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Growth of a genetically-modified Pichia pastoris and protein production in an industrial waste stream Yuen, Vivian Hoi Nga 2004

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Growth of a Genetically-Modified Pichia pastoris and Protein Production in an Industrial Waste Stream by Vivian Hoi Nga Yuen B . A . S c , University of British Columbia, 2002  A THESIS SUBMITTED IN P A R T I A L F U L F I L L M E N T OF THE REQUIREMENTS FOR T H E D E G R E E OF  M A S T E R OF APPLIED SCIENCE in T H E F A C U L T Y OF G R A D U A T E STUDIES (Department of Chemical and Biological Engineering)  We accept this thesis as conforming to the required standard  THE UNIVERSITY OF BRITISH C O L U M B I A  July 2004 © Vivian Hoi Nga Yuen, 2004  jggRITISH  COLUMBIA  F A C U L T Y OF G R A D U A T E S T U D I E S  Library Authorization  In p r e s e n t i n g t h i s t h e s i s in partial fulfillment of t h e r e q u i r e m e n t s for an a d v a n c e d d e g r e e at t h e U n i v e r s i t y o f British C o l u m b i a , I a g r e e t h a t t h e L i b r a r y s h a l l m a k e it freely available f o r r e f e r e n c e a n d study. I f u r t h e r a g r e e t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y p u r p o s e s m a y b e g r a n t e d by t h e h e a d o f m y d e p a r t m e n t o r b y his o r h e r r e p r e s e n t a t i v e s . It is u n d e r s t o o d t h a t c o p y i n g or p u b l i c a t i o n o f t h i s t h e s i s f o r f i n a n c i a l gain shall n o t be a l l o w e d w i t h o u t m y w r i t t e n p e r m i s s i o n .  28/07/2004  Hoi N g a ( V i v i a n ) Y u e n N a m e o f A u t h o r (please  Date (dd/mm/yyyy)  print)  Title o f T h e s i s :  G r o w t h o f a G e n e t i c a l l y - M o d i f i e d P i c h i a pastoris a n d P r o t e i n P r o d u c t i o n in a n I n d u s t r i a l W a s t e S t r e a m  Degree:  M a s t e r of A p p l i e d S c i e n c e  Department of  C h e m i c a l a n d B i o l o g i c a l E n g i n e e r i n g , F a c u l t y of A p p l i e d S c i e n c e  Year:  loo  If  T h e U n i v e r s i t y o f British C o l u m b i a Vancouver, B C  Canada  grad.ubc.ca/forms/?formlQ33  last updated: 28-Jul-04  ABSTRACT This study demonstrated the possibility of growing a genetically-modified Pichia pastoris (Geotrichum candidum recombinant Pichia  strain, GS115 (his4), harboring plasmid  YpDC420) and producing a recombinant protein in the distillation column bottom stream of Methanex Corporation, Kitimat, B.C.  The Pichia pastoris strain was grown in an  automatically controlled reactor, which originally contained 1.6 L of 10 g/L yeast extract and 20 g/L peptone, running in continuous mode at a temperature of 30°C, p H of 5.6, and dissolved oxygen concentration of 3.0 g/L. The Methanex wastewater, which had a methanol concentration of 2.5 g/L, was continuously fed into the reactor at dilution rates (D) of 0.011, 0.017, 0.026, 0.034 and 0.042 1/h.  The reactor reached steady state after about 120 hours for D = 0.011, 0.017 and 0.026 1/h. However, the reactor did not reach steady state even at extended running time (>150 hours) for D = 0.034 and 0.042 1/h, which were at or greater than the critical dilution rate, i.e., 0.034 1/h. The cell yield from methanol, product yield from cell, maximum specific growth rate and saturation constant for methanol were 3.3 ± 0.067 g/g, 0.015 + 0.0023 g/g, 0.034 1/h and 4.5 mg/L, respectively.  At the optimum dilution rate of 0.033 1/h, Q  x  and Q> were  maximized with values of 0.26 g/L/h and 4.0 mg/L/h.  Steady state methanol concentrations in the reactor were almost zero when dilution rates were well below the critical dilution rate. The corresponding cell and protein concentrations were about 8 g/L (dry cell weight) and 125 mg/L. As dilution rates approached the critical value, steady state methanol concentration increased while cell and protein concentrations ii  decreased. At the critical dilution rate, cell washout occurred and both steady state cell and protein concentrations reduced to zero. The corresponding methanol concentration in the reactor became the same as the methanol concentration in the feed.  The reactor system model under study could be represented by 4 ordinary differential equations (ODEs) and the following parameters: maximum specific growth rate for methanol = 0.034 1/h, saturation constant for methanol = 4.5 mg/L, cell yield from methanol = 3.3 g/g, product yield from cell = 0.015 g/g, maximum specific growth rate for yeast extract and peptone = 0.20 1/h, saturation constant for yeast extract and peptone = 200 mg/L, and cell yield from yeast extract and peptone = 0.20 g/g. The ODEs were solved numerically and the resultant model predictions compared favourably to the reactor behaviour.  in  TABLE OF CONTENTS ABSTRACT  ii  LIST OF FIGURES  ™  LIST OF T A B L E S  i x  GLOSSARY  x  NOMENCLATURE  x i i  ACKNOWLEDGEMENTS  W  1.0  INTRODUCTION  1  2.0  L I T E R A T U R E REVIEW  3  2.1  Methanol-containing Wastewater  •.. 3  2.1.1  Characteristics  3  2.1.2  Pulp and Paper Industry  4  2.1.3  Methanol Manufacturing Industry  2.2  '.  6  Methanol Removal Methods  7  2.2.1  Steam Stripping  7  2.2.2  Incineration  7  2.2.3  Biodegradation  8  2.3  Methylotrophie YeastPichia pastoris  2.3.1  Characteristics  2.3.2  Reaction Pathways  2.3.3  Advantages of Using Pichia pastoris  2.4 2.4.1  9 9 .....11 14  Protein Expression  15  Lipase  15 iv  2.4.2 2.5  Lipase Production in Previous Works  16  Factors Affecting Growth and Protein Production .:  17  2.5.1  Substrates  17  2.5.2  Temperature..,  18  2.5.3  Dissolved Oxygen  19  2.5.4  pH  19  2.5.5  Foaming  20  2.6  Reactor Operation Modes  20  2.6.1  Advantages of Discontinuous over Continuous Operations  20  2.6.2  Advantages of Continuous over Discontinuous Operations  21  3.0  P R O B L E M DEFINITION  23  4.0  R E S E A R C H OBJECTIVES  24  5.0  M A T E R I A L S A N D METHODS  25  5.1  Media Composition and Storage  25  5.2  Yeast Strain and Storage  26  5.3  Sterilization  27  5.4  Inoculum Preparation in a Shake Flask  27  5.5  Continuous Cultivation in a Computer-controlled Reactor  27  5.5.1  Data Acquisition and Reactor Control System  29  5.5.2  Data Logging  31  5.6 5.6.1  Assays Cell Concentration  •  33  '.  33  v  5.6.2  Methanol Concentration  34  5.6.3  Protein Concentration  34  5.6.4  Lipase Activity  35  .5.7  Data Analysis  •.  ,  36  5.7.1  Non-steady State Material Balance  36  5.7.2  Steady State Material Balance  39  5.7.3  Specific Growth Rate  41  5.7.4  Productivities  42  5.7.5  Critical and Optimum Dilution Rates  44  6.0  RESULTS A N D DISCUSSIONS  47  6.1  Methanol Concentration in the Feed  47  6.2  Cell and Protein Production  47  6.3  Parameters Estimation  50  6.4  Critical Condition  52  6.5  Optimum Condition  6.6  System Model  56  7.0  CONCLUSIONS  62  8.0  RECOMMENDATIONS  64  •  55  REFERENCES  65  APPEND LX A - Calibration Curves  73  APPEND LX B - Matlab Programs  75  A P P E N D I X C - Sample Calculations  78  vi  LIST OF FIGURES Figure 2-1. Three Major Monomers of Lignin  4  Figure 2-2. Typical Methanol Manufacturing Process  6  Figure 2-3. Pictures of Pichia pastoris  9  Figure 2-4. Steps of Expressing Foreign Genes in Pichia pastoris  11  Figure 2-5. Metabolic pathways of Methanol in Pichia pastoris  12  Figure 5-1. Flow Diagram of the Continuous Reactor System  29  Figure 5-2. Components o f the Reactor Control System  30  Figure 5-3. Development of Growth in a Typical Continuous Reactor  39  Figure 5-4. Steady State Concentrations at Different Dilution Rates  44  Figure 6-1. The Effect of Dilution Rate on Cell Density  48  Figure 6-2. The Effect of Dilution Rate on Protein Concentration  48  Figure 6-3. The Effect o f Dilution Rate on Methanol Concentration  49  Figure 6-4. Yields at D = 0.011, 0.017 and 0.026 1/h  51  Figure 6-5. Steady State Cell and Protein Concentrations at Different Dilution Rates  53  Figure 6-6. Steady State Methanol Concentrations at Different Dilution Rates  53  Figure 6-7. Cell and Product Productivities at Different Dilution Rates  55  Figure 6-8. Experimental and Calculated Cell Concentrations at D = 0.011 1/h  59  Figure 6-9. Experimental and Calculated Protein Concentrations at D = 0.011 1/h  59  Figure 6-10. Experimental and Calculated Cell Concentrations at D = 0.017 1/h  60  Figure 6-11. Experimental and Calculated Protein Concentrations at D = 0.017 1/h  60  Figure 6-12. Experimental and Calculated Cell Concentrations at D = 0.026 1/h  ;  61  Figure 6-13. Experimental and Calculated Protein Concentrations at D = 0.026 1/h  61 vii  Figure A - l . Cell Concentration Calibration Curve  73  Figure A-2. Methanol Concentration Calibration Curve  73  Figure A-3. Protein Standard (Bovine Serum Albumin) Concentration Calibration Curve.. 74  viii  LIST OF TABLES Table 2-1. Typical Constituents Concentration in Combined Evaporator Condensate  5  Table 2-2. Representative Functions of Major Elements for Microorganisms  18  Table 5-1. Compositions of Feed Solution  25  Table 5-2. Compositions of Nutrient Solution  26  Table 6-1. Calculated Parameters from Steady State Results  51  Table 6-2. Comparison of Parameters from Current Study to Literature Results  52  Table 6-3. Parameters used for Solving Non-steady State ODEs:  58  ix  GLOSSARY Biological oxygen demand (BOD)  The amount of oxygen that would be consumed by microorganisms to oxidize organic matter or waste in water  Chronic  Exerted over a long time period  Conjunctivitis  Inflammation of the conjunctiva (border of the eye), characterized by redness and often accompanied by a discharge  Dysfunction  Abnormal or impaired functioning  Endogenous  Produced inside an organism or cell  Heterologous  Derived from organisms of a different species  Marker  A gene or group of genes used to identify an individual or a cell that carries it  Mercaptans  Organic chemical compounds of the type R-SH (R = an alkyl group)  Ocular  Of, or relating to the eye  Reference Dose (RfD)  An estimate of a daily oral exposure of a chemical to the  human  population  (including  sensitive  subpopulations) that is likely to be without risk of deleterious non-cancer effects during a lifetime.  A process whereby the genetic code carried by messenger R N A directs the production of proteins from amino acids A self-replicating D N A molecule that is used to transfer foreign D N A fragments between cells Produced from autolyzed yeast cells and is highly soluble in water. It is used as an enrichment in a large number of culture media for general bacteriology  xi  NOMENCLATURE u  Specific growth rate (1/h)  Ucaic, i  Calculated specific growth rate for Experiment i (1/h)  Umax  Maximum specific growth rate (1/h)  P-max, M  Maximum specific growth rate for methanol (1/h)  H-max, Y  Maximum specific growth rate for yeast extract and peptone (1/h)  D  Dilution rate (1/h)  F  Volumetric flow rate (L/h)  kd  Specific death constant (1/h)  Ks  Saturation constant for substrate (g/L)  Ks, M  Saturation constant for methanol (g/L)  Ks, y  Saturation constant for for yeast extract and peptone (g/L)  mM  Specific rate of methanol uptake for maintenance activities (1/h)  my  Specific rate of yeast extract and peptone uptake for maintenance activities (1/h)  nip  Specific rate of product formation due to maintenance (g product/g cell/h)  qp  Specific rate of product formation for all classes of product (1/h)  qp-  Specific rate of product formation not directly linked with energy metabolism (1/h)  qM  Specific rate of methanol uptake (1/h)  qy  Specific rate of yeast extract and peptone uptake (1/h)  QP  Productivity of product formation (g/L/h)  Qx  Productivity of cell formation (g/L/h)  M  Methanol concentration in outlet or in reactor (g/L)  xii  Mi  Methanol concentration in feed (g/L)  S  Substrate concentration (g/L)  t  Time (h)  V  Volume (L)  X  Cell concentration in outlet or in reactor (g/L)  X  0  Cell  concentration in reactor at time 0 (g/L)  Xi  Cell concentration in feed (g/L)  Xt  Cell concentration in reactor at time t (g/L)  Y  Yeast extract and peptone concentration in outlet or in reactor (g/L)  Yi  Yeast extract and peptone concentration in feed (g/L)  Yp/x  Product yield from cell (g  Yp/x,avg  Average product yield from cell (g  Yp/M  Product yield from methanol (g  Y /Y  Product yield from yeast extract and peptone (g product/g yeast extract and e to  Yx/M  Cell yield from methanol (g ceu/g  Yx/M,avg  Average cell yield from methanol (g ceii/g methanol)  Yx/v  Cell yield from yeast extract and peptone (g ceii/g yeast extract and peptone)  P  pro  duct/g ceii)  pr0  duct/g ceii)  oduct/g methanol)  pr  P  met  hanoi)  P  ACKNOWLEDGEMENTS I would like to thank my supervisor, Dr. Sheldon Duff for his valuable advice and help during my graduate studies. I am grateful to my co-supervisor, Dr. Dusko Posarac for his guidance and inspirations. I also appreciate very much the support and help from people in my research group, especially Christine, Norman, Preston, Sharon and Steve.  