Biotechnol. keg. 1991, 7, 471-480
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Growth, Metabolic, and Antibody Production Kinetics of Hybridoma Cell Culture: 1. Analysis of Data from Controlled Batch Reactors Sadettin S. Ozturk' and Bernhard 0. Palsson Cellular Biotechnology Laboratory, Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan 48109
A mouse-mouse hybridoma cell line (167.4G5.3) was cultivated in a 1.5-L stirred-tank bioreactor under constant pH and dissolved oxygen concentration. The transient kinetics of cell growth, metabolism, and antibody production were followed by biochemical and flow cytometric methods. T h e cell-specific kinetic parameters (growth and metabolic rates) as well as cell size were constant throughout the exponential phase. Intracellular protein and RNA content followed a similar trend. Cell growth stopped when the glutamine in the medium was depleted. Glucose could not substitute for glutamine, as glucose consumption ceased after glutamine depletion. Ammonia and lactate production followed closely glutamine and glucose consumption, respectively. Alanine, glutamate, serine, and glycine were produced but other amino acids were consumed. The cells are estimated to obtain about 45% of the total energy from glycolysis, with the balance of the metabolic energy provided by oxidative phosphorylation. The antibody was produced a t a constant rate in both the exponential and decline phases of growth. The intracellular antibody content of the cells remained relatively constant during the exponential phase of growth and decreased slightly afterwards.
1. Introduction Ever since the inception of hybridoma technology there has been an enormous increase in the use of antibodies as reagents. In biological and medical research, antibodies are currently used to diagnose, treat, and even vaccinate against a wide range of diseases (Carlsson and Glad, 1989). There is also a potential use of antibodies as tailor-made, enzymelike catalysts for chemical reactions (Green and Tawfik, 1989). The development of bispecific antibodies is further expanding the range of possible applications for antibodies (Williams, 1988). Biotechnologists have used the selectivity and specificity of antibodies to detect and purify various ligands. These applications require a largescale production of antibody-which in some cases is on the order of several hundred kilograms of antibody per year (Smithson, 1988; Spier, 1988; Vosper, 1989). The high costs of producing sufficient quantities of monoclonals for commercial applications, plus the meager yields of antibody using conventional technology, are two important reasons why research and development of cost-effective large-scale culture of hybridomas is continuing and is important for commercial success. Hybridoma cells can be successfully grown in bioreactors using techniques similar to those developed for largescale cultivation of microbial cells. Many of the frequently articulated difficulties with large-scale cultivation of hybridoma cells, such as shear stress, expensive medium, cell fragility, and contamination problems, have proven to be less problematic than originally anticipated (Spier, 1988). However, a deeper understanding of cell physiology, i.e., growth, metabolic, and production characteristics of hybridoma cells in the bioreactor environment, is still in its infancy. Like other mammalian cells, hybridomas show a complex response to the changes in the bioreactor environment. The preparation of medium and the source of serum also
* To whom correspondence should be addressed at Verax Corp., 6 Etna Rd., Lebanon, NH 03766. 8756-7938/91/3007-047 1$02.50/0
can influence the kinetic variables obtained. The problems in determining culture kinetics is compounded even further by the alteration in cell behavior by the age in culture (Ozturk and Palsson, 1990c,1991a). However, a quantitative characterization of cell response to the changes in environmental and process variables is needed for reactor design and control purposes. One such comprehensive information and a reliable interpretation of cellular kinetics are available, one can develop model equations that quantify the performance of bioreactors. Kinetic behavior of hybridoma cells has been partially characterized. Low and Harbour (1985a,b) investigated the effects of serum and energy sources on hybridoma growth and metabolism in culture flasks. Dalili and Ollis (1989)and Heath et al. (1989) studied in detail the effects of serum concentration on cell growth, metabolism, and antibody production. Boraston et al. (1984) studied chemostat cultures of hybridoma cells with special attention to oxygen limitation. Reuveny et al. (1987) and Velez et al. (1986) investigated process variables such as oxygen tension, pH, temperature, and serum. Glacken et al. (1988, 1989) utilized an experimental protocol that resulted in mathematical descriptions on how initial cell growth and metabolic and antibody production rates are influenced by a variety of process variables. Truskey et al. (1990) focused on serum and waste product concentrations on hybridoma growth and metabolism. Miller et al. (1987, 1988a-c, 1989a,b) studied effects of various process variables such as nutrient levels, pH, oxygen, and dilution rates under steady-state and transient operating conditions. Except the study of Miller et al. (1987,1988a-c, 1989a,b), all of the studies mentioned above dealt with a limited number of cell kinetic parameters in response to changes only in a few process variables, and they were mostly carried out with different cell lines in tissue culture flasks rather than well-controlled bioreactors. The transient changes in medium composition,pH, oxygen,and cell concentration during a batch culture under uncontrolled conditions make
0 1991 American Chemical Society and American Institute of Chemical Engineers
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it difficult to conclusively relate variations in cellular activity to a particular process variable. Cell culture kinetics are complex, and in studying the effects of one variable, all other should be kept constant, if possible. Experiments have to be carried out with controlled pH and dissolved oxygen, and whenever possible, changes in kinetic behavior should be evaluated as a function of time. Transient changes in the kinetic parameters are ignored in most of the studies cited above. We have performed a comprehensive kinetic study on the characterization of hybridoma cell growth, metabolism, and antibody production. Experiments are carried out in controlled bioreactors for a single cell line and the same medium to relate the cell's response to important processing conditions. For each variable, cell growth, viability, metabolic rates for glucose, lactate, glutamine, ammonia, oxygen, and amino acids, energy metabolism, and antibody production rates are quantified and the results are interpreted in terms of cell biology. Previously, we have reported the effects of initial cell density, ammonia and lactate, and osmolarity, studied for the same cell line under less controlled conditions (Ozturk and Palsson, 1990b, 1991c; Ozturk et al., 1991). In this series we have investigated the effects of serum concentration, dissolved oxygen tension, and medium pH in a well-controlled batch bioreactor. In this first part, we consider the general characteristics of batch cultures of hybridoma cells and the analysis of the data obtained. The time profiles for cell, metabolite, and antibody concentrations are presented first, followed by the extracted transient kinetic parameters from the analysis of data and their interpretations. In the second part of this series we report how these kinetic parameters vary with important processing parameters.
