffectiveness of the selective pressure for the recombinant auxotrophic yeast was illustrated in the chemostat experiment with the selective medium. As shown in Figure 5.1, the fraction of plasmid-carrying cells dropped from 93% to 62% after 75 hours of fermentation. The possible causes for the appearance of plasmid-free cells under the selective pressure has already been discussed in the introduction and in chapter 3. Figure 5.1: Continuous fermentation with the nonselective medium at 25 at medium nonselective the with fermentation Continuous 5.1:Figure Concentration (g/1)

2. 4. 6. a. 1 0 . 0 Beta —gal (*50) ^ a

r~K / /P/Cf / 20 / . D- ie (h.r)Time otnos Fermentation Continuous eetv Medium Selective Glucose 40. 60. Fraction. 165 Batch Fermentation The kinetics of batch fermentations with three different media are shown in Figure 5.2. The kinetics of plasmid instability in batch fermentations would be different from that in the continuous fermentation. There are five different phases during a batch fermentation- lag phase, initial log phase, middle log phase, late log phase and stationary phase. The fraction of plasmid-carrying cells in the batch fermentation with the selective medium, shown in Figure 5.2.a, fluctuated between 110% and 80%, with an average of about 89%. This means that the plasmid can be maintained fairly well in the batch fermentation by using the selective medium, when the fermentation time is short. At the first three phases in the batch fermentation, the fraction dropped from 110% to 80%, but then rised back to 97% at the stationary phase. This come-b^k phenomena occurring during the late log phase and stationary phase might be resulted from the difference in the death rate between plasmid-free cells and plasmid-carrying cells. Apparently, the plasmid free cells died fast when the nutrient was depleted. The plasmid in auxotrophic yeasts was very unstable when the nonselective or rich medium was used. The nonselective medium, with the additional tryptophan added into the selective mediums, and the rich medium provides enough tryptophan in the medium for cell growth. Therefore, the selectivity for plasmid-carrying cells is lost. Thus, there was a significant drop from 83.5% to 60.8% in the fraction of plasmid-carrying cells in the batch fermentation with nonselective medium (Figure 5.2.b). Also, the population of plasmid-carrying cells dropped from 90% to 50% during the 37.5 hours batch fermentation with the rich medium (Figure 5.2.c). Figure 5.2: Batch recombinant yeast fermentations at 25 °C. (a) selective medium selective (a) °C. 25 at fermentations yeast recombinant Batch 5.2: Figure Concentration a N cn in <£>

20. 40. 60. 80. lOO. 120. 166 \ Concentration bfl iue52 Continuous 5.2. Figure 10 (0 Cl n . . 0 1. 20. 15. 10. 5. O. Fraction. (b) nonselective medium nonselective (b) Nonselective C 25 ie (h.r) Time el ( Cell*5 ) eagl (*10)Beta—gal 30. 35. CO O N o CO o O O o Cl o i 1 167 Fraction. 40. 35. 30. 25. Beta —gal (*10) —gal Beta . 20 (c) rich medium 25 c Medium Rich. Time Time (h-i') 15 . 10 5 Fraction Glucose O

ST OT Q 9 ’fr 3 Figure Figure 5.2. Continuous (I/'S) uonBJ^uaouoQ 169 Repeated Batch Fermentation The results from the repeated batch fermentation with the selective medium followed by adding the selective medium four times are shown in Figure 5.3. The fraction of plasmid-carrying cells remained between 100% and 80 % for the entire fermentation time of about 75.83 hours. Apparently, a good selectivity of plasmid- carrying cells was achieved in this repeated batch fermentation. The batch fermentation with the nonselective medium followed by adding the nonselective medium four times is shown in Figure 5.4. As expected, the fraction of plasmid-carrying cells during the first 27.5 hours batch fermentation dropped significantly from 95% to 65%. However, continuous addition of the nonselective medium during the repeated batch period did not result in any further serious plasmid loss. The declining rate of plasmid-loss slowed down during this late period and only 5% more drop in the fraction of plasmid-carrying cells was observed in the extended 50 hours fermentation after the initial batch fermentation. The result of having a better plasmid stability which gave a cyclic oscillation effect on the glucose concentration in the medium in this case was from the pulse addition of nutrient (glucose). Under the oscillation condition, plasmid-carrying cells with extra metabolic burden are slower to respond to changes in environmental conditions than plasmid-free cells. This may have reduced the growth rate difference between plasmid-carrying cells and plasmid-free cells, and thus allows the plasmid-carrying cells to compete well with plasmid-free cells. iue .: eetdbthfretto ih h slcie eim n followed and medium selective the with fermentation batch Repeated 5.3: Figure Concentration (g/1)

2. 4. 6. a. lO. 12. . 0 4. 0 80. 60. 40. 20. O. i - " A — A — Glucose A_ _ ^ by the addition of the selective medium at 25 °C. at 25 medium selective the of addition the by e b th Fretto (Sel/Sel) Fed —batch. Fermentation Fraction 'A A

add ie (hi*)Time d add add Beta —gal ) 5 * ( l l e C add * ( 1Q1

20. 40. 60. 80. lOO. 120. 170 iue .: eetd ac fretto wt te oslcie eim and medium nonselective the with fermentation batch Repeated 5.4: Figure Concentration, (g/1) 6 2 . 4. 6. a. 10 . 12. O. \ \ ; e b th Fretto (Nonsel/Nonsel) Fed —batch. Fermentation ucose s o c lu G Fraction followed by the addition of °C. at 25 of medium nonselective the addition the by followed 0 40. 20. v K d add add ie (h.r)Time add add . 0 6 80. N o CD O o o O 03 o 171

Fraction (%) Figure 5.5 shows the results from the batch fermentation with the selective medium followed by the addition of the selective medium. A similar effect on plasmid stability due to glucose oscillation was found in this experiment. The plasmid stability initially was maintained by using the selective medium. However, the repeated additions of the nonselective medium did not cause any significant decrease in the fraction of plasmid-carrying cells. For the entire 76.42 hours fermentation, the fraction of plasmid-carrying cells only changed from 100% to 90%. Similar results were found with the batch fermentation with the selective medium followed by adding a low-cost rich medium (Figure 5.6). Only 15% drop in the fraction of plasmid-carrying cells, from 100% to 85%, was found for the 85 hours fermentation time. These results indicate that this repeated batch fermentation method would allow the recombinant yeast fermentation to achieve high cell density and high productivity without using an expensive, selective medium. Concentration (g/1) o' Figure 5.5: Repeated batch fermentation with the selective medium and followed and medium selective the with fermentation batch Repeated 5.5: Figure 2- 4. 6. 8. 10. 12. sbaa, rA-A-A^. . A . ^ A - A - A /r o. Glucose. e b th emnain (Sel/Nonsel) Fed Fermentation —batch Fraction by the addition of the nonselective medium at 25 °C. at25 medium nonselective the of addition the by

20 . Cell(*5) ie (h-r)Time add 40. add Beta ;*10)—gal add. 60. 80. CM o o CO o o

o’ 20. 40. 60. 80. lOO. 120. 174 175 m Comparison of Various Fermentations

The effects of various fermentation methods on the plasmid stability have been discussed and are summarized in Table 5.1. However, the effects on cell yield, product yield, and specific production of the recombinant product are •discussed below.

fa) Cell Yield As can be seen from Table 5.2, the cell yields from the repeated batch fermentations were generally higher than that from corresponding batch fermentations. For examples, the cell yield from the repeated batch fermentation were 1.087 and 1.252 times of those from batch fermentations with the selective and nonselective media, respectively. The metabolism may be changed due to the glucose oscillation. As a result, the yeast may utilize glucose more efficiently and convert more glucose to the cell biomass instead of carbon dioxide.

fb) Product Yield In general, the repeated batch fermentations also gave higher product yields. For example, with the selective medium, the product yield was 1.38 times higher than that from the batch fermentation. However, for the case without the selective pressure, the product yield for the repeated batch fermentation was slightly lower than that in the batch fermentation. A lower product yield from the repeated batch fermentation was because that the fermentation was carried with a low fraction of plasmid-carrying cells for an extension period of time. If the same amount of glucose were to be fermented, the repeated batch should give a much higher yield than the batch fermentation. 176 (c) Specific Production Similarly, with the selective medium, the specific production from the repeated batch fermentation was 1.273 times higher than that from the batch fermentation. With the nonselective medium, the specific production in the repeated batch fermentation was even lower than that in the batch fermentation. The reason for this has been discussed before. However, higher cell yield, product yield and specific production were found for the other two repeated batches with additions of nonselective or a rich medium. The effects of the selective pressure in the first stage for batch growth and then the pulse addition of nutrient concentration for repeated batch growth on the recombinant yeast fermentation kinetics are thus significant. A significant improvement in me specific production was found when the selective pressure was applied initially. It seems that in the following period to the selective pressure is no longer important and an inexpensive, nonselective (rich) medium may be used to give high productivity. The repeated batch fermentation thus would open a new door for the development of high cell density recombinant yeast fermentations to produce high-value protein products from low-cost media.

Conclusions and Recommendation

As improved fermentation method for the production of a recombinant product in auxotrophic yeast was demonstrated. This method involves the use of a selective medium to initiate the fermentation then followed by pulse additions of a nonselective (rich) medium for extended fermentation period. The initial selective pressure and oscillation in glucose concentration between 0 g/L and 1 g/L were effective in maintaining plasmid stability and resulted in high productivity. The repeated batch fermentation by using the selective medium for batch growth and then followed with the pulse addition of a nonselective or low-cost rich medium should also be able to enhance the plasmid stability, cell yield, product yield and specific production of the recombinant protein in high cell density fermentations. However, an automatic medium addition method should be developed to control the glucose concentration within a proper range. Thus an on line glucose analyzer seems to be important. However, an alternative system based on an on-line measurement of the cell density has been developed and can be used for this purpose. This computer-controlled system is described in Appendix B. 173 Table 5.1. Comparison of plasmid stability in various fermentations

Fermentation Total Ferm. Fraction of Plasmid- Fraction Drop Time(hr) Carrying Cells Flask Selective 160.0 fluctuate between 71.6% and 95.9% Continuous Selective 75 drop from 93% to 70% 23.0% Batch Selective 33 fluctuate between 110.0% and 80.0% Nonselective 29 drop from 83.5% to 22.7% 60.8% Rich 37.5 drop from 90.0% to 40.0% 50.0% Repeated Batch Sel/Sel 75.83 Oscillate between 100% and 85% Nonsel/ 76.42 drop from 90.0% to 30.0% Nonsel 60.0% Sel/Nonsel 71.33 drop from 98.0% to 8 .0% 90.0% S el/Rich 83 drop from 98.0% to 13.0% 85.0% 179 Table 5.2. Comparison of cell dry weight, P-galactosidase production and specific production of P-galactosidase from various fermentations

Fermentation CDW(g/L) P(g/L) SP YX/S Yp/S Batch Selective (1) 0.928 0.264 0.284 0.232 0.066 (2) 0.860 0.379 0.441 0.215 0.095 Nonselective (1) 0.881 0.359 0.376 0.220 0.090 (2) 0.894 0.358 0.381 0.232 0.090 Rich (1) 1.924 0.674 0.350 0.481 0.169 (2) 1.865 0.684 0.367 0.466 0.171 Repeated Batch Sel/Sel (1) 2.150 1.041 0.484 0.269 0.130 (2) 2.004 1.077 0.537 0.251 0.135 Nonsel/Nonsel (1) 2.239 0.664 0.296 0.280 0.083 (2) 2.239 0.664 0.296 0.280 0.083 Sel/Nonsel (1) 2.132 0.978 0.459 0.266 0.123 (2) 2.132 's 978 0.459 0.266 0.123 S el/Rich (1) 2.552 i.207 0.473 0.319 0.151 (2) 2.552 1.207 0.473 0.319 0.151

Notation: (1) Last data point in each fermentation (2) Highest specific production in each fermentation CDW Cell dry weight (g/L) P Concentration of P-galactosidase (g/L) SP Specific production (g of p-galactosidase/g of CDW) Yx/S Cell yield (g of CDW/g of glucose) Yp/S Product yield (g of P-galactosidase/g of glucose) 180 References

Cault, P., Impoolsup, A. and Greenfield, P. F., The effect of oxygen limitation of stability of a recombinant plasmid in Saccharomvces cerevisiae. Biotechnol. Lett., 11, 5, 1989.

Crabtree, H. G., Observations on the carbohydrate metabolism of tumors, Biochem. J., 23, 536, 1929.

DiBiasio, D. and Sardonini, C., Stability of continuous culture with recombinant organisms, Ann. NY. Acad. Sci., 469, 111, 1986.

Hopkin, D. J., Betenbaugh, M. J., Dhurjati, P., Effects of dissolved oxygen shock on the stability of recombinant E. coli containing plasmid pKN401, Biotechnol. Bioeng., 29, 85, 1987.

Impoolsup, Caunt, P. and Greenfield. P. F., Stabilization of a recombinant yeast plasmid in nonselective mediu . by cyclic growth rate changes, Biotechnol. Lett., 9, 605, 1989a.

Jones, I. M., Primrose, S. B., Robison, A. and Ellwood, D. C., Maintenance of some colEl-type plasmids in chemostat culture, Mol. Gen. Gener., 180, 579, 1980.

Lauffenburger, D. A., Bacterioncin production as a method of maintaining plasmid-bearing cells in continuous culture, Bibtech., 5, 87, 1987.

Murray, A. W. and Szostak, J. W., Pedigree analysis of plasmid segregation in yeast, Cell, 34, 961, 1983.

Mason, C. A., Physiological aspects of growth and recombinant DNA stability in Saccharomvces cerevisiae. Antoine van Leeuwenhoek, 59, 269, 1991. 181

Mason, C. A. and Hamer, G., Cryptic growth in Klebsiella phneumoniae. Appl. Microbiol. Biotechnol., 25, 577, 1987.

Noach, D., Roth, M., Geuther, R., Muller, G., Undisz, K., Hof&neier, C. and Gaspar, S., Maintenance and genetic stability of vector plasmids pBR322 and pBR325 in E. coli K12 in a chemostat, Mol. Gen. Genet., 184, 121, 1981.

