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Automatic bioprocess control. 4. A prototype batch of Saccharomyces cerevisiae
Journal of Biotechnology, 29 (1993) 57-74
57
© 1993 Elsevier Science Publishers B.V. All rights reserved 0168-1656/93/$06.00
JBT00861
Automatic bioprocess control. 4. A prototype batch of Saccharomyces cerevisiae Georg Locher 1, Ulrike H a h n e m a n n , B e r n h a r d Sonnleitner and Armin Fiechter Institute of Biotechnology, ETH Hiinggerberg, Ziirich, Switzerland. (Received 18 March 1992; revision accepted 15 July 1992)
Summary The recent investigations in our high performance bioreactors have shown that living cells can be extremely sensitive to physical-chemical environmental conditions and their changes. Consequently, the relationship bioreactor-living cell must thoroughly be investigated in order to discuss both: whether bioreactor characteristics are limiting/dominating during cultivation and to what extent controlled changes of the cellular environment can lead the cells to a desired physiological state. For these investigations, a generally accepted biological test organism would be helpful, of which the requirements and reactions under certain conditions are well known. Saccharomyces cerevisiae is a well known, very robust but nevertheless sensitive organism, eligible for this purpose. In this article a typical batch cultivation on glucose is presented, collected from approx. 300 experiments. Regarding metabolite production and consumption, seven different phases are distinguished on the basis of approx. 20 sensor signals and their metabolic background is discussed. Prerequisite, however, was an exhaustive knowledge upon extracellular conditions, a task which could successfully be fulfilled with the highly automated equipment introduced in the preceding articles of this series.
Correspondence to: B. Sonnleitner, Institute of Biotechnology, ETH H6nggerberg, CH 8093 Ziirich, Switzerland. 1 Present address: MIT Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
58 Sensors; Automation; Bioprocess control; Saccharomyces cerevisiae prototype batch; Non-invasive measurement; Reference organism; Measurement; Respiratory regulation; Automated C-balance
Introduction
Saccharomyces cerevisiae-type yeasts are of considerable economic importance and, furthermore, well suited test organisms for metabolic studies. Many media and cultivation conditions have been described testifying an extraordinary flexibility to extra-cellular conditions. The exploitation of the yeasts capabilities by humans over several thousand years led to a multitude of products with alcohol and biomass still being economically the most important ones. However, not only the classical, low tech bioprocesses can be performed with yeasts. According to the mechanical robustness, chemical and genetical properties, easy handling and cultivation as well as usually non-pathogenity yeasts are often used as test organisms in research and development. The heterologous production of many proteins as well as stereoselective bioconversions are possible and yeasts became an important expression system in the recombinant technology. Such a huge potential of cellular capabilities can easily lead to misinterpretations of experimental results, i.e. a mixing up of biological phenomena with properties of the technical equipment when interpreting bioprocess data. Technically unbiased, i.e. sound biological data of a reference organism allow to make that distinction and improve both, basic biological research as well as bioprocess development (Adler, 1988). In this article, we recommend S. cerevisiae as such a reference because it is a very well known organism with a sophisticated metabolism and a broad spectrum of applicabilities. Some of the advantages resulting from this "biological test system" are briefly outlined in the following. A multitude of cellular capabilities is widespread over many species due to the conservative character of nature. This allows to study certain phenomena in one particular species and transfer the results to others. However, presumptious is the mechanistical understanding instead of a description of a multitude of distinct "effects". An example for this is the uptake and metabolism of a wide range of sugars such as maltose, galactose and melibiose which is regulated by glucose. This was discussed in the context of catabolite repression and, unfortunately, extended to the repression of the glucose utilization because of the detection of "free glucose" contemporary to a decreased growth rate during batch cultures. We now understand that mainly the magnitude of the glucose flux through the respiratory bottle-neck is responsible for the so called "Crabtee-" or "Glucose-" effect. Restricting the considerations to "static" concentrations does not account for the dynamics of fluxes, which are very often by far of greater importance. Many observations can be explained in view of respiration which is assumed to be a bottle-neck in the cellular metabolism. The distinction between "glucose-sensitive" and "glucose-insensitive" yeast strains was coined in the context of the
59 "Crabtree" effect (Fiechter et al., 1981). It can now be interpreted as the cells' ability of regulating the glucose consumption. Glucose-sensitive yeasts such as S. cereuisiae are not able to control the consumption according to their respiratory capability and - as a consequence - may overload it. This leads to the formation of intermediates such as ethanol which is utilized in further growth phases as a carbon a n d / o r energy source. Other glucose-sensitive yeasts lost the capability of utilizing ethanol as the carbon source and exclusively produce energy thereof. Glucose-insensitive yeasts control the glucose uptake rate according to the maximum respiratory capacity. Consequently, no overload of respiration occurs and ethanol is not formed. Undoubtedly, the details of cellular control are very complex network which should not be oversimplified. But, the above mentioned interpretation of metabolism is a comprehensive approach and refers to some general, underlying principles which can be studied in S. cereuisae. It is an instructive example for an overflow reaction and can facilitate the understanding of similar reactions in other cells, e.g. lactic acid in animal cells or acetic acid in E. coli (Fiechter and Seghezzi, 1992). Another example for the benefits of S. cereuisiae as a test system is the proliferation mechanism which can be studied in partially synchronized (along the cell cycle) populations during continuous cultures. In addition to the benefits for basic biological research (MiJnch et al., 1992) this effect is also a "measure" for the quality of the control equipment: unless sufficiently precise control tools for the microenvironmental conditions in a bioreactor are available, oscillations will or will not occur or may dampen out with time (Str~issle et al., 1989). Another point that comes along with qualifying the equipment by its ability of setting up a suited environment for sophisticated processes is the time constant of reactions. Bioreactions are very often considered to be slow, and particularly yeasts are even slower than many other living cells. However, they can (re)act in the time range of s. Ethanol excretion in a continuous culture, for example, starts immediately after a significant step up in the dilution rate and must not be explained by mechanisms on the level of transcription but certainly by inhibition or limitation/overflow phenomena of particular metabolic pathways. Of course, the equipment must be capable of this time resolution and should, further, neither disturb the bioprocess nor destroy the ceils. In industrial applications, the biological potential is generally not exploited exhaustively because of technical insufficiencies or limitations. The question whether and how to optimize the process can reasonably be answered only if the biological potential is known and strictly distinguished from technical bias. Test systems allow to evaluate specific bioreactor related properties from the differences between the results obtained with the respective equipment and a reference experiment. Potentials and limitations of bioreactors can be compared in order to find the one best suited for a given task. In this article, we quantitatively describe batch experiments with S. cereuisiae which - in our estimation - reflect exclusively the biological potential of the cells rather than a superposition with technical limitations. The intention is to promote the establishment of this organism as a test and reference system in biotechnology.
6o The trajectories of on-line and off-line measurements over typical batches are shown. Further, a synopsis of the metabolism is given.
Materials and Methods
Organism. The experiments were carried out with Saccharomyces cerevisiae strain H 1022 (ATCC 32167). Media. The inoculum for the first cultivation was provided either as a (containing 3% glucose) as described contained varying amounts of glucose,
batches in the repetitive batch mode of complex medium or as a defined medium by Hug et al. (1974). The complex medium 10 g 1-1 yeast extract and 20 g I- 1 peptone.
Cultivation conditions. The following cultivation conditions were controlled in the compact loop bioreactor (in house construction, 5 - 6 1 working volume): temperature 30 + 0.02°C, pH 5 ___0.03 ( N a O H / H 3 P O 4 ) , gas flow rate 1 _+ 0.03 vvm, pressure 1.1 + 0.01 bar. Analyses. Sterile sampling was provided by an automatic sampling valve (in house construction, see Fig. 1). Biomass was determined gravimetrically after membrane filtration (0.2/zm, Zetapor). Glucose was measured enzymatically (Yellow Springs, USA). The exhaust gas was analyzed with a paramagnetic O 2 (Helox 3, Helantec, Switzerland) and an infrared CO 2 analyzer (Binos 1, Leybold Heraeus, FRG). Partial pressures of ethanol, CO 2 and O 2 were approximated by a mass spectrometer (Leybold Heraeus, F R G ) with a membrane inlet. In addition, pO 2 was measured amperometrically (Ingold, Switzerland) and pCO 2 potentiometrically (Ingold, Switzerland). Cell-free supernatant was provided by a membrane filter (in house construction: residence time in loop approx. 5 s, Rayflow X100, Tech-Sep, France). Organic acids were measured with a gas chromatograph (Hewlett Packard 5830 A; 80/120 Carbopack B - D A / 4 % Carbowax 20M, Supelco). Pyruvic acid and glycerol were also determined enzymatically (Boehringer Mannheim, FRG).
