Vol. 57, No. 4APPLIED AND ENVIRONMENTAL MICROBIOLOGY, Apr. 1991, p. 918-9230099-2240/91/040918-06$02.0I00Copyright © 1991, American Society for Microbiology

Glucose-Stat, a Glucose-Controlled Continuous CultureGARY L. KLEMAN,1 JEFFREY J. CHALMERS,2 GREGORY W. LULI,'t AND WILLIAM R. STROHLl*Departments of Microbiology1 and Chemical Engineering,2 The Ohio State University, Columbus, Ohio 43210

Received 21 September 1990/Accepted 18 January 1991

A predictive and feedback proportional control algorithm, developed for fed-batch fermentations anddescribed in a companion paper (G. L. Kleman, J. J. Chalmers, G. W. Luli, and W. R. Strohl, Appl. Environ.Microbiol. 57:910-917, 1991), was used in this work to control a continuous culture on the basis of thesoluble-glucose concentration (called the glucose-stat). This glucose-controlled continuous-culture system wasfound to reach and maintain steady state for 11 to 24 residence times when four different background glucoseconcentrations (0.27, 0.50, 0.7, and 1.5 g/liter) were used. The predictive-plus-feedback control system yieldedvery tight control of the continuous nutristat cultures; glucose concentrations were maintained at the set pointswith less than 0.003 standard error. Acetate production by Escherichia coli B in glucose-stats was found not tobe correlated with the level of steady-state soluble-glucose concentration.

Several different types of continuous-culture fermentationprocedures have been developed over the years to studyvarious aspects of the metabolism of microorganisms. Themore popular of these include the chemostat, based onnutrient limitation (1); the turbidostat, in which the nutrientfeed is feedback controlled on the basis of culture turbidity(4); the pH auxostat, in which nutrient feed is based onfeedback control from a pH measurement (21); and thenutristat (19), in which the nutrient feed is based on feedbackcontrol of a nutrient concentration. Chemostats have beenused widely to study bacterial metabolism, population ge-netics, and plasmid stability, mostly because these are thesimplest and most easily constructed types of continuouscultures. Nutristats (19), of which one type is also called anauxostat (4), have been limited in use, largely because of thelack of sterilizable probes for the accurate, on-line measure-ment of substrate concentration. In 1984, Agrawal and Lim(1) noted that successful nutristats using direct control,although theorized, had not been reported. Since then, onlya few attempts have been made to run nutristats (4, 10, 15,27), although none of these efforts directly controlled glu-cose concentration. In this communication, we describe indetail the development and use of a "glucose-stat," anutristat that is controlled by using a combined predictiveand feedback control system based on the soluble-glucoseconcentration in the vessel. In this continuous-culture sys-tem, the glucose concentration is maintained at a predeter-mined set point. The glucose consumption rate of the grow-ing organism was found to dictate the dilution rate and,hence, the growth rate in the bioreactor. We found that thepredictive-plus-feedback control method was more success-ful than proportional control algorithms in maintaining glu-cose at the desired set point in continuous cultures (datapresented here) as well as in fed-batch cultures (9).

MATERIALS AND METHODS

Bacterial culture and maintenance. Escherichia coli B wasobtained from the Ohio State University Culture Collection(OSU 333) and was maintained as slant cultures at 4°Cbetween experiments. To begin an experiment, E. coli was

* Corresponding author.t Present address: Microlife Technics, Inc., Sarasota, FL 34230.

grown on Trypticase soy agar (2% agar) plates for 24 h at37°C. Seed cultures were started by loop inoculation of acolony from the plates into 50 ml of Trypticase soy broth andincubated for 12 h at 37°C at 150 rpm in a rotary shaker.

Glucose-stat medium. The defined medium described byPan et al. (20) for their chemostat work was modified slightlyfor the base medium for this study. This medium contained(in grams per liter) the following: KH2PO4, 0.75;K2HPO4 3H20, 0.98; NaH2PO4- H2O, 0.72; (NH4)2SO4,3.0; (NH4)Cl, 0.02; and MgSO4 7H20, 0.55. Trace ele-ments were present at 0.2 ml liter-'. The trace elementssolution, modified from those described by Pan et al. (20),contained (in grams per liter of 5 M HCl) the following:FeSO4 7H20, 40; MnSO4. H20, 10; AlSO4. 18H20,28.25; CoCl2 6H2O, 4; ZnSO4 7H20, 2; NaMoO4 2H20,2; CuCl2. 2H20, 1; and H3BO4, 0.5. The KH2PO4,K2HPO4 3H20, NaH2PO4 H20, (NH4)2SO4, and (NH4)Clwere combined and autoclaved in 17.8 liters of distilledwater in a 20-liter carboy. The pH was adjusted to 6.9 with5 M NaOH before the mixture was autoclaved. One liter wasremoved and placed in the fermentor. The glucose,MgSO4 7H20, and trace elements were combined in 200 mlof distilled water and added aseptically to the other compo-nents after cooling. In order to make the biomass equivalentat different background glucose concentrations, the glucoseconcentration in the feed solution was made to the desiredset point concentration plus an additional 3.0 g of glucose perliter (e.g., for set points of 0.27, 0.50, 0.70, and 1.5 g ofglucose per liter, the feed solution had concentrations of3.27, 3.5, 3.7, and 4.5 g of glucose per liter, respectively).

Fermentation hardware and procedures. The basic hard-ware and design of the glucose-stat are shown in Fig. 1. Thecontinuous cultures were carried out using a Virtis 2-literOmni Culture bench-top fermentor with a working volume of1.2 liters. The temperature was maintained at 37°C bycirculating water through internal baffles of the fermentor bymeans of a Lauda RM6 circulating water bath. An Apple Ilecomputer equipped with a Cyborg ISAAC 91A data acqui-sition system was used for computer control as describedelsewhere (25, 29).