Parada, G. and Acevedo, F., On the relation of temperature and RNA content to the specific growth rate in Saccharomvces cerevisiae, Biotechnol. Bioeng., 25, 2785, 1983.

Sardonini, C. A. and DiBiasio, D., A model for growth of Saccharomvces cerevisiae containing a recombinant plasmid in selective medium, Biotechnol. Bioeng., 29, 469, 1987.

Satyagal, 5. N. and Agrawal, P., O n f1 ■* effectiveness of selection pressure through use of a complementing product, Biotechnol. Bioeng., 34, 273, 1989.

Seo, J. H. and Bailey, J. E., Effects of recombaint plasmid content on growth properties and cloned gene product formation in E. coli, Biotechnol. Bioeng., 27, 1668, 1985.

Stephens, M. L. and Lyberatos, G., Effect of cycling on the stability of plasmid- bearing microorganisms in continuous culture, Biotechnol. Bioeng., 31, 464, 1988.

Sterkenburg, A., Prozee, G. A. P., Leegwater, P. A J. and Wouters, J. T. M>, Expression and loss of pBR322 plasmid in Klebsiella aerogenes NCTC 418 grown in chemostat culture, Antonie van Leewenhoek, 50, 397, 1984.

Walmsley, R., Gardner, D. and Oliver, S. G., Stability of a cloned gene in yeast growth in chemostat culture, Mol. Gen. Genet., 192, 361, 1983.

Weber, A.E. and San K. Y., Bioprocess Engineering Colloquium, ASME Winter Annual Meeting, Boston, MA, p. 75-78, Dean, R. C., Jr. and Nerem, R. M.(Eds), 1987. 182 Weber, A.E. and San K. Y., Enhanced plasmid maintenance in a CSTR upon square-wave oscillations in the dilution rate, Biotechnol. Lett., 8 , 531, 1988. CHAPTER VI CONCLUSION AND RECOMMENDATION

Conclusions

Engineering strategies including the employment of a selective pressure and oscillation of growth conditions to optimize plasmid stability and protein production in recombinant Saccharomvces cerevisiae fermentation were studied. The auxotrophic yeast has a temp^ dture-regulated expression system for the production of heterologous gene product, P-galactosidase, and uses tryptophan as the selective marker. The expression for P-galactosidase production is permitted at temperatures below 28 °C but restricted at temperatures above 30 °C. The effects of temperature (in the range of 22 °C to 32 °C) on batch recombinant yeast fermentations with selective and nonselective media were studied. The highest product yield of P-galactosidase was found in the selective medium at 25 °C. Almost no production was found in either selective or nonselective medium when the temperature was above 30 °C. The apparent specific growth rate of the recombinant yeast in selective and nonselective media increased with increasing the temperature in the range studied. In the nonselective medium, the plasmid-free cells grew faster than plasmid-carrying cells. Therefore, in the nonselective medium there was a significant drop in the fraction of plasmid- carrying cells present in the total cell population during batch cultivation. Also, a significant fraction of plasmid-free cells was found with cultures grown in the 183 184 selective medium. However, during the course of batch fermentation with the selective medium, the fraction of plasmid-carrying cells exhibited an interesting come-back phenomena. A kinetic model based on cell growth, P-galactosidase production and plasmid stability in batch recombinant yeast fermentations with selective and nonselective media was developed. This model simulates the experimental data very well. The dynamic responses of gene expression to temperature switch during fermentations were studied in the selective medium. The response of this recombinant yeast to gene turn-off took place slowly, but the response to gene tum-on was relatively quick. In continuous fermentations, the higher the dilution rate was, the longer the gene response time was. The long response time would impose severe limitations on the use of a two-stage fermentation process to separate growth phase and production phase by controlling the reactor temperature. Since the partially turned off gene could be quickly turned on, it would be feasible to apply cyclic oscillation of temperature to regulate the specific growth rate and to improve the plasmid stability while to maintain a high specific production. A dynamic model for simulating the dynamic changes in the concentration of the recombinant protein during the transient phase caused by a temperature switch was developed. This model can be used to estimate the cell response time for gene expression to a step change in temperature. The effects of oscillating glucose concentration on plasmid stability and specific production of the recombinant protein in repeated batch recombinant yeast fermentations were studied. Cyclic oscillation of glucose concentration by pulse additions of new media in the repeated batch fermentation was able to prevent the fraction of plasmid-carrying cells to fall over an extended fermentation period. The repeated batch fermentations with the selective medium for initial batch growth 185 and then followed with pulse additions of the nonselective or rich medium was able to maintain the plasmid stability and to increase the cell yield, product yield and the specific production of the recombinant protein.

Recommendations

1. One major problem in using a selective medium as the selective pressure for recombinant auxotrophic yeasts is that the oversynthesized tryptophan from plasmid-carrying cells may be sufficient to support the growth of plasmid-free cells. However, the trace amount of tryptophan is difficult, if possible to detect by any chemical assays. However, culture fluorescence can be easily detected and may be used as a method to measure the trace amount of tryptophan, fluorophor, on-line. This technique can be used to study the tryptophan effect on the kinetics of plasmid stability during the fermentation in the selective medium.

2. The effects of cyclic oscillation of environmental conditions such as glucose concentration, temperature and dissolved oxygen on the production of recombinant protein and cell in high density yeast fermentation need to be studied. An adaptive control method should be used in the high cell density fermentation. Some researchers (Hsieh et al., 1988 and Fieschko, et al., 1987) have studied high cell density fermentations with recombinant yeasts. However, some problems for their experiments include poor control method resulting in low cell yield, severe plasmid loss, and low product yield. The problem of low cell yield can be solved by applying an adaptive feedback control method based on direct measurement of the limiting substrate (glucose) using on-line glucose analyzers to control medium feeding and the glucose concentration in the fermentor. The plasmid instability problem can be alleviated by employing the cyclical oscillation strategy. This would allow the use of a low-cost (nonselective) medium in high cell density fermentations. However, this operation strategy remains to be tested on high cell density, fed-batch fermentation. Based on on-line glucose measurement, a direct control method to control the feeding substrate concentration in fed-batch fermentations has been developed and successfully used in recombinant E, coli fermentations. An accurate control of glucose level will avoid the Crabtree effect and allow the fermentor to reach extremely high cell densities. However, this technique has not been applied to yeast fermentation.

3. The major advantages in using glucose-stat are its ability to operate at the maximum specific growth rate steadily (as compared to the chemostat), and to wash-out the slow-growing cells (Kleman, et al., 1991). When cyclic oscillation in glucose concentration is applied to the glucose-stat, the plasmid-free cells which have a lower averaged growth rate, would be washed out from the system, while plasmid-carrying cells which have a higher averaged growth rate, would dominate in the fermentor. From the theoretical viewpoint, 100% of plasmid stability can be obtained in the glucose-stat with suitable oscillation conditions. The plasmid stability in the glucose-stat with cyclic oscillation thus would be better than those in conventional batch and fed-batch fermentations. Although a positive effect on the plasmid stability under the oscillation of glucose level between 1 g/L and 0 g/L was found in this study, the specific production was lower than that at the fixed glucose level at 1 g/L. A suitable amplitude of glucose concentration and cycling time for the cyclic oscillation of glucose level in the glucose-stat should be determined in order to further improve the plasmid stability and specific production. 4. In glucose-stat, cyclic oscillation of temperature between 24 °C, the permissive temperature, and 30 °C, the restrictive temperature, with 8 hours cycling time showed worse plasmid stability and lower specific production than the results without oscillation. However, more experiments should be carried out with better selected cycling time before a conclusion can be drawn.

5. Cyclic oscillation of dissolved oxygen level was shown to improve of plasmid stability for the recombinant yeast fermentation. However, the specific production under the oscillation was lower than that at the 80% of saturated oxygen level. A suitable amplitude of the dissolved oxygen level and cyclic time need to be determined. APPENDICES APPENDIX A EFFECT OF CYCLIC ENVIRONMENTAL CONDITIONS ON RECOMBINANT YEAST FEMENTATION

Abstract

Cyclic oscillation of environmental conditions, such as the specific growth rate and dissolved oxygen level, has been shown to have a positive effect on plasmid stability. Cyclic oscillations in the glucose concentration, temperature, and dissolved oxygen level were studL for their effects on plasmid stability in continuous recombinant yeast fermentations. A glucose-stat was used to maintain stable glucose concentration at the pre-set levels. Plasmid stabilities in the experiment at constant glucose concentration of 1 g/L and in the experiment with cyclic oscillation of glucose concentration between 1 g/L and 0 g/L were studied. The oscillation experiment with the chosen amplitude and cycling time showed little improvement in plasmid stability but had a lower specific production than that with the fixed glucose concentration. In a glucose-stat at 1 g/L glucose, cyclic oscillation of temperature between 24 °C, the permissive temperature, and 30 °C, the restrictive temperature, with 8 hours cycling time did not improve plasmid stability as compared to the experiment at a fixed temperature of 25 °C. However, the results showed that a slow response to gene turn-off, and a quicker response to gene tum-on. In continuous fermentation, cyclic oscillation of the dissolved oxygen level between 30% and 90% saturation improved the plasmid stability, but gave a lower production than that with a fixed 80% saturation in dissolved oxygen.

189 190 Introduction

Cyclic oscillation of fermentation conditions such as temperature, pH, and nutrient concentration have been shown to affect culture behavior, productivity and plasmid stability. Cyclic dilution rate (or specific growth rate) (Weber and San, 1987 and 1988 and Stephens and Lyberatos, 1988) was experimentally proved to be able to stabilize plasmid in recombinant cell fermnetations. In their work, cells experienced cyclic changes between substrate limited and unlimited conditions. Because of their extra metabolic burden, plasmid-containing cells were slower to adapt to changes in substrate concentration than plasmid free cells. During the period of substrate limitation, plasmid-free cells were growing at a sub-maximal growth rate and therefore had a lower mean growth rate. By manipulating the cycling time and amplitude, the normal growth differences between plasmid-free and plasmid-containing cells were removed. The larger the amplitude applied, the lower the mean growth rate of plasmid-free cells would be. The oscillation of specific growth rate was usually carried out by changing the dilution rate in continuous fermentation. The major limitation in using a chemostat is its unstable operation at the maximum specific growth rate. Therefore, the suitable range of the specific growth rate determined by the dilution rate is limited. This problem can be solved by using the glucose- stat (Kleman et al., 1991), where the specific growth rate controlled directly by the glucose concentration. Because the operation at the maximum specific growth rate in the glucose-stat is very stable, it is able to provide a larger range of specific growth rate. The amplitude of the change of glucose set-point will be determined from the glucose-dependant specific growth rate curve of yeast. Therefore, the 151 growth rate of plasmid-carrying cells and plasmid-free cells can be manipulated by changing the glucose concentration. It is also possible to change the specific growth rate by varying the temperature in a glucose-stat. The cycling time needs to be determined from the adaptation time for plasmid-free and plasmid-containing cells. Abulesz and Lyberatos (1989) found that baker's yeast had a time lag of about 3 hours in adapting its growth rate. However, the cycling time needs to be optimized in order to obtain significant improvement in the overall productivity. In this study, three types of oscillation experminent were carried out. The first two were to study the effects of oscillations in the concentration of glucose and temperature with chosen amplitudes and cycling times in the glucose-stat. Cyclic dissolved oxygen levels with a cycle time of a few minutes also has a stabilizing effect on recombinant yeast in a chemostat (Caunt et al., 1990). No specific productivity related to the plasmid stabilization was reported by them. The third experiment was to study the effects of oscillating dissolved oxygen on culture behaviors, productivity and plasmid stability.

Materials and Methods

Yeast and Plasmid The recombinant yeast and plasmid used in this work has been described in chapter 3.

Growth Media The composition of all media, used in this study, have been described in chapters 3 and 4. 192 Fermentations All continuous fermentations were started as a batch culture in the selective medium. After cells entered late log phase, a continuous feed of a rich medium was started and the fementor was operated either as a chemostat or glucose-stat.

(tt Glucose-stat A brief description of the glucose-stat and its installation is given in Appendix B (Kleman, et al., 1991). A predictive and feedback-proportional control algorithm, developed for fed-batch fermentation (Kleman, et al., 1991) was used to control a continuous culture based on soluble glucose concentration.

(2) Cyclic Oscillation of Glucose Concentration Glucose concentration in a glucose-stat was oscillated between 1 g/L for 8 hours and 0 g/L for 4 hours. The glucose concentration at 1 g/L was controlled by the computer. The computer control and feed pumps were turned off when the glucose concentration was set at 0 g/L. The pH was maintained at 5.5, temperature at 25 0 C, agitation speed at 400 rpm and the dissolved oxygen level at 80% saturation.

(3) Cyclic Oscillation of Temperature The temperature in a glucose-stat was changed between 24 0 C and 30 0 C every 8 hours. The glucose concentration was maintained at 1 g/L. The pH was maintained at 5.5, agitation speed at 400 rpm and the dissolved oxygen level at 80% saturation. 193 (4) Cyclic Oscillation of Dissolved Oxygen The dissolved oxygen level in a chemostat was oscillated between 90 % and 30% saturation. The dilution rate was 0.133 hr. The pH was maintained at 5.5, temperature at 25 0 C and agitation speed at 400 rpm.

Analytical Methods The analytical methods expect the measurement of ethanol concentration used in this study have been described in chapter 3.

m Ethanol Concentration

A high performance liquid otiromatagraph (HPLC) was employed to measure the ethanol concentration. The components of the chromatograph are shown in Table A. 1.

Table A. 1 Component of the HPLC Component Specification Solvent Delivery System Waters, Model 6000A Injector Waters, Model U 6K Organic Acid Analysis Column Bio-Rad, Model HPX-87H Column Heater Bio-Rad Differential Refractometer Waters, Model 410 Integrator Varian, Model 4270

The solvent, 0.7 ml H 2SO4 in 2 liters of degrassed distilled water, was pumped at a flow rate of 0.6 ml/min. Frozen samples were thawed, and suspended solids were removed by centrifugation. A 20 pi portion of the supernatant was injected into the HPLC. Standard solutions containing known amounts of ethanol 194 were prepared and used for calibration. By comparing the retention times and peak heights of the samples and standards, ethanol concentration were determined.