Results and Discussion
General remarks It is widely accepted to break a batch of S. cervisiae with glucose as the sole carbon and energy source into two phases. During the "glucose phase" glucose is converted into biomass and ethanol and during the second phase, ethanol is reconsumed again (Rose and Harrison, 1989; Berry et al., 1987). The growth on ethanol reveals a higher yield than the growth on glucose. From the numerous investigations on S. cerevisiae it is obvious that there are more intermediates formed and excreted which are responsible for a typical batch
61
Isterilization:,
air
.~ ~ ' ~ " ~
N II
s~m~le waste
air ~
steam L/~Jfilter
_
P0~!n.~J~!.° aJr
N
II
sample waste
Fig. 1. Schematic drawing of a sterilizable sampling valve. It can be mounted to the normed 25 mm connector port, is actuated pneumatically and in situ sterilizable. After sampling, the central bolt is held in a backward position for sterilization. Steam flushes a ceramic filter and all the surfaces which had been in contact with culture liquid. Afterwards, air is used for drying. During sampling, the bolt is pushed pneumatically into the forward position. Caused by a slight overpressure inside the bioreactor, the culture liquid is injected into respective receptacle. The sequence of actions is computer-controlled and allows a sampling frequency which is exclusively dependent on the time for sterilization and drying (1 min). No culture liquid needs to be drained.
under such conditions. A contiuous carbon balance over biomass, ethanol, CO 2 and glucose indicates that during exponential growth on glucose an increasing a m o u n t o f c a r b o n b y p a s s e s this t h e o r e t i c a l e v a l u a t i o n . U n k n o w n i n t e r m e d i a t e s t h a t a r e n o t i n c o r p o r a t e d in t h e set o f b a l a n c e e q u a t i o n s u s e d s u m u p to a p p r o x . 1 0 - 1 5 % e r r o r at t h e e n d o f t h e g r o w t h o n g l u c o s e . L a t e r d u r i n g c u l t i v a t i o n , t h e y
62
"6 E
~
ethanol
0
C02
~ time (h)
J
15.5
Fig. 2. Continuous carbon balance o f a prototype S. cerevisiae batch cultivation (from Locher er al.,
1992) over the bioreactor content. Analyses of glucose (Yellow Springs analyzer), ethanol (MS) and dry weight of biomass in the medium, as well as integrated losses by CO 2 (infrared gas analyzer) and ethanol (GC) through the exhaust gas are making up the C-balance. Biomass composition was assumed to be constant with a molar carbon fraction of 49%.
a r e r e c o n s u m e d a n d c o n v e r t e d i n t o b i o m a s s w h i c h is c o n s i d e r e d in t h e c a l c u l a t i o n - t h e c a r b o n b a l a n c e b e c o m e s v a l i d a g a i n ( F i g . 2). T h e b a s i s for t h e f o l l o w i n g p r o t o t y p e b a t c h o f S. cerevisiae a r e a p p r o x . 300 c u l t i v a t i o n s w h i c h w e r e c a r r i e d o u t u n d e r d i f f e r e n t c o n d i t i o n s (Fig. 3). T h e inoculum was provided from either defined or complex medium and the batches
time
,
Fig. 3. A widely accepted distinction is the separation of the "glucose" phase from the "ethanol" phase during batches of S. cerevisiae - type yeast. During the former glucose is metabolized into biomass, ethanol and CO 2 whereas during the latter, ethanol is reconsumed again. This behaviour was analyzed in approx. 300 repetitive batches under different conditions in order to gain a more detailed insight into the metabolism of yeast. In the figure are shown approx. 1% of the CO 2 exhaust gas analysis data obtained from 100 automated batches.
63 themselves were performed in defined medium. Due to the high sensitivity of S. cerevisiae to extracellular changes, a defined medium must be taken, otherwise the scatter of experimental results caused by changes of the complex medium components is contradictory to the intention of establishing a prototype cultivation (the presence of less than 0.25% of yeast extract distinguishes a batch significantly from the others; Locher et al., 1992). Further, the concentrations given in the following are approximate levels which were observed in cultures with 3% initial glucose concentration. The rough sequence of phases is usually not disturbed because of a very strict order of consecutive excretion and uptake steps where each one necessitates the next with a very high probability. Consequently, the cells do not deviate from the typical process development even under badly reproduced cultivation conditions; however, the absolute, quantitative data can vary significantly. Deviations in the overall time for a complete batch in our bioequipment with the repetitive batch mode of operation make up less than 1%. Even though the actual results reveal differences in the range of 2-3%, the main source of errors has been identified as a not yet sufficiently precisely reproduced amount of inoculum during repetitive batch mode of operation. However, we are convinced that the reproducibility of most of the typical analytical methods applied in biotechnology is less than that of the biological reactions. The quality of the off-line analyses was very much dependent on the interaction with other chemical compounds in the medium. Due to the broad spectrum of excreted and utilized intermediates, analyses can be disturbed seriously by the unknown matrix of substances.
Definition of characteristic process phases A batch culture of S. cerevisiae on defined glucose medium was distinguished into seven phases (Fig. 4). This classification does not account for an initial "lag phase" after inoculation because we assume an insufficient sensitivity of the measurin~g equipment rather than a biological reason behind that time phase without significant changes.
Phase 1. The first phase is the exponential growth on glucose with no significant limitations (compare phase 2). According to a glucose consumption overloading the respiratory bottleneck (Sonnleitner and K~ippeli, 1986), the cells make use of several metabolic pathways in order to get rid of the reduction equivalents. This gives rise to the excretion of secondary metabolites; the best known way is the reduction of acetaldehyde to ethanol. If the availability of acetaldehyde is restricted either by the use of inhibitors, such as bisulphite, or by the diversion of intermediates into other biosynthetic pathways, it is not available as a substrate for re-oxidation of NADH generated during glycolysis. Under these conditions, NADH is oxidized by the reduction of dihydroxyacetone phosphate to glycerol phosphate, which is then converted to glycerol and excreted. During batches under the condition described in this article, the production of glycerol led to an approximate
64
et no,
®
0 glucose
time - - - ~
® acetic acid
ac,0,
ethanol
Fig. 4. Data of CO 2 exhaust gas analysis. At least seven regulatory phases can be distinguished in the course of a prototype batch of S. cereuisiae. The "glucose phase" is split into two phases with the second one only determinable under sufficiently well mixed conditions. Phases 3 and 4 are characterized by the consumption of organic acids (pyruvic acid, acetic acid and propionic acid), whereas the metabolic background for the 5th phase is still unknown. During phase 6, mainly ethanol is metabolized and again acetic acid accumulated in the medium (as a waste product of the ethanol utilization). This is reutilized during phase 7, indicated by a sharp peak in the CO 2 evolution immediately following the depletion of ethanol from the medium. level o f 0.6 g 1-1 at t h e e n d of t h e s e c o n d p h a s e (see below, Fig. 7). O r g a n i c acids (e.g pyruvic acid, acetic acid a n d p r o p i o n i c acid) a r e also a result o f this b i a s e d r e l a t i o n s h i p b e t w e e n glucose c o n s u m p t i o n a n d l i m i t e d r e s p i r a t o r y capacity. T h e cells a r e short in e n e r g y r a t h e r t h a n in c a r b o n sources a c c o r d i n g to the e x c r e t i o n o f such useful m e t a b o l i t e s . Phase 2. D u r i n g t h e s e c o n d p h a s e , t h e g r o w t h on glucose c h a n g e s its c h a r a c t e r i s tics. T h e C O 2 evolution, m e a s u r e d in t h e exhaust gas a n d as t h e p a r t i a l p r e s s u r e in t h e liquid is no m o r e e x p o n e n t i a l . A c c o r d i n g to o u r e x p e r i e n c e , this effect could not b e o b s e r v e d w h e n y e a s t extract was a d d e d or the r e a c t o r was s t i r r e d less vigorously. A n e x p l a n a t i o n c o u l d be a s u b s t a n c e t h a t is a d d e d with yeast extract a n d m u s t b e s u b s t i t u t e d by t h e ceils in d e f i n e d m e d i a . In a s t a n d a r d b i o r e a c t o r , t h e mass t r a n s f e r is insufficient to reveal t h e t i m e c o n s t a n t of such an i n t r a c e l l u l a r s u b s t i t u t i o n r e a c t i o n b u t with i m p r o v e d mass transfer, this r e a c t i o n b e c o m e s r a t e limiting. Phase 3. I n t h e b e g i n n i n g o f t h e t h i r d p r o c e s s p h a s e , glucose is e x h a u s t e d a n d t h e cells start utilizing pyruvic acid. T h e a p p r o x i m a t e level of a c c u m u l a t i o n is 200 mg
65
CO 2 (MS)
pyruvlc acid (GC)
atartj
~ 1
/
atop 0.0
time (h)
16.0
Fig. 5. As a consequence of overloading the respiratory bottle-neck, even pyruvic acid is excreted in the second half of the growth on glucose. According to its central position in the metabolism and its great value for the cell, it is excreted as late as possible and utilized as the first metabolite after the depletion of glucose. Samples for GC off-line analyses were taken from different batches (different symbols). Here, they ar shown as a superposition (pyruvic acid: 0-200 mg 1 1; CO2: arbitrary units). Remark: "stop " and "start" indicate a time phase during the last experiment (providing the samples for the first batch phase) with a stopped stirrer. Caused by interrupted mixing, the batch lasts significantly longer than the others. In a subsequent paper, mixing effects due to variations in stirrer speed will be analyzed in more detail (Locher et al., 1993).
1 - t (Fig. 5). A n i n d i c a t i o n for t h e u p t a k e o f an acid c o m p o u n d f r o m t h e m e d i u m d u r i n g this b a t c h p e r i o d is t h e a m o u n t of acid n e e d e d to c o n t r o l p H . T h e time d i f f e r e n c e b e t w e e n t h e c o m p l e t e e x h a u s t i o n o f glucose a n d pyruvic acid (app r o x i m a t e d as t h e p e a k time o f t h e C O 2 exhaust gas analysis) is less t h a n 1 h; i.e. c h a n g e s in t h e m e t a b o l i s m m u s t b e faster. A p u l s e d a d d i t i o n o f pyruvic acid t h r o u g h o u t p h a s e s 3 - 7 l e a d s to an i m m e d i a t e u t i l i z a t i o n t h e r e o f ( L o c h e r et al., 1991). F u r t h e r , t h e u p t a k e o f glycerol sets in.