M y thanks are extended to NSERC for the financial support and Methanex for providing wastewater samples. I would like to acknowledge the staff at the Chemical Engineering Stores, Horace and Qi, for ordering materials and equipment for me.  Endless thanks to my family and friends for their love, care and support.  In particular, I  would like to thank my dad, mom and sister for taking care of me at all times and for everything that they have done for me. I would also like to express my deep gratitude to my brothers and sisters in Christ for their encouragement and prayers. Last but not least, thanks God for the wisdom, guidance, comfort, love and all the things He has given me.  xiv  1.0  INTRODUCTION  Methanol is widely recognized as a hazardous substance.  Acute exposure of humans to  methanol by inhalation or ingestion may result in visual disturbances such as blurred or dimness of vision; and neurological damage, particularly permanent motor dysfunction (National Library of Medicine, 2003; Sittig, 1985). Chronic inhalation or oral exposure to methanol may cause conjunctivitis, headache, giddiness, insomnia, gastric disturbances, visual disturbances, and blindness in humans (Budavari, 1989; Hardman et al., 2001).  Methanol is one of the pollutants in industrial effluents, such as wastewater from pulp and paper industry and methanol manufacturing industry.  The methanol and ammonia  manufacturing plants of Methanex Corporation in Kitimat, B.C., has a waste stream with methanol concentration of 2.5 g/L. One of the potential applications of this waste stream is to grow Pichia pastoris and to produce a recombinant protein in it.  Pichia pastoris is a methylotrophic yeast which can utilize methanol as its sole carbon and energy source.  It has been commonly used as a host for expressing a wide variety of  recombinant proteins. This research is to test the possibility of growing Pichia pastoris and producing a recombinant protein in the Methanex wastewater.  The body of this report begins with a literature review in Section 2.0.  Information on  methanol-containing wastewater and methanol removal methods is presented. Discussions on the characteristics of Pichia pastoris, protein expression and factors affecting growth and  1  protein production follow.  S e c t i o n s 3.0  a n d 4.0  present the p r o b l e m d e f i n i t i o n a n d  thesis  objectives, respectively.  T h e m a t e r i a l s a n d m e t h o d s u s e d to c o n d u c t the e x p e r i m e n t a l w o r k are d i s c u s s e d i n S e c t i o n 5.0.  T h e c u l t u r e m e d i a a n d y e a s t s t r a i n u s e d a r e first d e s c r i b e d , f o l l o w e d b y t h e m e t h o d s o f  sterilizing equipment  and preparing inoculum.  c o n t i n u o u s r e a c t o r is p r o v i d e d next.  A description o f the  T h e assays used to determine  computer-controlled the cell, product  and  substrate c o n c e n t r a t i o n s , a n d the m e t h o d s o f data a n a l y s i s are then d e t a i l e d .  T h e results f r o m the e x p e r i m e n t a l w o r k and data analysis are presented S e c t i o n 6.0.  and discussed in  T h i s s e c t i o n first p r e s e n t s t h e r e s u l t s o f f e e d s t r e a m a n a l y s i s , a n d t h e r e s u l t s o f  c e l l a n d p r o t e i n p r o d u c t i o n i n the reactor.  T h e parameters estimated f r o m the  experimental  results are then presented, f o l l o w e d b y d i s c u s s i o n s o n the critical a n d o p t i m u m c o n d i t i o n s o f the  reactor  system.  T h e system m o d e l used to describe the  p r e s e n t e d at t h e e n d o f S e c t i o n 6.0.  b e h a v i o r o f the  system  is  S e c t i o n 7.0 c o n c l u d e s a l l t h e f i n d i n g s i n t h i s s t u d y a n d  S e c t i o n 8.0 m a k e s r e c o m m e n d a t i o n s f o r f u t u r e r e s e a r c h o n r e l a t e d t o p i c s .  2  2.0  LITERATURE REVIEW  2.1  Methanol-containing Wastewater  2,1.1  Characteristics  M e t h a n o l is o n e o f the pollutants i n industrial effluents.  T w o sources o f methanol-containing  w a s t e w a t e r are f r o m the p u l p a n d paper industry and m e t h a n o l m a n u f a c t u r i n g industry.  M e t h a n o l is c o m p l e t e l y m i s c i b l e i n water. at 2 5 ° C ) .  It h a s a r e l a t i v e l y h i g h v a p o u r p r e s s u r e ( 0 . 1 6 a t m  T h e r e c a n be a significant transfer o f m e t h a n o l to the atmosphere w h e n m e t h a n o l is  i n its p u r e phase.  H o w e v e r o n c e m e t h a n o l dissociates into water, its l o w v a l u e o f H e n r y ' s  L a w c o n s t a n t ( 1 . 0 9 x 1 0 " at 2 5 ° C ) s u g g e s t s t h a t m e t h a n o l i s n o t r e a d i l y t r a n s f e r r e d 4  to  the  v a p o u r p h a s e ( G a f f n e y et a l . , 1 9 8 7 ) . D u e t o its l o w v o l a t i l i t y a n d h i g h s o l u b i l i t y , m e t h a n o l i n w a t e r is n o t l i k e l y t o b e r e m o v e d b y v o l a t i l i z a t i o n ( M a l c o l m P i r n i e Inc., 1 9 9 9 ) .  Alcohols,  which  are  polar molecules, generally  do  not  hydrolyze in water.  Therefore,  m e t h a n o l is stable i n w a t e r and is not l i k e l y to be r e m o v e d b y a b i o t i c , i.e., n o n - b i o l o g i c a l o r chemical,  degradation.  anaerobic conditions.  However,  methanol  is easily b i o d e g r a d e d  in both  aerobic  and  T h e b i o l o g i c a l o x y g e n d e m a n d ( B O D ) e q u i v a l e n t o f m e t h a n o l is  1.0,  i . e . , e a c h k i l o g r a m o f m e t h a n o l e x e r t s a b o u t 1 k g B O D w i t h i n 5 d a y s ( B l a c k w e l l et a l . , 1 9 7 9 ) . Compared mechanism  to  abiotic  degradation  o f methanol  loss  i n the  and soil,  volatilization, groundwater,  biodegradation and  surface  is  water  the  dominant  environments  ( M a l c o l m P i r n i e Inc., 1999).  3  Although the United States Environmental Protection Agency (EPA) has not set a maximum methanol concentration in drinking water, it has set a reference dose (RfE>) of 0.5 mg/kgbody weight/day (Smith et al., 2002). Based on the RfD value, the average body weight and water consumption of an adult, Smith et al. (2002) estimated that a maximum methanol concentration in drinking water to be 3.5 mg/L. Different places may have different allowable upper limits for methanol in drinking water, e.g. 3 - 5 mg/L in North America (United States Environmental Protection Agency, 1993).  2.I.2  Pulp and Paper Industry  In a kraft pulp mill, wood chips are digested under heat and pressure with a caustic solution containing mainly sodium hydroxide (NaOH) and sodium sulphide (Na2S).  The process  separates lignin, a resin that bonds the cell walls of plants, from cellulose. Cellulose is the material used to make paper. During the digestion process, methanol is formed from the methoxyl group of lignin aromatics. Other by-products of digestion are ethanol and sulphur compounds, commonly referred to as total reduced sulphur (TRS).  CH,OH  CH,OH  OH  OH  j^cpuiT^aryl alcohol  coniferyl alcohol  CH OH 2  OH  Figure 2-1. Three Major Monomers of Lignin (Helm, 2000) 4  Methanol is the largest single source of volatile organic compounds (VOC) emissions from kraft pulp mills, accounting for 70 to 90 % of total emissions (Moretti, 2002; Teja et al., 2000).  In a kraft pulping process, the waste streams from the evaporators are usually  condensed into a combined condensate stream, which contains the volatile low molecular weight compounds present in black liquor, including methanol, TRS compounds such as hydrogen sulphide and dimethyl disulphide (Stratton & Gleadow, 2003). Methanol is the primary constituent, accounting for up to 95% of the total organic content in the condensate stream (Stratton & Gleadow, 2003). Typical concentrations of constituents in combined condensates are listed in Table 2-1.  In the past, pulp mills released these foul-smelling condensates into rivers and streams, resulting in environmental problems related to odours, BOD loading and toxicity. There are about 150 kraft pulp mills in North America. The pulp and paper industry is identified by the EPA as the largest single source of methanol pollution (Moretti, 2002).  Table 2-1.  Typical Constituents Concentration in Combined Evaporator Condensate  (Berube & Hall, 1999) Typical Concentration (mg/L) Methanol  263 - 960  Hydrogen Sulphide  143 -730  Methyl Mercaptans  31-101  Dimethyl Sulphide  1.6-2.4  Dimethyl Disulphide  16 5  2.1.3  Methanol Manufacturing Industry  The methanol manufacturing process consists of three stages. The first stage is reforming in which natural gas is combined with steam under heat to form synthesis gas, which consists of hydrogen, carbon monoxide and carbon dioxide.  The next stage is compression and  conversion in which the synthesis gas is compressed and reacted to produce methanol. The last stage is distillation where the components are separated to obtain high purity methanol (Methanex, 2004).  In the distillation step, aqueous methanol and by-products are fed into a distillation column that has three outlet streams. Methanol is drawn off the top of the column as a vapour which is cooled and condensed for storage.  By-products that have boiling points higher than  methanol are removed in a side stream at the middle of the column. Water, which has the highest boiling point, flows out from the bottom with some methanol and by-products. The bottom waste stream is discharged or recycled to the manufacturing process.  ]  Aqueous mediatioi Natural gas Reforming Conversing Compression  * Methanol Byproducts  by-products  Distillation  Waste (water + some methanol and by-products)  F i g u r e 2-2. Typical Methanol Manufacturing Process  6  2.2  The  Methanol Removal Methods  c o m m o n l y used  methods  o f treating  methanol-containing waste  streams are  steam  stripping, incineration and biodegradation.  2.2.1  Steam Stripping  A c o m m o n m e t h o d o f treating m e t h a n o l i n p u l p m i l l c o n d e n s a t e s is s t e a m s t r i p p i n g , w h i c h is a d e s o r p t i o n p r o c e s s i n w h i c h s t e a m is u s e d to heat a l i q u i d t o a p o i n t w h e r e the d i s s o l v e d volatile  contaminants  vaporize (Mesar/Environair  Inc.).  The  filtered  a n d t h e n f e d t o a s t r i p p i n g c o l u m n w h e r e it i s c o n t a c t e d w i t h  m e t h a n o l , T R S c o m p o u n d s a n d o t h e r p o l l u t a n t s as v a p o u r s . water  from  the  column  overhead  recovered and processed.  vapour  stream,  and  condensate  stream  is  steam to  first  remove  A condenser is u s e d to r e m o v e  the  remaining vapours  are  then  T h e stripped condensate leaves the b o t t o m o f the c o l u m n a n d c a n  b e r e u s e d i n the p u l p i n g p r o c e s s o r sent to the w a s t e treatment s y s t e m ( C r u t c h e r & B u l l o c k , 1999).  A d i s a d v a n t a g e o f s t e a m s t r i p p i n g is that it is h i g h l y e n e r g y i n t e n s i v e .  2.2.2  Incineration  I n c i n e r a t i o n is a n o t h e r c o m m o n l y u s e d m e t h o d o f treating w a s t e s t r e a m s w i t h h i g h m e t h a n o l c o n c e n t r a t i o n s u c h as n o n - c o n d e n s a b l e g a s e s ( N C G s ) a n d s t r i p p e r o f f - g a s .  Methanol  and  other c o n t a m i n a n t s i n these w a s t e streams are burnt a n d c o n v e r t e d to c a r b o n d i o x i d e , s u l p h u r dioxide  and  nitrogen  w a r m i n g and acid rain.  oxides (Moretti,  2002).  These  gases  are  associated  with  global  Incineration cannot c o m p l e t e l y s o l v e the p o l l u t i o n p r o b l e m , a n d is a  costly and energy intensive process (Greenpeace, 2002).  7  2.2.3  Biodegradation  Since methanol can be easily biodegraded in both aerobic and anaerobic conditions, biodegradation is an alternative to remove methanol in waste streams (Malcolm Pirnie Inc., 1999).  For example, methanol in pulp and paper wastewater is commonly degraded by  activated sludge treatment.  Compared to steam stripping and incineration, biodegradation is a slower and more complex process to operate, but it has a much lower energy cost and is capable of completely removing methanol in the waste stream. A wide range of aerobic and anaerobic bacteria can metabolize methanol (Smith et al., 2002).  