Figure A. 1 shows chromatagrams of the standard solutions and a typical sample. The moles of ethanol produced throughout a fermnetation were determined from the amount of base added to maintain a constant pH.

Acid produced (mole/L) = Concentrationbase (v base added 1 v 2reactor)

Results and Discussion

Oscillation in glucose In chapter 3, the value of the saturation constant k in the Monod equation was found to be 0.1 g/L. Kleman et al. (1991) stated that the setpoint of concentration in glucose-stat can be as low as 0.25 g/L and the glucose concentration can be controlled as tight as 0.02 g/L. Therefore, it is feasible to control the glucose concentration between 0 g/L and 1 g/L ( or 0.25 g/L). Figure A.l shows the kinetics of the recombinant yeast fermentation in the glucose-stat at the setpoint of 1.0 g/L glucose concentration. The results from glucose oscillation experiment are shown in Figure A.2. After the setpoint of glucose concentration was switched from 1 g/L to 0 g/L. the residual glucose in the vessel would be consumed by cells for growth. Therefore, the cell mass would continue to increase during the period with the setpoint of 0 g/L glucose. The control was back on to 1 g/L, a new steady state in glucose-stat will be reached. At the end of fermentation, the fraction of plasmid-carrying cells under the oscillation condition, dropped from 97% to 55%, was slightly higher than that at the fixed glucose concentration, dropped from 82% to 50%. The specific 195 production, 0.1 (g/g), under the oscillation condition was only one third of that, about 0.3 (g/g), at the fixed glucose concentration at the end of fermentation. Although the oscillation might have improved the plasmid stability, it also resulted in poor production of recombinant p-galactosidase. This was because cells were under starvation at the setpoint of 0 g/L. As long as cells are under starvation condition, the recombinant proteins may be degraded and used as the nutrient for the maintenance energy. This argument was proved by the observation of reduced protein concentration in the stationary phase in batch fermentation in chapter 3.

Oscillation in Temperature

The temperature in the glucose-stat was oscillated between 24 0 C, the permissive temperature, and 30 0 u , the restrictive temperature. The specific growth rate at 24 0 C and 30 0 C are 0.236 and 0.30 hr , respectively (see chapter 3). From the results in chapter 4, the response time for the turn-off of gene expression around 73 hours is much slower than that for the tum-on of gene expression, about 28 hours. Therefore, the chosen suitable cycling time can eliminate the problem of the loss of production by the cyclic effect between expression level at low temperature and non-expression level at high temperature. Applying this specific characteristic to our system, one can expect that the slow reduction in the specific production caused by gene turn-off can be quickly recovered by gene tum-on. Therefore, the average of gene expression with cyclic temperature oscillation should be close to that at the permissive temperature. Figure A.I. The kinetic of cell physiology and plasmid stability of recombinant recombinant of stability plasmid and physiology cell of kinetic The A.I. Figure Scale o 1 o to W CO N O 0.0 uoesa a 1 / wt rc, du t 5 C 25 at edium m rich, with g/L 1 at lucose-stat G yeast fermentation in glucose-stat at the setpoint of 1.0 g/L glucose 1.0 g/L of setpoint the at glucose-stat in fermentation yeast concentration. 00 00 60.0 40.0 20.0 pcfc production Specific lcs (g/L) glucose — a (g/L) B—gal ie (hr) Time tao (g/L) Ethanol 80.0 el (g/L). cell 100.0 O CO o o CO o N o o

Fractipn (^) 196 Figure A.2. Cyclic oscillation of glucose concentration between between concentration glucose of oscillation Cyclic A.2. Figure Scale o o o o W 1 CO CO N 0.0 uoesa -ih ih du t 5 C 25 at edium m rich -with lucose-stat G glucose with cycling time, with Fraction. 00 00 60.0 40.0 20.0 -—4^4 4-4— — ie (h.i*)Time 8 leii: 'prodluetion Slpecifit: hours at 1g/L.0 at g/L at and hours 4 hours el (g/L) cell 30.0 1 / ad g/L 0 and g/L 100.0 O o O N O O 03 o CO ■* 197 Fraction &\ KO 198 (Ti Plasmid Stability at Various Temperature From the chapter 3, the degree of plasmid instability in nonselective medium is seen to be associated with temperature. The plasmid is more stable at the restrictive temperature, 30 0 C, than at the permissive temperature, 25 0 C.

(2) Theoretical Explanation Under Cyclic Temperature Cells experience cyclic changes between tum-on of gene expression at low temperature (24 0 C) and tum-off of gene expression at high temperature (30 0 C). The maximum specific growth rate of cells is also controlled by the temperature which increased by enhancing the temperature. Because of their extra metabolic burden, plasmid-containing cells are slower to adapt to changes in temperature than plasmid-free cells. On the other hand, the lag time for plasmid- carrying cells to adapt to new environmental conditions is longer than that for plasmid-free cells. During the periods of the change of temperature, plasmid free cells are growing at a sub-maximal growth rate and therefore have a lower mean growth rate than plasmid-carrying cells. By manipulating the cycling times and amplitudes of temperature, the growth differences between plasmid free and plasmid containing cells are removed or reduced. The use of glucose-stat also can wash out the slow- growing strain. The plasmid stability therefore can be maintained.

(3) The Comparison of Specific Productivity and Plasmid Stability Between Cells Under Cyclic Temperature and Cells With Fixed Temperature in Glucose-stat The experimental results are shown in Figure A. 3. The plot of cycling time,

8 hours, between 24 0 C and 30 0 C is given in Figure A.4. The results showed that the specific production and plasmid stability were lower with temperature 199 oscillation than with fixed temperature at 25 0 C. Figure A.3 states that the recombinant yeast respond slowly during gene turn-off, but faster response occurrs for gene tum-on. In order to improve the plasmid stability and specific production by applying this method, a suitable amplitude for temperature change and cycling time should be determined first. 200

Glucose — stat with rich, medium with temperature oscillation

(between 24 C and 30 C) W □ cell (g/L) a glucose (g/L) v B —gal (g/L)

CO 0 Specific production t> Fraction

h r — —

CO o

o o o.o 20.0 40.0 60.0 80.0 100.0 T i m e ( h r )

Figure A.3. The experimental results of the kinetic behavior of recombinant yeast in glucose-stat in rich medium with temperature oscillation

i— ih tb ti? lb- kb dH.H.H.-Mb Lb.__4h

0 . 0 20.0 40.0 60.0 80.0 100.0 T im e (h r)

Figure A.4. The plot of cycling time, 8 hours, between 24 0 C and 30 0 C 201 The Comparison of Specific Productivity and Plasmid Stability Between Cells Under Cyclic Oxygen Level and Cells With Fixed Oxygen Level in Chemostat The effect of the cyclic oscillation of dissolved oxygen level, the comparison of the cell physiology and plasmid stability on the recombinant yeast with and without the oscillation of dissolved oxygen level in the chemostat was made. Figure A.5 shows the kinetics of continuous yeast fermentation with the rich medium at 80% of saturated dissolved oxygen level. Figure A .6 shows the influence of the oscillation of dissolved oxygen level on the cell physiology and plasmid stability in the chemostat. The experimental results are summarized in Table A.2 and Table A.3. The plasmid is more stable with the oscillation ' dissolved oxygen level than with 80% of saturated dissolved oxygen level. This stabilizing effect resulted from the quicker adaptability of plasmid-free cells to changes in dissolved oxygen tension. Therefore, the plasmid-free cells have a lower average growth rate than plasmid- carrying cells. This experiment also showed that the specific productivity with the oscillation, about 0.34, was lower than that without the oscillation, about 0.41. The recombinant cells experiencing the oscillation oxygen level between 30% and 90% of saturated dissolved oxygen must generate more types of precursors and metabolites in order to adapt to both oxidative and fermentative metabolism. However, recombinant cells at 80% of saturated oxygen level is carried out under the oxidative metabolism only. Therefore, the oscillation will slightly reduce the specific production of recombinant cells. This explains why the specific production of recombinant cells under the oxygen level oscillation was lower, even though the plasmid stability was improved. Figure A.5. The physiology and plasmid stability in yeast continuous fermentation continuous yeast in stability plasmid and physiology The A.5. Figure Concentration (g/1) 4= o cvi co CO w co 'j

?- A -A '? o. Glucose - Fraction - o o a with rich medium at 80% of saturated dissolved oxygen level. oxygen saturateddissolved of at80% rich medium with 1 O ------otnos Fermentation Continuous 20 1 ------. A 1 ------a Bth Sl Cn. Rich) Cont.: Sel, : (Batch 1 ----

i ^ a ie (hr) Time 40. J I. .‘A-A1. .I-A i I 1 A AA ■ihu 0/ Oclain c\j Oscillation; 2 02/N (■without 60. Cell(*2.5 Cell(*2.5 ) eagl (*10)^ Beta—gal G-'"" 80. a 1 A O 'A— 1 1 lOO. CO o o o o N o o co o CO o

fo 4J •H u a) 0 0 CJ 202 Figure A. Figure Concentration (g/1) fro- o 2 . 4. 6. a. io. 12 o. Glucose 6 Fraction Teifune fte silto fdsovdoye ee o h cell the on level oxygen dissolved of oscillation the of influence The . physiology and plasmid stability in the chemostat. the stabilityin and plasmid physiology 20 otnos FermentationContinuous . ie (h.r)Time 0 60. 40. Bth Sl Cn. Rich)- Cont.: Sel, : (Batch 0/ Oscillation) 2 (02/N 1 A Cell( *2.5 ) 4 C 24 eagl (*10) Beta—gal O 80. o

1O0. 0 01 o CO o CO o o 01 0 o 203 & + u a 0 0 fj j 204 Table A.2. The comparison of plasmid stability between cells experiencing the cyclic oscillation of oxygen level and cells without any oscillation

Fermentation Status Total Ferm. The Change Fracl Time(hr) of Fraction Drop (a)24(C,S+R) w/o about 100 from 95% to 45% oscillation hours 50% (b)24(C,S+R) w oscillation about 100 from 95% to 32% hours 63%

Table A.3. The comparison of cell dry weight, fB-galactosidase production and specific productivity between cells experiencing the cyclic oscillation of oxygen level and cells without any oscillation

Fermentation Status CDW(g/L) P(g/L) SP

(a)24(C,S+R) (1) w/o oscillation 2.405 1.065 0.4428 (2) 3.175 1.249 0.3956

(b)24(C,S+R) (1) w oscillation 2.518 1.0105 0.3264 (2) 2.972 1.0105 0.3399

Notation:

24 : Temperature ( 0 C) C : Continuous Fermentation S+R : Selective medium in batch growth then rich medium in continuous cultivation (1) : Last data point in each fermentation (2) : Highest specific productivity in each fermentation CDW: Cell dry weight (g/L) P : Production of (3-galactosidase (g/L) SP : Specific productivity (g of P-galactosidase/g of CDW) 205 Conclusions

Improvements in plasmid stabilities by cyclic oscillations of the glucose concentration in a glucose-stat and the dissolved oxygen level in a chemostat with the chosen amplitude and cycling time were found. However, the stability of plasmid under the cyclic oscillation of temperature in a glucose-stat was worse than that at the permissive temperature. The overall production and specific production by oscillations of glucose concentration, temperature, and dissolved oxygen level showed negative results. In order to improve the plasmid stability and recombinant protein production, a proper amplitude and cycling time need to be identified.

References

Abulesz, E-M. and Lyberatos, G., Periodic operation of a continuous culture of baker's yeast, Biotechnol. Bioeng., 34, 741, 1989.

Gaunt, P., Impoolsup, A. and Greenfield P.F., A method for the stabilization of recombinant plasmid in yeast, J. Biotechnol., 14, 311, 1990.

Kleman, G. L., Chalmers, J. J. Luli, G. W. and Strohl, W. R., Glucose-stat, a glucose-controlled continuous culture, Applied and Environmental Microbiology, 57, 918, 1991.

Stephens, M. L. and Lyberatos, G., Effect of cycling on the stability of plasmid- bearing microorganisms in continuous culture.. Biotechnol. Bioeng., 31, 464, 1988.