2. Materials and Methods 2.1. Cell Lines, Medium, and Culture Maintenance. Murine hybridoma cell line 167.4G5.3 was provided by Dr. Latham Claflin from the Medical Center at The University of Michigan. The antibody produced by this cell line is an IgG1, directed against phosphorylcholine (PC) (Briles et al., 1984). Hybridoma cells were made by fusion of BALB/c mice spleen cells with the nonsecreting plasmacytoma fusion line P3X63-Ag8.653. Antibody was generated from mice immunized with PC-keyhole limpet hemocyanin (KLH). Cells were maintained at 37 "C in a 95% air/5% COZ atmosphere in humidified incubators (VWR Scientific, San Francisco, CA). The cultures were passed every 2 days with a dilution factor of 1:4 with fresh medium. Iscove's modified Dulbecco's medium (IMDM, Sigma Chemical Co., St. Louis, MO) supplemented with 5% fetal bovine serum (FBS, Gibco Laboratories, Grand Island, NY) was used as medium unless otherwise specified. Antibiotics, 100 units/mL potassium penicillin G and 100 pg/mL streptomycin sulfate (Sigma) were added to the medium to protect against contamination. The culture was tested routinely for mycoplasmal and low levels of bacterial contamination. No contamination was detected during the course of this study. 2.2. Bioreactor Experiments for Determination of Metabolic Dynamics. One week before the start of each run, the passage of cells was done daily at a dilution factor of 1:2. The cells were propagated by increasing the number of flasks. Thus cells were accumulated enough to inoculate the reactor and they were maintained in "almost" fresh medium. This protocol resulted in a robust inoculum and eliminated the lag phase in most cases. A 1.5-L stirred-tank bioreactor (Celligen, New Brunswick) was used to investigate cellular kinetics during batch
cultivation. IMDM with 5% FBS was used as medium. The pH and dissolved oxygen (DO) concentration were kept constant at 7.2 andat 20% air saturation, respectively, using a microprocessor controller throughout the run. The pH was controlled at the set point by varying the COa content of the gas phase. Agitation was provided by a screen-impeller system (New Brunswick) at 80 rpm. Temperature was controlled at 37 "C. Cells were inoculated at an initial concentration of 5 X lo4 cells/mL. The viability of the inoculum was always greater than 95%. A total sample volume of 5 mL was taken twice daily. After the cells had been counted, they were removed by centrifugation. The cells were washed with PBS and fixed with cold 70% ethanol for flow cytometric analysis. After ethanol fixation, cells could be stored in 70% ethanol at -20 "C for more than a month. The supernatants were then kept frozen at -80 "C for later analysis. Cell counts were performed using a hemacytometer. Cell viability was determined by the trypan blue exclusion method. The glucose and lactate concentrations were measured using a Model 2000 YSI glucose L-lactate analyzer (Yellow Springs Instruments, Yellow Springs, Ohio). Ammonia was measured with a gas-sensitive electrode (Ozturk et al., 1989). Amino acids were analyzed using HPLC using the OPA (0-phthaldialdehyde) precolumn derivatization technique. Antibody IgGl was quantified using an enzymelinked immunosorbent assay (ELISA). Specific oxygen uptake of the cells in the reactor was determined by measuring both gas- and liquid-phase concentrations of oxygen as described below. Cell size determinations were performed in a Coulter counter (Model ZM) with channelyzer (Ozturk and Palsson, 1991~).The EPICS 751 flow cytometer (Coulter) was used to analyze the macromolecular composition of the cells (Ozturk and Palsson, 199Oc, 1991a). 2.3. Determination of Kinetic Constants. Two approaches were used for parameter estimation: the integral and the differential methods. The differential method was used for obtaining transient kinetics. Experimental data were smoothed using a cubic spline technique and the kinetic parameters, defined below, were evaluated as functions of time. The integral method was applied to the data confined in the exponential phase only. The time span in which the parameters obtained by the differential method stayed constant was identified as the duration of exponential phase. DifferentialMethod. The following model equations were used for the differential method: Growth and death rates
-dXd
dt
- 'dXv
(3)
where XT,X,, and Xd are the total, viable, and dead cells, respectively, t is time, and p and kd are the specific growth and death rates. The apparent growth rate papp differs from the actual rate ( p ) by the death rate (kd). The consumption and production rates were defined with respect to the viable cell counts and were determined
Biotechnol. Prog., 1991, Vol. 7, No. 8
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using dS, dt
--=
q,Xv (consumption)
dpi - p i x v(production) dt
(4)
where S and P are consumed substrate and product concentrations, respectively, and q and p are their specific consumption and production rates. Ammonia and glutamine kinetics were determined by considering both the first-order chemical decomposition of glutamine to ammonia and metabolic activity:
(5)
The first-order decomposition rate constants of glutamine in IMDM supplemented with different serum concentrations have been reported in Ozturk and Palsson (1990a). Here we used a value of k = 0.0023 h-l. Monoclonal antibody production rates were calculated from d[MAb] -dt - qAbXv where [MAb] is antibody concentration and specific production rate.
(7) qAb
is the
Integral Method. The above equations were integrated for use in the integral analysis. Due to the sensitivity of determination for dead cell and antibody concentration, the conventional integral method was slightly modified for the evaluation of death rates and specific antibody productivities. Growth rates were calculated from the time profiles of viable cells:
The above equations were fitted to the data confined to exponential phase as explained in Ozturk and Palsson (1990a). Antibody productivity was determined from a plot of antibody concentration against the time integral of viable cells (Renard et al., 1988; Ozturk et al., 1990b):
2.4. Measurement of Oxygen UptakeRates. Oxygen uptake rates (qoJ were measured in the reactor using the mass balance
where kla is the volumetric mass transfer coefficient, C* and CL are the concentrations of oxygen in the gas and liquid phases, respectively, and X , is the viable cell concentration. Hence oxygen uptake rates could be measured in the reactor provided all the parameters in the above equation are measured. The mass transfer coefficient in the reactor was measured using dynamic gas absorption technique (Bailey and Ollis, 1986). Oxygen concentrations in both gas and liquid phases were measured using galvanic oxygen probes (Ozturk, 1990). 2.5. Estimation of ATP Production Rates. Production rate of ATP was estimated using the lactate production and oxygen consumption rates following the procedure of previous investigators (Glacken et al., 1986; Miller et al., 1987). Here one adds the contributions of glycolysis and oxidative phosphorylation by qATP = fqLec + 2(p/o)q02
Death rates were calculated from a plot of dead cells against integral of viable cells (following eq 3):
X , = k, x X vdt
(9)
Hence a plot of dead cell concentration versus the time integral of viable cell concentration should yield a straight line whose slope is the death rate (Ozturk and Palsson, 1991b). Except glutamine and ammonia, metabolite uptake and production rates are evaluated from the plot of metabolite concentrations against viable cell numbers:
S+Si
x,-x,O Pi - P;
x,-x,O
=-
qi
(consumption)
papp
=- pi
(production)
papp
Glutamine and ammonia specific rates are calculated from Glacken et al. (1988):
(15)
where QATP, qLac, and qo2are the production rates of ATP, lactate, and oxygen,respectively, f is the fraction of lactate coming from glycolysis, and PI0 is the phosphorylation ratio. The majority of the lactate produced comes from glucose. However, lactate can also be produced from glutamine (Reitzer et al., 1979;Zielke et al., 1980). Then, the factor f can differ from unity to a lower or a higher value. Reitzer et al. (1979) have shown that 80% of the glucose was converted to lactate and only 4-5 % centered the TCA cycle. On the other hand, 35% of glutamine is oxidized to COz and 13% is converted to lactate. We assume that the lactate production from glutamine and the entry of glucose to the TCA cycle counter-balance each other, leaving f at unity. This assumption has been used by previous investigators (Glacken et al., 1986; Miller et al., 1987). The phosphorylation ratio can vary between 2 and 3. However, under ordinary conditions a value of 3 can be used (Glacken et al., 1986). Then we have that (16) The term qLac corresponds to the contribution of glycolysis, and the term 6q02corresponds to the contribution of oxidative phosphorylation. qATP
= qLac + 6q02
Biotechnol. Prog., 1991, Vol. 7, No. 6
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00 0 0
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Figure 1. Kinetics of hybridoma batch culture for 167.4G5.3 murine hybridoma cells at pH 7.2 and dissolved oxygen concentrationof 20% air saturation. Cells are grown in IMDMmedia with 5% FBS at 37 O C . (A)Viable (closed circles) and total cell (open circles) concentrations,cell viability (closed squares),and antibody concentrations in milligrams per liter (open squares). (B) Concentration profiles for glucose (closed circles), lactate (open circles), glutamine (open squares),and ammonia (closed squares).