Phase 4. T h e f o u r t h b a t c h p h a s e is c h a r a c t e r i z e d by t h e u t i l i z a t i o n o f acetic acid (approx. 300 m g 1-1, Fig. 6), glycerol (Fig. 7) a n d - to a m i n o r d e g r e e - o f p r o p i o n i c acid (approx. 30 m g l - l ) . If y e a s t extract is a d d e d to t h e m e d i u m , the s h a p e o f t h e curve for C O 2 can b e d i s t i n g u i s h e d easily f r o m c u l t u r e s grown on d e f i n e d m e d i u m . A c e t i c acid p u l s e s d u r i n g p h a s e s 3 - 7 i n c r e a s e t h e e x t r a c e l l u l a r c o n c e n t r a t i o n d u r i n g p h a s e 3 a n d p r o l o n g t h e f o u r t h phase. H o w e v e r , this m e t a b o lite is n o t u t i l i z e d b e f o r e the e x h a u s t i o n of pyruvic acid.
66
acetic acid (GC)
C02 (MS)
/
start
/
/
stop 0.0
time (h)
16.0
Fig. 6. The time trajectories of the acetic acid (0-300 mg 1-1) concentration reveals the changes of the cellular metabolism in the course of phases 3-7. In agreement with the overload of the respiratory capacity, acetic acid is excreted in the early phases of the batch and accumulates until the fourth phase where it is reconsumed again. During phases 5 and 6 acetic acid is excreted again caused by the utilization of ethanol. We assume that the scatter of data for pyruvic acid (Fig. 5) and acetic acid is mainly due to the fact that the data were obtained off-line (even though the samples were cell-free deep frozen just after sampling)
_
biomass Y
glucose
0
time [h]
16
Fig. 7. Off-line data of glucose (0-30 g 1-1), biomass (0-10 g 1-1), glycerol (0-0.6 g l - I ) and 4-methyl-2,3-pentanedione (MPD; arbitrary units). The CO 2 signal is given for orientation. MPD was measured off-line by means of a 'Total Analysis System' (Kresbach et al., 1991) revealing about 20 further volatile metabolites. They cover short chain alcohols, aldehydes, ketones, esters, and some heterocyclic compounds. MPD can be regarded as typical member of the waste products accumulating in the medium until the end of the batch.
67 Acetic acid and propionic acid must not exceed a certain concentration (in the order of 3 g I-1), otherwise growth is inhibited. This inhibition effect could not be observed for pyruvic acid in a concentration up to 4 g 1-1. Phase 5. The fifth and sixth phase are ethanol dominated but can be distinguished by a weak drop in the CO 2 signal at the end of the fifth phase. So far, no particular metabolite or other explanation can be given. Acetic acid is excreted again and accumulates until ethanol is completely exhausted. Glycerol is also re-utilized. Phase 6. The sixth phase is mainly caused by ethanol (and glycerol) consumption in combination with acetic acid excretion. This can be interpreted in the context with phases 3-7, the metabolism after the depletion of glucose. A general property seems to be that the higher the ethanol concentration in the medium, the lesser the cells capability in utilizing highly reduced carbon sources such as ethanol. This can be interpreted as a reduced respiratory capacity caused by ethanol. Consequently, the metabolism is "mainly reductive" with a significant effect on cellular energetics. Energy rather than carbon sources is limiting during these phases of growth. When ethanol disappears at the end of the batch, the respiratory capacity is improved allowing for the more effective oxidative phosphorylation. This interpretation could explain why acetic acid is consumed by the cells during the fourth phase (as a highly oxidized carbon source) and consecutively excreted again (as a waste product of the ethanol oxidation). The acetic acid production during ethanol consumption was proven by batch experiments on ethanol as the sole carbon souce (data not shown). Phase 7. The seventh phase is determined by the depletion of ethanol and glycerol and the subsequent utilization of acetic acid as the final carbon source which is left in medium. It is remarkable that the CO 2 peak in the exhaust gas evolves immediately (within s) after ethanol vanishs. Further, the peak heights are dependent on the stirrer speed, i.e. the cellular provision with 0 2 and the degassing of CO z from the liquid. Time trajectories of several sensors
In the following, the prototype batch culture is documented by different sensor signals. Some analyses were performed off-line. The results for biomass, glucose, glycerol and 4-methyl-2,3-pentanedione as a member of the group of waste products are shown in Fig. 7. Frequent flow cytometric analyses of the DNA enable to correlate the proliferation of the cells with the time evolution of the batch (Fig. 8). The synchronous exposition of all cells to new conditions during inoculation leads to a partial synchronization of the population and could be another explanation for the second phase.
68
10.2 G1 lmlto
bi~
i
13.2
o
oe -
13.2
Fig. 8. Flow cytometric data (from Mfinch et al., 1992) obtained off-line from batch cultivation. The distributions of the DNA content and the cell size are illustrated by the time course plot of histogram shapes. Further, the dry weight of biomass is given. PI is the DNA stain propidium iodide. G1, Glmito, S and G2+ M are the distinguishable subpopulations in different cell cycle phases in the sequence of increasing DNA content.
Carbon dioxide.
C O 2 w a s e i t h e r m e a s u r e d as a p a r t i a l p r e s s u r e in t h e m e d i u m or as a m o l a r fraction in t h e exhaust gas (Fig. 9). T h e l a t t e r p r o v i d e d t h e least signal noise a n d t h e most c h a r a c t e r i s t i c d e v e l o p m e n t with time. O u r analytical m e t h o d s for the p a r t i a l p r e s s u r e s rely on m e m b r a n e c o v e r e d p r o b e s p r o v i d i n g a semiq u a n t i t a t i v e signal only. F u r t h e r , it s h o u l d b e t a k e n into a c c o u n t t h a t a l i n e a r r e l a t i o n s h i p b e t w e e n p a r t i a l p r e s s u r e s a n d c o n c e n t r a t i o n s ( H e n r y ' s law) is - for physical a n d c h e m i c a l r e a s o n s ( c h a n g i n g c o n c e n t r a t i o n s , c o a l e s c e n c e p r o p e r t i e s ) a first a p p r o x i m a t i o n only. A l l p r o c e s s p h a s e s could b e i d e n t i f i e d with the m e n t i o n e d C O z sensors.
Ethanol.
T h e p a r t i a l p r e s s u r e of e t h a n o l was d e t e r m i n e d by MS. A n approx. c o n c e n t r a t i o n is given in Fig. 9. D u r i n g p h a s e s 1 a n d 2, which c a n n o t be disting u i s h e d by m e a n s o f this signal, e t h a n o l a c c u m u l a t e s up to a level o f 10 g I-1.
69
time
== 002 ( ~ . ~
Fig. 9. C O 2 in the liquid phase was measured either via a m e m b r a n e inlet MS or a commercially available sensor (Ingold: pCO2). Both determination methods measure partial pressures (not concentrations) and are d e p e n d e n t on the m e m b r a n e characteristics. D u e to the measuring principle of the Ingold sensor, the signal is in logarithmic scale. CO 2 in the exhaust gas was determined by the "classical" method based on the infrared absorption of CO 2. Ethanol was also measured with the mentioned MS; however, the shown concentration range is an approximate estimation only (assuming that Henry's law is valid). Phases as in Fig. 4.
Ethanol is both blown out with the exhaust gas as well as utilized as a substrate. So far it is not clear in which of the phases 3-5 the utilization definitely sets in.
Oxygen. 0 2 was determined in the liquid (polarographically and by MS) and in the exhaust gas (Fig. 10). The determination of the partial pressure allows to gain insight into the potential of the O 2 supply; however, a final estimation upon this is only possible, if the degree of mass transfer and mixing is considered as well (I_ocher et al., 1992). On the contrary, the O 2 in the exhaust gas of the bioreactor is lost for the culture (i.e. cannot be used by the cells). Nevertheless, the general development of the signals is comparable even if the scatter of data is highest with the MS. Process phases 2 and 7 cannot be resolved by the O 2 determination methods; phase 5 may or may not be distinguished from phase 6.
Optical density (OD). OD measurements were inconsistent over different batch series (i.e. lots of prepared media) whereas the changes within a single series were small (Fig. 10). The main differences concerned phases 3 and 4 where an increasing, a decreasing as well as a constant development with time could be observed. The discrimination of phases was low; in Fig. 10, only the 'classical' distinction between the glucose and the ethanol phase can be made. Due to the effect of ethanol on the coalescence properties of the medium, its depletion at the end of the batch results in a sudden increase of the OD signal.
70
~
time--~
@®
P02
f
u Fig. 10. The partial pressure of 02 in the liquid was measured polarographically(Ingold) and via MS. Due to the dependency of the determination method for the molar fraction of 02 in the exhaust gas (based on paramagnetism), the measuring cell must be recalibrated quite often. OD measurements were obtained on-line (Aquasant). The signal is very sensitive to coalescence changes and the bubble spectrum in the medium. Phases 1-6 correspondingto Fig. 4.
pH controller. An uptake of acidic compounds such as organic acids increases the p H in the medium and vice versa (Fig. 11). This is compensated for by the pH controller with the addition of acid. Accordingly, the consumption of (neutral) glucose under excretion of organic acids in phases 1 and 2 requires the continuous addition of alkali. Phases 3 and 4 can easily be distinguished. The signal is highly dependent on the controller parameters. If, for instance, these settings apply to a very fast performance (on the cost of stability) the vanishing of pyruvic acid is compensated by a sharp addition of acid lasting very few minutes only. Additional information about the unknown substance responsible for phase 5 cannot be gained by this signal.