Weber, A.E. and San K. Y., Bioprocess Engineering Colloquium, ASME Winter Annual Meeting, Boston, MA, p. 75-78, Dean, R. C., Jr. and Nerem, R. M. (Eds), 1987. 206 Weber, A.E. and San K. Y., Enhanced plasmid maintenance in a CSTR upon square-wave oscillations in the dilution rate, Biotechnol. Lett., 8 , 531, 1988 APPENDIX B COMPUTER-CONTROLLED BIOFLO IIFERMENTOR

Installation

The installation and the functions of BioFlo II fermentor (New Brunswick Scientific, NJ) are shown in Figure B. 1. This BioFlo II fermentor employed for batch and continuous cultures has mir'oprocesser controls of pH, DO, agitation,temperature, nutrient feed, and electronic foam control. A removable agitation servo motor provides agitation speed range of 25 to 999 (+ 1)RPM. The media temperature is sensed by an RTD (Resistance Temperature Detector) thermometer submerged in the thermowell. The culture temperature can be selected in the range from 20 °C to 60 °C (+ 0.1°C) and is controlled by the microprocesser based PI controller. Sterile air is introduced into the medium through a ring sparger, and is controlled by the needle valve of a flowmeter. The pH is controlled in the range of 2.00-9.99 (+ 0.01). Control is maintained by PI controller which operates two peristaltic pumps, connected to acid and base addition ports. DO is controlled in the range of 5-95% (± 1%). It is sensed by a DO electrode. The schematic diagram for computer-assisted on-line glucose close-loop fermentation system is shown in Figure B.2. The control system starts from the uptake of cell broth from the fermentor. The cell broth is pumped by a peristaltic

2 0 7 208 pump and transported through a tangential flow filter with 0.22 mm filtration membrane. Retentate with the concentrated cell broth and most of the filtrate are transferred back to the fermentor. A small portion of the filtrate is transferred to a glucose analyzer by the insertion of a Cole-parmer #7014-13 silicone tube into the filtrate tube. The glucose concentration in the filtrate is detected by the glucose analyzer and an analog signal in the range of 0-1 voltage corresponding to the glucose concentration is sent out from its output port. The translation of continuous analog signal to the discrete digital signal is executed in a 16 channel A/D interface (DMA Models DASH-16). This data information form the digital signal in the range of 0-4095 is stored in the memory of IBM PC/XT computer. Using a BASIC control program, the computer control the rotating speed of the feed pump according to the required amount of glucose. Based on an optimal feeding operation strategy for glucose solution which will be shown in the next section, the input digital signal is converted to the optimal digital number for the glucose feeding. A 6 channel D/A interface with 24 parallel digital I/O lines Model DDA- 06 converts this discrete output digital signal (0-4095) to a continuous current signal (4-20 mA). This 4-20 mA signal is fed into the pump to vary the pumping speed. Therefore, different feeding rates of the glucose solution from the reservoir to the fermentor can be operated. 209 Control Methods

Feeding of Nutrient by On-Line Glucose Control System The values of operation parameters such as pH, temperature and dissolved oxygen are set up on the control panel of the BioFlo II fermentor. The built-in PI controller controls these parameters at the desired level. In this study, pH value was set at 5.5 or varied by the desired operation conditions. Temperature is chosen to be either 24 °C (the permissive temperature) or 30 °C (the restrictive temperature), depending on the control strategies. The level of dissolved oxygen was maintained at 70%. In the study of cyclic oscillation of dissolved oxygen between 30% and 90% the dissolved oxygen level during the course of fermentation were controlled. The block diagram of on-line glucose adaptive plus feedback control system is shown in Figure B.3. The IBM PC/XT computer control the rotating speed of the pump according to the glucose demand of cells in order to maintain the glucose concentration in the fermentor at the desired level. The feed is controlled using an analog output of 4-20 mA to a Cole-parmer pump #7534-30 peristaltic pump with a #7013-20 head. The calibration of the pump is made by feeding the feed solution into a sterilized 1 L flask on a balance. The linear regression between the output current from the computer and the volumetric flow rate of the feed solution is thus established. The control scheme is developed as an adaptive control algorithm. A predictive or adaptive control is based on the calculation of glucose demand and the prediction of glucose demand for the next datum point. The glucose consumption rate at a particular time, t , is determined by

GCR = GFti _t0 +[(ERR_i - ERRq )*V]/dt 210 where: GCR is the glucose consumption rate (in g/min) GF stands for the amount of glucose fed to vessel (in g/min) ERR is the difference between set point and actual glucose concentration

measured (in g/ 1) V equals volume of solution in the vessel (in L)

dt is the interval between sampling (2 min). Linear regression is conducted on GCRt .5 to GCRt_i , and GCR^o is stored for the next sample, which compensates for the lag time between the glucose analyzer and the fermentor. From this linear regression, a future glucose demand at a particular time, t.^ i, is determined. The predicted glucose feed rate is calculated as below. PGF = GCR / GC Where: PGF is the predicted glucose feed rate (L/min) GCR is the predicted glucose consumption rate (g/min) GC is the glucose concentration in the reservoir (g/L) From the previous calibration equation controlling the pump speed between the output digital number and glucose volumetric flow rate, the pumping speed is able to be controlled. 211

Flowmeter A ir—Q —["►

Acid ► onaenser Base- Inoculation

Sample Nutrient

Antifoam

Heater Water

Drain

Harvest Vessel

Figure B.l. BioFlo II fermentor and its functions. 4—20m A O ptical Count Fiber Count A/D

0 -H )0 m V | G lu cose Light Photomultiplei A nalvzer Source

Pum p

Tangential Pum p Filter

m2 ^ ^ Pump Pump Pum p

G lu cose Solution

Low M iddle High

Figure B.2. The schematic diagram for computer-assisted on-line glucose close- loop fermentation system. 213

Cst Error Flow Rate Controller Process

Glucose Analyzer

Figure B.3. The block diagram of on-line glucose adaptive plus feedback control system.

Feeding of Nutrient by On-Line Measurement of Turbidity The fermentation broth was cL ilated through an external glass tunnel. The light which was generated by the light generator and delivered by the optical fiber was emitted from one side of the glass tunnel. The intensity of emitted light source can be adjusted in the light generator. From the other side of the glass tunnel, the light was received and the received light intensity was dependent on the turbidity of the culture broth. The light was then transported from the recieved end to the photomultiplier. In the photomultiplier, the intenisty of light was converted into a voltage signal (0 mV to 100 mV). The translation of continuous analog signal to the discrete digital signal is executed in a 16 channel A/D interface (DMA Models DASH-16). This data information form the digital signal in the range of 0-4095 is stored in the memory of IBM PC/XT computer. The block diagram of on-line control by the measurement of the turbidity is shown in Figure B.4. The calibration curve between the value of the turbidity from the device of optical fiber and the cell dry weight is shown in Figure B.5. 214 Therefore, based on this calibration curve, the cell concentration is determined from the turbidity of the broth. The glucose consumption rate is estimated by using the following equation:

dX = (Xnew - X 0id ) / dt

dS 1 d X

d t ^ x /s d t Where : S : the concentration of glucose (g/L) X0ld : cell concentration (g/L) in the previous sampling time Xnew : cell concentration (g/L) in the current sampling time Yx/S : cell yield (g cell dry weight g glucose) dt: the interval between samplmg (30 min). In our case, a constant cell yield (0.3 g cell dry weight/ g glucose),which was obtained from the experimental results of batch fermentation in chapter 3, was assumed during the fed-batch fermentation. The glucose consumption rate is then estimated by GCR = (dS/dt) * V Where: GCR is the glucose consumption rate (in g/min) V equals the solution volume in the vessel (in L) The predicted glucose feed rate is also calculated as below. PGF = GCR / GC Where: PGF is the predicted glucose feed rate (L/min) GCR is the predicted glucose demand (g/min) GC is the glucose concentration in the reservoir (g/L) Three types of glucose solution with the correponding nutrient were prepared. For low glucose (25 g/L) solution, it contained 2.5% (wt/vol) glucose and 0.25% yeast extract. For middle glucose (150 g/L) solution, it contained 15% glucose and 1.5% yeast extract. For high glucose (750 g/L) solution, it possessed 75% glucose, 7.5% yeast extract and 10.5% casamino acid. The feeding rate of each glucose solution was controlled by the pump and monitored by the computer. The computer will automatically identify the suitable feeding solution based on the predicted glucose feed rate. Using a BASIC control program, the computer controls the rotating speed of the feed pump according to the required amount of glucose.

Flow Rate Error ProcessController

new Reading .0 - 4095 ,4 to 20 mA Calibration Device of A/D Curve Optical Fiber

Figure B.4. The block diagram of on-line control by the measurement of the turbidity.

Figure B.5. shows the experimental result based on this control strategy. From the experimnetal result, this control method can maintain a low glucose concentration in the vessel. The comparison of maximum cell density, glucose cosumed, cell yield and product yield between the batch fermentation in the selective medium from chapter 3 and fed-batch fermentation based on this control method is given in Table B. 1. Cell yield and product yield in the fed-batch fermentation were lower than those in the batch fermentation. Further studies such 216 as the medium formulation and better control strategies are needed in order to reach high cell density and high production.

Table B.l. Comparison of maximum cell density, glucose cosumed, cell yield and product yield between the batch fermentation in the selective medium and the fed-batch fermentation

Batch Fed-Batch Final Volume (L) 3.0 5.0 Final Cell Dry Wt. (g) 3.3 100.0 Max. Cell Concentration 1.1 g/L about 20 g/L (g/L) Total Glucose Consumed 4g 905 g (g) Final Protein 0.54 0.5153 Concentration (g/L) YX/S 0.225 0.11 YP/S 0.135 0.002847

Where: Yx/S: ( g of cell/ g of glucose consumed)

Yp/S; ( g of P-galactosidase/ g of glucose consumed) Figure B.5. fermentation kinetics of on-line control by the measurement of theof measurement theby controlon-line of kinetics fermentation B.5.Figure

Concentration (g/L) O CO co w H o O O N o CO o O o o o 0 turbidity. O. Be t u ^1 — cgala tose a Cell □ Glucose 30. Intensity 60. ie (hr) Time el (g/L) Cell 90. O. O 1 120 . 15. 150. 1 QO. 20 . 217 APPENDIX C THE ADAPTIVE COMPUTER CONTROL PROGRAM IN FED-BATCH FERMNETATION FOR BIO-FLO II BIOREACTOR

Filename: main.bas

10CLS 20 PRJNT:PRINT 30 PRTNT"*******************************************************" 40 PRINT "** 50 PRINT "** = = Adapt? Control = **" 60 PRINT "** 70 PRINT ”** DATA ACQUISITION PROGRAM FOR DASH-16 * *" 80 PRINT "** 90 PRINT "** CHIN YUAN CHENG **" 100 PRINT "** 110 PRINT "** Department of Chemical Engineering **" 120 PRINT "** The Ohio State University **" 130 PRINT "** 140 PRINT "** 1-1-1991 **" 150 PRINT "**

170 PRINT : PRINT:PRINT:PRINT 180 PRINT " » » Hit any key to start the program. « « " 190 A$=INKEY$ : IF A$=,m GOTO 190 200 CLS

2 1 0 ' 220 '------Description of Program ------230 ' This example program shows how to set up DASH-16 to log data from 240 'its 15 analog channels and 3 digital inputs. The data is transferred to 250 'a random access data file on disk at any interval ranging from 1 second 260 'up. Options are provided for subsequent printing out or on- screen 270 'viewing of the data file. 280 ' The data acquired through the operation of DASH-16 mode 4 can be 218 290 'shown on the screen with a table type or a diagram type output. 300' 310 '- —- Display menu with setup options ------320 '*** You can add other options of your own here *** 330 LOCATE 1, l:PRINT"Choose from following options:-" 340 LOCATE 3,5:PRINT"<1> - Read and log data to disk" 350 LOCATE 5,5:PRINT"<2> - Display data from disk data file" 360 LOCATE 7,5:PRINT"<3> - Print out data from disk data file" 370 LOCATE 9,5:PRINT"<4> - Generate lotus 1-2-3 files from disk data file" 380 LOCATE 11,5:PRINT"<5> - Generate VAX files from disk data file" 390 LOCATE 13,5:PRINT"<6> - Calibration the pump" 400 LOCATE 15,5:PRINT"<7> - Exit to BASIC" 410 LOCATE 17,2:PRINT"Choose option (1-7): 420 A$=INKEY$:IF A$="" GOTO 420 430 PRINT A$ 'echo response to screen 440 X% = VAL(A$) 450 IF X%>=1 AND X%<=7 GOTO 470 'check for valid response 460 LOCATE 19,1:PRINT"[";A$;"] j ’.ot a valid response. Re-enter": LOCATE 17,1:PRINT SPC(79):UOTO 410 470 LOCATE 19,1:PRINT SPC(79) 480 Now go and do option chosen. 490 IF X%=1 THEN CHAIN "fiml"„ALL 500 IF X%=2 THEN CHAIN "fun2"„ALL 510 IF X%=3 THEN CHAIN "fun3"„ALL 520 IF X%=4 THEN CHAIN "fun4"„ALL 530 IF X%=5 THEN CHAIN "fun5"„ALL 540 IF X%=6 THEN CHAIN "fun 6"„ALL 550 IF X%=7 THEN CLS:NEW:END 220 Appendix C.2