0.0
3. Results 3.1. Concentration Profiles. Experimental data on cell growth, metabolite concentrations, and antibody synthesis are presented in Figure 1. Cells grew exponentially for 75 h (Figure 1A) following inoculation. Viable cell concentration reached a maximum count of 1.5 X lo6 cells/mL after 120hand then decreased during the decline phase. The total cell concentration was very close to viable cell concentration during the growth phase; thus the viability remained high. The total cell concentration reached a plateau at 2 X 106cells/mL, and the cell viability ' to 25 ?4 in 2 days. Except for dropped sharply from 90 % the dead and viable cell counts, the changes in the measured variables were negligible and the culture was terminated after the viability dropped below 25 ?4 . Glucose and glutamine concentrations decreased during the growth phase and lactate and ammonia were produced (Figure 1B). The medium contained an initial glutamine concentration of 3.7 mM and all the glutamine was depleted after 120 h, which coincides with the maximum of viable cell count and cessation of growth. The glucose concentration, on the other hand, dropped from 23 mM at the beginning to 11mM at the end of the culture. Cells could not substitute glucose for glutamine and continue growth after glutamine depletion and glucose consumption ceased. Although the cells had oxygen available at 20% air saturation, significant lactate was produced as a waste product (Figure 1B). About 21 mM lactate was produced by the consumption of 1 2 mM glucose, and hence the overall yield of lactate from glucose was 1.75 (mol/mol). Ammonia is produced from glutamine metabolism and by chemical decomposition of glutamine. Ammonia accumulated in the medium to reach a concentration of 3 mM. Both lactate and ammonia production ceased following glutamine depletion.
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Time, hr
200
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Time, hr
Figure 2. Time profiles of amino acids measured by HPLC in the batch culture of 167.4G5.3 murine hybridoma cells. Experimental conditions are presented in Figure 1. The IgGl antibody was produced continually during both the growth and decline phases, and a concentration of 30 pg/mL was obtained at the end of the culture (Figure 1A). Antibody production did not stop after cessation of cell growth, suggesting that antibody production, for this cell line, was not growth associated. Amino acid concentrations analyzed by HPLC are presented in Figure 2. The OPA technique detects 17 of the amino acids. Proline, tryptophan, cysteine, and cystine are not detected by this technique. Most of the amino acids were consumed, with leucine, isoleucine, valine, lysine, and threonine consumption being most prominent. Glutamate, serine, glycine, and alanine were produced, with the production of alanine being the most pronounced. About 2.5 mM alanine was produced by the cells. 3.2. Calculation of Kinetic Parameters. The data presented in the previous subsection were analyzed using the mathematical techniques described in the Materials and Methods section. The transient rates are evaluated by the differential method. Figure 3 shows the cell growth rates, along with glucose and glutamine uptake rates. The specific growth rate remained constant only over the first 75 h of the culture (Figure 3) and then decreased to zero at 120 h when glutamine was depleted. Specific glucose and glutamine uptake rates followed the same trend; they remained constant during the first 75 hand then decreased to zero. These data indicate that glucose and glutamine uptake are growth related. Lactate and ammonia production rates and amino acid metabolic rates were also
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Wiotechnol. Prog., 1991, Vol. 7, No. 6
Table I. Specific Rates Evaluated during the Exponential Phase of Growth.
0.ooL 0
-\
*
'
'
'
25
50
75
100
'r 2
125
-
150
,
175
0.0 200
-I0.00
T h e , hr
Figure 3. Transient kinetics in batch mode obtained from the differential method. Actual growth rate (open circles), glucose uptake rate (closed circles), and glutamine uptake rate (open squares) are shown. The values are constant in the first 75 h a t & = 0.042 h-1, = 0.214 &mol/(lOscells.h), qGh = 0.046 &mol/ (lo6 ce1ls.h).