Heat production.
The temperature difference between the cooling circuit and the culture is a first approximation for the heat production of the cells (Fig. 11). However, the very low energy to be resolved (few W 1-1) makes this signal very noisy. Only the end of phases 2 and 7 can be resolved reliably. Additional expenditure for noise reduction allowed to distinguish phases 3 and 4 from phase 5 (Locher et al., 1991).
Fluorescence.
During phases 1 and 2 the (NADH) fluorescence signal grows exponentially in parallel with the biomass; this is due to a maximal cellular load with reduction equivalents which allows to correlate this signal with the biomass concentration during this growth period (Fig. 11). Later in the process when, amongst other changes, the carbon sources undergo shifts from one to another, this correlation does no longer hold true.
71
FI
I
|
"..~
time "" -~
redox
Fig. 11. The temperature difference between cooling circuit and the cultivation medium (AT) is a first approximation of the heat produced by the cells. Due to the low energy to be resolved, this signal is very noisy in this equipment. The pH controller output signal reveals the amount of acid or alkali pumped into the reactor for maintaining the pH setpoint. A step down codes for acid which is pumped into the reactor, e.g. the compensation of an organic acid metabolized by the cells. Fluorescence measurements are dependent on both, the cell concentration in the medium as well as their metabolic state. Since the signal is correlated with the NADH concentration, it is one of the very few intracellular measurements which are available today. The redox potential as measured in a biotechnological medium is rather related to an "overall availability of electrons", than to a specific redox couple. However, during these batch cultivations, this signal was the only one except the CO2 measurements, which allowed to distinguish the first and the second process phase (a distinction, which has not been made so far). Phases 1 a n d 2 c a n n o t be distinguished by this signal. T h e e n d of the the d e p l e t i o n of all extracellular c a r b o n sources causes a sharp drop of T h e energetics of the cells are reflected in the phase p l a n e plot of reveals the cellular load with r e d u c t i o n equivalents a n d the efforts to t h e m by the excretion of ethanol.
batch, i.e. the signal. Fig. 12. It get rid of
Redox.
T h e redox signal was the only o n e with the exception of the C O 2 signals which is capable to identify p h a s e 2 (Fig. 11). If the fluorescence signal reflects the i n t r a c e l l u l a r redox state, the redox signal applies to the extracellular "overall availability of e l e c t r o n s " (Kjaergaard, 1977). This leads to a n " a n t i p a r a l l e l " signal d e v e l o p m e n t but, w h e r e a s the fluorescence sensor is i n c a p a b l e of resolving the second growth phase, the redox sensor can.
Conclusions Batch cultivations with S. cerevisiae can be subdivided into seven different phases o n the basis of m e t a b o l i t e p r o d u c t i o n a n d c o n s u m p t i o n . T h e o r d e r of these
72
0
A
e-
~no
q o. .
.
.
.
.
.
.
.
.
.
L
Fig. 12. A superposition of seven batch cultivations is a "phase plane plot" of fluorescence and ethanol (MS) reveals the course of the NADH household during batch experiments. In a first approximation, the signal is dependent on the concentration of the cells and on their load with reduction equivalents. During growth on glucose, the respiration is the bottle-neck for the preferred oxidative utilization; consequently, the NADH concentration remains constant on a high value. So does the (uncontrolled) glucose consumption of the cells because of the high extra-cellular concentration and poses a high need to neutralize reduction equivalents. This is primarily performed by the reduction of acetaldehyde to ethanol, which leads to the "linear" increase in the fluorescence - ethanol phase plane plot. In the course of the organic acid consumption, ethanol is blown out with the exhaust gas and insignificantly metabolized by the cells. In combination with the growing biomass concentration this leads to a slight increase of the fluorescence signal. During growth on ethanol the increasing biomass in parallel with the decreasing ethanol concentration leads to a relatively constant fluorescence signal. This can be due to the attenuation of reduction equivalents produced in the course of vanishing ethanol. During the final peak the fluorescence signal drops (cannot be shown adequately in this plot because the very few data points are hidden behind those which are measured during the refill procedure of the reactor).
phases is highly d e p e n d e n t on the respiratory b o t t l e - n e c k of the cells, which is c o n f i r m e d to be c e n t r a l to metabolism. A c c o r d i n g to this i n t e r p r e t a t i o n , the excretion of glycerol, pyruvic acid, acetic acid a n d p r o p i o n i c acid d u r i n g the glucose g o v e r n e d phases (1, 2) of a batch cultivation is a n overflow reaction which allows the cells to n e u t r a l i z e their r e d u c t i o n equivalents. W h e n the m e d i u m is d e p l e t e d of glucose, the cellular m e t a b o l i s m u n d e r g o e s the changes of a r e c u p e r a t ing oxidation capability for m e t a b o l i t e s due to the decreasing e t h a n o l c o n c e n t r a tion. This is likely to be a n i m p o r t a n t r e a s o n for p h e n o m e n a such as the c o n s u m p tion of acetic acid d u r i n g phase 4, the excretion d u r i n g phases 5 a n d 6 a n d utilization again d u r i n g phase 7. T h e following questions r e m a i n to be answered. - T h e biological m e c h a n i s m responsible for the second a n d the fifth phase. - T h e role of e t h a n o l in metabolism. F r o m the e x p e r i m e n t s it c a n n o t be determ i n e d w h e n exactly the e t h a n o l utilization sets in d u r i n g phases 3 - 5 . - T h e e t h a n o l i n h i b i t i o n of metabolism. A c c o r d i n g to the very fast r e s p o n s e ( i m m e d i a t e acetic acid c o n s u m p t i o n ) on the d e p l e t i o n of e t h a n o l in the seventh phase, the effect must be strong. - T h e role of glycerol ( a n d acetaldehyde) in relation to the e t h a n o l metabolism.
73 - T h e d e l a y e d pyruvic acid u t i l i z a t i o n ( p h a s e 3) which m a y b e c a u s e d by the generation of enzymes capable of the transport through the membrane. A c c o r d i n g to t h e s o p h i s t i c a t i o n a n d the versatility o f the m e t a b o l i s m of S. cerevisiae in c o m b i n a t i o n with its p r o v e n r e p r o d u c i b i l i t y o f e x p e r i m e n t s a n d t h e a c c u m u l a t e d k n o w l e d g e , this o r g a n i s m is p e r f e c t l y eligible as a test a n d r e f e r e n c e o r g a n i s m in b i o t e c h n o l o g y . F u r t h e r d o c u m e n t a t i o n of " p u r e " biological r e s p o n s e s - also u n d e r d i f f e r e n t cultivation c o n d i t i o n s - a r e highly d e s i r a b l e a n d w o u l d c o n t r i b u t e to both: an i n c r e a s e d k n o w l e d g e a b o u t f u n d a m e n t a l m e t a b o l i c principles a n d a basis for a s o u n d d i s c r i m i n a t i o n what, in a given b i o p r o c e s s , has b e e n c a u s e d by biological a n d w h a t by n o n - b i o l o g i c a l effect. T h e above d o c u m e n t e d analyses a p p l y to e x t r a c e l l u l a r c o n c e n t r a t i o n s exclusively (with t h e e x c e p t i o n of the f l u o r e s c e n c e signal). I n t r a c e l l u l a r i n t e r m e d i a t e s involve difficult a n d t i m e - c o n s u m i n g e x t r a c t i o n p r o c e d u r e s , a n d a r e the next s t e p t o w a r d s an entirely d o c u m e n t e d p r o t o t y p e batch. In this context, the time constants of the b i o r e a c t i o n s m u s t b e r e c o n s i d e r e d w h e n designing a s u i t e d s a m p l i n g system. C h a n g e s in t h e m e t a b o l i s m can be in the o r d e r of s a n d r e q u i r e for cell inactivation m e t h o d s in at least the s a m e time m a g n i t u d e .
Acknowledgements T h e a u t h o r s t h a n k C. G u b y for his c o n t r i b u t i o n d u r i n g analytical work.
References Adler, I. (1988) Entwicklung und Einsatz biologischer Testsysteme zur Beurteilung von Bioreaktoren. Habilitation thesis, Swiss Federal Institute of Technology, Switzerland. Berry, D.R., Russell, I. and Stewart, G.G. (1987) Yeast Biotechnology. Unwin Hyman, London. Fiechter, A., Fuhrmann, G. and K~ippeli, O. (1981) Regulation of glucose metabolism in growing yeast cells. Adv. Microb. Physiol. 2, 123-183. Fiechter, A. and Seghezzi, W. (1992) Regulation of glucose metabolism in growing yeast cells. J. Biotechnol. 27, 27-45. Hug, H., Blanch, H.W. and Fiechter, A. (1974) The functional role of lipids in hydrocarbon assimilation. Biotechnol. Bioeng. 16, 965-985. Kjaergaard, L. (1977) The redox potential: its use and control in biotechnology. Adv. Biochem. Eng. 7, 131-150. Kresbach, G.M., Ehrat, M. and Widmer, H.M. (1991) Bioprocess monitoring and biopattern recognition using a total analysis system. Herbstversammlung Schweizerische Chemische Gesellschaft, Schweizerischer Chemiker-Verband, Univ. Bern. Locher, G., Sonnleitner, B. and Fiechter, A. (1991) Automatic bioprocess control. 3. Impacts on process perception. J. Biotechnol. 19, 173-192. Locher, G., Sonnleitner, B. and Fiechter, A. (1992) On-line measurements in biotechnology: Exploitation, objectives and benefits. J. Biotechnol. 25, 55-73. Locher, G., Sonnleitner, B. and Fiechter, A. (1993) Automatic bioprocess control. 5. Biologically and technically caused effects during cultivation. J. Biotechnol. 29, 75-89. Miinch, T., Sonnleitner, B. and Fiechter, A. (1992) The decisive role of the Saccharomyces cerevisiae cell cycle behaviour for dynamic growth characterization. J. Biotechnol. 22, 329-351.