Under aerobic conditions, methanol degradation occurs as: C H O H + 3/2 0 -> C 0 + 2 H 0 3  2  2  2  Under anaerobic conditions, degradation can occur as: CH3OH + N 0 "-> C 0 + 2 H 0 + 1/2 N 3  2  2  2  CH3OH + 3/4 S 0 " -> C 0 + 2 H 0 + 3/4 S " 2  4  2  2  2  Methanol is expected to biodegrade at a relatively fast rate when concentration is less than about 3 g/L. There is likely a significant inhibitory effect on the microbial population when methanol concentration exceeds 8 to 10 g/L (Smith et al., 2002). If methanol concentration exceeds 50 to 100 g/L, microbial degradation of methanol is not likely to occur at any  8  significant rate. Above the inhibition threshold of 10 g/L, methanol tends to persist in the wastewater (Smith et al., 2002).  2.3  Methylotrophic Yeast Pichia pastoris  Pichia pastoris is a methylotrophic yeast which can utilize methanol as its sole carbon and energy source (Cereghino & Cregg, 2000; d'Anjou & Daugulis, 2001). Because of its robust growth, Pichia pastoris has been developed as a host for the expression of a wide variety of recombinant proteins at the bench and pilot scales, and the commercial production of both intracellular and extracellular heterologous proteins in the biotechnology, pharmaceutical and food industries (Sreekrishna et al., 1997).  (a)  (b)  Figure 2-3. Pictures of Pichia pastoris. a) Phase-contrast picture; b) Green fluorescent protein (GFP) expressing Pichia pastoris cells: GFP triggered fluorescence is induced by U V light (Bottner, 2003)  2.3.1  Characteristics  Pichia pastoris can grow to high cell densities of up to 150 g-dry-cell-weight/L (Curvers et al., 2002). Expression levels reported for recombinant proteins produced in Pichia pastoris are highly variable and range from the mg/L to g/L levels (d'Anjou & Daugulis, 2001). 9  Two steps are involved in expressing foreign genes in Pichia pastoris. 1) insertion of the desired gene into an expression vector; 2) introduction of the expression vector into the Pichia yeast cell. In addition to its own D N A , bacteria such as Pichia pastoris may also have an additional small segment of D N A , called plasmid, within its cytoplasm.  Plasmids are autonomously replicating extra-chromosomal circular D N A molecules, distinct from the normal bacterial genome and nonessential for cell survival under non-selective conditions  (http://www.ornl.gov/sci/techresources/Human_Genome/glossary/glossary.shtml).  They are easy to isolate and manipulate, and can be used as an expression vector for transferring the gene of interest from a foreign source to the expression host. A plasmid can be removed from Pichia pastoris, a desired gene can be inserted into it, and then the plasmid can be introduced back into the cell. Pichia pastoris may then produce the foreign protein as i f the protein were native to it (Dosanjh & Stone, 1996). However, there is no guarantee that Pichia pastoris with the expression vector is capable of growing and producing the protein of interest.  The desired gene for protein expression can be obtained from a foreign source. However, the promoter for the gene, which is the segment of D N A located immediately in front of each gene, must come from the host that will be producing the protein (Dosanjh & Stone, 1996). The promoter is responsible for regulating when, how much and how often the gene is transcribed. Pichia pastoris has a strong, inducible promoter that can be used for protein production (Curvers et al., 2002).  10  1.  2.  insert the g e n e o f interest  i n t r o d u c e the e x p r e s s i o n  v e c t o r i n t o P.  into an expression vector  pastoris  l ^ ^ ^ e n e of interest  Figure 2-4.  Steps o f E x p r e s s i n g F o r e i g n G e n e s i n  Pichia pastoris  (Cereghino &  Cregg,  2000)  2.3.2  Reaction Pathways  The inducible promoter of ( D o s a n j h & Stone, 1996).  Pichia, Candida  and  Pichia pastoris  is r e l a t e d to the fact that it i s a m e t h y l t r o p i c y e a s t  T h e f o u r k n o w n g e n e r a o f m e t h y l o t r o p h i c y e a s t , i:e.,  Torulopsis,  Hansenula,  share a c o m m o n m e t a b o l i c p a t h w a y that enables t h e m  to  u s e m e t h a n o l as a s o l e c a r b o n s o u r c e , as s h o w n i n F i g u r e 2 - 5 .  T h e first step i n m e t h a n o l  utilization  hydrogen  is the  molecular oxygen.  oxidation o f methanol  to  formaldehyde  and  peroxide  using  T h e o x i d a t i o n reaction is c a t a l y z e d b y a n e n z y m e c a l l e d a l c o h o l o x i d a s e  (Cereghino & Cregg, 2000).  11  Cytosol  Peroxisome  *CH OH 3  -J I  02  G SSH U  S-  *—»v  U1O2*—i  - HCHO „  J HCHO |02+H 0 2  v  2  .  temaiigemeat reactions  GAP D H A ,  — V  GS-CH20H^4 HCOOH jr?* CO2 NAD \ NAD \ NADH NADH constituents  DHA  ;>^-«£DHAPv  I ATP  ADP -4  GAP'  YiFBP^i^p  Pi  D/£4 = Dihydroxyacetone; DHAP = Dihydroxyacetone phosphate; ATP = Adenosine triphosphate; ADP = Adenosine diphosphate; FBP = Fructose-1 6-bisphosphatase; F6P = fructose-6- phosphate; Pi = Inorganic phosphate; GAP = GlyceraIdehyde-3-phosphate; X«.sP = Xylulose-5rphosphate; GS= Glutamine synthetase; GSH= Glutathione; NAD = Nicotinamide adenine dinucleotide; NADH= reduced form of N A D  Figure 2-5. Metabolic pathways of Methanol in Pichia pastoris - 1) alcohol oxidase; 2) catalase; 3) formaldehyde dehydrogenase; 4) formate dehydrogenase; 5) dihydroxyacetone synthase; 6) dihydroxyacetone kinase; 7) fructose 1,6-bi-phosphate aldolase; 8) fructose 1,6bisphosphatase (Cereghino & Cregg, 2000)  There are two alcohol oxidase genes: AOX1 and AOX2.  AGX1 is responsible for the  majority, i.e., 85%, of alcohol oxidase activity in the cell (Cereghino & Cregg, 2000; Inan & Meagher, 2001). The promoter region for both genes has a repressor region that leads to the inhibition of gene expression, and an activation region that leads to the enhancement of gene expression (Ohi et al., 1994). The AOX1 gene has been isolated and a plasmid-borne version of the AOX1 promoter is used to drive expression of the gene of interest encoding the heterologous protein. AOX2 is about 97% homologous to AOX1.  However, growth on  methanol with AOX2 is much slower than with AOX1 (Yu & Fu, 2004). 12  Repressor 1  Repressor 2  Repressor 2  <S*N  Promoter  Ope rater  Ope rater  | Gene (AOXl]  -—\J  polymerase Rich Carbon  Rich Carbon Source  (a) Promoter  Operater  ^\Cy\J  ^  Gene (AOX1)  u  \ Inducer (MeOH)  Gene (AQX1)  RNA polymerase. Transcription Permitted  (C)  Inducer (MeOH)  (d)  Figure 2-6. Mechanism of Alcohol Oxidase Gene Regulation - a) transcription is prevented by a rich carbon source and Repressor 1; b) rich carbon source is exhausted but Repressor 2 still inhibits transcription; c) the inducer (methanol) binds to Repressor 2 and removes it; d) transcription is permitted and alcohol oxidase is produced (Hoy, 2004)  The expression of the A O X l gene is tightly regulated and induced by methanol to very high levels. When Pichia pastoris is grown on methanol, alcohol oxidase can make up to 35% of the total cellular protein (Wallman, 2000), or 30% of the total intracellular protein content in the cells (Chen et al., 2000; de Graaff, 2003). However, when it is grown on glucose, glycerol, ethanol or other carbon sources, alcohol oxidase is not detectable (Cregg et al., 1985). Therefore, the presence of methanol is essential for inducing the A O X promoter which drives protein expression.  13  2.3.3  Advantages of Using Pichia pastoris  There are many benefits to use Pichia pastoris as a host system for synthesizing recombinant proteins. It is an ideal host because it is a simple microorganism that can grow to high cell densities on inexpensive, defined media using well-developed cultivation protocols (d'Anjou & Daugulis, 2001; Thorpe et al., 1999).  It can also produce many recombinant proteins in  large amounts without adverse effects to itself or the protein (Advances in Life Science, 2002).  As a simple single-celled eukaryote, Pichia pastoris is easier and less expensive to work with than insect or mammalian cells.  It contains plasmids, which are shuttle vectors that can  replicate in both Escherichia coli and yeast. While E. coli is the original host organism of choice, it is no longer in favour because of its inability to make post-translational modifications (Dosanjh & Stone, 1996).  These post-translational modifications include  processing of signal sequences, folding, formation of disulphide bridges and glycosylation (Cereghino & Cregg, 2000; Chen et a l , 2000).  Another type of yeast, Saccharomyces cerevisiae has also been recognized and used as a host for protein expression.  Pichia pastoris favoured because of its ability to perform post-  translational modifications that are more similar to human protein modifications than those carried out by Saccharomyces cerevisiae (Dosanjh & Stone, 1996).  Pichia pastoris grows on a simple mineral media.  It does not secrete high amounts of  endogenous protein and secretes only few extracellular proteins of its own (de Graaff, 2003).  14  Therefore the heterologous proteins secreted into the culture are relatively pure and constitute most of the proteins in the medium after cultivation (de Graaff, 2003). This makes it easier to isolate the heterologous proteins and can simplify the downstream purification process (Faber etal., 1995).  2.4  Protein Expression  Protein production involves four major steps: i) gene expression in the host, ii) posttranslational modifications, iii) protein secretion and intracellular transport,  and iv)  downstream processing. Expression of heterologous protein in Pichia pastoris can be either intracellular or extracellular. Many types of proteins have been expressed in the Pichia system, including enzymes, proteases, protease inhibitors, receptors, single-chain antibodies and regulatory proteins (Advances in Life Science, 2002; Cereghino & Cregg, 2000).  Production of extracellularly secreted proteins facilitates the purification process. Thus most heterologous proteins of interest are those produced extracellularly. One of the proteins that Pichia pastoris is capable of producing extracellularly is lipase (Holmquist et al., 1997; Hoy et al., 2003; Hoy, 2004; Minning et al., 2001).  2.4.1  Lipase  Lipase, also known as triacylglycerol acylhydrolase, is a lipid-degrading enzyme which can decompose fats into more water-soluble compounds by hydrolysing the ester bonds between the glycerol backbone and fatty acid. It is an important industrial enzyme, for example, it has  15  been used extensively in the dairy industry, for household detergents, and in the production of esters (Dong et al., 1999). In the pulp and paper industry, lipase has been shown to be capable of removing pitch, which is a sticky substance present mainly in softwoods and is composed of lipids (Leisola et al., 2001). It therefore has a potential application for treating extractives in paper making process streams.  2.4.2  Lipase Production in Previous Works  It has been reported that lipase can be expressed extracellularly from Pichia pastoris, and well-established lipase assay protocols are available (Holmquist et al., 1997; Hoy et al., 2003; Hoy, 2004). Holmquist et al. (1997) succeeded in expressing Geotrichum candidum lipase in Pichia pastoris to levels of about 60 mg/L. The experiments were conducted in a 250 mL Erlenmeyer flask placed in a shaking incubator at 30°C and 250-300 rpm for 4 days with a daily addition of 0.5 mL 80% (v/v) methanol to maintain induction (Holmquist et al., 1997).  Hoy et al. (2003) succeeded in growing a recombinant strain of Pichia pastoris (GS115 (his4)) expressing lipase from the fungus Geotrichum candidum in various media compositions. The experiments were conducted in a 1.8-L (working volume) reactor in fedbatch mode. It was found that yeast-peptone solution, which contained 10 g/L yeast extract and 20 g/L peptone dissolved in either distilled water or combined evaporator condensate from a kraft pulp mill, was required for lipase expression. Cell densities of 8-12 g/L (dry cell weight), protein concentrations of 48-57 mg/L, and lipase activity of about 12 umol/min/mL were reached (Hoy et al., 2003; Hoy, 2004).  16  2.5  Factors Affecting Growth and Protein Production  Growth of Pichia pastoris and protein production can be affected by many different factors, including types and concentrations of substrate, dissolved oxygen level, pH, temperature and in the case of reactor cultivation, the amount of foaming. These factors would affect the amount and rate of cell and protein production (Invitrogen, 1995).  2.5.1 Substrates Commonly used substrates for Pichia pastoris cultivation are glucose, glycerol and methanol. A l l these substrates can be used as carbon and energy sources for Pichia pastoris, however, only methanol can induce the A O X promoter that drives protein expression.  Pichia pastoris can grow on single or mixed substrates.  Successful expression of  recombinant proteins has been achieved using methanol alone, as well as in a mixed feed of glycerol and methanol (d'Anjou & Daugulis, 2000; d'Anjou & Daugulis, 2001; Sreekrishna, 1989). While alcohol oxidase promoter is activated by methanol, it is repressed by other carbon sources such as glycerol or glucose (Tschopp et al., 1987).  