constant in the first 75 h of culture and decreased later (data not shown). The calculated rates during the exponential phase are summarized in Table I. In Figure 4 the use of the integral method is illustrated for the evaluation of cell growth, glucose and glutamine uptake, and cell death rates. Model equations for the integral method (eqs 8-13) were linearized so that the parameters could be evaluated from the slope and/or the intercept of the regression lines. Data over the first 75 h yield constant values for the kinetic parameters, as apparent from the slope of the regression curves. This time span of 75 h of cell growth is then the exponential phase of growth, as also suggested by the differential method. The values for growth rate and for glucose and glutamine uptake rates obtained from the integral method in this phase were similar to the initial rates obtained from the differential method. I t should be pointed out that the parameter values obtained from the differential method were also constant during the exponential phase. The absence of any lag phase and the careful selection of the time span of the exponential phase resulted in meaningful kinetic parameters that can be referred as both initial and exponential rates. The integral method of analysis revealed two distinct death rates in the course of batch culture. The data confined to exponential and decline phases yielded two different slopes (Figure 4D). The death rate in the exponential growth phase was k d = 0.004 h-l. This death rate increased by 1order of magnitude and a death rate of k d = 0.031 h-l was obtained in the decline phase. The decreases in growth and metabolic rates over time were accompanied by a decrease in the average cell size (Figure 5A). The mean cell diameter remained constant over the first 75 h of culture at 13.5 pm in diameter. It then decreased to about 10.5 fim. The corresponding cell decrease in volume is 2-fold. The gross macromolecular intracellular composition is presented in Figure 5A. Cell protein and RNA content measured in a flow cytometer showed the same trend as the growth rate. Mean fluorescence channel numbers are presented in this figure for protein (green fluorescence) and RNA content (red fluorescence). Since the cells are stained under the same conditions and on the same day, and the fluorescence levels are proportional with the amount of protein and RNA, the mean channel number corresponds to a relative scale on which comparisons can be made. Cell cycle analysis was carried out using the DNA histogram obtained by PI staining after RNase treatment. Using available software for cell cycle analysis (PARAI, from Coulter Electronics), we identified the number of cells in
parameter growth rate death rate (exponential) death rate (decline) glucose uptake lactate production glutamine uptake ammonia production oxygen uptake antibody production
units h-1 h-1 h-l pmol/(l@ cells-h) &mol/(108 cells-h) pmo1/(1@cellsh) pmol/(l@ ce1ls.h) qmol/(l@ cellsh) pg/ (cells-h)
value 0.042 f 0.004 0.004 f 0.001 0.031 f 0.004 0.216 f 0.013 0.379 f 0.015 0.046 f 0.008 0.031 f 0.007 0.078 f 0.006 0.215 f 0.009
mol/mol 1.77 mol/mol 0.58 The standard deviations are calculated from duplicate experiments. YLacJGlu yNlc+/Ch
+
+
GO G1, S, and G2 M phases. This data is presented in Figure 5B as a function of time. At the beginning of the experiments 39% of the cells were in GO + G1 phase and 44% of the cells were in the S phase. With culture time the fraction of GO + G1 phase increased and the fraction of cells in S phase decreased. The fractions of cells in M phase was 15% at the beginning, then later decreased to 5% at the end of the culture. Amino acid consumption and production rates are summarized in Table 11. The rates are calculated using the integral method. The values obtained from the differential method are similar but more scattered. The amino acid metabolic rates are compared to those of Adamson (1987) and Miller et al. (1988~)in Table 11. Figure 6 outlines the evaluation of specific antibody production rates. The specific antibody production rate stayed constant around 0.2 pg/ (ce1l.h) throughout the run including both exponential and decline phases of growth (Figure 6A). These data indicate that the antibody production rate is not growth dependent. Intracellular antibody content of the cells measured during the batch is presented in Figure 6A. The intracellular antibody content of the cells, like the specific antibody production rate, is constant in both exponential and decline phases. There is a slight decrease in the late decline phase, probably due to the changes in the cell volume. The integralmethod evaluation of specificantibody production rate is presented in Figure 6B. The antibody concentrations are plotted against the integral of viable cell concentrations and the specific antibody production rates are obtained from the slope of these curves. In this figure we included all the data points, in both exponential and decline phases. The same straight line could correlate all the data points, indicating that cells in both exponential and decline phases have the same specific antibody production rate. The respiration rate for the hybridoma cell line 167.4G5.3 was measured in the exponential phase to be 0.0078 pmol/(l06 cells-h) (Table 111). ATP production rates were estimated from oxygen uptake rates and lactate production rates as explained in the Materials and Methods section. These rates were all constant in the exponential phase. The calculations for ATP production rate are summarized in Table 111. ATP was produced at a relatively constant rate in the exponential phase at 0.844 kmol/( 106 cells-h). The contributions of oxidative phosphorylation and glycolysis were calculated from relative rates of oxygen consumption and lactate production rates, respectively. Oxidative phosphorylation contributed about 55 % of the total energy production. The apparent yield was of NADH formation from glutamine, YNADH/G~ calculated from oxygen uptake rates and glutamine uptake rates and is indicated in Table 111. In these calculations
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Biotechnol. Prog., 1991, Vol. 7, No. 6
.
18 y = 4.73e+4
y
E
22.486
- 53085c.6~
. (B) -
R A 2 I 0.975
-
R A 2 = 0.99
1OL(1.7k-2x)
u.ue+O
1.0e+6
1.5e+6
Viable cells/ml
c+8
exp(Wxp(-kt) -.----.----.-.---. xo
Integral of viable celldml-hr
k+F
Figure 4. Evaluation of parameters in the integral method using linearized model equations. (A) Apparent growth rate; (B)glucose uptake rate; (C) glutamine uptake rate; (D)death rates in exponential and decline phases. The values obtained in the exponential phase are plPp= 0.039 h-l, qG1" = 0.21 pmol/(106 cells-h), p ~ =h 0.044 pmo1/(108 cells-h). Cell death rate increased from k d = 0.004 h-l in the exponential phase to k d = 0.031 h-l in the decline phase. -65 -60 -55
E-so 2 4 0 '
;-45
=
- 40 - 35 130 0
25
50
75
100
125
150
175
-130
200
Time, hr
80
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Table 11. Amino Acid Consumption and Production Rates for Murine Hybridoma Cell Line 167.4G5.3 Cells Grown in IMDM Medium with 5% FBS. Adamson et al. (1986) Miller et al. (1989) this work cell line: Antl-HT AB2-143.2 167.4G5.3 medium: DME DME IMDM Aspartate n.d 0.67 1.45 Glutamate [3.01 [1.041 [3.43] Asparagine L1.01 0.75 0.85 Serine 4.0 1.04 [2.26] Glutamine 79.0 35.41 45.80 Histidine 1.0 1.58 0.94 Glycine n.d [2.83] [0.78] Threonine 4.0 2.38 1.36 Arginine 6.0 2.08 2.71 Alanine [34.0] [13.30] [33.63] Tyrosine 2.0 0.96 2.65 Methionine 2.0 1.58 1.10 Valine
4.0
3.71
4.45
Phenylalanine 6.0 1.33 0.85 Isoleucine 9.0 4.17 5.90 Leucine 10.0 4.46 6.77 Lysine 6.0 2.67 2.65 The data are compared to some literature values. The rates are in nanomoles per 106 cells per hour. The square brackets indicate that the amino acid is being produced.
'0
25
50
75
100
125
150
175
200
Time, hr
Figure 5. Variation of cell composition during batch culture. (A) Mean cell size (closed circles) and relative RNA (closed squares) and protein (open squares) contents. (B)Cell cycle variations in batch mode.
the NADH production by the metabolism of branched amino acids was not considered. The yield coefficient was about 3.4 mol of NADH formed/glutamine consumed (Table 111).