74 Rose, A.H. and Harrison, J.S. (1989) The Yeasts. Metabolism and physiology of yeast. Academic Press, New York. Sonnleitner, B. and Kiippeli, O. (1986) Growth of Saccharomyces cerevisiae is controlled by its limited respiratory capacity: formulation and verification of a hypothesis. Biotechnol. Bioeng. 28, 927-937. Striissle, C., Sonnleitner, B. and Fiechter, A. (1989) A predictive model for the spontaneous synchronization of Saccharomyces cerevisiae grown in continuous culture. II. Experimental verification. J. Biotechnol. 9, 191-208.
57
© 1993 Elsevier Science Publishers B.V. All rights reserved 0168-1656/93/$06.00
JBT00861
Automatic bioprocess control. 4. A prototype batch of Saccharomyces cerevisiae Georg Locher 1, Ulrike H a h n e m a n n , B e r n h a r d Sonnleitner and Armin Fiechter Institute of Biotechnology, ETH Hiinggerberg, Ziirich, Switzerland. (Received 18 March 1992; revision accepted 15 July 1992)
Summary The recent investigations in our high performance bioreactors have shown that living cells can be extremely sensitive to physical-chemical environmental conditions and their changes. Consequently, the relationship bioreactor-living cell must thoroughly be investigated in order to discuss both: whether bioreactor characteristics are limiting/dominating during cultivation and to what extent controlled changes of the cellular environment can lead the cells to a desired physiological state. For these investigations, a generally accepted biological test organism would be helpful, of which the requirements and reactions under certain conditions are well known. Saccharomyces cerevisiae is a well known, very robust but nevertheless sensitive organism, eligible for this purpose. In this article a typical batch cultivation on glucose is presented, collected from approx. 300 experiments. Regarding metabolite production and consumption, seven different phases are distinguished on the basis of approx. 20 sensor signals and their metabolic background is discussed. Prerequisite, however, was an exhaustive knowledge upon extracellular conditions, a task which could successfully be fulfilled with the highly automated equipment introduced in the preceding articles of this series.
Correspondence to: B. Sonnleitner, Institute of Biotechnology, ETH H6nggerberg, CH 8093 Ziirich, Switzerland. 1 Present address: MIT Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
58 Sensors; Automation; Bioprocess control; Saccharomyces cerevisiae prototype batch; Non-invasive measurement; Reference organism; Measurement; Respiratory regulation; Automated C-balance
Introduction
Saccharomyces cerevisiae-type yeasts are of considerable economic importance and, furthermore, well suited test organisms for metabolic studies. Many media and cultivation conditions have been described testifying an extraordinary flexibility to extra-cellular conditions. The exploitation of the yeasts capabilities by humans over several thousand years led to a multitude of products with alcohol and biomass still being economically the most important ones. However, not only the classical, low tech bioprocesses can be performed with yeasts. According to the mechanical robustness, chemical and genetical properties, easy handling and cultivation as well as usually non-pathogenity yeasts are often used as test organisms in research and development. The heterologous production of many proteins as well as stereoselective bioconversions are possible and yeasts became an important expression system in the recombinant technology. Such a huge potential of cellular capabilities can easily lead to misinterpretations of experimental results, i.e. a mixing up of biological phenomena with properties of the technical equipment when interpreting bioprocess data. Technically unbiased, i.e. sound biological data of a reference organism allow to make that distinction and improve both, basic biological research as well as bioprocess development (Adler, 1988). In this article, we recommend S. cerevisiae as such a reference because it is a very well known organism with a sophisticated metabolism and a broad spectrum of applicabilities. Some of the advantages resulting from this "biological test system" are briefly outlined in the following. A multitude of cellular capabilities is widespread over many species due to the conservative character of nature. This allows to study certain phenomena in one particular species and transfer the results to others. However, presumptious is the mechanistical understanding instead of a description of a multitude of distinct "effects". An example for this is the uptake and metabolism of a wide range of sugars such as maltose, galactose and melibiose which is regulated by glucose. This was discussed in the context of catabolite repression and, unfortunately, extended to the repression of the glucose utilization because of the detection of "free glucose" contemporary to a decreased growth rate during batch cultures. We now understand that mainly the magnitude of the glucose flux through the respiratory bottle-neck is responsible for the so called "Crabtee-" or "Glucose-" effect. Restricting the considerations to "static" concentrations does not account for the dynamics of fluxes, which are very often by far of greater importance. Many observations can be explained in view of respiration which is assumed to be a bottle-neck in the cellular metabolism. The distinction between "glucose-sensitive" and "glucose-insensitive" yeast strains was coined in the context of the
59 "Crabtree" effect (Fiechter et al., 1981). It can now be interpreted as the cells' ability of regulating the glucose consumption. Glucose-sensitive yeasts such as S. cereuisiae are not able to control the consumption according to their respiratory capability and - as a consequence - may overload it. This leads to the formation of intermediates such as ethanol which is utilized in further growth phases as a carbon a n d / o r energy source. Other glucose-sensitive yeasts lost the capability of utilizing ethanol as the carbon source and exclusively produce energy thereof. Glucose-insensitive yeasts control the glucose uptake rate according to the maximum respiratory capacity. Consequently, no overload of respiration occurs and ethanol is not formed. Undoubtedly, the details of cellular control are very complex network which should not be oversimplified. But, the above mentioned interpretation of metabolism is a comprehensive approach and refers to some general, underlying principles which can be studied in S. cereuisae. It is an instructive example for an overflow reaction and can facilitate the understanding of similar reactions in other cells, e.g. lactic acid in animal cells or acetic acid in E. coli (Fiechter and Seghezzi, 1992). Another example for the benefits of S. cereuisiae as a test system is the proliferation mechanism which can be studied in partially synchronized (along the cell cycle) populations during continuous cultures. In addition to the benefits for basic biological research (MiJnch et al., 1992) this effect is also a "measure" for the quality of the control equipment: unless sufficiently precise control tools for the microenvironmental conditions in a bioreactor are available, oscillations will or will not occur or may dampen out with time (Str~issle et al., 1989). Another point that comes along with qualifying the equipment by its ability of setting up a suited environment for sophisticated processes is the time constant of reactions. Bioreactions are very often considered to be slow, and particularly yeasts are even slower than many other living cells. However, they can (re)act in the time range of s. Ethanol excretion in a continuous culture, for example, starts immediately after a significant step up in the dilution rate and must not be explained by mechanisms on the level of transcription but certainly by inhibition or limitation/overflow phenomena of particular metabolic pathways. Of course, the equipment must be capable of this time resolution and should, further, neither disturb the bioprocess nor destroy the ceils. In industrial applications, the biological potential is generally not exploited exhaustively because of technical insufficiencies or limitations. The question whether and how to optimize the process can reasonably be answered only if the biological potential is known and strictly distinguished from technical bias. Test systems allow to evaluate specific bioreactor related properties from the differences between the results obtained with the respective equipment and a reference experiment. Potentials and limitations of bioreactors can be compared in order to find the one best suited for a given task. In this article, we quantitatively describe batch experiments with S. cereuisiae which - in our estimation - reflect exclusively the biological potential of the cells rather than a superposition with technical limitations. The intention is to promote the establishment of this organism as a test and reference system in biotechnology.
6o The trajectories of on-line and off-line measurements over typical batches are shown. Further, a synopsis of the metabolism is given.
Materials and Methods
Organism. The experiments were carried out with Saccharomyces cerevisiae strain H 1022 (ATCC 32167). Media. The inoculum for the first cultivation was provided either as a (containing 3% glucose) as described contained varying amounts of glucose,
batches in the repetitive batch mode of complex medium or as a defined medium by Hug et al. (1974). The complex medium 10 g 1-1 yeast extract and 20 g I- 1 peptone.
Cultivation conditions. The following cultivation conditions were controlled in the compact loop bioreactor (in house construction, 5 - 6 1 working volume): temperature 30 + 0.02°C, pH 5 ___0.03 ( N a O H / H 3 P O 4 ) , gas flow rate 1 _+ 0.03 vvm, pressure 1.1 + 0.01 bar. Analyses. Sterile sampling was provided by an automatic sampling valve (in house construction, see Fig. 1). Biomass was determined gravimetrically after membrane filtration (0.2/zm, Zetapor). Glucose was measured enzymatically (Yellow Springs, USA). The exhaust gas was analyzed with a paramagnetic O 2 (Helox 3, Helantec, Switzerland) and an infrared CO 2 analyzer (Binos 1, Leybold Heraeus, FRG). Partial pressures of ethanol, CO 2 and O 2 were approximated by a mass spectrometer (Leybold Heraeus, F R G ) with a membrane inlet. In addition, pO 2 was measured amperometrically (Ingold, Switzerland) and pCO 2 potentiometrically (Ingold, Switzerland). Cell-free supernatant was provided by a membrane filter (in house construction: residence time in loop approx. 5 s, Rayflow X100, Tech-Sep, France). Organic acids were measured with a gas chromatograph (Hewlett Packard 5830 A; 80/120 Carbopack B - D A / 4 % Carbowax 20M, Supelco). Pyruvic acid and glycerol were also determined enzymatically (Boehringer Mannheim, FRG).