To avoid toxicity problems, it is recommended that glycerol concentration be no more than 4 g/L (Invitrogen, 1995). High levels of methanol are also toxic to Pichia pastoris.  It was  found that methanol concentrations above 4 g/L inhibit growth and protein production (Katakuga, 1998; Zhan et al., 2000). To achieve maximum levels of recombinant protein productivity, it is crucial to control the methanol concentration.  17  Major elements that are essential for growth, protein production and other functions are listed in Table 2-2.  Table 2-2. Representative Functions of Major Elements for Microorganisms (Nester et al., 2001)  Chemical  Function  Carbon, oxygen, hydrogen  Component of cellular constituents, including amino acids, lipids, nucleic acids, sugars  Nitrogen  Component of amino acids and nucleic acids  Sulphur  Component of some amino acids  Phosphorus  Component of nucleic acids, membrane lipids, A T P  Potassium, magnesium, calcium  Required for the functioning of certain enzymes; additional functions as well  Iron  2.5.2  Part of certain enzymes  Temperature  Both growth and protein production rates are temperature sensitive. Researchers have found that optimum temperature for protein production in Pichia pastoris is 30°C (Cino, 2003). When temperature is greater than 32°C, protein expression ceases (Cino, 2003; Invitrogen, 1995). Since high heat loads occur when Pichia pastoris is actively growing or expressing high levels of protein, temperature control devices must be designed to regulate temperature for optimum growth and protein production.  18  2.5.3  Dissolved Oxygen  Dissolved oxygen (DO) level can be expressed as a concentration, or a percentage of oxygen in the medium relative to the saturation level. A D O level of 100% means that the medium is oxygen-saturated (Invitrogen, 1995). DO level is important to both cell growth and protein production. For Pichia pastoris, D O level in the culture medium must be greater than 20% for metabolizing the substrates (Invitrogen, 1995).  D O level is affected by several factors such as temperature, aeration and agitation rates. Warm water cannot dissolve as much oxygen as cold water, e.g. oxygen solubility in clean water is 7.53 mg/L at 30°C and 8.11 mg/L at 25°C. Consumption of oxygen depends on substrate concentration and the protein being expressed (Invitrogen, 1995).  2.5.4  pH  The acidity and alkalinity of the culture medium are important for optimal growth and protein production. It is therefore necessary to control the pH at an appropriate level. The optimum p H depends on the type of recombinant protein being produced.  One drawback of using Pichia pastoris as a recombinant protein expression host is that its own proteases may degrade the secreted recombinant proteins. It has been reported in the literature that if the pH of the culture is lowered to 3.0, neutral proteases are inhibited (Invitrogen, 1995). Alternate methods to decrease protease activity include the addition of protease inhibitors such as PMSF and pepstatin A, and the use of a protease-deficient Pichia strain (Goodrick et al., 2001; Holmquist et al., 1997). 19  2.5.5  Foaming  Excess foam in the reactor may denature secreted protein and reduce headspace.  An  appropriate amount of a chemical antifoam agent is usually added to control foam (Invitrogen, 1995).  2.6  Reactor Operation Modes  Reactors for growing Pichia pastoris can be operated in both continuous and discontinuous, e.g., batch or fed-batch, modes. Traditionally, cultivations of Pichia pastoris are performed in fed-batch mode because well-developed fed-batch operation methods are available (Goodrick, 2001; Invitrogen, 1995). Less research has been done on continuous cultivations of Pichia pastoris.  However, biological treatment of wastewater is usually performed in  continuous mode.  This is because batch or fed-batch operations are not economically  feasible to handle the huge loadings of wastewater, which are often measured in mega liters per hour.  2.6.1  Advantages of Discontinuous over Continuous Operations  Since cells are not removed during the cultivation, batch or fed-batch reactors are well suited for expressing proteins that are only produced during very slow or zero growth. Continuous cultures are not suitable for products which are predominantly produced when growth ceases because when there is no growth in the continuous reactor, any dilution rate greater than zero will result in washing out of the cells (Williams, 2002).  20  Batch or fed-batch reactors are less likely to have contamination problems than continuous reactors. Contamination of continuous reactors can have a disastrous effect on the operation, especially i f the contaminant is able to grow at a lower substrate concentration than Pichia pastoris. A contaminant may cause Pichia pastoris to wash out and completely take over a reactor (Williams, 2002).  2.6.2  Advantages of Continuous over Discontinuous Operations  In a continuous reactor, the operational conditions are invariable when steady state is attained (da Costa et al., 1997). Cells can be maintained at a constant physiological state, and the quality and the production rate of the final product is constant during steady state. The specific growth rate and substrate concentration can be easily adjusted by changing the feed flow rate. In a batch or fed-batch system, it is much more difficult to maintain a desired specific growth rate (Henriques et al., 1999; Williams, 2002).  Continuous cultivation can be used to determine the kinetics of growth and protein production. In batch or fed-batch operations, concentrations and metabolic rates change over time, thus analysis of growth kinetics has been limited to quasi-steady-state data.  In  continuous cultivation, the steady state data is time invariant, and can be used to describe the regulatory response of the culture and to determine the kinetics parameters more precisely (Curvers et al., 2002; Williams, 2002).  Continuous reactors do not have to shut down as frequently as batch or fed-batch reactors do. At the end of a discontinuous cultivation, it is necessary to empty, clean, sterilize and refill 21  the reactor ( W i l l i a m s , 2 0 0 2 ) .  S i n c e c o n t i n u o u s reactors shut d o w n less often t h a n b a t c h o r  fed-batch reactors, they have less loss i n p r o d u c t i v i t y d u r i n g shut d o w n a n d a shorter p h a s e at t h e b e g i n n i n g o f t h e c u l t i v a t i o n .  C o n t i n u o u s reactors reduce the t i m e and  lag  costs  a s s o c i a t e d w i t h c l e a n i n g a n d f i l l i n g o f the reactor.  Since  most  downstream  processing  operations  are  operated  in  a  continuous  manner,  c o n t i n u o u s c u l t i v a t i o n a l l o w s the process to be i n tune w i t h other o p e r a t i o n s i n a b i o p r o c e s s plant.  C o n t i n u o u s c u l t i v a t i o n m a k e s it e a s i e r t o o p t i m i z e p r o d u c t i v i t y a n d o f f e r s t h e p o t e n t i a l  o f higher productivities.  A s a r e s u l t , it is p o s s i b l e t o h a v e s m a l l e r r e a c t o r s a n d  associated  e q u i p m e n t w h i c h l e a d t o l o w e r c a p i t a l c o s t s a n d h i g h e r p r o f i t s ( d a C o s t a et a l . , 1 9 9 7 ) .  22  3.0 The  PROBLEM DEFINITION methanol  and  ammonia  manufacturing  plants  K i t i m a t , B . C . , generate large v o l u m e o f wastewater the d i s t i l l a t i o n c o l u m n b o t t o m stream.  located  at  O n e o f the w a s t e streams is 3  Currently all wastewater  and process water make-up.  everyday.  Corporation,  T h i s w a s t e s t r e a m has a t o t a l f l o w rate o f 12 m / h ,  w i t h t e m p e r a t u r e at 1 2 7 ° C a n d p r e s s u r e at 1 4 8 k P a . to 3 0 ° C w i t h a cooler.  of Methanex  Part o f the stream is c o o l e d to a b o u t 25  f r o m this stream is r e c y c l e d to the  T h e r e is n o treatment to the w a s t e w a t e r  before  process  reuse ( K e v i n  M a l o n e y , e l e c t r o n i c m a i l , J a n u a r y 14, 2 0 0 4 ) .  Methanex  Corporation  is  currently  looking  for  an  a p p l i c a t i o n s o f the m e t h a n o l - c o n t a i n i n g wastewater. grow  Pichia pastoris  a p p l i c a t i o n has  and to produce  a potential  methanol  treatment  or  possible  O n e o f the p o s s i b l e a p p l i c a t i o n s is to  a recombinant  o f degrading  alternative  protein i n this waste stream.  i n the  waste stream  and  This  producing  a  p r o d u c t u s e f u l t o t h e i n d u s t r y at t h e s a m e t i m e .  L i p a s e is a n i m p o r t a n t industrial e n z y m e a n d has a potential a p p l i c a t i o n i n the p u l p a n d p a p e r industry.  pastoris  It h a s b e e n s u c c e s s f u l l y e x p r e s s e d i n a  s t r a i n ( H o l m q u i s t et a l . , 1 9 9 7 ; H o y et a l . , 2 0 0 3 ; H o y , 2 0 0 4 ) .  the c o m b i n e d evaporator w a s t e stream, to g r o w study  Geotrichum candidum  the  possibility o f growing  and to produce lipase.  this  Pichia  strain  and  Pichia  H o y et a l . ( 2 0 0 3 ) u s e d  condensate f r o m a kraft m i l l , w h i c h w a s a  Pichia pastoris  recombinant  methanol-containing  A potential research area is to expressing  lipase  in  different  m e t h a n o l - c o n t a i n i n g w a s t e streams.  23  4.0  RESEARCH OBJECTIVES  The main objective of this research was to grow Pichia pastoris and to produce a recombinant protein in an industrial waste stream in a continuous reactor. The recombinant protein of interest was lipase and the wastewater used in this study was the distillation column bottom stream from Methanex.  The specific research objectives were to: i)  Determine methanol concentration in the wastewater from the Methanex distillation column bottom stream  ii)  Assemble a lab-scale reactor for growing Pichia pastoris  iii)  Develop an automated control system for running the reactor in continuous mode  iv)  Determine whether or not Pichia pastoris can grow in the Methanex wastewater  v)  Determine whether or not protein can be produced  vi)  Measure the level of cell growth and protein production  vii)  Perform steady state material balance and use the Monod equation to estimate the kinetic parameters  viii)  Use the steady state data and estimated parameters to calculate the critical and optimum dilution rates  ix)  Implement a program to solve the non-steady state material balance equations with the estimated parameters  x)  Represent the reactor system model with a set of ordinary differential equations and estimated parameters  24  5.0  MATERIALS AND METHODS  5.1  Media Composition and Storage  The Methanex wastewater was collected from the distillation column bottom stream on January 21, 2003. It was delivered in high-density polyethylene containers by courier from the Methanex plants in Kitimat, BC, to the Pulp and Paper Centre at the University of British Columbia. The wastewater was stored in a dark, cold room at 5°C.  The media used in this study was the yeast-peptone solution that consisted of 10 g/L yeast extract and 20 g/L peptone in distilled water. The compositions of the feed and nutrient solutions were listed in Tables 5-1 and 5-2. The yeast-peptone and feed solutions were freshly prepared before each experimental run.  The nutrient solution was prepared by  Preston Hoy, Master of Applied Science candidate at the University of British Columbia, on August 23, 2001 and was stored in the refrigerator at 4°C.  Table 5-1. Compositions of Feed Solution (Todar, 2001) Substance added to Methanex wastewater  Concentration  Function  (NH ) S0  3 g/L  Nitrogen and sulphur source  14.2 g/L  pH buffer; phosphorus source  6.95 g/L  pH buffer  MgSCVH 0  0.3 g/L  Sulphur and magnesium source  Nutrient solution  1 mL/L  See Table 5-2  4  2  Na HP0 2  4  4  Citric acid 2  25  Table 5-2. Compositions of Nutrient Solution (Todar, 2001) Substance added to distilled water  Concentration  Function  Biotin  200 ug/L  Folic acid  200 ug/L  Calcium pantothenate  40 mg/L  Niacin  40 mg/L  Pyridoxine-HCl  40 mg/L  Inositol  200 mg/L  Riboflavin  20 mg/L  Biosynthetic reactions that require CO2 fixation Synthesis of thymine, purine bases, serine, methionine and pantothenate Oxidation of keto acids and acyl group carriers in metabolism Electron carrier in dehydrogenation reactions Transamination, deamination, decarboxylation and racerhation of amino acids A major component of cell membranes, affecting structure and function Oxidation-reduction reactions; electron carrier  5.2  Yeast Strain and Storage  A. Pichia pastoris strain, GS115 (his4) harboring plasmid YpDC420, expressing lipase from the fungus Geotrichum candidum was used.  