20'* Function 1: Read and log data to disk * 30 '* Filename: Funl.bas *

50' 60 '------— Initialize ------70 CLEAR, 65535! ’contract workspace to 62 K 80 DIM DIO%(7) 'set up channel data array 90 NR=2 100 'Make screen announcement while loading driver routine 110 SCREEN 2:KEY OFF: CLS 120 LOCATE 12,12:PRINT"« Wait - Loading DASH16.BIN driver & DASH16.ADR»" 130 LOCATE 25,1 :PRINT"DATATAKER.BAS—DASH-16 Data logging utility 140 'Find segment of memory where BASIC program workspace is loaded. 150 DEF SEG = 0 '~eady to read low memory 160 SG = 256 * PEEK(&H511) + PEEK(&H510) 'find BASIC's segment 170 TSTow load driver at end of BASIC's workspace 180 SG = SG + 65535 !/16 'CALL load segment 190 DEF SEG = SG 200 BLOAD "DASH16.BIN",0 'load CALL at SG 210 ’*** Set Base I/O address to suit your board *** 220 OPEN "DASH 16.ADR" FOR INPUT AS #1 ’fetch DASH-16 I/O address 230 INPUT #1, BASADR% 240 CLOSE #1 250 BASE=768 ’I/O address for D/A on DDA06 260 ’Do Mode 0 initialization of DASH-16 270 DASH 16= 0 'Initialize DASH-16 driver 280 DIO%(0)=BASADR% 290 DIO%(l)=2 300 DIO%(2)=3 310 FLAG% = 0 'and CALL parameters 320 MD% = 0 330 CALL DASH 16 (MD%, DIO%(0), FLAG%) 'run initialization 340 IF FLAG% <>0 THEN PRINT'INSTALLATION ERROR",FLAG%:END ’? any errors 350 LOCATE 12,1 :PRINT SPC(79) 'remove WAIT message 360' 221 370' 380 ' ------Get name of user's data file ------390' : 400 LOCATE 19,1:INPUT "Name of data file (e.g. B:MYFILE.DAT),=JUNK";FILE$ 410 IF FILE$="" THEN FILE$="JUNK" 420 LOCATE 21,1: INPUT "Description to be used as header ";HEADER$ 430' 440 '------Open random access file with records as follows:- 450' 460 OPEN FILES AS #1 LEN = 38 470 FIELD #1,30 AS HD$,2 AS NC$, 2 AS CSCANS, 4 AS FREQS 480 '*** You can choose & declare your own data file structure *** 490 'This program stores the A/D data (0 to +4095 bits) as integers 500 'which is most economical of disk storage space. A 320K disk would 510 'hold 8,888 records. At a 10 second sampling rate this would amount 520 'more than 24 hours of data. Saving space may not be as important to 530 'you as having the best record str "hire for your needs - there are 540 'tradeoffs here! 550' 560 ' Log data to disk ...... 570 'LPRINT : LPRINT FILE$:LPRINT HEADERS:LPRINT 580’LPRINT" Time (min) pH Temp D.O." 590 ’LPRINT" ...... " 600 MAXN= 1500 610 DIM TIM(MAXN), CH0%(MAXN), CHI %(MAXN), CH2%( MAXN), CH3 %(MAXN), C H4%(MAXN),GCR(MAX,N),X%(7) 620 DIM COEF(6) 630 GOSUB 1690 'Initial conditions for the operation 640 GOSUB 1770 'set-up the set point for glucose conc. 650 GOSUB 1970 'Enter glucose conc. in each reservior 660 GOSUB 2070 'Set up the parameters for figures 670 GOSUB 2200 'plot x axis and y axis 680 GOSUB 3080 'open indexA&pump files to take coef. forcalibration 690 TIMER ON:DATE=0:TIME$="00:00:00" 'zero time and date 700 CSCAN%=0 'initial record#=0 710 LOCATE 1, LPRINT "-Scanning Loop (Push Esc buttom to save data)- LOCATE 1,48:PRINT "Date =":LOCATE 1,60:PRINT "Time =" 720 LOCATE 1,55:PRINT DATE 222 730 LOCATE 1,68:PRINT TIMES 732 GOSUB 900 'take data 735 GOSUB 5000 'on/off control 02 and N2 flow rate 740 IF (CSCAN%*DT*60 - TIMER) < .05 THEN GOTO 780 750 A$=INKEY$:IF A$="" THEN GOTO 770 760 IF ASC(A$)=27 THEN GOTO 860 770 GOTO 730 780 TIM(CSCAN%)=DT*CSCAN%:TIMS=TIM(CSCAN%) 790 CSCAN%=CSCAN%+1 800 IF (TIM(CSCAN%) > 40*60) THEN GOTO 860 'time is greater than time max. 810 IF (TIM(CSCAN%) >1440*(DATE+1)) THEN DATE=DATE+1:LOCATE 1,55:PRINT DATE 820 GOSUB 900 'take data 830 'GOSUB 2770 'adaptive control(get future glucose demand 835 GOSUB 5000 'on/off control 02 and N2 flow rate 840 GOSUB 2590 'plot data 850 GOTO 730 860 A$=INKEY$:A$=INKEY$:A$=INKEY$:A$=INKEY$:A$=INKEY$ ’clear keyboard buffer 870 GOSUB 1430 'save data 880 ERASE X%,COEF 890 CHAIN "main"„ALL 900 ’ START OF MAIN LOGGING LOOP ...... 910' 920 ' Fetch A/D data from channels 0 thru 3 and return in ARRAY — 930 ' Prompt for scan limits and set using model 1 ------940 'scan limits will default to 0-7 (8 channel) or 0-15 (16 channel) if you 950 'skip this step 960' 970 DIO%(0)=0 'set lower channel=0 980 DIO%(l)=4 'set upper channel=4 990 NC%=DIO%(0)-DIO%(1)+1 'scan channels = 5 1000 MD%=1 'mode 1 - set scan limits 1010 CALL DASH 16 (MD%, DIO%(0),FLAG%) 1020 IF FLAG%oo THEN PRINT "Error in setting scan limits #";FLAG%:STOP 1030' 1040 ' Set timer rate to trigger A/D using mode 17 ------1050 'Setting timer to 10 Hz (jumper *1 position): ( 10 times/sec) :- 1060 DIO%(0)=100 'you can set anther rate here if you want 1070 DIO%(1)=1000 '2 < DIO%(0) < 65535, 2 < DIO%(l) < 65535 223 1080 MD%=17 ' mode 17 - timer set 1090 FREQ=1000000!/(DIO%(0)*DIO%( 1)) 'freq = 10 Hz 1100 CALL DASH 16 (MD%, DIO%(0), FLAG%) 'set timer 1110 IF FLAG%0 THEN PRINT "Error in setting timer error #";FLAG%:STOP

1120 ' 1130 '------Take data using mode 4 ------1140 CHX0=0: CHX 1=0: CHX2=0:CHX3=0: CHX4=0 1150 FOR J=1 TO 10 'run 10 timers to take average value 1160 DIO%(0)=5 '5 conversions required 1170 DIO%(1)=VARPTR(X%(0)) 'provide array location 1180 DIO%(2)=l 'trigger source, l=timer, 0=extemal on IPO 1190 MD%=4 'mode 4 - A/D to array 1200 CALL DASH 16(MD%, DIO%(0),FLAG%) 'read data into array 1210 IF FLAG%o0 THEN PRINT "Error in setting timer error #";FLAG%:STOP

1220 ' 1230 LOCATE 1,55:PRINT DATE:LOCATE 1,68:PRINT TIMES 1240 CHX0=X%(0)+CHX0 'take date from channel 0 (0-409.5), Glucose Conc. 1250 CHX1=X%(1)+CHX1 'take aate from channel 1 (0-409.5), pH 1260 CHX2=X%(2)+CHX2 'take date from channel 2 (0-409.5), Temp 1270 CHX3=X%(3)+CHX3 'take date from channel 3 (0-409.5), D.O. 1280 CHX4=X%(4)+CHX4 'take date from channel 4 (-2408-0), OD 1285 LOCATE 20,60:PRINT "X%(4)=";X%(4) 1290 NEXT J 1300 CH0%(CSCAN%)=CHX0/10 'GC in (0-409.5) 1310 CH1 %(CSCAN%)=CHX 1/10 'pH in (0-409.5) 1320 CH2%(CSCAN%)=CHX2/10 ’Temp in (0-409.5) 1330 CH3%(CSCAN%)=CHX3/10 'D.O. in (0-409.5) 1340 CH4%(CSCAN%)=CHX4/10 'OD in (-2048-0) 1350 GC=(CH0%(CSCAN%)* l*50)/409.5 'convert to GC real value 1360 PH=(CH1%(CSCAN%)* 1 * 10)/409.5 'convert to pH real value 1370 TEMP=(CH2%(CSCAN%)*1* 100)/409.5 'convert to Temp realvalue 1380 DOX=(CH3%(CSCAN%)* 1 *l)/409.5 'convert to D.O. real value 1390 OD=((CH4%(CSCAN%)+2048)* 1 *50)/2048 ’convert to OD real value 1400 LOCATE 2, LPRINT CSCAN% 1402 LOCATE 2,5:PRINT TIMS 1404 LOCATE 2,15:PRINT " GC=";GC 1406 LOCATE 2,27:PRINT " pH=";PH 1407 LOCATE 2,39:PRINT " Temp=";TEMP 1408 LOCATE 2,5 LPRINT " D.O.=";DOX 1409 LOCATE 2,63:PRINT " OD=";OD 224 1410 RETURN 1420' 1430 '— —------Fetch DASH-16 digital data to disk------1440' 1450 LOCATE 23, LPRINT" TRANSFER DATA TO DISK" 1460 LSET HD$ = HEADERS 1470 LSET NC$ = MKI$(NC%) 'Scanchannels=4 (total= 8 ) 1480 LSET CSCANS = MKI$(CSCAN%) 'Total record # 1490 LSET FREQS = MKSS(FREQ) 'freq =10 Hz 1500 PUT #1, 1 1510 FIELD #1, 4 AS TIMS, 2 AS CH0$,2 AS CH1S, 2 AS CH2S, 2 AS CH3S, 2 AS CH4S, 4 AS GCRS 1520 NR=2 1530 FOR 1=0 TO CSCAN%-1 1540 LSET TIMS = MKS$(TIM(I)) 1550 LSET CH0S = MKI$(CH0%(I)) 'Gluco. conc. in (0-4095) 1560 LSET CH1S = MKI$(CH1%(I)) 'pH in (0-4095) 1570 LSET CH2S = MKI$(CH2%(I)' 'Temp, in (0-4095) 1580 LSET CH3S = MKI$(CH3%(I)) 'D.O. in (0-4095) 1590 LSET CH4S = MKI$(CH4%(I)) 'OD in (0-4095) 1600 LSET GCR$=MKS$(GCR(I)) 'Glue, comsumption rate (g/min) in real # 1610 PUT #1,NR 1620 NR=NR+1 1630 NEXT I 1640 LOCATE 23,1 : PRINT SPC(30) 1650 CLOSE #1 1660 ERASE TIM,CH0%,CH1%,CH2%,CH3%,CH4%,GCR 1670 RETURN 1680' 1690' 1700 '------Initial conditions for the operation ...... 1705 NC=0 'first time D/A use channel 0 1710' 1720 ERR4=0:ERR5=0 'intial error=0 1730 GF5=0:GF6=0 'Intial flow rate =0 1/min 1740 GCR 1=0:GCR2=0:GCR3=0:GCR4=0:GCR5=0 'Intial glucose demand =0 g/min 1750 RETURN 1760' 1770 ' set up the set points for temp., pH, DO and Glucose ------1780' 1790 CLS.‘LOCATE 1,20:PRINT "Check the set point of each parameter" 1800 V5=3 'set intial volume V5=3 liter 1810 LOCATE 3, LPRINT "Initial volume of medium =";V;"liter" 1820 GCSET=.5 'glucose concentration at set point = 0.5 g/1 1830 LOCATE 5,LPRINT "Glucose Conc. at set point =";GCSET;" g/1" 1840 DT=30 'sampling time = 30 minutes 1850 LOCATE 7, LPRINT "Sampling time =";DT;"minutes" 1860 PHSET=5.5 1870 LOCATE 9, LPRINT "pH at set point =";PHSET 1880 TSET=25 1890 LOCATE 11, LPRINT "Temperature at set point =";TSET;" C" 1900 DOSET=.7 1910 LOCATE 13, l.PRINT "G.O. at set point =";DOSET 1920 PRINT : PRINT:PRINT:PRINT 1930 PRINT " » » Hit any key to continuous « « " 1940 A$=INKEY$ : IF A$="" GOTO 1940 1950 RETURN I960' 1970 ' Enter the glucose concentration in each reservior ------1980' 1990 CLS:LOCATE 3,25:PRINT "Enter the glucose concentration in each reservior" 2000 DIM GCV(2) 'glucose concentration in each reservior 2002 GCV(0)=25 'glucose conc. in reservior #1 = 25 g/1 2004 GCV(1)=150 'glucose conc. in reservior #2 =150 g/1 2006 GCV(2)=750 'glucose conc. in reservior #3 =750 g/1 2010 LOCATE 5,20:PRINT "Glucose concentration in #1 reservior(g/l) =";GCV(0) 2020 LOCATE 7,20:PRINT "Glucose concentration in U2 reservior(g/l) =";GCV(1) 2030 LOCATE 9,20:PRINT "Glucose concentration in U3 reservior(g/l) =";GCV(2) 2032 PRINT : PRINT:PRINT:PRINT 2034 PRINT " » » Hit any key to continuous « « " 2040 A$=INKEY$ : IF A$="" GOTO 2040 2050 RETURN 2060' 2070 '------set up the parameters for figures ------2080' 2090 CLS:LOCATE 1,20:PRINT "Check the min. and max. values for each axis" 226 2100 LOCATE 3,LPRINT "Time min.=";0;"(day)":LOCATE 3,40:PRINT "Time max.="; 8 ;"days" 2110 LOCATE 5,LPRINT "Glu. conc. min =";0;"(g/l)";:LOCATE 5,40:PRINT "Glu.conc. max =";5;"(g/l)" 2120 LOCATE 7, LPRINT "pH min =";0:LOCATE 7,40:PRINT "pH max =";10 2130 LOCATE 9,LPRINT "Temp min =";0;" C":LOCATE 9,40:PRINT "Temp max.=";40;"C" 2140 LOCATE 11,LPRINT "D.O. min.=";0:LOCATE 11,40:PRINT "D.O. max.=";l 2150 PRINT : PRINT:PRINT:PRINT 2160 PRINT " » » Hit any key to continuous. « « " 2170 A$=INKEY$ : IF A$="" GOTO 2170 2180 RETURN 2190' 2200 ' plot x axis, y axis ------

2210 ' 2220 CLS 2230 PSET (50,40):DRAW "d80;r30^ ' 2240 PSET (50,130):DRAW "d80;r300" 2250 PSET (50,220):DRAW "d80;r300" 2260 PSET (400,40):DRAW "d80;r300" 2270 PSET (400,130):DRAW "d80;r300" 2280 PSET (400,220):DRAW "d80;r300" 2290 LOCATE 3,7:PRINT "Glucose conc.(g/l)":LOCATE 10,7:PRINT "pH":LOCATE 17,7:PRINT "Temp. (C)" 2300 LOCATE 3,46:PRINT "D.O.":LOCATE 10,46:PRINT "OD":LOCATE 17,46:PRINT"Glu.Consumption rate(g/min)" 2310 LOCATE 23,40:PRINT "Time (day)" 2320 L=0 2330 FOR J=1 TO 6 2340 FOR K=0 TO 10 2350 M=J-1 2360 IF (J>3) THEN L=350:M=J-4 2370 PSET (50+L,40+8*K+90*M) 2380 IF (K=0 OR K=5 OR K=10) THEN DRAW "110" ELSE DRAW "15" 2390 NEXT K 2400 NEXT J 2410 L=0 2420 FOR J=1 TO 6 2430 FOR K=0 TO 40 227 2440 M=J-1 2450 IF (J>3) THEN M=J-4:L=350 2460 PSET: (50+L+K*7,120+M*90) 2470 IF (K MOD 5 =0) THEN DRAW "dlO” ELSE DRAW "d5" 2480 NEXT K 2490 NEXT J 2500 LOCATE 3,2:PRINT "5":LOCATE 6,2:PRINT "2.5":LOCATE 9,2:PRINT