Results and Discussion
General remarks It is widely accepted to break a batch of S. cervisiae with glucose as the sole carbon and energy source into two phases. During the "glucose phase" glucose is converted into biomass and ethanol and during the second phase, ethanol is reconsumed again (Rose and Harrison, 1989; Berry et al., 1987). The growth on ethanol reveals a higher yield than the growth on glucose. From the numerous investigations on S. cerevisiae it is obvious that there are more intermediates formed and excreted which are responsible for a typical batch
61
Isterilization:,
air
.~ ~ ' ~ " ~
N II
s~m~le waste
air ~
steam L/~Jfilter
_
P0~!n.~J~!.° aJr
N
II
sample waste
Fig. 1. Schematic drawing of a sterilizable sampling valve. It can be mounted to the normed 25 mm connector port, is actuated pneumatically and in situ sterilizable. After sampling, the central bolt is held in a backward position for sterilization. Steam flushes a ceramic filter and all the surfaces which had been in contact with culture liquid. Afterwards, air is used for drying. During sampling, the bolt is pushed pneumatically into the forward position. Caused by a slight overpressure inside the bioreactor, the culture liquid is injected into respective receptacle. The sequence of actions is computer-controlled and allows a sampling frequency which is exclusively dependent on the time for sterilization and drying (1 min). No culture liquid needs to be drained.
under such conditions. A contiuous carbon balance over biomass, ethanol, CO 2 and glucose indicates that during exponential growth on glucose an increasing a m o u n t o f c a r b o n b y p a s s e s this t h e o r e t i c a l e v a l u a t i o n . U n k n o w n i n t e r m e d i a t e s t h a t a r e n o t i n c o r p o r a t e d in t h e set o f b a l a n c e e q u a t i o n s u s e d s u m u p to a p p r o x . 1 0 - 1 5 % e r r o r at t h e e n d o f t h e g r o w t h o n g l u c o s e . L a t e r d u r i n g c u l t i v a t i o n , t h e y
62
"6 E
~
ethanol
0
C02
~ time (h)
J
15.5
Fig. 2. Continuous carbon balance o f a prototype S. cerevisiae batch cultivation (from Locher er al.,
1992) over the bioreactor content. Analyses of glucose (Yellow Springs analyzer), ethanol (MS) and dry weight of biomass in the medium, as well as integrated losses by CO 2 (infrared gas analyzer) and ethanol (GC) through the exhaust gas are making up the C-balance. Biomass composition was assumed to be constant with a molar carbon fraction of 49%.
a r e r e c o n s u m e d a n d c o n v e r t e d i n t o b i o m a s s w h i c h is c o n s i d e r e d in t h e c a l c u l a t i o n - t h e c a r b o n b a l a n c e b e c o m e s v a l i d a g a i n ( F i g . 2). T h e b a s i s for t h e f o l l o w i n g p r o t o t y p e b a t c h o f S. cerevisiae a r e a p p r o x . 300 c u l t i v a t i o n s w h i c h w e r e c a r r i e d o u t u n d e r d i f f e r e n t c o n d i t i o n s (Fig. 3). T h e inoculum was provided from either defined or complex medium and the batches
time
,
Fig. 3. A widely accepted distinction is the separation of the "glucose" phase from the "ethanol" phase during batches of S. cerevisiae - type yeast. During the former glucose is metabolized into biomass, ethanol and CO 2 whereas during the latter, ethanol is reconsumed again. This behaviour was analyzed in approx. 300 repetitive batches under different conditions in order to gain a more detailed insight into the metabolism of yeast. In the figure are shown approx. 1% of the CO 2 exhaust gas analysis data obtained from 100 automated batches.
63 themselves were performed in defined medium. Due to the high sensitivity of S. cerevisiae to extracellular changes, a defined medium must be taken, otherwise the scatter of experimental results caused by changes of the complex medium components is contradictory to the intention of establishing a prototype cultivation (the presence of less than 0.25% of yeast extract distinguishes a batch significantly from the others; Locher et al., 1992). Further, the concentrations given in the following are approximate levels which were observed in cultures with 3% initial glucose concentration. The rough sequence of phases is usually not disturbed because of a very strict order of consecutive excretion and uptake steps where each one necessitates the next with a very high probability. Consequently, the cells do not deviate from the typical process development even under badly reproduced cultivation conditions; however, the absolute, quantitative data can vary significantly. Deviations in the overall time for a complete batch in our bioequipment with the repetitive batch mode of operation make up less than 1%. Even though the actual results reveal differences in the range of 2-3%, the main source of errors has been identified as a not yet sufficiently precisely reproduced amount of inoculum during repetitive batch mode of operation. However, we are convinced that the reproducibility of most of the typical analytical methods applied in biotechnology is less than that of the biological reactions. The quality of the off-line analyses was very much dependent on the interaction with other chemical compounds in the medium. Due to the broad spectrum of excreted and utilized intermediates, analyses can be disturbed seriously by the unknown matrix of substances.
Definition of characteristic process phases A batch culture of S. cerevisiae on defined glucose medium was distinguished into seven phases (Fig. 4). This classification does not account for an initial "lag phase" after inoculation because we assume an insufficient sensitivity of the measurin~g equipment rather than a biological reason behind that time phase without significant changes.
Phase 1. The first phase is the exponential growth on glucose with no significant limitations (compare phase 2). According to a glucose consumption overloading the respiratory bottleneck (Sonnleitner and K~ippeli, 1986), the cells make use of several metabolic pathways in order to get rid of the reduction equivalents. This gives rise to the excretion of secondary metabolites; the best known way is the reduction of acetaldehyde to ethanol. If the availability of acetaldehyde is restricted either by the use of inhibitors, such as bisulphite, or by the diversion of intermediates into other biosynthetic pathways, it is not available as a substrate for re-oxidation of NADH generated during glycolysis. Under these conditions, NADH is oxidized by the reduction of dihydroxyacetone phosphate to glycerol phosphate, which is then converted to glycerol and excreted. During batches under the condition described in this article, the production of glycerol led to an approximate
64
et no,
®
0 glucose
time - - - ~
® acetic acid
ac,0,
ethanol
Fig. 4. Data of CO 2 exhaust gas analysis. At least seven regulatory phases can be distinguished in the course of a prototype batch of S. cereuisiae. The "glucose phase" is split into two phases with the second one only determinable under sufficiently well mixed conditions. Phases 3 and 4 are characterized by the consumption of organic acids (pyruvic acid, acetic acid and propionic acid), whereas the metabolic background for the 5th phase is still unknown. During phase 6, mainly ethanol is metabolized and again acetic acid accumulated in the medium (as a waste product of the ethanol utilization). This is reutilized during phase 7, indicated by a sharp peak in the CO 2 evolution immediately following the depletion of ethanol from the medium. level o f 0.6 g 1-1 at t h e e n d of t h e s e c o n d p h a s e (see below, Fig. 7). O r g a n i c acids (e.g pyruvic acid, acetic acid a n d p r o p i o n i c acid) a r e also a result o f this b i a s e d r e l a t i o n s h i p b e t w e e n glucose c o n s u m p t i o n a n d l i m i t e d r e s p i r a t o r y capacity. T h e cells a r e short in e n e r g y r a t h e r t h a n in c a r b o n sources a c c o r d i n g to the e x c r e t i o n o f such useful m e t a b o l i t e s . Phase 2. D u r i n g t h e s e c o n d p h a s e , t h e g r o w t h on glucose c h a n g e s its c h a r a c t e r i s tics. T h e C O 2 evolution, m e a s u r e d in t h e exhaust gas a n d as t h e p a r t i a l p r e s s u r e in t h e liquid is no m o r e e x p o n e n t i a l . A c c o r d i n g to o u r e x p e r i e n c e , this effect could not b e o b s e r v e d w h e n y e a s t extract was a d d e d or the r e a c t o r was s t i r r e d less vigorously. A n e x p l a n a t i o n c o u l d be a s u b s t a n c e t h a t is a d d e d with yeast extract a n d m u s t b e s u b s t i t u t e d by t h e ceils in d e f i n e d m e d i a . In a s t a n d a r d b i o r e a c t o r , t h e mass t r a n s f e r is insufficient to reveal t h e t i m e c o n s t a n t of such an i n t r a c e l l u l a r s u b s t i t u t i o n r e a c t i o n b u t with i m p r o v e d mass transfer, this r e a c t i o n b e c o m e s r a t e limiting. Phase 3. I n t h e b e g i n n i n g o f t h e t h i r d p r o c e s s p h a s e , glucose is e x h a u s t e d a n d t h e cells start utilizing pyruvic acid. T h e a p p r o x i m a t e level of a c c u m u l a t i o n is 200 mg
65
CO 2 (MS)
pyruvlc acid (GC)
atartj
~ 1
/
atop 0.0
time (h)
16.0
Fig. 5. As a consequence of overloading the respiratory bottle-neck, even pyruvic acid is excreted in the second half of the growth on glucose. According to its central position in the metabolism and its great value for the cell, it is excreted as late as possible and utilized as the first metabolite after the depletion of glucose. Samples for GC off-line analyses were taken from different batches (different symbols). Here, they ar shown as a superposition (pyruvic acid: 0-200 mg 1 1; CO2: arbitrary units). Remark: "stop " and "start" indicate a time phase during the last experiment (providing the samples for the first batch phase) with a stopped stirrer. Caused by interrupted mixing, the batch lasts significantly longer than the others. In a subsequent paper, mixing effects due to variations in stirrer speed will be analyzed in more detail (Locher et al., 1993).