The yeast strain was obtained from M .  Holmquist and D.C. Tessier of the Biotechnology Research Institute, National Research Council of Canada, Montreal, Quebec.  An agar plate was used to culture Pichia pastoris. Agar (14 g/L) was added to yeast-peptone solution and the mixture was autoclaved at 121°C and 10 psi for 20 minutes. To prepare an agar plate, the molten mixture was poured into a petri dish and 10 g/L glucose was added. When the plate was cooled to room temperature, an inoculating loop was used to aseptically remove a trace of Pichia cells from the original stock, and streak it out on the agar plate. The plate was incubated at 30°C with the agar side up for 2 days.  It was then sealed with 26  p a r a f i l m a n d s t o r e d i n a r e f r i g e r a t o r at 4 ° C .  A n e w agar plate w a s prepared every m o n t h  w i t h c e l l s f r o m the p r e v i o u s plate i n the s a m e m a n n e r to ensure the v i a b i l i t y o f the yeast.  5.3  Sterilization  T h e yeast-peptone  solution, all glassware and connection tubings used i n this project  s t e r i l i z e d b y a u t o c l a v i n g at 1 2 1 ° C a n d 1 0 p s i f o r 6 0 m i n u t e s .  were  A l l other solutions w e r e filter  sterilized w i t h C o r n i n g ® D i s p o s a b l e Sterile B o t t l e - T o p Filters o f 0 : 2 2 p m pore size (Fisher Scientific).  5.4  A  Inoculum Preparation in a Shake Flask  s i n g l e c o l o n y f r o m the m o s t recent agar plate w a s used to i n o c u l a t e 5 0 m L o f yeast-  peptone s o l u t i o n in a sterile 2 5 0 m L E r l e n m e y e r flask c o r k e d w i t h f o a m p l u g to a l l o w air permeation. solution.  G l u c o s e w a s u s e d as a n i n i t i a l c a r b o n s o u r c e b y a d d i n g 2 m L o f 5 0 0 g / L g l u c o s e  T h e shake flask was then incubated in an orbital shaker (Innova 4 2 3 0 Refrigerated  I n c u b a t o r , N e w B r u n s w i c k S c i e n t i f i c ) at a t e m p e r a t u r e o f 3 0 ° C a n d a n a g i t a t i o n r a t e o f 1 5 0 r p m for 1 day.  5.5  Continuous Cultivation in a Computer-controlled Reactor  T h e culture i n the shake flask w a s aseptically transferred to an a u t o c l a v e d 2 . 5 - L glass reactor ( C a n a d i a n S c i e n t i f i c G l a s s b l o w i n g , R i c h m o n d , B C ) , w h i c h i n i t i a l l y c o n t a i n e d 1.6 L o f y e a s t peptone solution.  A f t e r i n o c u l a t i o n , the reactor w a s started up to r u n i n c o n t i n u o u s  mode.  F e e d s o l u t i o n w a s a u t o m a t i c a l l y p u m p e d i n t o t h e r e a c t o r at t h e s a m e r a t e as t h e o u t l e t s t r e a m  27  was pumped out to the drain. Experiments were performed at 5 dilution rates: 0.011, 0.017, 0.026, 0.034 and 0.042 1/h. The corresponding flow rates were 18, 27, 42, 54 and 67 mL/h.  Dissolved oxygen level in the reactor broth was continuously measured by a polargraphic, autoclavable dissolved oxygen probe (Cole Parmer). DO level was kept constant at 3.0 mg/L by changing the aeration rate which ranged from 0-15 L/min.  Aeration was supplied by  fdter-sterilized building air regulated by a digital airflow controller (GFC mass flow controller, Alaborg). Mixing and agitation were facilitated by using an air sparger that broke the incoming air into small bubbles, and by placing the reactor with a magnetic stir bar on a stir plate. The reactor was jacketed with a water bath to maintain the broth temperature at 30°C. pH was continuously monitored by a sealed, double junction, autoclavable pH probe (Cole Parmer), and was kept constant at 5.6 by adding either 1.0 M ammonium hydroxide (NFLOH) or 1.0 M sulphuric acid (H2SO4) to the reactor broth as needed.  Antifoam A  (Sigma) was added as needed to prevent excessive foaming. Evaporation was compensated by manually adding distilled water as needed to keep the broth volume at 1.6 L . A flow diagram of the continuous reactor system was shown in Figure 5-1.  28  Figure  5-1. Flow Diagram of the Continuous Reactor System  5.5.1  Data Acquisition and Reactor Control System  A data acquisition and control system was assembled by Norman Woo, Master of Applied Science candidate at the University of British Columbia, to continuously monitor and control the pH, D O level, aeration rate, feed and outlet flowrates in a self-cycling batch reactor. The system was modified by Preston Hoy, another Master of Applied Science candidate at the University of British Columbia, to run the same reactor in fed-batch mode for growing Pichia pastoris in pulp mill condensate. The system was modified in this study to run the reactor in continuous mode.  29  The system consisted of four pieces of equipment:  a signal data logging unit, a main  computer containing the Instrumentation and Automation board (DAQ PCI-6024E, National Instruments), a secondary computer equipped with a data acquisition and control board (Strawberrry Tree Inc., Model Acjr, Sunnyvale, California), and an electrical digital output switch box, as shown in Figure 5-2.  Analog inputs & outputs  Digital Outputs Secondary computer  To pumps, stir plate  Main computer  ©00© 63 0 0 © OO OO  Electric switch box  Data logging unit  From air flow controller, pH probe & DO probe To air flow controller  Figure 5-2. Components of the Reactor Control System (Hoy, 2004)  There was a bank of signal ports in the data logging unit. Each signal port could be selected to receive either current or voltage signal from the air flow controller, pH probe and D O probe. The data logging unit was used to transmit raw signals through a parallel port to the National Instruments board installed in the main computer. With the data logging unit, it was much easier to connect measurement devices to, or remove them from the reactor control system. A 5-volt analog output port was installed in the unit for sending commands to the air flow controller.  30  The Instrumentation and Automation board in the main computer was the central interface device which could send and receive signals in both analog and digital forms. The raw input signals from the data-logging box were first converted to numerical values. Then, these values were read into control programs developed with the LabVIEW instrumentation and control programming package (National Instruments, Austin, Texas).  The programs  determined and sent appropriate control responses to the secondary computer or data logging box through a parallel port. User-defined parameters could be entered through the graphical interface to control the reactor behaviour. The responses generated by the programs were either digital on/off signals or analog signals.  A Pascal program was used to access the data acquisition and control board in the secondary computer and process the digital signals. The processed digital signals were then transmitted through the electrical digital output switch box to the pumps and stir plate.  The analog  signals were sent through the data logging box to the air flow controller.  5. 5. 2 Data Logging Measurements of pH, DO and air flow rates were taken every 2 seconds.  The sampling  frequency was short enough to ensure that the real-time responses of the pumps and air flow controller could adequately control the reactor conditions. To prevent accumulation of an excessively large amount of data and to even out short-term fluctuations, the main LabVIEW program calculated the 10-minute averaged values for each measurement and logged only the averaged values in the computer. Since each experimental run lasted for about 160 hours, the  31  10-minute logging interval was capable of providing good enough resolution on the reactor trends.  Several control loops were implemented in the main program to continuously monitor and control pH, D O level, aeration rate, feed and outlet flowrates. When the measured pH was lower than the setpoint of 5.6, the program triggered the base pump to add NH4OH. When the pH was higher than the setpoint, the acid pump was triggered by the program to add H2SO4. The base pump and acid pump speeds were fixed at about 0.37 mL/s. For the feed and outlet pumps, the speeds were adjusted at the beginning of each experimental run by turning the knobs on the pump drives. The program was used to turn on or off the pumps but not to adjust the speeds.  To ensure oxygen was not limiting, the dissolved oxygen level was kept at 3.0 mg/L, which was about 40% of the saturated oxygen concentration at 30°C. The main program used a proportional-integral (PI) control algorithm, which is a built-in subroutine available in the LabVIEW programming package.  The PI algorithm was used to adjust the aeration rate  between 0 and 15 L/min to keep the DO at its setpoint. The values for proportional (P) and integral (I) settings were chosen by Preston Hoy who used the same reactor for growing Pichia pastoris in fed-batch mode. The values were chosen such that the control algorithm acted slowly enough to ignore short-term fluctuations. The P and I values that best suited for this reactor system were 1 and 0.01, respectively. It was a noisy system so no derivative control was used.  32  A  s e c o n d a r y p r o g r a m , w h i c h ran c o n c u r r e n t l y w i t h the m a i n p r o g r a m , w a s i m p l e m e n t e d to  c o n t r o l the  time  intervals o f defoamer  addition and the  d e f o a m e r p u m p s p e e d w a s f i x e d at a b o u t 0 . 4 1 r n L / s . small amount  5.6  duration o f each  The  D e p e n d i n g o n the reactor c o n d i t i o n s , a  (about 3-4 m L ) o f the a n t i f o a m agent w a s a d d e d e v e r y 8-10 h o u r s .  Assays  A b o u t 3 m L samples o f reactor broth were taken once o r t w i c e per day. mL  addition.  F o r e a c h s a m p l e , 0.5  w a s u s e d f o r c e l l d e n s i t y a n a l y s i s r i g h t after t h e s a m p l e w a s t a k e n .  The  remaining  p o r t i o n w a s f i r s t c e n t r i f u g e d f o r 5 m i n u t e s at 6 7 0 0 x g , a n d t h e n s t o r e d i n a f r e e z e r a n d w a s u s e d later for d e t e r m i n i n g m e t h a n o l concentration, protein c o n c e n t r a t i o n a n d lipase a c t i v i t y .  5.6.1  Cell Concentration  A p i p e t t e w a s u s e d t o transfer 0.5 m L o f a s a m p l e i n t o a n e w c e n t r i f u g e t u b e w h i c h w a s t h e n c e n t r i f u g e d f o r 5 m i n u t e s at 6 7 0 0 x g . suspended  T h e supernatant w a s discarded and the pellet w a s re-  i n 10 m L o f d i s t i l l e d w a t e r  i n a c l e a n test-tube.  The absorbance  o f the  s u s p e n d e d s o l u t i o n w a s m e a s u r e d at 6 0 0 n m b y a s p e c t r o p h o t o m e t e r ( H A C H D R / 2 0 0 0 ) . concentration,  expressed  calibration curve.  in dry  cell  weight  per  volume,  was  T o construct a calibration curve, absorbances  then  determined  reCell  from  a  o f dense cell culture serial  d i l u t i o n s w e r e m e a s u r e d a n d plotted against the c o r r e s p o n d i n g d r y cell w e i g h t s obtained b y drying  known volumes  spectrophotometer.  at  103  ° C for  2 hours.  Distilled  water  was  used  to  zero  T h e c a l i b r a t i o n c u r v e is i n c l u d e d i n A p p e n d i x A .  33  the  5.6.2  Methanol Concentration  T h e first step o f d e t e r m i n i n g m e t h a n o l concentration w a s to take out the s a m p l e s f r o m f r e e z e r a n d d e f r o s t t h e m at r o o m t e m p e r a t u r e . for 5 minutes.  the  T h e s a m p l e s w e r e t h e n c e n t r i f u g e d at 6 7 0 0 x g  F o r e a c h s a m p l e , the pellets w e r e d i s c a r d e d a n d 1 m L o f the supernatant w a s  transferred to a vial w i t h a pipette.  F i f t y u L o f 5 g / L 1-butanol s o l u t i o n w a s added to the v i a l  as the i n t e r n a l s t a n d a r d f o r gas c h r o m a t o g r a p h y ( G C ) .  T h e c o n c e n t r a t i o n o f m e t h a n o l i n the reactor broth w a s measured b y a V a r i a n C P - 3 8 0 0 gas chromatograph w i t h a Supelco ( S u p e l c o w a x - 1 0 ™ 2 4 0 8 0 - U ) capillary c o l u m n (fused 3 0 m x 0.32 i.d. x 0.25 u m film thickness). o f 25 m L / m i n .  2  H e l i u m w a s f e d as t h e c a r r i e r g a s at a f l o w r a t e  T h e f l u e g a s e s w e r e h y d r o g e n a n d a i r , w h i c h w e r e f e d at 3 0 m L / m i n a n d 3 0 0  m L / m i n , respectively. 250°C.  silica,  B o t h the  flame  ionization detector and injector w e r e maintained  at  T h e d e t e c t i o n m e t h o d w a s t o i n i t i a l l y h o l d t h e c o l u m n o v e n t e m p e r a t u r e at 8 0 ° C f o r  minutes,  methanol  and then to  i n c r e a s e t h e t e m p e r a t u r e t o 2 0 0 ° C at 2 0 ° C / m i n .  1-butanol  was  determined  by  the  GC.  