" 0 " 2510 LOCATE 10,2:PRINT "10":LOCATE 13,2:PRINT "5":LOCATE 15,2:PRINT "0" 2520 LOCATE 16,2:PRINT "40":LOCATE 19,2:PRINT "20":LOCATE 22,2:PRINT "0" 2530 LOCATE 3,41:PRINT 'T':LOCATE 6,41:PRINT "0.5":LOCATE 9,41:PRINT "0" 2540 LOCATE 10,41:PRINT "50":LOCATE 13,41:PRINT "25":LOCATE 15,41:PRINT"0" 2550 LOCATE 16,41:PRINT ”50":LOCATE 19,41:PRINT "25”:LOCATE 22,41:PRINT "0" 2560 LOCATE 23,6:PRINT "0”:LOCaTE 23,22:PRINT "4":LOCATE 23,37:PRINT "8 " 2570 LOCATE 23,6LPRINT "4":LOCATE 23,77:PRINT "8 " 2580 RETURN 2590' 2600 ’------Plot data ------2610’ 2620 TIMEP=(TIMS*300/(8*24*60))+50 2630 GCP = 120-(GC*80/5) 2640 PSET (TIMEP,GCP) 2650 PHP=210-(PH*80/10) 2660 PSET (TIMEP,PHP) 2670 TEMPP=300-(TEMP*80/40) 2680 PSET (TIMEP,TEMPP) 2690 TIMEP=(TIMS*300/(8*24*60))+400 2700 DOP = 120-(DOX*80/1) 2710 PSET (TIMEP,DOP) 2720 ODP = 210-(OD*80/50) 2730 PSET (TIMEP,ODP) 2740 GCRP = 300-(GCR(CSCAN%)*80/50) 2750 PSET (TIMEP,GCRP) 2760 RETURN 2770 ’ 2780 ' Adaptive plus feedback control ------2790' 2800 ERR5=GC-GCSET ’WHERE: GCSET=.5 G/L 2810 V5=V5+GF5*DT 2820 GCR5=GF5+((ERR4-ERR5)*V5)/DT 'Glucose consumption rate (g/min) 2830 GCR(I)=GCR5 2840 IF TIMS <1 THEN GOTO 3050 2850 GCR1=10:GCR2=8:GCR3=6:GCR4=4:GCR5=2:NC=0 'zero channel 2860 GOSUB 3390 linear regression 2870 GCR 6=COEF(l) 2880 FOR CNT%=5 TO 1 STEP -1 2890 GCR 6=GCR6+ COEF(CNT%+l)*(TIMS+DT)ACNT% 'Future glucose consumption rate 2900 NEXT CNT% 2910 LOCATE 1,68:PRINT TIMES 2920 GF 6=GCR6/GCV(NC) 'Flow rate (1/min) 2930 D=A(NC, 1) 'd=data range (0-4095) 2940 FOR CNT%=5 TO 1 STEP -1 2950 'polynomial equation get count # 2960 D=D+A.(NC,CNT%+1)*GF6ACNT% 'get d from the calibration curve 2970 NEXT CNT% 2972 IF (D <= 3200) THEN GOTO 2980 2974 NC=NC+1 2980 GOSUB 3310 'turn on the pump 2990 GCR1=GCR2 3000 GCR2=GCR3 3010 GCR3=GCR4 3020 GCR4=GCR5 3030 GCR5=GCR6 3040 ERR4=ERR5:GF5=GF6 3050 A$=INKEY$:IF A$="" THEN GOTO 3070 3060 IF ASC(A$)=27 THEN ERASE COEF:GOSUB 1430:CHAIN "main”„A 3070 RETURN 3080' 3090 ' ------Open Index 6 & Pump file to take coef. from calibration 3100' 3110 OPEN "Index 6" AS #2 LEN=2 3120 FIELD #2, 2 AS BN$ 3130 GET #2,1 3140 N%=CVI(BN$) 3150 CLOSE #2 3160' 3170 OPEN "Pump" AS #3 LEN=24 3180 FIELD #3, 4 AS Al$, 4 AS A2$, 4 AS A3$, 4 AS A4$, 4 AS A5$, 4 AS A6$ 3190 DIM A( 6,6) 3200 FORI = 1 TON% 3210 A(I-1,1)=CVS(A1$) 3220 A(I-1,2)=C VS(A2$) 3230 A(I-1,3)=CVS(A3$) 3240 A(I-1,4)=CVS(A4$) 3250 A(I- 1,5 )=C VS (A5 $) 3260 A(I-1,6)=CVS(A6$) 3270 NEXT I 3280 CLOSE #3 3290 RETURN 3300' 3310 '------EX.BAS: Subroutine to output data to D/A on DDA06 — 3320' 3330 'D=data range (0-4095), NC=Channel (0-5), Base=I/0 address 3340 XH%=INT(D/256) 'Workout high byte 3350 XL%=D-256*XH% 'remainder^ low byte 3360 OUT BASE +2 *NC,XL% 'write low byte to D/A 3370 OUT BASE +1+2*NC,XH% 'write high byte & load D/A 3380 RETURN 3390' 3400 '------3 order polynominal equation ------3410' 3420 DIM MTX(6,7),SM(10),RT(6),X(5),Y(5) 3430 FOR 1=1 TO 5 3440 X(I)=TIMS-(5-I)*DT 3450 NEXT I 3460 Y(1)=GCR1 3470 Y(2)=GCR2 3480 Y(3)=GCR3 3490 Y(4)=GCR4 3500 Y(5)=GCR5 3510 ' PERFORM LINEAR REGRESSION -...... 3520 LOCATE 24,l:PRINT"POLYNOM - PERFORMING LINEAR REGRESSION"; 3530 ORD=2 230 3540 FOR 1=1 TO 2*ORD 3550 SM(I)=0 3560 NEXT I 3570 LOCATE 1,68:PRINT TIMES 3580 FOR I = 1 TO ORD+1 3590 RT(I)=0 3600 NEXT I 3610 FORPNT = 1 TO 5 3620 FOR 1= 1 TO ORD*2 3630 SM(I)=SM(I) + X(PNT)AI 3640 NEXT I 3650 FORI= 1 TO ORD+1 3660 IF 1=1 THEN RT(I)=RT(I) + Y(PNT) 3670 IF i o l THEN RT(I) = RT(I) + Y(PNT)*(X(PNT)A(I-1)) 3680 NEXT I 3690 NEXT PNT 3700MTX(1,1)=5 3710 LOCATE 1,68:PRINT TIMES 3720 FOR 1=1 TO ORD+1 3730 MTX(I,ORD+2)=RT(I) 3740 FOR J=1 TO ORD+1 3750 IF I+ J02 THEN MTX(I,J)=SM(I+J-2) 3760 NEXT J 3770 NEXT I 3780 FOR K = 1 TO ORD 3790 KTMP=K+1 3800 L=K 3810 FOR I=KTMP TO ORD+1 3820 IF ABS(MTX(I,K))>ABS(MTX(L,K)) THEN L=I 3830 NEXT I 3840 LOCATE 1,68:PRINT TIMES 3850 IF L=K THEN GOTO 3910 3860 FOR J=K TO ORD+2 3870 TMP=MTX(K,J) 3880 MTX(K,J)=MTX(L,J) 3890 MTX(L,J)=TMP 3900 NEXT J 3910 FOR 1= KTMP TO ORD+1 3920 FTR = MTX(I,K)/MTX(K,K) 3930 FOR J= KTMP TO ORD+2 3940 MTX(I,J)=MTX(I,J) - FTR * MTX(K,J) 3950 NEXT J 3960 NEXT I 3970 NEXT K 3980 COEF(ORD+l) = MTX(ORD+l,ORD+2)/MTX(ORD+l,ORD+1) 3990 I=ORD 4000 ITMP= 1+1 4010 TOT = 0 4020 FOR J= ITMP TO ORD+1 4030 TOT=TOT + MTX(I,J)*COEF(J) 4040 NEXT J 4050 COEF(I)=(MTX(I,ORD+2)-TOT)/MTX(I,I) 4060 1=1-1 4070 IF I>=1 THEN GOTO 4000 4080 LOCATE 24,1:PRINT SPC(40) 4090 ERASE MTX,SM,RT,X,Y 4100 A$=INKEY$:IF A$="" THEN GOTO 4120 4110 IF ASC(A$)=27 THEN GOTO 4130 4120 GOTO 4160 4130 ERASE COEF 4140 GOSUB 1430 4150 CHAIN "main"„ALL 4160 RETURN 5000'------5010 ' ON/OFF CONTROL FOR OXYGEN AND NITROGEN FLOW RATE 5020'------5025 LOCATE 3,60:PRINT "enter" 5030 IF (DOX < .3) GOTO 5100 5040 IF (DOX > .9) GOTO 5200 5050 GOTO 5300 5100 NC=3 :D=0 'shut down nitrogen flow 5105 LOCATE 4,60:PRINT "open o2 close n2" 5110 GOSUB 3300 'output data to D/A on channel #3 5120 NC=4:D=4095 'turn on oxygen flow 5130 GOSUB 3300 'output data to D/A on channel #4 5140 GOTO 5300 5200 NC=3 :D=4095 'turn on nitrogen flow 5205 LOCATE 4,60:PRINT "open n2 close o2" 5210 GOSUB 3300 'output data to D/A on channel #3 5220 NC=4:D=0 'shut down oxygen flow 5230 GOSUB 3300 'output data to D/A on channel #4 232 5240 GOTO 5300 5300 LOCATE 3,60:PRINT "exit " 5350 RETURN 233 Appendix C.3

10 * 20 '* Function 2: Display data from disk data file * 30 '* Filename: Fun2.bas *

* 50' 60 CLS:KEY OFF 70 LOCATE 1,1:INPUT "Name of data file (e.g. B:M YFILE.DAT),=JUNK" ;FILE$ 80 IF FILES-'" THEN FILE$="JUNK" 90 LOCATE 3,1: INPUT "Description to be used as header ";HEADER$

1 0 0 ' 110 ' Open random access file with records as follows

120 ' 130 OPEN FILES AS #1 LEN = 38 140 FIELD #1,30 AS HD$,2 AS NCS, 2 AS CSCANS, 4 AS FREQS 150 '------Read record and mask our digital data ------160' 170 LOCATE 24,1:PRINT" TRANSFERING DATA FROM DISK"; 180 GET #1, 1 'get record from record#l 190 HEADER$=HD$ 200 LOCATE 1,1 : PRINT HEADERS 210 NC%=CVI(NC$):CSCAN%=CVI(CSCAN$):FREQ=CVS(FREQ$) 220 NN=CSCAN%-1 230 CLS 'clear screen for logging mode and display title 240 LOCATE 25,1 :PRINT"DATAKER.BAS -- DASH-16 Data logging utility 250 LOCATE 1,1:PRINT"** ANALOG DATA ***" 260 LOCATE 3,1:PRINT" Time (min) Glu.Con. pH Temp D.O. OD GCR" 270 LOCATE 4,1:PRINT"...... " 280 PAGE=1 290 LOCATE 22,60 : PRINT"** Page # = ":LOCATE 22,70:PRINT PAGE 300 ROW = 5 3 io '*** Routines to scale & linearize data can be inserted here *** 320 'Remember to change record structure if you store real variables 330 DIM TIME(NN),CH0%(NN),CH1%(NN),CH2%(NN),CH3%(NN), 234 CH4%(NN),GCR(NN) 340 NR=2 350 FIELD #1, 4 AS TIMS, 2 AS CH0$,2 AS CH1S, 2 AS CH2S, 2 AS CH3S, 2 AS CH4S, 4 AS GCRS 360 FOR 1=0 TO NN 370 LOCATE ROW,l 380 GET #1, NR 390 TIME(I)=CVS(TIM$) 400 CH0%(I)=CVI(CH0$) 'Glucose conc. in (0-4095) 410 CH 1%(I)=CVI(CH 1 $) ’pH in (0-4095) 420 CH2%(I)=CVI(CH2$) 'Temp, in (0-4095) 430 CH3%(I)=CVI(CH3$) 'D.O. in (0-4095) 440 CH4%(I)=CVI(CH4$) 'OD in (0-4095) 450 GCR(I)=CVS(GCR$) 'Glue, consumption rate (g/min) in real # 460 TIMS=TIME(I) 470 GC=(CH0%(I)*50)/4095 480 PH=(CHl%(I)*10)/4095 490 TEMP=(CH2%(I)*100)/4095 500 DOX=(CH3%(I)*1)/4095 510 OD=(CH4%(I) *50)/4095 520 GCRS=GCR(I) 530 PRINT USING "####.# ##.##MM U.U #M# M.U ###.##";TIMS;GC;PH;TEMP;DOX;OD;GCRS 540 ROW = ROW+1 550 IF ROW < 22 GOTO 610 'pause to scroll next screen of data 560 LOCATE 23,1: PRINT" - Press any key to continue display - ";:PRINT" to exit" 570 A$=INKEY$ : IF A$="" GOTO 570 580 IF ASC(A$)=27 THEN CLOSE #l:CLS:LOCATE 1,1:END 590 PAGE=PAGE+1 600 ROW=5:LOCATE 22,70:PRINT PAGE 610 NR=NR+1 620 NEXT I 630 CLOSE #1 640 LOCATE 24,1 : PRINT SPC(79) 650 ERASE TIME,CH0%,CH1%,CH2%,CH3%,CH4%,GCR 660 LOCATE 23,1:PRINT SPC(79) 670 LOCATE 23,20:PRINT " » » Hit any key to go back to Main Program ««" 680 A$=INKEY$ : IF A$="" GOTO 680 690 CHAIN "main",,ALL Appendix C.4

20 '* Function 3: Print out data from disk data file 30 '* Filename: Fun3.bas

50' 60 CLS:KEY OFF 70 LOCATE 1,1:INPUT "Name of data file (e.g. B:MYFELE.DAT),=JUNK";FILE$ 80 IF FILES-'" THEN FILES-'JUNK" 90 LOCATE 3,1: INPUT "Description to be used as header ";HEADER$