1 - t (Fig. 5). A n i n d i c a t i o n for t h e u p t a k e o f an acid c o m p o u n d f r o m t h e m e d i u m d u r i n g this b a t c h p e r i o d is t h e a m o u n t of acid n e e d e d to c o n t r o l p H . T h e time d i f f e r e n c e b e t w e e n t h e c o m p l e t e e x h a u s t i o n o f glucose a n d pyruvic acid (app r o x i m a t e d as t h e p e a k time o f t h e C O 2 exhaust gas analysis) is less t h a n 1 h; i.e. c h a n g e s in t h e m e t a b o l i s m m u s t b e faster. A p u l s e d a d d i t i o n o f pyruvic acid t h r o u g h o u t p h a s e s 3 - 7 l e a d s to an i m m e d i a t e u t i l i z a t i o n t h e r e o f ( L o c h e r et al., 1991). F u r t h e r , t h e u p t a k e o f glycerol sets in.
Phase 4. T h e f o u r t h b a t c h p h a s e is c h a r a c t e r i z e d by t h e u t i l i z a t i o n o f acetic acid (approx. 300 m g 1-1, Fig. 6), glycerol (Fig. 7) a n d - to a m i n o r d e g r e e - o f p r o p i o n i c acid (approx. 30 m g l - l ) . If y e a s t extract is a d d e d to t h e m e d i u m , the s h a p e o f t h e curve for C O 2 can b e d i s t i n g u i s h e d easily f r o m c u l t u r e s grown on d e f i n e d m e d i u m . A c e t i c acid p u l s e s d u r i n g p h a s e s 3 - 7 i n c r e a s e t h e e x t r a c e l l u l a r c o n c e n t r a t i o n d u r i n g p h a s e 3 a n d p r o l o n g t h e f o u r t h phase. H o w e v e r , this m e t a b o lite is n o t u t i l i z e d b e f o r e the e x h a u s t i o n of pyruvic acid.
66
acetic acid (GC)
C02 (MS)
/
start
/
/
stop 0.0
time (h)
16.0
Fig. 6. The time trajectories of the acetic acid (0-300 mg 1-1) concentration reveals the changes of the cellular metabolism in the course of phases 3-7. In agreement with the overload of the respiratory capacity, acetic acid is excreted in the early phases of the batch and accumulates until the fourth phase where it is reconsumed again. During phases 5 and 6 acetic acid is excreted again caused by the utilization of ethanol. We assume that the scatter of data for pyruvic acid (Fig. 5) and acetic acid is mainly due to the fact that the data were obtained off-line (even though the samples were cell-free deep frozen just after sampling)
_
biomass Y
glucose
0
time [h]
16
Fig. 7. Off-line data of glucose (0-30 g 1-1), biomass (0-10 g 1-1), glycerol (0-0.6 g l - I ) and 4-methyl-2,3-pentanedione (MPD; arbitrary units). The CO 2 signal is given for orientation. MPD was measured off-line by means of a 'Total Analysis System' (Kresbach et al., 1991) revealing about 20 further volatile metabolites. They cover short chain alcohols, aldehydes, ketones, esters, and some heterocyclic compounds. MPD can be regarded as typical member of the waste products accumulating in the medium until the end of the batch.
67 Acetic acid and propionic acid must not exceed a certain concentration (in the order of 3 g I-1), otherwise growth is inhibited. This inhibition effect could not be observed for pyruvic acid in a concentration up to 4 g 1-1. Phase 5. The fifth and sixth phase are ethanol dominated but can be distinguished by a weak drop in the CO 2 signal at the end of the fifth phase. So far, no particular metabolite or other explanation can be given. Acetic acid is excreted again and accumulates until ethanol is completely exhausted. Glycerol is also re-utilized. Phase 6. The sixth phase is mainly caused by ethanol (and glycerol) consumption in combination with acetic acid excretion. This can be interpreted in the context with phases 3-7, the metabolism after the depletion of glucose. A general property seems to be that the higher the ethanol concentration in the medium, the lesser the cells capability in utilizing highly reduced carbon sources such as ethanol. This can be interpreted as a reduced respiratory capacity caused by ethanol. Consequently, the metabolism is "mainly reductive" with a significant effect on cellular energetics. Energy rather than carbon sources is limiting during these phases of growth. When ethanol disappears at the end of the batch, the respiratory capacity is improved allowing for the more effective oxidative phosphorylation. This interpretation could explain why acetic acid is consumed by the cells during the fourth phase (as a highly oxidized carbon source) and consecutively excreted again (as a waste product of the ethanol oxidation). The acetic acid production during ethanol consumption was proven by batch experiments on ethanol as the sole carbon souce (data not shown). Phase 7. The seventh phase is determined by the depletion of ethanol and glycerol and the subsequent utilization of acetic acid as the final carbon source which is left in medium. It is remarkable that the CO 2 peak in the exhaust gas evolves immediately (within s) after ethanol vanishs. Further, the peak heights are dependent on the stirrer speed, i.e. the cellular provision with 0 2 and the degassing of CO z from the liquid. Time trajectories of several sensors
In the following, the prototype batch culture is documented by different sensor signals. Some analyses were performed off-line. The results for biomass, glucose, glycerol and 4-methyl-2,3-pentanedione as a member of the group of waste products are shown in Fig. 7. Frequent flow cytometric analyses of the DNA enable to correlate the proliferation of the cells with the time evolution of the batch (Fig. 8). The synchronous exposition of all cells to new conditions during inoculation leads to a partial synchronization of the population and could be another explanation for the second phase.
68
10.2 G1 lmlto
bi~
i
13.2
o
oe -
13.2
Fig. 8. Flow cytometric data (from Mfinch et al., 1992) obtained off-line from batch cultivation. The distributions of the DNA content and the cell size are illustrated by the time course plot of histogram shapes. Further, the dry weight of biomass is given. PI is the DNA stain propidium iodide. G1, Glmito, S and G2+ M are the distinguishable subpopulations in different cell cycle phases in the sequence of increasing DNA content.
Carbon dioxide.
C O 2 w a s e i t h e r m e a s u r e d as a p a r t i a l p r e s s u r e in t h e m e d i u m or as a m o l a r fraction in t h e exhaust gas (Fig. 9). T h e l a t t e r p r o v i d e d t h e least signal noise a n d t h e most c h a r a c t e r i s t i c d e v e l o p m e n t with time. O u r analytical m e t h o d s for the p a r t i a l p r e s s u r e s rely on m e m b r a n e c o v e r e d p r o b e s p r o v i d i n g a semiq u a n t i t a t i v e signal only. F u r t h e r , it s h o u l d b e t a k e n into a c c o u n t t h a t a l i n e a r r e l a t i o n s h i p b e t w e e n p a r t i a l p r e s s u r e s a n d c o n c e n t r a t i o n s ( H e n r y ' s law) is - for physical a n d c h e m i c a l r e a s o n s ( c h a n g i n g c o n c e n t r a t i o n s , c o a l e s c e n c e p r o p e r t i e s ) a first a p p r o x i m a t i o n only. A l l p r o c e s s p h a s e s could b e i d e n t i f i e d with the m e n t i o n e d C O z sensors.
Ethanol.
T h e p a r t i a l p r e s s u r e of e t h a n o l was d e t e r m i n e d by MS. A n approx. c o n c e n t r a t i o n is given in Fig. 9. D u r i n g p h a s e s 1 a n d 2, which c a n n o t be disting u i s h e d by m e a n s o f this signal, e t h a n o l a c c u m u l a t e s up to a level o f 10 g I-1.
69
time
== 002 ( ~ . ~
Fig. 9. C O 2 in the liquid phase was measured either via a m e m b r a n e inlet MS or a commercially available sensor (Ingold: pCO2). Both determination methods measure partial pressures (not concentrations) and are d e p e n d e n t on the m e m b r a n e characteristics. D u e to the measuring principle of the Ingold sensor, the signal is in logarithmic scale. CO 2 in the exhaust gas was determined by the "classical" method based on the infrared absorption of CO 2. Ethanol was also measured with the mentioned MS; however, the shown concentration range is an approximate estimation only (assuming that Henry's law is valid). Phases as in Fig. 4.
Ethanol is both blown out with the exhaust gas as well as utilized as a substrate. So far it is not clear in which of the phases 3-5 the utilization definitely sets in.
Oxygen. 0 2 was determined in the liquid (polarographically and by MS) and in the exhaust gas (Fig. 10). The determination of the partial pressure allows to gain insight into the potential of the O 2 supply; however, a final estimation upon this is only possible, if the degree of mass transfer and mixing is considered as well (I_ocher et al., 1992). On the contrary, the O 2 in the exhaust gas of the bioreactor is lost for the culture (i.e. cannot be used by the cells). Nevertheless, the general development of the signals is comparable even if the scatter of data is highest with the MS. Process phases 2 and 7 cannot be resolved by the O 2 determination methods; phase 5 may or may not be distinguished from phase 6.
Optical density (OD). OD measurements were inconsistent over different batch series (i.e. lots of prepared media) whereas the changes within a single series were small (Fig. 10). The main differences concerned phases 3 and 4 where an increasing, a decreasing as well as a constant development with time could be observed. The discrimination of phases was low; in Fig. 10, only the 'classical' distinction between the glucose and the ethanol phase can be made. Due to the effect of ethanol on the coalescence properties of the medium, its depletion at the end of the batch results in a sudden increase of the OD signal.