T h e area  Methanol concentration  ratio  was  of  then  d e t e r m i n e d f r o m the calibration curve, w h i c h w a s constructed b y p l o t t i n g the area ratios o f m e t h a n o l to 1-butanol against methanol concentrations for 6 m e t h a n o l standards w i t h k n o w n c o n c e n t r a t i o n s b e t w e e n 4 0 a n d 1 0 0 0 0 m g / L . T h e c a l i b r a t i o n c u r v e is a v a i l a b l e i n A p p e n d i x A.  5.6.3 Similar  Protein Concentration to  methanol  concentration  determination,  the  first  step  of  measuring  protein  c o n c e n t r a t i o n w a s t o d e f r o s t t h e s a m p l e s a n d c e n t r i f u g e t h e m at 6 7 0 0 x g f o r 5 m i n u t e s . 34  For  e a c h s a m p l e , the pellets w e r e discarded a n d 2 m L o f the supernatant w a s transferred  with a  pipette to a C e n t r i c o n Y M - 3 0 centrifugal fdter ( M i l l i p o r e , B e d f o r d , M A ) . T h e s a m p l e c e n t r i f u g e d a g a i n a t 3 5 0 0 xg f o r 6 0 m i n u t e s .  was  T h e filtrate w a s d i s c a r d e d a n d 2.0 m L o f  3-[N-  M o r p h o l i n o ] p r o p a n e s u l f o n i c a c i d ( M O P S ) buffer, w h i c h had a c o n c e n t r a t i o n o f 2 0 m M a n d pH  o f 7.0,  was  added  to  resuspend  the  retentate.  The  resuspended  mixture  was  then  solution  were  c e n t r i f u g e d at 3 5 0 0 xg for 3 0 m i n u t e s .  I n t o a c l e a n test-tube, 3 m L o f d i s t i l l e d water a n d 1 m L o f the r e s u s p e n d e d  added together w i t h 1 m L o f bovine serum a l b u m i n ( B S A ) , w h i c h was a protein standard  and  w a s available i n the ' P r o t e i n A s s a y K i t ' supplied b y B i o - R a d ( H e r c u l e s , C A ) . A l l o w i n g 5 minutes  for stabilization, absorbance  spectrophotometer  (HACH  o f the m i x t u r e w a s t h e n  DR/2000).  Protein  concentration  measured was  at 5 9 5  nm by  a  from  a  determined  calibration curve, w h i c h was constructed by plotting optical densities against 8 standard B S A solutions w i t h k n o w n concentrations between 0 m g / L to 140 m g / L . A s o l u t i o n c o n t a i n i n g 3 mL  o f distilled water,  spectrophotometer.  5.6.4 A  1 m L o f B S A and  1 mL of MOPS  buffer  was  used  to z e r o  the  T h e c a l i b r a t i o n c u r v e is i n c l u d e d i n A p p e n d i x A .  Lipase Activity  lipase assay was  performed  d e t e r m i n e the lipase activity.  to c h e c k whether  water.  The  was  lipase and  to  T h e first step w a s to p r e p a r e a substrate m i x t u r e c o n t a i n i n g 1  m L o f olive oil (Sigma-Aldrich), 1 distilled  the protein p r o d u c e d  mixture  was  g  of  CaCl2-2H 0  emulsified  2  by  and 2  g  blending  o f g u m arabic i n 100 m L o f it w i t h a n  electrical  Braun  35  H a n d b l e n d e r for 2 minutes.  T h e p H o f the e m u l s i f i e d m i x t u r e w a s t h e n adjusted to 7.0 b y  the a d d i t i o n o f s o d i u m h y d r o x i d e ( N a O H ) .  A p o r t i o n o f the resuspended s o l u t i o n f r o m the protein c o n c e n t r a t i o n d e t e r m i n a t i o n w a s u s e d i n this assay.  F i f t y u L o f the re-suspended s o l u t i o n w a s a d d e d t o 2 0 m L o f the e m u l s i f i e d  m i x t u r e t o start the r e a c t i o n .  L i p a s e w a s e x p e c t e d to h y d r o l y s e o l i v e o i l a n d release h y d r i d e  ions (FT), resulting in a p H drop.  O n c e the reaction started,  the  p H was  continuously  m o n i t o r e d a n d m a i n t a i n e d at 7 . 0 b y a d d i n g 0 . 0 0 5 M N a O H w i t h a n a u t o m a t i c t i t r a t o r , T i t r a L a b T I M 854 Titration Manager (Radiometer, Denmark).  The amount o f N a O H added  was  c o n t i n u o u s l y m e a s u r e d a n d l o g g e d into a c o m p u t e r until the end o f the reaction, w h i c h  was  indicated by zero addition o f N a O H . added  A c t i v i t y o f l i p a s e w a s e x p r e s s e d as u m o l e s o f N a O H  per m L o f reactor broth per minute.  Natural change  o f p H i n the  substrate  was  c o m p e n s a t e d b y s u b t r a c t i n g t h e a m o u n t o f N a O H n e e d e d t o k e e p t h e p H at 7 . 0 w h e n 5 0 u L o f M O P S buffer instead o f the resuspended s o l u t i o n w a s added to the substrate.  5.7  5.7. J  Data Analysis  Non-steady State Material Balance  F o r the c o n t i n u o u s reactor u n d e r study, the material b a l a n c e e q u a t i o n s yeast extract and peptone, section.  a n d p r o d u c t ( i . e . , p r o t e i n ) at n o n - s t e a d y  for cell,  methanol,  state are s h o w n i n this  T h e s y m b o l s u s e d i n the e q u a t i o n s are l i s t e d i n the L i s t o f A b b r e v i a t i o n s .  36  Material balance for cell at non-steady state: V^-  = F-X -F-X i  + \i-X-V-k -X-V  (5-1)  d  Feed solution was filter sterilized so there was no cell in the feed (Xj = 0). It was assumed that there was negligible death compared to growth such that kd «  u. The  dilution rate (D) in a continuous reactor is defined as:  D= —  (5-2)  V  Thus, Equation (5-1) becomes: %  = -»X  + rX  (5-3,  Material balance for methanol at non-steady state: V— = dt  F'M,-F-M-  • + mM •  XV  (5-4)  PIM  It was assumed that there was no maintenance effect (mM = 0) and protein production was directly linked to energy metabolism (qp'=0). By definition, the specific rate of methanol uptake is:  « =TTM  (5-5)  37  Equation (5-4) can therefore be written as:  —Ljr  ^ - = D(M,-M) dt  Y  (5-6)  x/M  (iii) Material balance for yeast extract and peptone at non-steady state: V— = dt  F-Y -F-Y t  q + -— + m \-X-V p/r ) r  (5-7)  1  There was no yeast extract and peptone in the feed so that Y; = 0. It was assumed that there was no maintenance effect (mM = 0) and product production was directly linked to energy metabolism (qp=0). By definition, the specific rate of yeast extract and peptone uptake is: It  (5-8)  XIY  Equation (5-7) can be simplified as: d  = -  Y  dt  D  .  - J L - x  Y  1  (5-9)  XIY  (iv) Material balance for product at non-steady state: dP V — = F-P - F-P + q -X-V dt i  p  (5-10)  By definition, Ip = P/X-M Y  + ™  P  (5-11) 38  Assuming that there was no maintenance effect (m = 0) and no product in the feed (Pi P  = 0), Equation (5-10) can be expressed as: ^ = -D-P Y - -X at +  p/x  (5-12)  M  5.7.2 Steady State Material Balance The continuous reactor under study would eventually reach steady state at which cell, substrate, and product concentrations did not change with time.  Steady State: Cell growth rate equals removal rate  Time in Hours Figure 5-3. Development of Growth in a Typical Continuous Reactor  The material balance equations for cell, methanol, yeast extract and peptone, and product at steady state are as follows.  39  (0  Material balance for cell at steady state: At steady state, dX/dt in Equation (5-3) was zero so the material balance becomes: -D-X  + pX = 0  (5-13)  Rearranging Equation (5-13) to get an expression for specific growth rate:  P = y = *>  (5-14)  This means the specific growth rate is equal to the dilution rate in a continuous reactor at steady state.  (ii)  Material balance for methanol at steady state: Since methanol concentration in the reactor did not change with time at steady state, dM/dt was zero. Equation (5-6) becomes: Z)(M. -M) - —^—-X = 0  (5-15)  Equation (5-15) can be rearranged to get the following expression: X = Y (M,-M) XIU  (5-16)  (iii) Material balance for yeast extract and peptone at steady state: Since there was no yeast extract and peptone in the feed solution and it was assumed that all yeast extract and peptone in the reactor broth was used up when the reactor  40  reached steady state, dY/dt and Y in Equation (5-9) were both zero. Therefore, there was no expression for steady state material balance for yeast extract and peptone.  (iv) Material balance for product at steady state: At steady state, dP/dt in Equation (5-12) was zero so the material balance becomes: -D-P  + Y -/u-X p/x  =0  (5-17)  Equation (5-17) can be rearranged to get an expression for steady state product concentration in the reactor: P = Y -X  (5-18)  PIX  5.7.3  Specific Growth Rate  The Monod equation is a commonly used expression that relates the specific growth rate of the cell to substrate concentration:  _____  , _ ) 5  1 9  K S s+  A higher value of u means that the cell is growing faster. The specific growth rate increases with substrate concentration until reaching a maximum that is referred to as the maximum specific growth rate (u  max  ). u  m a x  is the maximum achievable growth rate at which substrate  concentration is not limiting.  The Monod constant (K ) is defined as the substrate concentration at which u = A u l  s  represents an affinity of the organism to the substrate.  The values of u  m a x  m a x  . It  and K are s  41  dependent on the organism, substrate and reactor conditions such as pH and temperature. Typical values of K are in the order of mg/L for carbohydrates substrates and ug/L for other s  compounds such as amino acids (Doran, 1995).  The specific growth rate in a continuous reactor at steady state is equal to the dilution rate, as shown in Equation (5-14). In this work, the weighted least-squares method was used to calculate the best-fit values of u  m a x  started by using initial estimates of u  and K for the Monod equation. The calculation was s  m a x  and K and Equation (5-19) to calculate u (u i ) for s  ca  c  all experiments with valid steady state results. Then the sum of least squares were calculated as below: SUM=  -A)*  (5-20)  where n is the total number of experiments with valid steady state results.  An Excel solver was used to adjust the values of u S U M was found. The values of u  m a x  m a x  and K until the minimum value of s  and K at which S U M is minimum were used in the s  Monod equation for this reactor system.  5.7.4  Productivities  The productivities of cell and product formation, i.e., Qx and Qp, are defined as: Qx = ™=*>*  (5-21)  42  (5-22)  At steady state, X = Y (M x/M  -M) and P = Y -Xas  j  p/X  shown in Equations (5-16) and (5-18)  respectively. The two volumetric rates can therefore be expressed as:  Q =D-Y (M -M)  (5-23)  Q =L>Y -Y (M-M)  (5-24)  x  x/M  P  i  P/X  XIM  When the reactor reached steady state, u = D and it was assumed that the only substrate in the reactor was methanol. The Monod equation (5-19) becomes: D  =  J^M  (  5  2  5  )  K +M SM  A n expression for steady state methanol concentration in the reactor can be obtained by rearranging the above equation: M =  ^ —  (5-26)  Thus, the expressions for the two volumetric rates become: f  Qx =  XIM  M  DK  SM S M  P-max.A/  ^  (5-27)  D  43  Qp  (5-28)  ~D Y Y m  m  plx  xIM  M-max,A/  5.7.5  _  D j  Critical and Optimum Dilution Rates  Washout is the situation at which the dilution rate is so high that the cell concentration in the reactor reduces to zero. It occurs when the rate of cell removal in the reactor outlet is greater than the rate of cell growth. The dilution rate at which washout occurs is called the critical dilution rate (D j ). cr t  Rase  ti  s '"""•41 ?A  Dilution Rate  Figure 5-4. Steady State Concentrations at Different Dilution Rates (Ngee Ann Polytechnic)  For dilution rates well below the critical point, the steady state cell (biomass), product and substrate concentrations are more or less constant, as shown in Figure 5-4. The steady state substrate concentration is almost zero at low dilution rates because nearly all substrate is 44  consumed.  Steady  state  cell  and  product  concentrations  c o n c e n t r a t i o n s o n l y , as s h o w n i n E q u a t i o n s ( 5 - 1 6 ) a n d ( 5 - 1 8 ) .  are  related  to  substrate  W i t h c o n s t a n t y i e l d s (YX/M  a n d Y p / x ) , s a m e feed substrate concentration ( M j ) and steady state substrate  concentrations  a p p r o a c h i n g z e r o , t h e s t e a d y s t a t e c e l l a n d p r o d u c t c o n c e n t r a t i o n s at l o w d i l u t i o n r a t e s a r e m o r e o r less constant.  A s d i l u t i o n r a t e i n c r e a s e s , s u b s t r a t e c o n c e n t r a t i o n i n c r e a s e s s l o w l y at first a n d t h e n i n c r e a s e s m o r e q u i c k l y as D a p p r o a c h e s the c r i t i c a l v a l u e .  A s substrate c o n c e n t r a t i o n i n the  increases, c e l l a n d p r o d u c t concentrations decreases.  reactor  W h e n t h e d i l u t i o n r a t e i s at, o r g r e a t e r  t h a n the c r i t i c a l v a l u e , w a s h o u t o c c u r s , s u c h that cell a n d p r o d u c t c o n c e n t r a t i o n s r e d u c e to zero.  O n the other hand, substrate c o n c e n t r a t i o n i n the reactor a p p r o a c h e s the v a l u e o f feed  substrate concentration.  