4. Discussion 4.1. Batch Culture Kinetics. Batch culture exhibits transient behavior that complicates kinetic analysis. It is desirable to measure growth and metabolic rates without significant changes in medium composition since these rates may depend on medium composition. This condition can be attained by employing low inoculum sizes and evaluating initial rates (Glacken et al., 1988). Significant changes in the medium composition, however, are necessary for accurate measurements of metabolic activities. Our earlier experiments in spinner flasks showed that kinetic parameters were not altered by the initial cell
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Biotechnol. Rag.., 1991, Vol. 7, No. 6
10
0 50
0
100
150
200
Time, hr
+ l
E
0 ue+O
5e+7
le+8
2e+8
Integral of Viable Celldml-hr
Figure 6. Antibody synthesis in batch mode. (A) Transient rates of specific antibody production and time profiles of intracellular antibody content. (B) Integral method evaluation of specific antibody production rate. Table 111. Calculations of ATP Production Rates and Relative Contribution of Glycolysis and Oxidative Phosphorylation on Energy Production.
parameter oxygen uptake rate, qo2 lactate production rate, q h c ATP production rate, qATP = qL.c + 6q0, contribution from glycolysis, qbc/qAW contribution from oxidative phosphorylation, 6 q & / q ~ w NADH yield from glutamine, YNADHIGln
value 0.078 0.379 0.844 0.45 0.55
3.4
= q N A D H / q G l n = %O,/qGln
The rates were determined in the exponential phase of cell growth. The rates are in units of micromoles per lo6 cells per hour. (I
density between lo3 and 105 cells/mL levels (Ozturk and Palsson, 1990b). An initial cell density of 5 X lo4 was used in this study. Under these conditions 3-4 cell doublings could be obtained during steady exponential growth and accurate determination of changes in medium components could be made. When the lag phase was absent, the exponential phase rate parameters were the same as the initial rates. We eliminated the lag phase of growth by keeping the inoculum in "almost" fresh medium by daily passages. The accuracy of kinetic parameters is enhanced by (1) increasing frequency of sampling, (2) increasing the variations in the medium composition enough to be detected accurately, and (3) prolonging the duration of the exponential phase. These three goals were achieved by taking samples twice a day and by keeping the inoculum size at a low level to get a high number of cell doublings but high enough to get measurable changes in medium composition. We have studied the effects of one variable on the kinetic parameters, by running batch cultures in which only the parameter under consideration is varied, while keeping all others constant (Ozturk and Palsson, 1990b, 1991c,d; Ozturk et al., 1991). The exponential or initial rates were then only influenced by the particular parameter studied. By using the same medium, controlling pH and dissolved oxygen, and keeping the age of inoculum the same, a comparison of different batches could be made.
Following exponential growth, the specific rates decreased monotonically. Cell growth rate dropped to zero when glutamine was depleted. However, growth rate decreased even when glutamine was present between 75 and 125 h. Apparently, buildup of waste products such as ammonia and lactate contributed to this drop in growth rate. We observed for the same cell line that, at a concentration of 2.5 mM, ammonia can decrease the growth rate by a factor of 2 (Ozturk et al., 1991). The decrease in growth rate could also be due to the deactivation of serum as described by Glacken et al. (1989). The transient behavior of the rates presented in Figure 3 can be compared with data from previous reports. The decrease in growth rate was similar to that previously reported by Miller et al. (1988b) and Glacken et al. (1989). The glutamine uptake rate has been reported to decrease throughout a batch culture by Dalili and Ollis (1989). Our calculation of glutamine consumption and ammonia production rates included the chemical decomposition rate of glutamine, while Dalili and Ollis ignored this process. When this rate is not included, the rates of glutamine uptake and ammonia production (apparent rates) show a constant decrease. We have discussed in detail the error introduced by neglecting the chemical decomposition rate of glutamine (Ozturk and Palsson, 1990a), which can be as high as 200% for glutamine uptake at the beginning of the culture and 300% for ammonia production rate. The decrease in metabolic rates could be related to the changes in growth rate. The consumption rates of glucose and glutamine and the production rates of lactate and ammonia were correlated with the growth rate (Figure 7). The linearity in these plots could be explained by the maintenance energy model postulated by Pirt (1975): Q, = G / Y J + m (17) where qsis the nutrient consumption rate, 1.1 is the growth rate, Y, is the growth yield, and m is the maintenance energy. Our analysis resulted with a glucose growth yield of YGlu = 1.87 X lo8 cells/mmol and a glutamine growth yield of Y G=~10.4 X 108 cells/mmol. It is interesting to note that these numerical values are very close to those reported for a different hybridoma cell growing in a different medium (Miller et al., 1988b). Due to the scatter at low growth rates, it is difficult to report accurate values for maintenance energy (m).However, from Figure 7 it is clear that the maintenance energy for the nutrients are very low. Note that Miller et al. also obtained low values for maintenance energy. [The applicability of the maintenance energy depends on how the growth rate is altered. In batch mode considered here, growth rate changed due to the variations in culture composition. This is different than a continuous culture where growth rate is dictated by the dilution rate. Another complication for mammalian cells arises when the growth rate is altered by changing the growth factors in the medium. We have not established a relationship between the growth and nutrient consumption rates when growth rate was changed by serum levels (Ozturk and Palsson, 1991d).] 4.2. Cell Growth. A maximum viable cell concentration was attained when glutamine was depleted. Then during the decline phase, the total cell concentration remained constant but the viability fell. We have seen a continued cell growth when additional glutamine was added after its depletion (datanot shown). This indicates that cell growth was limited by glutamine. Although the glucose consumption rate was higher than that for glutamine [qclU= 0.214 pmol/(106 cells-h)versus q ~ =h0.046 pmol/ (106 cells-h)], glucose was not depleted because of
Biotechnol. Prog., 1991, Vol. 7, No. 6 NucWida
Glqeose '
t
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03.
0.2
-
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Oxidative Phosphorylation
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NADH
Figure 8. Simplified descriptionof hybridoma cell metabolism. Both glucose and glutamine are used for energy production. Glucose is utilized in glycolysiswith lactate being the end product. Glutamine is catabolized in the TCA cycle after being converted to a-ketoglutarate in the metabolic pathways indicated. u.00
'
10 u.00
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Growth rate, llhr
I 0.01
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Figure 7. Correlationof metabolic rates (A and B) and cell size (C) to variation in the cell growth rate. The maintenancemode was applied to the metabolic rate data in the form of q1 = ( p / Y.)