1 0 0 ' 110 ' Open random access file with records as follows:-

1 2 0 ' 130 OPEN FILES AS #1 LEN = 38 140 FIELD #1,30 AS HD$,2 AS NCS, 2 AS CSCANS, 4 AS FREQS 150 '------Read record and mask our digital data ------160' 170 LOCATE 24,1:PRINT" TRANSFERING DATA FROM DISK"; 180 GET #1,1 'get record from record# 1 190 HEADER$=HD$ 200 LOCATE 1,1 : PRINT HEADERS 210 NC%=CVI(NC$):CSCAN%=CVT(CSCAN$):FREQ=CVS(FREQ$) 220 NN=CSCAN%-1 230 CLS 'clear screen for logging mode and display title 240 LOCATE 25,1 :PRINT"DATAKER.BAS - DASH-16 Data logging utility 250 LOCATE 12,35:PRINT " « PRINTING » " 260 LOCATE 22,1:PRINT " -Press to abandon printing 270 'Get record 280 LPRINT :LPRINT FILE$:LPRINT HEADERS :LPRINT 290 LPRINT" Time (min) Glu.Con. pH Temp D.O. OD GCR" 300 LPRINT"...... 3 jo '*** Routines to scale & linearize data can be inserted here *** 320 'Remember to change record structure if you store real variables 330 DIM TIME(NN),CH0%(NN),CH1%(NN),CH2%(NN), CH3%(NN),CH4%(NN),GCR(NN) 340 NR=2 350 FIELD #1, 4 AS TIMS, 2 AS CH0$,2 AS CH1S, 2 AS CH2S, 2 AS CH3S, 2 AS CH4$,4 AS GCRS 360 FOR 1=0 TONN 370 GET #1, NR 380 TIME(I)=CVS(TIM$) 390 CH0%(I)=CVI(CH0$) 'Glucose conc. in (0-4095) 400 CH1%(I)=CVI(CH1$) 'pH in (0-4095) 410 CH2%(I)=CVI(CH2$) 'Temp, in (0-4095) 420 CH3%(I)=CVI(CH3$) 'D.O. in (0-4095) 430 CH4%(I)=CVI(CH4$) ’OD in (0-4095) 440 GCR(I)=CVS(GCR$) 'Glue, consumption rate (g/min) in real # 450 TIMS=TIME(I) 460 GC=(CH0%(I) *50)/4095 470 PH=(CHl%(I)*10)/4095 480 TEMP=(CH2%(I)* 100)/4095 490 DOX=(CH3%(I)*1)/4095 500 OD=(CH4%(I)*50)/4095 510 GCRS=GCR(I) 520 LPRINT USING "####.# ##M M.M ##.###M# MM# ###.##";TIMS;GC;PH;TEMP;DOX;OD;GCRS 530 A$=INKEY$ : IF A$="" GOTO 550 540 IF ASC(A$)=27 THEN CLOSE #l:CLS:LOCATE 1,1:END 550 NR=NR+1 560 NEXT I 570 CLOSE #1 580 LOCATE 24,1 : PRINT SPC(79) 590 ERASE TIME,CH0%,CH1%,CH2%,CH3%,CH4%,GCR 600 LOCATE 22, LPRINT SPC(79) 610 LOCATE 22, LPRINT "Finish Printing" 620 LOCATE 23,20:PRINT " » » Hit any key to go back to Main Program ««" 630 A$=INKEY$ : IF A$="" GOTO 630 640 CHAIN "main"„ALL 237 Appendix C.5

20 '* Function 4: Generate Lotus 1-2-3 files from disk data file 30 '* Filename: Fun4.bas

50' 60 CLS:KEY OFF 70 LOCATE 1,1:INPUT "Name of data file (e.g. B:M YFILE.DAT),=JUNK";FILE$ 80 IF FILES-'" THEN FILE$="JUNK" 90 LOCATE 3,1: INPUT "Description to be used as header ";HEADER$

1 0 0 ' 110 '------Open random access file with records as follows:-

120 ' 130 OPEN FILES AS #1 LEN = 38 140 FIELD #1,30 AS HD$,2 AS NCS, 2 AS CSCANS, 4 AS FREQS 150 '------Read record and mask our digital data ------160' 170 GET #1,1 'get record from record# 1 180 HEADER$=HD$ 190 LOCATE 5,1 : PRINT HEADERS 200 NC%=CVI(NC$):CSCAN%=CVI(CSCAN$):FREQ=CVS(FREQ$) 210 NN=CSCAN%-1 220 NR=1 230 LOCATE 9,LPRINT " If F$= Return";:PRINT " Then file will be stored in junk4.pm file" 240 LOCATE 7,1 .'INPUT "Lotus.pm file name [DRIVE]: Name (Automatic .pm ext.):";F$ 250 CLS 260 IF F$="" THEN F$="junk4" 270 LOCATE 12,25 .'PRINT " « Transferring to Lotus 1-2-3 files » " 280 LOCATE 24,LPRINT" TRANSFERING DATA FROM DISK"; 290 F$=F$+".pm" 300 OPEN F$ FOR OUTPUT AS #2 310 PRINT #2, HDS, NCS, CSCANS, FREQS 320 DIM TIME(NN),CH0%(NN),CH1%(NN),CH2%(NN), CH3 %(NN), CH4%(NN), GCR(NN) 330 NR=2 340 FIELD #1, 4 AS TIMS, 2 AS CH0$,2 AS CH1S, 2 AS CH2S, 2 AS CH3S, 2 AS CH4S, 4 AS GCRS 238 350 FOR 1=0 TO NN 360 GET #1, NR 370 TIME(I)=CVS(TIM$) 380 CH0%(I)=CVI(CH0$) 'Glucose conc. in (0-4095) 390 CH 1%(I)=CVI(CH 1 $) 'pH in (0-4095) 400 CH2%(I)=CVI(CH2$) 'Temp, in (0-4095) 410 CH3%(I)=CVI(CH3$) 'D.O. in (0-4095) 420 CH4%(I)=CVI(CH4$) 'OD in (0-4095) 430 GCR(I)=CVS(GCR$) 'Glue, consumption rate (g/min) in real # 440 TIMS=TIME(I) 450 GC=(CH0%(I)*50)/4095 460 PH=(CH1%(I)* 10)/4095 470 TEMP=(CH2%(I)* 100)/4095 480 DOX=(CH3%(I)* l)/4095 490 OD=(CH4%(I)*50)/4095 500 GCRS=GCR(I) 510 T$=STR$(TIMS) 520 C0$=STR$(GC) 530 C1$=STR$(PH) 540 C2$=STR$(TEMP) 550 C3$=STR$(DOX) 560 C4$=STR$(OD) 570 C5$=STR$(GCRS) 580 PRINT #2, T$,C0$,C1$,C2$,C3$,C4$,C5$ 590 A$=INKEY$ : IF A$="" GOTO 610 600 IF ASC(A$)=27 THEN CLOSE :CLS:LOCATE 1,1:END 610 NR=NR+1 620 NEXT I 630 CLOSE 640 LOCATE 24,1 : PRINT SPC(79) 650 ERASE TIME,CH0%,CH1%,CH2%,CH3%,CH4%,GCR 660 LOCATE 22, LPRINT SPC(79) 670 LOCATE 22,30:PRINT "- Finish Transferring -" 680 LOCATE 23,20:PRINT " » » Hit any key to go back to Main Program ««" 690 A$=INKEY$ : IF A$="" GOTO 690 700 CHAIN "main"„ALL 239 Appendix C.6

20 '* Function 5: Generate VAX files from disk data file 30’* Filename: Fun5.bas 40'**************************************************************** 50' 60 CLS:KEY OFF 70 LOCATE 1,1:INPUT "Name of datafile (e.g. B:M YFILE.DAT),=JUNK";FILE$ 80 IF FILES-'" THEN FILE$="JUNK" 90 LOCATE 3,1: INPUT "Description to be used as header ";HEADER$

100 ' 110 ' Open random access file with records as follows:-

120 ' 130 OPEN FILES AS #1 LEN = 38 140 FIELD #1,30 AS HD$,2 AS NCS, 2 AS CSCANS, 4 AS FREQS 150 '------Read record and mask our digital data ------160' 170 GET #1, 1 'get record from record#! 180 HEADER$=HD$ 190 LOCATE 5,1 : PRINT HEADERS 200 NC%=CVI(NC$):CSCAN%=CVI(CSCAN$):FREQ=CVS(FREQ$) 210 NN=CSCAN%-1 220 NR=1 230 LOCATE 9,LPRINT "If F$= Return";:PRINT "Then file will be stored in junk5.dat file" 240 LOCATE 7,1:INPUT "VAX.DAT file name [DRIVE]: Name (Automatic .DAText.):";F$ 250 CLS 260 IF F$="" THEN F$="junk5" 270 LOCATE 12,25 :PRINT " « Transferring to VAX files» " 280 LOCATE 24,LPRINT" TRANSFERING DATA FROM DISK"; 290 F$=F$+".dat" 300 OPEN F$ FOR OUTPUT AS #2 310 PRINT #2, HDS, NCS, CSCANS, FREQS 320 PRINT #2," Time (min) Glu.Con. pH Temp D.O. OD GCR" 330 DIM TIME(NN),CH0%(NN),CH1%(NN),CH2%(NN), CH3 %(NN), CH4%(NN), GCR(NN) 340 NR=2 240 350 FIELD #1, 4 AS TIM$, 2 AS CH0$,2 AS CH1$, 2 AS CH2$, 2 AS CH3$, 2 ASCH4$,4 AS GCR$ 360 FOR 1=0 TO NN 370 GET #1, NR 380 TIME(I)=CVS(TIM$) 390 CH0%(I)=CVI(CH0$) 'Glucose conc. in (0-4095) 400 CHI%(I)=CVI(CH 1 $) 'pH in (0-4095) 410 CH2%(I)=CVI(CH2$) 'Temp, in (0-4095) 420 CH3%(I)=CVI(CH3$) 'D.O. in (0-4095) 430 CH4%(I)=CVI(CH4$) 'OD in (0-4095) 440 GCR(I)=CVS(GCR$) 'Glue, consumption rate (g/min) in real # 450 TIMS=TIME(I) 460 GC=(CH0%(I)*50)/4095 470 PH=(CH1%(I)* 10)/4095 480 TEMP=(CH2%(I)* 100)/4095 490 DOX=(CH3 %(I) * l)/4095 500 OD=(CH4%(I)*50)/4095 510 GCRS=GCR(I) 520 PRINT #2,USING'MM.# ##.## ##M ##.## #.### MM ###.##";TIMS;GC;PH;TEMP;DOX;OD;GCRS 530 A$=INKEY$ : IF A$="" GOTO 550 ' 540 IF ASC(A$)=27 THEN CLOSE :CLS:LOCATE 1, LEND 550 NR=NR+1 560 NEXT I 570 CLOSE 580 LOCATE 24,1 : PRINT SPC(79) 590 ERASE TIME,CH0%,CH1%,CH2%,CH3%,CH4%,GCR 600 LOCATE 22, LPRINT SPC(79) 610 LOCATE 22,30:PRINT Finish Transferring -" 620 LOCATE 23,20:PRINT " » » Hit any key to go back to Main Program ««" 630 A$=INKEY$ : IF A$="" GOTO 630 640 CHAIN "main"„ALL 241 Appendix C.7

************************ 20 '* Function 6: Examples D/A output on DDA 06 30 •'* Filename: Fun 6.bas 4QI*************************************************************** 50' 60 '------INITIAL SCREEN PRE-AMBLE------70 SCREEN 0,0,0:WIDTH 80:CLS: KEY OFF 80' 90 ' ------STEP 1: LOAD DASH16.BIN DRIVER BY CONTRACTING ORKSPACE— 100 CLEAR, 49152! 110 DEF SEG = 0 120 SG = 256 *PEEK(&H511)+PEEK(&H510) 130 SG=SG+491521/16 140 DEF SEG = SG 150 BLOAD "dashl 6.bin",0 160' 170 ' STEP 2: INITIALIZE WITH MODE 0------180 DIM DIO%(4) 190 OPEN "dashl 6.adr" FOR INPUT AS#1 200 INPUT #1, BASE% 210 CLOSE #1 220 DIO%(0) = BASE% 230 DIO%(l) = 2 240 DIO%(2) = 3 250 DASH 16 = 0 260 FLAG%=0 270 MD%=0 280 CALL DASH 16 (MD%,DIO%(0),FLAG%) 290 IF FLAG%o0 THEN PRINT "installation error":STOP

^ 0 01 jjc 5J1 *jc jjc jj* f|c jjc)jc jjc jjf #|C jJ* »jc $|c *jc §jc #|» jjc jjc #|c #|C jjc 5^C sj* 5^C j|* jjs *{c #|» s|c *jc 5^C jj? ^ jjc 3^C j|C «j( Sjc ?jc 310 '* THE CALIBRATION OF COLE-PARMER PUMP 320 '* OUTPUT CHANNELS (#0,#1,#2,#3,#4,#5) ON DDA-06 ARE VAIL ABLE*