T h e s t e a d y s t a t e c e l l c o n c e n t r a t i o n c a n b e r e w r i t t e n as b e l o w b y s u b s t i t u t i n g E q u a t i o n ( 5 - 2 6 ) into E q u a t i o n (5-16):  X = YX/M  M.  DK SM max,A/ .  (5-29)  D  T o find t h e c r i t i c a l d i l u t i o n r a t e , p u t X = 0 i n t o E q u a t i o n ( 5 - 2 9 ) a n d r e a r r a n g e t o o b t a i n :  Z) , =  "*  (5-30)  K M, SM+  A c o n t i n u o u s r e a c t o r is c o n s i d e r e d t o b e o p e r a t i n g at o p t i m u m c o n d i t i o n s w h e n t h e v a l u e s o f Q x and Q  P  are m a x i m i z e d .  T h e d i l u t i o n r a t e at w h i c h Q  x  and Q  P  reach m a x i m u m is called  45  the optimum dilution rate ( D ) . To find the optimum dilution rate, the expression for Q or OPT  X  QP, i.e., Equations ( 5 - 2 7 ) or ( 5 - 2 8 ) was differentiated with respect to D . It was assumed that  YX/M and Y  P / X  are independent of D .  The values of — o r — w a s then set to zero dD dD  Thus, the expression for critical dilution rate is:  A*=n opt r*max,M  K SM M +K t  SM  j  (5-31)  46  6.0  RESULTS AND DISCUSSIONS  6.1  Methanol Concentration in the Feed  According to gas chromatography results, the methanol concentration in the feed, which consisted of the Methanex wastewater and some chemicals as listed in Table 5-1, was 2.5 g/L (i.e., M ; = 2.5 g/L). The chemicals added to the Methanex wastewater, except the small amount of vitamin solution, were in powder form. Thus, the methanol concentration in the Methanex wastewater was expected to be about the same as in the feed solution.  6.2  Cell and Protein Production  The cell, protein and methanol concentrations for each experiment were plotted against time in Figures 6-1, 6-2 and 6-3 respectively. Each experiment was run at different dilution rates (D) except for two experiments which were both run at D = 0.017 1/h. The experiment was repeated at D = 0.017 1/h because there was a problem in controlling the pH for the first run. The resulting cell and protein concentrations were unexpectedly low (represented by dotted lines in Figures 6-1, 6-2 and 6-3), and therefore the results for this run were not used for data analysis in this study.  47  50  100  150  200  Time, t (h)  Figure 6-1. The Effect of Dilution Rate on Cell Density  48  Figure 6-3. The Effect of Dilution Rate on Methanol Concentration  The reactor was considered to reach steady state when the cell and protein concentrations were more or less constant over time, i.e., change in cell concentration within 1 g/L and change in protein concentration within 20 mg/L. For D = 0.011, 0.017 and 0.026 1/h, the reactor reached steady state after running for about 120 hours. For each of these 3 dilution rates, the average values for cell, protein and methanol concentrations after 120 hours were calculated, and were taken as the steady state concentrations. For D = 0.034 and 0.042 1/h, there were greater fluctuations in cell and protein concentrations even at extended hours (>150 hours) so it was difficult to determine whether the reactor reached steady state. Section 6.3 shows that these 2 dilution rates were actually at or greater than the critical rate such that the reactor was not stable.  The average values of the last 3 data points were  calculated and assumed to be the steady state concentrations for these 2 dilution rates; however, they were not used for parameters estimation in the next section. 49  The procedures for measuring lipase activity, as described in Section 5.6.4, were followed. There were great fluctuations in the pH measurement which resulted in unstable addition of NaOH. It was suspected that the fluctuations in pH readings were due to the interference of electrical signals from other equipments in the laboratory. In attempt to solve the problem, a wire was attached to the titrator to ground the system. However, the fluctuations still existed. As a result, no lipase activity was measured in this study, and it was assumed that all the protein produced was lipase. It was a reasonable assumption because Hoy et al. (2003) succeeded in producing lipase with the same Pichia strain.  6.3  Parameters Estimation  For D = 0.011, 0.017 and 0.026 1/h, the steady state results were used to calculate the yields (YX/M and Yp/x) with Equations (5-16) and (5-18). The results were plotted in Figure 6-4. It was shown on the graph that the variations in both YX/M and Yp/x were not significant. The average values of YX/M and Y /x were 3.3 ± 0.067 g/g and 0.015 ± 0.0023 g/g respectively. P  50  0.01  0.02  0.03  Dilution rate, D or specific growth rate, u (1/h)  Figure 6-4. Yields at D = 0.011, 0.017 and 0.026 1/h  The steady state results for D = 0.011, 0.017 and 0.026 1/h were also used to find the values of u  MAX  ,M and KS,M by following the method described in Section 5.7.3. With values of u ax,M m  and KS.M, the critical and optimum dilution rates can be calculated with Equations (5-30) and (5-31). The calculated results were summarized in Table 6-1.  Table 6-1. Calculated Parameters from Steady State Results  Yx/M, avg  (g/g)  3.3 ±0.067  Y /x,avg (g/g)  0.015 ±0.0023  H-max.M  0.034  P  K  S > M  (1/h)  (mg/L)  4.5  DcntO/h)  0.034  D  0.033  o p t  (l/h)  51  Some of these parameters were reported in the literature. The results from this study and the literature were compared in Table 6-2. It was found that both  u  m a x >  M  and K  S j M  in this study  were smaller than the literature values. The results were expected because in this study Pichia pastoris was grown in wastewater which may contain impurities, such as ether, esters, acetone and other hydrocarbons, that may not be favourable for growth. dilution rate found in this study was within the range of  D t o p  The optimum  published in the literature.  Table 6-2. Comparison of Parameters from Current Study to Literature Results Current study  Literature*  M-max,M(l/h)  0.034  0.08-0.27  K , (g/L)  0.0045  0.005 - 0.22  Dopt  0.033  0.03 -0.035  s  M  (1/h)  *(Curvers et al, 2002; d'Anjou & Daugulis, 2000; d'Anjou & Daugulis, 2001; Goodrick et al., 2001; Kocken, 1999; Zhang et al., 2000)  6.4  Critical Condition  Equation (5-26) can be used to calculate the steady state methanol concentration at different dilution rates. The corresponding cell and protein concentrations can then be calculated with Equations (5-16) and (5-18). The experimental (determined in Section 6.2) and calculated steady state concentrations were plotted against dilution rates in Figures 6-5 and 6-6.  52  -X (calculated) -P (calculated)  • X (experimental) A P (experimental)  o o 3 O  O 3  0.00  0.01  ~i 0.02  3  r~ 0.03  0.04  0.05  Dilution rate, D or specific growth rate, u (1/h)  Figure 6-5. Steady State Cell and Protein Concentrations at Different Dilution Rates  A M (experimental)  M (calculated)  E c o c » u c o o o c re  **  0.00  0.01  0.02  0.03  0.04  0.05  Dilution rate, D or specific growth rate, u (1/h)  Figure 6-6. Steady State Methanol Concentrations at Different Dilution Rates  53  The curves for the calculated results in Figures 6-5 and 6-6 were in good agreement with the expected results, as shown in Figure 5-4. At low dilution rates (i.e.,  D «  Dcrit=  0.034 1/h),  steady state methanol concentrations were almost zero because nearly all methanol was consumed. Cell and protein concentrations reached about 8 g/L (dry cell weight) and 125 mg/L respectively. The results were compared to the literature results.  As mentioned in  Section 2.4.2, Hoy et al. (2003) succeeded in growing Pichia pastoris in various media to a cell density of 8-12 g/L (dry cell weight) and protein concentration of 48-57 g/L. Holmquist et al. (1997) succeeded in expressing Geotrichum candidum lipase in Pichia pastoris to levels of about 60 mg/L.  As dilution rate approached the critical value, steady state methanol concentration increased while cell and protein concentrations decreased. When the critical dilution rate was reached, cell washout occurred such that steady state cell and protein concentrations reduced to zero, and methanol concentration in the reactor became the same as methanol concentration in the feed (i.e., M = M ; = 2500 g/L).  For dilution rates smaller than the critical rate, the experimental concentrations matched the calculated ones.  As mentioned in Section 6.2, there were greater fluctuations in  concentrations at D = 0.034 and 0.042 1/h even at high hours.  Thus, the experimental  concentrations at these 2 dilution rates were not the true steady state concentrations such that the experimental and calculated results were not in very good agreement. However, both experimental and calculated results showed similar trends, i.e., a rapid drop in cell and  54  protein concentrations, and a dramatic increase in methanol concentration near the critical dilution rate.  6.5  Optimum Condition  At each of the 5 dilution rates under study, the experimental cell and protein concentrations at steady state were used to determine the rates of cell (Qx) and product production (Qp) with Equations (5-21) and (5-22). Qx and Qp'were also calculated with Equations (5-27) and (528) at different dilution rates by using the calculated parameters from the last section. Both experimental and calculated production rates were plotted in Figure 6-7.  « •  Qx (experimental) Qp (experimental)  Qx (calculated) Qp (calculated)  Dilution rate, D or specific growth rate, u (1/h)  Figure 6-7. Cell and Product Productivities at Different Dilution Rates  The experimental results showed that Qx and QP were maximized when dilution rate was between 0.026 and 0.034 1/h. This means that the optimum dilution rate should lie between  55  0.026  and  0.034  was about  1/h.  0.033 1/h  T h e calculated at w h i c h b o t h  Qx a n d Qp c u r v e s  Qx a n d Qp w e r e  s h o w e d that the o p t i m u m d i l u t i o n rate  m a x i m i z e d , i . e . at a b o u t  0.26  g / L / h and  4.0 m g / L / h r e s p e c t i v e l y .  I t s h o u l d b e n o t e d t h a t t h e o p t i m u m c o n d i t i o n i n t h i s s t u d y r e f e r r e d t o a d i l u t i o n r a t e at w h i c h Qx  a n d Qp  were maximized.  T h i s means the reactor system w a s o p t i m i z e d i n terms  p r o d u c t i v i t i e s o n l y but not i n terms o f cost and other factors. o p t i m u m d i l u t i o n rate ( D  0.034  1/h).  o p t  =  0.033  of  It s h o u l d a l s o b e n o t e d t h a t t h e  1/h) w a s o n l y s l i g h t l y s m a l l e r t h a n t h e c r i t i c a l r a t e  T h u s , i t m a y n o t b e a g o o d i d e a t o r u n t h e r e a c t o r at D  o p t  (0011=  as a s m a l l f l u c t u a t i o n i n  the f l o w rate m a y result i n w a s h i n g out o f the cells.  6.6  System Model  A s discussed in Section differential  5.7.1,  the reactor system m o d e l c a n be represented b y  equations ( O D E s ) .  r e a c t o r i n n o n - s t e a d y state.  4  ordinary  These equations can be s o l v e d n u m e r i c a l l y to m o d e l  the  In this study, M a t l a b p r o g r a m s ( A p p e n d i x B ) w e r e w r i t t e n to  s o l v e t h e f o l l o w i n g set o f O D E s .  (i)  M a t e r i a l b a l a n c e f o r c e l l at n o n - s t e a d y s t a t e :  — = -D-X + \i-X dt where  u =  K +M SM  (5-3)  H  K, +Y r  56  (ii)  Material balance for methanol at non-steady state: —  dt U  = D(M -M)  Y  l  1  £—X  (5-6)  XIM  1 W ^ K +M M  where u. =  SM  (iii) Material balance for yeast extract and peptone at non-steady state: ^- = -D-Y dt .  ^—-X Y  (5-9)  xn  M'max.M  where u.  (iv) Material balance for product at non-steady state: ^- = -D-P + Y - -X at p/x  ,  1 W / '  M  U  where u = K M *  SM+  T7~  (5-12)  M  1  i  h  max,/^  K +Y SJ  To solve the above ODEs, some of the parameters Section 6.2 were used. The values of  u ax,Y, m  (u x,M, K ,M, YX/M, ma  S  Yp/x) estimated in  K , y and Yx/y were estimated by observation. s  All the parameters used in solving the ODEs were listed in Table 6-3. The initial conditions were the first data points (at time ~ 0 hour) of the experimental measurement for cell, methanol, yeast extract and peptone, and product concentrations.  57  Table 6-3. Parameters used for Solving Non-steady State ODEs  Hmax,M  K  s> M  (^h)  (mg/L)  0.034 4.5  Yx/M (g/g)  3.3  Yp/x (g/g)  0.015  Umax,Y  0.20  K  s>Y  (1/h)  (mg/L)  YXA- (g/g)  200 0.20  For each of the 3 experiments with dilution rates less than the critical rate (i.e., D = 0.011, 0.017 and 0.026 1/h), the above parameters were used to solve the 4 ODEs. The calculated cell and protein concentrations were plotted in Figures 6-8 to 6-13 to compare with the experimental results. It was shown in the plots that the calculated results were in good agreement with the experimental ones.  Therefore, the ODEs and the parameters shown  above can be used to predict the behaviour of the reactor system under study.  