+ m.
high initial concentration (25 mM glucose versus 3.7 mM glutamine). Further, glutamine breaks down by chemical decomposition, which accounted for about 40% of net glutamine dissipation. [This ratio, r, is calculated from the overall mass balances: r = (.f k[Gln] dt)/(J k[Gln] dt + .f qGlnXv dt)]. Other amino acids could not be limiting nutrients as none of them was depleted. The level of dissolved oxygen was maintained above limitation at 20 96 air saturation by increasing the gas-phase oxygen concentration via a microprocessor. Maximum cell concentration in the batch reactor is determined by growth and death rates and by the concentration of limiting nutrient. More cells could be obtained by supplying more glutamine in the decline phase (S. S. Ozturk, unpublished data). Glacken et al. (1986) and Hu et al. (1987) obtained increased cell numbers by adding the limiting nutrients in a fed-batch operation. Cell concentration in the reactor is also determined by the death rates. Our death rates are presented in Table I. The death rate during the exponential phase was low compared to the growth rate. However, the death rate increased by an order of magnitude during the decline phase as quantified by Ozturk and Palsson (1991b). Dalili et al. (1990) reported a similar increase in death rate in the decline phase. Cell volume decreased about 2-fold during the decline phase. This shrinkage could not be attributed to changes in osmolarity, which increased from an initial value of 290
mosM to 310 mosM at the end of the culture. Flickinger et al. (1987) also observed a 2-fold decrease in cell volume in batch culture. Cell size decreased, probably due to the decrease in growth rate. Figure 7C illustrates the relationship between cell size and growth rate. A good linear relationship was obtained between these two variables. Cell protein and RNA content also decreased during the decline phase. Changes in growth rate, in medium composition, or in cell size can be responsible for these variations, by individual or concerted action. The fraction of cells in the GO + G1 phase increased during the decline phase accompanied with a decrease in the size of the population in the S phase. These data are in agreement with the results of Sen et al. (1988). Flow cytometric data showed that cells in the decline phase have double chromosomes. The fraction of cells in M phase did not drop to zero but stayed around 5 % of total. However, the net cell growth rate was zero in the decline phase. It seems, therefore, that cells in M phase do not divide, even though they have enough DNA synthesized. Detailed experiments should be carried out to understand the physiology of cells and the variations of cell cycle during the decline phase. 4.3. Cell Metabolism. Cells utilized both glucose and glutamine for the production of metabolic energy. The key metabolic routes are outlined in Figure 8. Glucose is utilized primarily through anaerobic glycolysis,with a flux diversion through the pentose pathway to give the pentose building blocks for nucleic acids. Most of the pyruvate generated from glycolysis was not utilized in the TCA cycle but converted to lactate. The yield coefficient for lactate from glucose was 1.75 mol/mol, about 80% of the theoretical maximum for anaerobic growth. Similar yield coefficients were reported for other hybridoma cells (Adamson, 1987; Miller et al., 1988a-c). The reasons for significant lactate formation from glucose under aerobic conditions is not fully understood. Loss of control in the regulation of glycolysis, the presence of other energy sources, i.e., glutamine, and faulty shuttle systems to mitochondria have been suggested as possible reasons (Eigenbrodt et al., 1985). Glutamine is used as a major energy source for cells growing in culture (Reitzer et al., 1979; Zielke et al., 1984; McKeehan, 1986). The metabolic fate of glutamine is considerably more complex than that of glucose (Figure 8). Initially it is deaminated with glutaminase (with
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ammonia as a byproduct) or coupled to biosynthetic pathways where the ammonia group is used in the formation of a biosynthetic product, particularly for pyrimidine and purine base synthesis. The product formed by either route is glutamate. The second step of glutaminolysis is the conversion of glutamate to &-ketoglutarate. Again this conversion may be accomplished by more than one enzyme. An active transaminase can remove the ammonia group from glutamate. Less active transaminases appear to deliver the ammonia group to the glycolytic intermediate 3-phosphoglycerate to form serine, which subsequently can be transformed to glycine. Glutamate can also be transformed by glutamate dehydrogenase to form a-ketoglutarate, which liberates a second ammonium ion. a-Ketoglutarate is then metabolized via the TCA cycle. The hybridoma cell line used in this study followed the metabolism outlined above for glutamine and other amino acids. Glutamate was produced from glutamine and subsequently metabolized by the transaminase and probably the dehydrogenase reactions. Alanine transaminase apparently was very active in these cells converting pyruvate to alanine. The alanine yield coefficient on glutamine calculated from alanine production and glutamine utilization was around 0.75 mo/mol. In lymphocytes, aspartate transferase is known to be more active than alanine transferase (Ardawi and Newsholme, 1982, 1984) and it converts oxaloacetate to aspartate. However, aspartate production was negligible compared to alanine for both hybridoma cells used. It seems that the concentration of pyruvate derived from hyperactive glycolysis is high compared to oxaloacetate, making alanine transamination more dominant. The production of serine and glycine by the hybridoma cell used in this study supports the above-mentioned metabolic pathway. Most of the amino acids were consumed for energy metabolism and generation of cell mass. Aminoacids such as leucine, isoleucine,lysine, and valine were utilized in the reactions which involve the conversion of a-ketoglutarate to glutamate. Amino acid metabolism for 167.4G5.3 cells was similar to that obtained by previous investigators (Table I). It should be pointed out that medium type also can influence the relative distribution of metabolic rates. For instance, when the 167.4G5.3 cell line used in RPMI-1640 medium, the glutamate production rate was higher and alanine production was lower (data not shown). The lack of pyruvate in RPMI-1640 medium apparently decreased the extent of the alanine transaminase reaction, yielding lower glutamate consumption and alanine production. The net glutamate production rate was higher, as glutamate was constantly produced from glutamine. 4.4. Energy Metabolism. Cells used glucose and glutamine for energy production. The ATP production rate obtained in this study, qATP = 0.844 pmo1/(lO6 celleh), is close to the value measured by Miller et al. (l987,1988a,b) for hybridoma cell line AB2-143.2 [QATP = 0.875 pmol/ (lo6 cells-h)]. About 80% of the glucose consumed was not utilized in the TCA cycle but was converted to lactate. Glycolysis accounted for about 45% of ATP production. Oxidative phosphorylation was a major contribution to ATP production as it provided about 55 % of the energy (Table 111). Glutamine enters the TCA cycle after being converted to glutamate and finally a-ketoglutarate (Figure 8). Transaminase and glutamate dehydrogenase reactions are indicative of the amount of a-ketoglutarate formed in the cells. Our data show that more than 80% of glutamine entered into the TCA cycle. The energy provided by the
TCA cycle or oxidative phosphorylation is thus glutamine derived, and glutamine is the major energy source for the hybridoma cell line used. The calculations showed that about 3.4 mol of NADH was produced/mol of glutamine utilized. If we assume that 3 mol of ATP is produced/mol of NADH, then ATP yield of glutamine is obtained to be 10 mol of ATP/glutamine. For comparison, a complete oxidation of glutamine to COz produces 21 mol of ATP. This result indicates that glutamine is not completely oxidized and it is possible that some glutamine was partially oxidized to give lactate. In our calculations of ATP production, we have neglected the lactate production from glutamine. However, our assumption is still valid, as the maximum amount of lactate produced from glutamine is very low. The total lactate production rate is 1 order of magnitude higher than total glutamine consumption. Hence, neglectingthe glutamine-derived lactate could introduce very little effect on our calculation. 4.5. Specific Antibody Productivity. Antibody production was not growth associated for the hybridoma cell line used in this study. Specific antibody production rate was constant in both exponential growth and decline phase. This non-growth-associated production rate was accompanied by the constant internal antibody content of the cells measured in flow cytometry. Our data show that the specific antibody production rate is relatively constant during the batchrun, and further, it is not affected by serum, oxygen concentration, and pH values higher than 7.2 (Ozturk and Palsson, 1991d). Only acidic pH (Ozturk and Palsson, 1991d) and high osmolarity (Ozturk and Palsson, 1991c) altered the specific antibody productivity for the 167.4G5.3 hybridoma cell line. Since antibody production is not growth associated in the cell line used, more antibody can be produced during batch cultivation by keeping the viable cell count high. Higher antibody concentrations can be achieved by decreasing the death rates in the decline phase as the cells still produce antibody at a constant rate.