340 DIM COUNT(IO) 350 DIM COEF(6),MTX(6,7),SM( 10),RT(6) 360 BASE=768 370 LOCATE 1,5:PRINT "Calibation of Cole-parmer pump" 380 LOCATE 3,5:PRINT "Output channels (#0,#1,#2,#3,#4,#5) are available" 390 LOCATE 5,5:INPUT "Total number of channels will be calibrated <=6):";N$ 400 N%=VAL(N$) 410 IF N%>=1 AND N%<=6 THEN GOTO 450 420 BEEP 430 LOCATE 5,65:PRINT " 440 GOTO 390 450 LOCATE 7,5:INPUT "Enter the number of calibration for each ump(<= 10)" ;NUMC 460 GOSUB 760 'open pump.dat files for the storage of poly, oef. 470 FOR 11=1 TO N% 480 CLS 490 NC=II-1 500 LOCATE 1, LPRINT "Calibration of the pump on channel #";NC 510 FOR J=1 TO NUMC 520 LOCATE (J+l)*2, LPRINT "number=";J;:PRINT " Enter D/A data in its (0-4095) to start the pump:" 530 LOCATE (J+l)*2+l, LPRINT " Enter D/A data in bit (0) o top the pump:" 540 NEXT J 550 FOR K=1 TO NUMC 560 LOCATE (K+1)*2,65:INPUT COUNT(K):D=COUNT(K) 570 GOSUB 870 580 LOCATE (K+1)*2+1,65 :INPUTD 590 GOSUB 870 600 NEXT K 610 GOSUB 940 620 LSET A1 $=MKS$(COEF(1)) 630 LSET A2$=MKS$(COEF(2)) 640 LSET A3 $=MKS$(COEF(3)) 650 LSET A4$=MKS $(COEF(4)) 660 LSET A5$=MKS$(COEF(5)) 670 LSET A6$=MKS$(COEF(6)) 680 PUT #1,11 690 ERASE X,Y 700 NEXT II 710 GOSUB 800 720 CLOSE #1 730 ERASE DIO%,COUNT,COEF,MTX,SM,RT 243 740 CHAIN"main"„ALL 750 END 760 '------Open pump file for the storage of poly. coef. ------770 OPEN "pump" AS #1 LEN=24 780 FIELD #1, 4 AS Al$, 4 AS A2$, 4 AS A3$, 4 AS A4$, 4 AS A5$, 4 AS6$ A 790 RETURN 800 '------Open Index 6 file------810 OPEN "index 6" AS #2 LEN=2 820 FIELD #2, 2 AS BN$ 830 LSET BN$=MKI$(N%) 840 PUT #2,1 850 CLOSE #2 860 RETURN 870 1------Ex.Bas :subrountine to output data to D/A on DA-06 880 'D=data range (0-4095), NC= channel (0-5), Base = i/O address 890 XH%=INT(D/256) 'work out high bye 900 XL%=D-256*XH% 'remainder = low byte 910 OUT BASE + 2 *NC, XL% 'write low byte to D/A 920 OUT BASE +1 +2*NC, XH% 'write high byte & load D/A 930 RETURN ********************** 950 '* 960 '* FIFTH ORDER LEAST SQUARES POLYNOMIAL UTILITY 970 '* MetraByte Corporation Rev. 1.10 8/16/83 9g0'************************************************************ 990' 1000 ' This program evaluates the coefficients C l -6 for the polynomial 1010 'approximation:-

1020 ' 1030' Y = Cl + C2*X + C3*XA2 + C4*XA3 + C5*XA4 + C6*XA5 1040’ 1050 ' such that the sum of the squares of the errors between the actual 1060 'value of Y and the polynomial value of Y for all data points entered 1070 'is minimised (i.e. curve fitting). 1080 ' This approximation is useful for linearizing transducer outputs. 1090 'e.g. flowmeters, thermocouples, tacho-generators etc.. The transducer 244 1100 'output is obtained from the A/D converter (suitably scaled if required) 1110 'as variable X and the linearized output from the transducer e.g. flow, 1120 'temperature, velocity etc. is calculated as variable Y. The coefficients 1130 'Cl-6 are calculated from a set of Y,X data or calibration points. 1140 ' Type RUN(CR) to run the program. The prompts are self explanatory. 1150 'You should be prepared to provide the number of data pdints (N) and the 1160 'data (arrays X(N), Y(N)). The data is displayed and you may make any 1170 'changes to correct entry mistakes. The program then proceeds to perform 1180 'a regression analysis to calculate the coefficients of the polynomial. 1190 'You are prompted to select the order required, up to 5th. order. Usually 1200 '5th. order is the best option unless you want to experiment with trying 1210 'a lower order. After the analysis is finished, the coefficients are 1220 'displayed and you can check the conformance by inputting various values 1230 'of X and seeing how accurate Y is. If you wish, before exiting the 1240 'program, you can run the regression at another order on the same data 1250 'to see how good the conformance is with a different order polynomial. 1260' 1270 ' Once the coefficients are evaluated the polynomial can be inserted 1280 'into your programs as a subroutine. The neatest way is to use a loop to 1290 'evaluate it as follows:- 1300' 1310’ xxxOO Y = COEF(l) 1320 ' xxxlO FOR CNT% = 5 TO 1 STEP -1 1330 ' xxx20 Y = Y + COEF(CNT% + 1) * X A CNT% 1340 ' xxx30 NEXT CNT% 245 1350 1 xxx40 RETURN 1360' 1370' 1380 ' START - INITIALIZATION SECTION ------

1390 SCREEN 0,0,0:KEY OFF:CLS:LOCATE 25,l:PRINT"POLYNOM"; 1400 — DATA POINT ENTRY------

1410 CLS:LOCATE 25,l:PRINT"POLYNOM - DATA POINT ENTRY"; 1420 LOCATE 2, LPRINT "Number of data points that you should enter? " ;NUMC :N=NUMC 1430 'ERASE X,Y 1440 DIM X(N), Y(N) 1450 LOCATE 25,l:PRINT"POLYNOM - DATA POINT ENTRY";:LOCATE 2,1 1460 FORNUM = 1 TON 1470 ROW = CSRLIN+1 1480 LOCATE 25,40:PRINT USING "ENTERING POINT #### OF ####";NUM,N; 1490 LOCATE ROW, LPRINT "POINT # =";NUM:LOCATE ROW+1,10:PRINT "COUNT = ";COUNT(NUM):LOCATE ROW+1,30:INPUT "FLOW RATE (liter/hr) = " ;X(NUM): Y(NUM)=COUNT(NUM) 1500 NEXT NUM 1510 — DISPLAY & CORRECT DATA POINTS------

1520 DISP=0:FLG=0 1530 CLS:LOCATE 25,l:PRINT"POLYNOM - DISPLAY & CORRECT DATA"; 1540 LOCATE 1, LPRINT "POINT # COUNT(output) FLOW RATE (l/hr)(input)" 1550 PRINT"...... " 1560 FOR 1= 1 TO N 1570 PRINT I,Y(I),X(I) 1580 IF CSRLIN = 20 THEN GOSUB 1620 1590 NEXT I 1600 FLG=1:GOSUB 1620 1610 GOTO 1760 1620 'Scroll display 1630 LOCATE 22, LPRINT SPC(79);:LOCATE 22,1:INPUT "WHICH POINT DO YOU 246 WISH TO CHANGE (Enter # or 0 if none)? ",P 1640 IF P>N THEN GOTO 1630 1650 IF P=0 THEN GOTO 1700 1660 LOCATE 22,l.PRINT SPC(79);:LOCATE 22,l:PRINT,,POINT ";P;" ENTER DATA FLOW RATE (input) - ";:INPUT X 1670 Y(P)=COUNT(P) :X(P)=X 1680 LOCATE P+2-17*DISP,LPRINT SPC(79);:LOCATE CSRLIN, LPRINT P,Y(P),X(P) 1690 GOTO 1630 1700 DISP=DISP +1 1710 IF FLG = 1 GOTO 1750 1720 CLS:LOCATE 25,l:PRINT"POLYNOM - DISPLAY & CORRECT DATA"; 1730 LOCATE 1,1: PRINT "POINT # COUNT (output) FLOW RATE(l/hr) (input)" 1740 PRINT"...... " 1750 RETURN 1760 ' PERFORM LINEAR REGRESSION------

1770 CLS:LOCATE 25,l:PRINT"POLYNOM - PERFORMING LINEAR REGRESSION"; 1780 LOCATE 2,l:INPUT"ORDER OF ANALYSIS REQUIRED (0-5)? ",ORD 1790 IF ORD <0 OR ORD>5 THEN GOTO 1780 1800 LOCATE 10,20:PRINT"WAIT - REGRESSION ANALYSIS IN PROGRESS" 1810 FOR 1=1 TO 2*ORD 1820 SM(I)=0 1830 NEXT I 1840 FORI = 1 TO ORD+1 1850 RT(I)=0 1860 NEXT I 1870 FORPNT = 1 TON 1880 FOR 1= 1 TO ORD*2 1890 SM(I)=SM(I) + X(PNT)AI 1900 NEXT I 1910 FORI = 1 TO ORD+1 1920 IF 1=1 THEN RT(I)=RT(I) + Y(PNT) 1930 IF i o l THEN RT(I) = RT(I) + Y(PNT)*(X(PNT)A(I-1)) 1940 NEXT I 247 1950 NEXT PNT 1960 MTX(1,1)=N 1970 FOR 1=1 TO ORD+1 1980 MTX(I,ORD+2)=RT(I) 1990 FOR J=1 TO ORD+1 2000 IF I+ Jo 2 THEN MTX(I,J)=SM(I+J-2) 2010 NEXT J 2020 NEXT I 2030 FOR K = 1 TO ORD 2040 KTMP=K+1 2050 L=K 2060 FOR I=KTMP TO ORD+1 2070 IF ABS(MTX(I,K))>ABS(MTX(L,K)) THEN L=I 2080 NEXT I 2090 IF L=K THEN GOTO 2150 2100 FOR J=K TO ORD+2 2110 TMP=MTX(K, J) 2120 MTX(K,J)=MTX(L,J) 2130 MTX(L,J)=TMP 2140 NEXT J 2150 FOR 1= KTMP TO ORD+1 2160 FTR = MTX(I,K)/MTX(K,K) 2170 FOR J= KTMP TO ORD+2 2180 MTX(I,J)=MTX(I,J) - FTR * MTX(K,J) 2190 NEXT J 2200 NEXT I 2210 NEXT K 2220 COEF(ORD+l) = MTX(ORD+l,ORD+2)/MTX(ORD+l,ORD+1) 2230 I=ORD 2240 ITMP= 1+1 2250 TOT = 0 2260 FOR J= ITMP TO ORD+1 2270 TOT=TOT + MTX(I,J)*COEF(J) 2280 NEXT J 2290 COEF(I)=(MTX(I, ORD+2)-TOT)/MTX(I,I) 2300 1=1-1 2310 IF I>=1 THEN GOTO 2240 2320 ' DISPLAY COEFFICIENTS------

2330 CLS:LOCATE 1,1 2340 FOR 1=1 TO ORD+1 248 2350 PRINT"COEF(";I;") = ”;COEF(I) 2360 NEXT I 2370 ' TEST FIT------

2380 LOCATE 25,LPRINT SPC(79):LOCATE 25,l:PRINT"POLYNOM - TEST CONFORMANCE"; 2390 LOCATE 9,1:PRINT"TEST CONFORMANCE" :PRINT" ------" 2400 LOCATE 12,LPRINT SPC(79);:LOCATE 12,1:INPUT "FLOW RATE VALUE (type Q to quit)? ",A$ 2410 IF A$="Q" OR A$="q" THEN GOTO 2490 2420 X=VAL(A$) 2430 Y = COEF(l) 2440 FOR CNT%= 5 TO 1 STEP -1 2450 Y = Y + COEF(CNT%+l) * XACNT% 2460 NEXT CNT% 2470 LOCATE 14,LPRINT SPC(79):LOCATE 14,l:PRINT"Calculated count (output) = ";Y;" for flow rate (input) = ";X 2480 GOTO 2400 2490 LOCATE 14,LPRINT SPC(79):LOCATE 14,1:INPUT "TRY REGRESSION WITH A DIFFERENT ORDER (Y/N)? ",A$ 2500 IF A$="y" OR A$="Y" THEN GOTO 2520 2510 LOCATE 25, LPRINT SPC(79):LOCATE 20,1:RETURN 2520 ERASE SM, MTX, RT, COEF 2530 DIM COEF(6), MTX(6,7), SM(10), RT(6) 2540 GOTO 1760 2550 RETURN APPENDIX D A COMPUTER PROGRAM FOR THE KINETIC MODEL IN BATCH FERMENTATION

Kinetic model for batch fermention

* delcare array and variable *

implicit real (a-z) dimension xc( 0:1000),xf( 0:1000),s(0:1000) dimension p( 0:1000),xt( 0:1000),f(0:1000) dimension xshow( 0:1000),pshow( 0:1000),fshow( 0:1000) integer i,j real umc,um,ks,beta,dt,yxsc,yxsf,ypsc,ypsf,tlag,uc,uf real total_time

* Constant *

4* • ks = 0.1

******** beta : segregational instability beta = 0.08

******** d t: time interval (hr) dt = 0.05

******** yxsc : cell yield of plasmid-carrying cells yxsc = 0.22214

******** yxsf: cell yield of plasmid-free cells yxsf = 0.25992 2 4 9 250 c ******** ypSC . production yield of plasmid-carrying cells ypsc = 0.004895 c ******** tlag : lag time (hr) tlag = 2.5 c ******** ujho ; max> specific growth rate of plasmid-carrying cells q ******** (i/hr) umc = 0.286 c ******** • max Specific growth rate of plasmid-free cells q ******** ( 1/hr) umf = 0.17 c c * Initial Condition * c c ******** xt(0) : initial cell concentration (g/L) xt(0) = 0.0175 c ******** f^o) : initial fraction of plasmid-carrying cells f(0) = 0.8053 c ******** s(o) ; initial glucose concentration (g/L) s(0) = 3.93 c ******** total_time at 0 hr total_time = 0.0 c * Start the program *

xc( 0) = xt( 0) * f( 0) xf( 0) = xt( 0) - xc( 0)

do i = 1, 700, 1 total time = total time + dt 251 if (total_tiine.lt.tlag) goto 10 uc = ( umc * s(i-l) ) / ( ks + s(i-l) ) uf = ( rnnf * s(i-l)) / ( ks + s(i-l)) xc(i) = xc(i-l) + ( ( 1.0 - beta) * uc * xc(i-l)) * dt xf(i) = xf(i-l) + ( ( beta * uc * xc(i-l) ) + ( uf * xf(i-l) ) ) * dt s(i) = s(i-l)- ( ( uc * xc(i-l) / yxsc) + ( uf * xf(i-l) / yxsf))*dt p(i) = p(i-l) + ( ypsc * uc * xc(i-l) / yxsc) * dt xt(i) = xc(i) + xf(i) f(i) = xc(i) / xt(i) goto 20

10 xt(i) = xt(i-l) xc(i) = xc(i-l) xf(i) = xf(i-l) s(i) = s(i-l) P(i) = P(i-l) f(i) = f(i-l)

20 xshow(i) = xt(i) * 5.0 pshow(i) = p(i) * 10.0 fshow(i) = f(i) * 5.0

write(41, ■*)total_time,xshow(i) write(42, *)total_time, s(i) write(43, *)total_time,pshow(i) write(44, *)total_time,fshow(i) enddo

stop end LIST OF REFERENCES

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