70
~
time--~
@®
P02
f
u Fig. 10. The partial pressure of 02 in the liquid was measured polarographically(Ingold) and via MS. Due to the dependency of the determination method for the molar fraction of 02 in the exhaust gas (based on paramagnetism), the measuring cell must be recalibrated quite often. OD measurements were obtained on-line (Aquasant). The signal is very sensitive to coalescence changes and the bubble spectrum in the medium. Phases 1-6 correspondingto Fig. 4.
pH controller. An uptake of acidic compounds such as organic acids increases the p H in the medium and vice versa (Fig. 11). This is compensated for by the pH controller with the addition of acid. Accordingly, the consumption of (neutral) glucose under excretion of organic acids in phases 1 and 2 requires the continuous addition of alkali. Phases 3 and 4 can easily be distinguished. The signal is highly dependent on the controller parameters. If, for instance, these settings apply to a very fast performance (on the cost of stability) the vanishing of pyruvic acid is compensated by a sharp addition of acid lasting very few minutes only. Additional information about the unknown substance responsible for phase 5 cannot be gained by this signal.
Heat production.
The temperature difference between the cooling circuit and the culture is a first approximation for the heat production of the cells (Fig. 11). However, the very low energy to be resolved (few W 1-1) makes this signal very noisy. Only the end of phases 2 and 7 can be resolved reliably. Additional expenditure for noise reduction allowed to distinguish phases 3 and 4 from phase 5 (Locher et al., 1991).
Fluorescence.
During phases 1 and 2 the (NADH) fluorescence signal grows exponentially in parallel with the biomass; this is due to a maximal cellular load with reduction equivalents which allows to correlate this signal with the biomass concentration during this growth period (Fig. 11). Later in the process when, amongst other changes, the carbon sources undergo shifts from one to another, this correlation does no longer hold true.
71
FI
I
|
"..~
time "" -~
redox
Fig. 11. The temperature difference between cooling circuit and the cultivation medium (AT) is a first approximation of the heat produced by the cells. Due to the low energy to be resolved, this signal is very noisy in this equipment. The pH controller output signal reveals the amount of acid or alkali pumped into the reactor for maintaining the pH setpoint. A step down codes for acid which is pumped into the reactor, e.g. the compensation of an organic acid metabolized by the cells. Fluorescence measurements are dependent on both, the cell concentration in the medium as well as their metabolic state. Since the signal is correlated with the NADH concentration, it is one of the very few intracellular measurements which are available today. The redox potential as measured in a biotechnological medium is rather related to an "overall availability of electrons", than to a specific redox couple. However, during these batch cultivations, this signal was the only one except the CO2 measurements, which allowed to distinguish the first and the second process phase (a distinction, which has not been made so far). Phases 1 a n d 2 c a n n o t be distinguished by this signal. T h e e n d of the the d e p l e t i o n of all extracellular c a r b o n sources causes a sharp drop of T h e energetics of the cells are reflected in the phase p l a n e plot of reveals the cellular load with r e d u c t i o n equivalents a n d the efforts to t h e m by the excretion of ethanol.
batch, i.e. the signal. Fig. 12. It get rid of
Redox.
T h e redox signal was the only o n e with the exception of the C O 2 signals which is capable to identify p h a s e 2 (Fig. 11). If the fluorescence signal reflects the i n t r a c e l l u l a r redox state, the redox signal applies to the extracellular "overall availability of e l e c t r o n s " (Kjaergaard, 1977). This leads to a n " a n t i p a r a l l e l " signal d e v e l o p m e n t but, w h e r e a s the fluorescence sensor is i n c a p a b l e of resolving the second growth phase, the redox sensor can.
Conclusions Batch cultivations with S. cerevisiae can be subdivided into seven different phases o n the basis of m e t a b o l i t e p r o d u c t i o n a n d c o n s u m p t i o n . T h e o r d e r of these
72
0
A
e-
~no
q o. .
.
.
.
.
.
.
.
.
.
L
Fig. 12. A superposition of seven batch cultivations is a "phase plane plot" of fluorescence and ethanol (MS) reveals the course of the NADH household during batch experiments. In a first approximation, the signal is dependent on the concentration of the cells and on their load with reduction equivalents. During growth on glucose, the respiration is the bottle-neck for the preferred oxidative utilization; consequently, the NADH concentration remains constant on a high value. So does the (uncontrolled) glucose consumption of the cells because of the high extra-cellular concentration and poses a high need to neutralize reduction equivalents. This is primarily performed by the reduction of acetaldehyde to ethanol, which leads to the "linear" increase in the fluorescence - ethanol phase plane plot. In the course of the organic acid consumption, ethanol is blown out with the exhaust gas and insignificantly metabolized by the cells. In combination with the growing biomass concentration this leads to a slight increase of the fluorescence signal. During growth on ethanol the increasing biomass in parallel with the decreasing ethanol concentration leads to a relatively constant fluorescence signal. This can be due to the attenuation of reduction equivalents produced in the course of vanishing ethanol. During the final peak the fluorescence signal drops (cannot be shown adequately in this plot because the very few data points are hidden behind those which are measured during the refill procedure of the reactor).
phases is highly d e p e n d e n t on the respiratory b o t t l e - n e c k of the cells, which is c o n f i r m e d to be c e n t r a l to metabolism. A c c o r d i n g to this i n t e r p r e t a t i o n , the excretion of glycerol, pyruvic acid, acetic acid a n d p r o p i o n i c acid d u r i n g the glucose g o v e r n e d phases (1, 2) of a batch cultivation is a n overflow reaction which allows the cells to n e u t r a l i z e their r e d u c t i o n equivalents. W h e n the m e d i u m is d e p l e t e d of glucose, the cellular m e t a b o l i s m u n d e r g o e s the changes of a r e c u p e r a t ing oxidation capability for m e t a b o l i t e s due to the decreasing e t h a n o l c o n c e n t r a tion. This is likely to be a n i m p o r t a n t r e a s o n for p h e n o m e n a such as the c o n s u m p tion of acetic acid d u r i n g phase 4, the excretion d u r i n g phases 5 a n d 6 a n d utilization again d u r i n g phase 7. T h e following questions r e m a i n to be answered. - T h e biological m e c h a n i s m responsible for the second a n d the fifth phase. - T h e role of e t h a n o l in metabolism. F r o m the e x p e r i m e n t s it c a n n o t be determ i n e d w h e n exactly the e t h a n o l utilization sets in d u r i n g phases 3 - 5 . - T h e e t h a n o l i n h i b i t i o n of metabolism. A c c o r d i n g to the very fast r e s p o n s e ( i m m e d i a t e acetic acid c o n s u m p t i o n ) on the d e p l e t i o n of e t h a n o l in the seventh phase, the effect must be strong. - T h e role of glycerol ( a n d acetaldehyde) in relation to the e t h a n o l metabolism.
73 - T h e d e l a y e d pyruvic acid u t i l i z a t i o n ( p h a s e 3) which m a y b e c a u s e d by the generation of enzymes capable of the transport through the membrane. A c c o r d i n g to t h e s o p h i s t i c a t i o n a n d the versatility o f the m e t a b o l i s m of S. cerevisiae in c o m b i n a t i o n with its p r o v e n r e p r o d u c i b i l i t y o f e x p e r i m e n t s a n d t h e a c c u m u l a t e d k n o w l e d g e , this o r g a n i s m is p e r f e c t l y eligible as a test a n d r e f e r e n c e o r g a n i s m in b i o t e c h n o l o g y . F u r t h e r d o c u m e n t a t i o n of " p u r e " biological r e s p o n s e s - also u n d e r d i f f e r e n t cultivation c o n d i t i o n s - a r e highly d e s i r a b l e a n d w o u l d c o n t r i b u t e to both: an i n c r e a s e d k n o w l e d g e a b o u t f u n d a m e n t a l m e t a b o l i c principles a n d a basis for a s o u n d d i s c r i m i n a t i o n what, in a given b i o p r o c e s s , has b e e n c a u s e d by biological a n d w h a t by n o n - b i o l o g i c a l effect. T h e above d o c u m e n t e d analyses a p p l y to e x t r a c e l l u l a r c o n c e n t r a t i o n s exclusively (with t h e e x c e p t i o n of the f l u o r e s c e n c e signal). I n t r a c e l l u l a r i n t e r m e d i a t e s involve difficult a n d t i m e - c o n s u m i n g e x t r a c t i o n p r o c e d u r e s , a n d a r e the next s t e p t o w a r d s an entirely d o c u m e n t e d p r o t o t y p e batch. In this context, the time constants of the b i o r e a c t i o n s m u s t b e r e c o n s i d e r e d w h e n designing a s u i t e d s a m p l i n g system. C h a n g e s in t h e m e t a b o l i s m can be in the o r d e r of s a n d r e q u i r e for cell inactivation m e t h o d s in at least the s a m e time m a g n i t u d e .
Acknowledgements T h e a u t h o r s t h a n k C. G u b y for his c o n t r i b u t i o n d u r i n g analytical work.
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74 Rose, A.H. and Harrison, J.S. (1989) The Yeasts. Metabolism and physiology of yeast. Academic Press, New York. Sonnleitner, B. and Kiippeli, O. (1986) Growth of Saccharomyces cerevisiae is controlled by its limited respiratory capacity: formulation and verification of a hypothesis. Biotechnol. Bioeng. 28, 927-937. Striissle, C., Sonnleitner, B. and Fiechter, A. (1989) A predictive model for the spontaneous synchronization of Saccharomyces cerevisiae grown in continuous culture. II. Experimental verification. J. Biotechnol. 9, 191-208.