Acknowledgment This work was supported by National Science Foundation Grant EET-8712756. We thank Dr. J. Latham Claflin for providing the hybridoma cell line used in this study. Literature Cited Adamson, S. R.; Behie, L. A.; Gaucher, G. M.; Lesser, B. H. Metabolism of Hybridoma Cells in Suspension Culture: Evaluation of Three Commercially Available Media. In Commercial Production of Monoclonal Antibodies: A Guide for Scale-up; Seaver, S. S., Ed.; Marcel Dekker, Inc.: New York, 1987. Ardawi, M. S. M.; Newsholme, E. A. Maximum Activitiesof Some Enzymes of Glycolysis, the Tricarboxylic Acid Cycle and Ketone-body and Glutamine Utilization Pathways of Lymphocytes of the Rat. Biochem. J. 1982,208, 743-748. Ardawi, M. S. M.; Newsholme, E. A. Glutamine Metabolism in Lymphoid Tissues. In Glutamine Metabolism in Mammalian Tissues;Haussinger, D., Sies, H., Eds.; Springer-Verlag: Berlin and Heidelberg, 1984; pp 235-246. Bailey, J. E.; Ollis, D. F. Biochemical Engineering Fundamentals, 2nd Ed.; McGraw-Hill: New York, 1986. Boraston, R.; Thompson, P. W.; Garland, S.; Birch, J. R. Growth and Oxygen Requirements of Antibody Producing Mouse Hybridoma Cells in Suspension Culture. Deu. Biol. Stand. 1984, 55, 103-111. Briles, D. E.; Forman, C.; Hudak, S.; Claflin, J. L. The Effects of Idiotype on the Ability of ZgGl anti-phosphorylcholine Antibodies to Protect Mice from Fatal Injection with Streptococcuspneumoniae. Eur. J . Zmmunol. 1984,14,1027-1030.
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Carlsson, R.; Glad, C. Monoclonal Antibodies into the '90s: The All Purpose Tool. BiolTechnology 1989, 7, 567-573. Dalili, M.; Ollis, D. F. Transient Kinetics of Hybridoma Growth and Monoclonal Antibody Production in Serum-Limited Cultures. Biotechnol. Bioeng. 1989, 33, 984-990. Dalili, M.; Sayles, G. D.; Ollis, D. F. Glutamine-Limited Batch Growth and Antibody Production: Experiment and Model. Biotechnol. Bioeng. 1990, 36, 74-82. Eigenbrodt, E.; Fister, P.; Reinacher, M. New Perspectives on Carbohydrate Metabolism in Tumor Cells. In Regulation of Carbohydrate Metabolism; Beitner, R., Ed.; CRC Press: Boca Raton, FL, 1985; Vol. 11, pp 141-179. Flickinger, M. C.; Goebel, N. K.; McNeil, D.; Bergold, A.; Bohn, M.; Karl, D. W. A Total Cell Recycling Reactor for Investigation of Hybridoma Maintenance Energy Demand and Monoclonal Antibody Modification. Paper presented a t the 194th National Meeting of the American Chemical Society, New Orleans, Aug. 30-Sept. 4, 1987. Glacken, M. W.; Fleischaker, R. J.; Sinskey, A. J. Reduction of Waste Product Excretion via Nutrient Control: Possible Strategies for Maximizing Product and Cell Yields on Serum in Cultures of Mammalian Cells. Biotechnol. Bioeng. 1986, 28, 1376-1389. Glacken, M. W.; Adema, E.; Sinskey, A. J. Mathematical Descriptions of Hybridoma Culture Kinetics: I. Initial Metabolic Rates. Biotechnol. Bioeng. 1988, 32, 491-506. Glacken, M. W.; Adema, E.; Sinskey, A. J. Mathematical Descriptions of Hybridoma Culture Kinetics: 11. The Relationship Between Thiol Chemistry and the Degradation of Serum Activity. Biotechnol. Bioeng. 1989, 33, 440-450. Green, B. S.; Tawfik, D. S. Catalytic Monoclonal Antibodies: Tailor-made Enzyme-like Catalysts for Chemical Reactions. Trends Biotechnol. 1989, 7, 304-310. Heath, C. A.; Dilwith, R.; Belfort, G. Methods for Increasing Antibody Production in Suspension and Entrapped Cell Cultures: Biochemical and Flow Cytometric Analysis as a Function of Serum Content. J. Biotechnol. 1989,15,71-89. Hu, W.-S.; Dodge, T. C.; Frame, K. K.; Nimes, V. B. Effect of Glucose on the Cultivation of Mammalian Cells. Dev. Biol. Stand. 1987, 66, 279-290. Low, K.; Harbour, C. Growth Kinetics of Hybridoma Cells: (1) The Effects of Varying Foetal Calf Serum Levels. Dev. Biol. Stand. 1985a, 60, 17-24. Low, K.; Harbour, C. Growth Kinetics of Hybridoma Cells: (2) The Effects of Varying Energy Source Concentrations. Dev. Biol. Stand. 1985b, 60,79-84. McKeehan, W. L. Glutaminolysis in Animal Cells. In Carbohydrate Metabolism in Cultured Cells; Morgan, M. J., Ed.; Plenum Press: New York, 1986; pp 111-150. Miller, W. M.; Blanch, H. W.; Wilke, C. R. The Effects of Dissolved Oxygen Concentration on Hybridoma Growth and Metabolism in Continuous Culture. J. Cell. Physiol. 1987, 132, 524-530. Miller, W. M.; Blanch, H. W.; Wilke, C. R. Transient Responses of Hybridoma Cells to Lactate and Ammonia Pulse and Step Changes in Continuous Culture. Bioprocess Eng. 1988a, 3, 113-122. Miller, W. M.; Blanch, H. W.; Wilke, C. R. Kinetic Analysis of Hybridoma Growth and Metabolism in Batch and Continuous Culture: Effect of Nutrient Concentrations, Dilution Rate, and pH. Biotechnol. Bioeng. 1988b,32, 947-965. Miller, W. M.; Wilke, C. R.; Blanch, H. W. Transient Responses of Hybridoma Cells to Changes in the Oxygen Supply Rate in a Continuous Culture. Bioprocess Eng. 1988c, 3, 103-112. Miller, W. M.; Blanch, H. W.; Wilke, C. R. Transient Responses of Hybridoma Cells to Nutrient Additions in Continuous Culture: 11. Glucose Pulse and Step Changes. Biotechnol. Bioeng. 1989a, 33, 477-486. Miller, W. M.; Blanch, H. W.; Wilke, C. R. Transient Responses of Hybridoma Cells to Nutrient Additions in Continuous Culture: 11. Glutamine Pulse and Step Changes. Biotechnol. Bioeng. 1989b,33, 487-499.