58  Figure 6-8. Experimental and Calculated Cell Concentrations at D = 0.011 1/h  Figure 6-9. Experimental and Calculated Protein Concentrations at D = 0.011 1/h  O  m e a s u r e d X (g/L) c a l c u l a t e d X (g/L)  Figure 6-10. Experimental and Calculated Cell Concentrations at D = 0.017 1/h  140  120  100  E  +  measured P (mg/L) calculated P (mg/L)  c o c a) o c o o c <u o  Figure 6-11. Experimental and Calculated Protein Concentrations at D = 0.017 1/h  o  time (h)  Figure 6-12. Experimental and Calculated Cell Concentrations at D = 0.026 1/h  200  time (h)  Figure 6-13. Experimental and Calculated Protein Concentrations at D = 0.026 1/h  7.0  CONCLUSIONS  This project studied the possibility of growing a genetically-modified Pichia (Geotrichum candidum recombinant Pichia  strain, GS115 (his4),  pastoris  harboring plasmid  YpDC420) and producing a recombinant protein in the wastewater from the Methanex distillation column bottom stream in a continuous reactor at 5 different dilution rates, i.e., 0. 011. 0.017, 0.026, 0.034 and 0.042 1/h. The conclusions of this study are summarized below:  1.  Pichia pastoris was capable of growing and producing protein in the Methanex wastewater, which had a methanol concentration of 2.5 g/L.  2.  For D = 0.011, 0.017 and 0.026 1/h, the reactor reached steady state after about 120 hours. For D = 0.034 and 0.042 1/h, the reactor did not reach steady state even at extended running times (>150 hours).  3.  From the steady state results of D = 0.011, 0.017 and 0.026 1/h, it was calculated that the values of Y x / , Y M  P / X  , u  max  , and K were 3.3 ± 0.067 g/g, 0.015 ± 0.0023 g/g, 0.034 s  1/h, and 4.5 mg/L, respectively. Both u  m a x  and K in this study were smaller than the s  literature values because Pichia pastoris was grown in wastewater which may contain impurities not favourable for growth. 4.  The optimum dilution rate was about 0.033 1/h, which was within the range of D  o p t  published in the literature. At the optimum dilution rate, Q x and Q p were maximized and had values of 0.26 g/L/h and 4.0 mg/L/h, respectively. 5.  The critical dilution rate was about 0.034 1/h. At dilution rates well below the critical rate, steady state methanol concentrations were almost zero while cell and protein 62  concentrations were about 8 g/L (dry cell weight) and 125 mg/L, respectively. As dilution rate approached the critical value, steady state methanol concentration increased while cell and protein concentrations decreased. At the critical dilution rate, steady state cell and protein concentrations reduced to zero because of cell washout, and methanol concentration in the reactor became the same as the feed methanol concentration. The reactor system model under study could be represented by 4 ordinary differential equations and the following parameters: u 3.3 g/g, Y,./x = 0.015 g/g, u  m a x > Y  max  , M - 0.034 1/h, K ,  = 0.20 1/h, K  s  S > Y  M  = 4.5 mg/L, YX/M  =  = 200 mg/L, and YX/Y = 0.20 g/g.  The ODEs were solved numerically and were able to predict the reactor behaviour. The calculated solutions were in good agreement with the experimental results.  63  8.0  RECOMMENDATIONS  P o s s i b l e future  projects  are to g r o w  Pichia pastoris  i n other  methanol-containing  s t r e a m s , o r i n t h e M e t h a n e x w a s t e w a t e r at d i f f e r e n t c o n d i t i o n s , e . g . , w i t h d i f f e r e n t supplements.  Pichia  nutrient  strains e x p r e s s i n g different proteins c a n a l s o be tested to see i f t h e y c a n  g r o w i n the M e t h a n e x wastewater and other m e t h a n o l - c o n t a i n i n g waste  A  waste  detailed characterization o f the M e t h a n e x wastewater  streams.  should be done  i n the  future  to  i d e n t i f y t h e c o n s t i t u e n t s i n it. It w o u l d t h e n b e p o s s i b l e t o t e s t t h e e f f e c t o f e a c h c o m p o n e n t on growth and protein production.  T h e o p t i m u m c o n d i t i o n i n t h i s s t u d y r e f e r r e d t o a d i l u t i o n r a t e at w h i c h t h e p r o d u c t i v i t i e s w e r e m a x i m i z e d . In the future, it is r e c o m m e n d e d t o s t u d y the o p t i m u m c o n d i t i o n s i n t e r m s o f m i n i m u m costs, m a x i m u m profits and other factors.  A further i n v e s t i g a t i o n o n the fluctuations i n p H m e a s u r e m e n t s d u r i n g l i p a s e assay s h o u l d b e done  i n the future.  I f the p r o b l e m is f i x e d ,  p r o d u c e d is lipase a n d to determine  it i s p o s s i b l e t o m a k e  its a c t i v i t y .  sure that the  It i s a l s o r e c o m m e n d e d  protein  to m o n i t o r  the  m e t h a n o l c o n c e n t r a t i o n i n the reactor c o n t i n u o u s l y .  T h e r e a c t o r s y s t e m u n d e r s t u d y s h o u l d a l s o b e r u n i n o t h e r o p e r a t i o n m o d e s , s u c h as b a t c h a n d f e d - b a t c h m o d e s , to c o m p a r e the results f r o m the c o n t i n u o u s runs.  It s h o u l d b e  then  p o s s i b l e to d e t e r m i n e w h i c h o p e r a t i o n m o d e is m o r e suitable for treating m e t h a n o l i n the waste stream, g r o w i n g  Pichia pastoris  a n d p r o d u c i n g the p r o t e i n o f interest.  64  REFERENCES Advances in Life Science. (2002, December 2). Pichia Protein Expression Usage Takes OffUse of Pichia Expression System is Worldwide. Retrieved June 15, 2004, from Advances in Life Science Web site: http://www.advancesinlifescience.com/news_39.htm Berube, P.R., & Hall, E.R. (1999). Treatment of, Evaporator Condensate Using a High Temperature Membrane Bioreactor: Determination of Maximum Operating Temperature and System Costs. 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Chemical Engineering Progress, 98(3), 34-41. Yu, Z., & Fu, Y. (2004). Recombinant Human Albumin Fusion Proteins with Long-lasting Biological Effects. U.S. Patent No. 20040063635. Washington, DC: U.S. Patent and Trademark Office Zhang, W., Bevins, M.A., Plantz, B.A., Smith, L.A., & Meagher, M.M. (2000). Modeling Pichia pastoris Growth on Methanol and Optimizing the Production of a Recombinant Protein, the Heavy-chain Fragment C of Botulinum Neurotoxin, Serotype A. Biotechnology and Bioengineering, 70(1), 1-8.  72  APPENDIX A - Calibration Curves  Absorbance at 600nm  Figure A - l . Cell Concentration Calibration Curve  1 2 0 0 0 -1  •  Area ratio of methanol to 1-butanol  Figure A-2. Methanol Concentration Calibration Curve  F i g u r e A-3.  Protein Standard (Bovine Serum Albumin) Concentration Calibration Curve  74  APPENDIX B - Matlab Programs 1) Main Program: thesis, m clear a l l g l o b a l D mumaxm ksm mumaxy ksp S i Yxsm Yxsp Ypx mumaxm=0.03445; %Maximum s p e c i f i c growth r a t e f o r methanol{1/h) ksm=4.461; %Monod Constant f o r methanol(mg/L) mumaxy=0.2; ^Maximum s p e c i f i c growth r a t e f o r y e a s t e x t r a c t and peptone(1/h) ksp=200; %Monod Constant f o r y e a s t e x t r a c t and peptone(mg/L) Si=2500; %Feed methanol c o n c e n t r a t i o n (mg/L) Yxsm=3.266; %Biomass Y i e l d from methanol (g/g) Yxsp=0.2; %Biomass Y i e l d from y e a s t e x t r a c t and peptone (g/g) Ypx=0.015; %Product Y i e l d from biomass (g/g) j=l; % d a t a p o i n t index time = [0 200]; f p r i n t f ( ' \ n D i l u t i o n Rate, D (1/h):') D = i n p u t ( \ n E n t e r 0.011, 0.017, 0.026, 0.034, o r 0.042: ' ) ; i f D == 0.011 t l = [ 0 . 0 5 27.81 71.2 95.18 120.1 144.3 167.5 191.4]';%time(h) sub= [232.6 208.8 28.80 6.492 6.592 5.030 11.40 4.853]'; %[MeOH] (mg/L) c e l l = [ 0 . 1 3 5 6 : 4.487 4.952 5.998 8.269 8.522 7.827 8.405] ' ; % [ C e l l ] (g/L) t2 = t l ; %time(h) pro = [0 20.64 58.93 92.52 102.2 99.539 106.8 108.0]'; % [ p r o t e i n ] ( m g / L ) e l s e i f D == 0.017 t l = [0.1 19.63 45.31 67.60 115.2 141.1 163.7]'; %time(h) sub = [89.50 31.43 43.85 39.50 42.71 31.47 11.41]'; %[MeOH](mg/L) c e l l = [0.1276 4.577 4.604 5.653 8.119 8.206 8.076]'; % [ C e l l ] ( g / L ) t2 = t l ; %time(h) pro = [0 15.92 90.22 98.03 135.63 126.05 126.5]'; % [ p r o t e i n ] ( m g / L ) e l s e i f D == 0.026 t l = [0.06 19.00 21.05 23.26 42.99 48.24 67.66 73.37 94.67 114.4 119.6 140.3 143.5 164.7]'; %time(h) sub = [6.579 3.779 0.641 1.784 2.224 28.45 70.04 46.45 40.21 3.891 0.777 2.210 9.107 2.904]'; %[methanol](mg/L) c e l l = [0.084 3.922 4.076 4.176 4.146 4.657 6.419 5.633 6.879 8.327 7.887 8.094 7.595 7.900]'; % [ C e l l ] ( g / L ) t2 = [0.06 19.00 21.05 23.26 42.99 48.24 67.66 73.37 94.67 114.4 119.6 140.3 164.7]'; %time(h) pro = [0 12.00 8.890 13.28 16.12 71.66 101.6 92.94 106.3 116.7 130.6 138.5 140.7]'; % [ p r o t e i n ] (mg/L) e l s e i f D == 0.034 t l = [0.15 4.46 24.42 27.53 47.95 72.83 95.30 119.7 124.4 144.3 147.9 169.0 171.6 192.9]'; %time(h) sub = [14.11 17.56 1158 1233 1401 1364 544.3 9.495 12.05 9.286 19.00 11.45 23.36 27.43]'; %[MeOH](mg/L) c e l l = [0.2951 0.5583 4.760 4.648 5.095 4.574 3.797 5.379 5.573 6.427' 6.466 7.466 7.092 7 . 1 5 5 ] ' ; % [ C e l l ] ( g / L ) t2 = [ 0 . 1 5 4.46 27.53 47.95 72.83 95.3 119.66 124.35 147.89 168.98 171.57 192.9]'; %time (h) 1  75  pro = [0 -0.889 1.667 18.89 49.93 48.56 73.15 61.91]'; % [ p r o t e i n ] (mg/L) e l s e i f D == 0.042 t l = [0.05 3.44 21.9 25.44 44.94 70.55 166.3 192.9]'; %time(h) sub = [147.8 380.9 1155 1177 1293 1873 %[MeOH](mg/L) c e l l = [0.1356 0.2361 3.318 2.900 2.722 2.233 2.100]'; % [ C e l l ] ( g / L ) t2 = [0.05 3.44 21.9 25.44 70.55 95.78 %time(h) pro = [ 0 0 7.430 9.487 3.220 44.64 41.78 %[protein](mg/L) else error(' I n v a l i d entry!') return end  65.01 67.07 63.39 77.62  95.78 119.5 145.8 1552 1871 2292 2491  2304]';  2.457 2.667 3.031 2.664 119.5 145.8 166.3 192.9]'; 38.10 33.91 26.25]*;  x 0 = [ s u b ( j ) 20000 c e l l ( j ) p r o ( j ) ] ; % i n i t i a l c o n d i t i o n f o r methanol c o n c e n t r a t i o n (mg/L), y e a s t e x t r a c t and peptone c o n c e n t r a t i o n (mg/L), c e l l c o n c e n t r a t i o n (g/L) & p r o t e i n c o n c e n t r a t i o n (mg/L) [ t , x ] = o d e 4 5 ( ' c s t r ' , t i m e ,x0); %methanol for i = l : s i z e ( t ) mu_calcm(i,1)=mumaxm*x(i,1)/(ksm+x(i,1)); end for i=l:size(sub) mu_measm (i,1)=mumaxm* s u b ( i ) / ( k s m + s u b ( i ) ) ; end % y e a s t e x t r a c t and peptone for i=l:size(t) m u _ c a l c p ( i , 1)=mumaxy*x(i, 2 ) / ( k s p + x ( i , 2)) ; end  p l o t ( t l , s u b , ' x ' , t , x ( : , 1 ) ,'-') % p l o t methanol cone versus time legend('measured M ( m g / L ) ' , ' c a l c u l a t e d M (mg/L)'), x l a b e l ( ' t i m e y l a b e l ( ' m e t h a n o l c o n c e n t r a t i o n , M (mg/L)')  (h)'),  figure p l o t ( t , x ( : , 2 ) , '-*) % p l o t yeast e x t r a c t and peptone cone v e r s u s time l e g e n d ( ' c a l c u l t e d Y (mg/L)'), x l a b e l ( ' t i m e ( h ) ' ) , y l a b e l ( ' y e a s t e x t r a c t and peptone c o n c e n t r a t i o n , Y (mg/L)') figure p l o t ( t l , c e l l , ' o ' , t , x ( : , 3 ) , ' - ' ) % p l o t c e l l c o n c e n t r a t i o n versus time legend('measured X ( g / L ) ' , ' c a l c u l a t e d X ( g / L ) ' ) , x l a b e l ( ' t i m e (h) * ) , y l a b e l ( ' c e l l c o n c e n t r a t i o n , X (g/L)') figure p l o t ( t 2 , p r o , ' + ' , t , x ( : , 4 ) , ' - ' ) % p l o t p r o t e i n cone versus time legend('measured P ( m g / L ) ' , ' c a l c u l a t e d P (mg/L)'), x l a b e l ( ' t i m e y l a b e l ( ' p r o t e i n c o n c e n t r a t i o n , P (mg/L)')  (h)*),  76  figure plot(tl,mu_measm', *',t,mu_calcm', ' - ') % p l o t s p e c i f i c growth r a t e v e r s u s time legend('measured mu (1/h)', ' c a l c u l a t e d mu ( 1 / h ) ' ) , x l a b e l ( ' t i m e ( h ) ' ) , y l a b e l ( ' s p e c i f i c growth r a t e , u (1/h)') 1  figure p l o t (t,mu_calcp ' , ' - ' ) %plo.t s p e c i f i c growth r a t e versus time l e g e n d ( ' c a l c u l a t e d mu (1/h)'), x l a b e l ( ' t i m e (h) ') , y l a b e l ( ' s p e c i f i c growth r a t e , p (1/h)')  2) Secondary Program: cstr.m function z=cstr(t,x) g l o b a l D mumaxm ksm mumaxy ksp S i Yxsm Yxsp  Ypx  z=zeros(4,1); %methanol z(l)=D*(Si-x(l))-  mumaxm*x(l)/(ksm+x(l))  *x(3)*1000/Yxsm;  % y e a s t e x t r a c t and peptone z(2)=-D*x(2)%cell z(3)=x(3)*(-D+  mumaxy*x(2)/(ksp+x(2))  *x(3)*1000/Yxsp;  ((mumaxm*x(1))/(ksm+x(l)) + (mumaxy*x(2))/(ksp+x(2)))  z(4)=-D*x(4)+Ypx*1000* ((mumaxm*x(l))/(ksm+x(l))+(mumaxy*x(2))/(ksp+x(2)))  ) ;  *x(3);  77  APPENDIX C - Sample Calculations n Yield •  Average:  YY _ ^  (3,3 + 3.3+3.2)  *XIM,avg  ~  n  •  3  Standard deviation:  ^XIM.avg) X/M,  SD  n-l (3.3-3.3) +(3.3-3.3) +(3.2-3.3) _ 2  '  2  2  3-1  Q  ^ = b = =  -  2) Critical Dilution Rate: D cn  = »-M. ' £ +M,.  =  S  (0m4/h\2.5 /L) (4.5 /ng / L)(l g 11000 mg) +.(2.5 g IL) g  3) Optimum Dilution Rate:  (5-31)  : (0.034 lh  (4.5 mg IL) (2.5_ /L\\000mgIg) +  (4.5mgIL))  = 0.033  78  

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