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Ozturk, S. S. Kinetic Characterization of Hybridoma Growth, Metabolism, and Monoclonal Antibody Production Rates. Ph.D. Thesis, University of Michigan, Ann Arbor, MI, 1990. Ozturk, S. S.; Palsson, B. 0. Chemical Decomposition of Glutamine: Effect of MediaType, pH, and Serum Concentration. Biotechnol. Prog. 1990a, 6, 121-128. Ozturk, S. S.; Palsson, B. 0. Effects of Initial Cell Density on Hybridoma Cell Growth, Metabolism, and Antibody Production Rates. J. Biotechnol. 1990b, 16, 259-278. Ozturk, S. S.;Palsson, B. 0.Loss of Antibody Production During Long-term Cultivation of a Hybridoma Cell Line in Low-serum and Serum-free Media. Hybridoma 199Oc, 9, 167-175. Ozturk, S. S.; Palsson, B. 0. Physiological Changes During the Adaptation of Hybridoma Cells to Low Serum and Serumfree Medium. Biotechnol. Bioeng. 1991a, 37, 35-46. Ozturk, S. S.; Palsson, B. 0. Examination of Serum and Bovine Serum Albumin as Shear Protective Agents in Agitated Cultures of Hybridoma Cells. J. Biotechnol. 1991b, 18, 1328. Ozturk, S. S.; Palsson, B. 0. Effects of Osmolarity on Hybridoma Cell Growth, Metabolism, and Antibody Production Rates. Biotechnol. Bioeng. 1991c, 37, 989-993. Ozturk, S. S.; Palsson, B. 0. Growth, Metabolic, and Antibody Production Kinetics of Hybridoma Cell Culture: 2. Effects of Serum Concentration, Dissolved Oxygen, and Medium pH. Biotechnol. Prog. 1991d, following paper in this issue. Ozturk, S. S.; Meyerhoff, M. E.; Palsson, B. 0. Measurement of Ammonia and Glutamine in Cell Culture Media by Gas Sensing Electrodes. Biotechnol. Tech. 1989, 3, 217-222. Ozturk, S. S.; Riley, M. R.; Palsson, B. 0. Effects of Ammonia and Lactate on Hybridoma Cell Growth, Metabolism, and Antibody ProductionRates. BiotechnoL Bioeng. 1991,in press. Pirt, S. J. Principles of Microbe and Cell Cultivation; Blackwell Scientific Publications, Cambridge, England. Reitzer, L. J.;Wice, B. M.; Kennell, D. Evidence that glutamine, not sugar, is the major energy source for cultured HeLa cells. J. Biol. Chem. 1979,254,2669-2674. Renard, J. M.; Spagnoli, R.; Mazier, C.; Salley, M. F.; Mandine, E. Evidence That Monoclonal Antibody Production Kinetics is Related to the Integral of Viable Cells Curve in Batch Systems. Biotechnol. Lett. 1988, 10, 91-96. Reuveny, S.; Velez, D.; Macmillan, J. D.; Miller, L. Factors Affecting Monoclonal Antibody Production in Culture. Dev. Biol. Stand. 1987, 66, 169-175. Sen, S.; Srienc, F.; Hu, W.-S. Flow Cytometric Analysis of Hybridoma Batch Culture. Paper presented a t the 194th National Meeting of the American Chemical Society, New Orleans, LA, 1987. Smithson, L. H. Biotechnology: Now and soon. CHEMTECH 1988,6, 168-173. Spier, R. Animal Cells in Culture: Moving into the Exponential Phase. Trends Biotechnol. 1988, 6, 2-6. Truskey, G. A.; Nicolakis, D. P.; Dimasi, D.; Haberman, A.; Swartz, R. W. Kinetic Studies and Unstructured Models of Lymphocyte Metabolism in Fed-Batch Culture. Biotechnol. Bioeng. 1990,36, 797-807. Velez, D.; Reuveny, S.; Miller, L.; Macmillan, J. D. Kinetics of Monoclonal Antibody Production in Low Serum Growth Medium. J . Immunol. Methods 1986,86, 45-52. Vosper, N. New technology for large scale mammalian cell culture. Biomed. Prod. 1989, 14, 86-92. Zielke, H. R.; Sumbilla, C. M.; Sevdalian, D. A.; Hawkins, R. L.; Ozand, P. T. Lactate: A Major Product of Glutamine Metabolism by Human Diploid Fibroblasts. J . Cell Physiol. 1980,104,433-441. Zielke, H. R.; Zielke, C. L.; Ozand, P. T. Glutamine: a Major Energy Source for Cultured Mammalian Cells. Fed. Proc. 1984, 43, 121-125. Accepted September 30, 1991. Registry No. Glucose, 50-99-7; glutamine, 56-85-9.