Agitation was held constant at 650 rpm, and the air flowwas controlled at 2.4 liters min-' (2 vol of air per vol ofmedium) by a Tylan model R020A air controller. The pH wascontrolled at 7.0 + 0.1 by the addition of a 1.0 M NH40Hsolution with a Horizon model 5997-20 (Horizon Ecology

918

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from

GLUCOSE-STAT 919

Apple lie Computer

FIG. 1. Set up of the glucose-stat. Abbreviations: V, volume (1.2 liter); x, biomass (grams per liter); Sv, glucose concentration in the vessel(grams per liter); Fi, flow rate into the vessel (liters per minute); F., flow rate out of the vessel (liters per minute). The feed pump is drivenby a 4- to 20-mA signal generated by the computer and ISAAC data acquisition device.

Co., Chicago, Ill.) pH controller with a Fisher gel-filled pHprobe. The probe was sterilized with a diluted Cloroxsolution and rinsed with sterile distilled water before beinginserted into the vessel.The on-line glucose analysis system described by Luli et

al. (12) was used with the modifications detailed in theaccompanying paper (9). A concentration of 2.00 g of glu-cose per liter was used for standardization of the on-linesystem for all continuous fermentations run.The feed solution was added by a Cole-Parmer peristaltic

pump (model 7534-30) equipped with a model 7013 pumphead. The computer-ISAAC system controlled the pumpspeed by using a 4- to 20-mA RCA plug. The pump wascalibrated before each run by pumping the feed into a sterile1-liter Erlenmeyer flask placed on a Mettler PJ6000 balance.The change of weight over time determined the flow rate foreach setting. A linear regression was performed on thecalibrations to obtain a slope and intercept for the feed rate,and this information was given to the computer to determinethe needed electrical output for the calculated feed rate. Thepump was calibrated again after the run was over to deter-mine if any changes had occurred during the run because oftube wear; no significant differences were found (data notshown).

Control scheme. Control of the glucose-stat was based on

the principle that all nutrients, being added with a single feedsolution, were in slight excess in relation to the concentra-tion of glucose. The computer algorithm used to control theglucose-stat is described in a companion paper (9). Thiscontrol scheme is based on feedback proportional controlaround a moving (predictive control) set point. For controlof the glucose-stat at the desired set point, the computercalculates a predicted glucose demand based on a linearregression of the last 10 calculated values for the rate ofglucose consumption. When the culture is at steady state,the glucose demand is a constant value.

Culture analyses. Cell growth was monitored by measuringculture turbidity (Klett-Summerson colorimeter) and dry cellweight as described previously (9). Off-line glucose concen-trations were determined by using a YSI model 2000 glucoseanalyzer, and acetate concentrations in the culture brothwere determined by high-pressure liquid chromatography asdescribed by Luli and Strohl (13).

RESULTS AND DISCUSSION

Construction of glucose-stat and algorithm governing glu-cose concentration. In early experiments, proportional con-trol algorithms were used to maintain the soluble-glucoseconcentration at the desired set point, but without much

VOL. 57, 1991

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from

APPL. ENVIRON. MICROBIOL.

TABLE 1. Summary of data obtained from steady-state glucose-stat fermentations of E. coli B

Results in fermentation:Parameter Avg

A B C D

Soluble-glucose concn (g liter-')' 0.27 + 0.01" 0.49 ± 0.01 0.70 ± 0.02 1.5 ± 0.03Dilution rate (1/h)" 0.81 ± 0.10 0.89 ± 0.07 0.90 ± 0.13 0.84 ± 0.12 0.86 + 0.04Residence time (h) 1.23 1.12 1.11 1.19 1.16 ± 0.05No. of residence times in steady state' 11 24 11 12Dry cell wt (g- liter-')' 0.98 ± 0.03 0.99 + 0.05 0.85 + 0.02 0.80 ± 0.03 0.91 ± 0.09SGCRe 2.8 2.8 3.2 2.8 2.9 ± 0.2Cell yield (g/g)f 0.29 0.32 0.28 0.30 0.30 ± 0.02Soluble-acetate concn (g liter-Y) 0.28 ± 0.02 0.45 ± 0.04 0.28 + 0.03 0.26 ± 0.02 0.32 ± 0.08

c Based on more than 100 measurements made automatically by the computer.b Average ± 1 standard deviation from the average.'Starting from five residence times after continuous culture began. All of the cultures were stopped for reasons other than loss of steady state.d Based on a minimum of eight measurements.eIn grams of glucose consumed per grams of DCW per hour. A minimum of 100 calculations were made to obtain the values given.f Calculated as described in equation 7.g Based on a minimum of three measurements during steady state.

success. When proportional control algorithms were used, acertain amount of drift was observed in the feed rate, whichcaused either starvation of the culture or an accumulation ofglucose and other nutrients. Thus, when the predictive-plus-feedback proportional control algorithm was developed forthe fed-batch fermentations (9), we decided to try thismethod for controlling the glucose-stat.The glucose concentration was maintained at the set point

by a combination of predictive control and feedback controlas described in the companion paper (9). A linear regressionwas run on the previous 10 calculated glucose demandpoints, rather than 5, which was the optimal number used infed-batch cultures (9). When the culture attains steady state,the slope of the linear regression should become zero, withthe intercept equal to the glucose demand. Ten datum points(20 min total time) was found to be the maximum number forstable control while still allowing enough freedom for thescheme to adjust to potential changes in glucose consump-tion rates. When only the previous five glucose demandcalculations were used to control the glucose-stat, the fluc-tuation in dilution rates was considerably greater (data notshown). Under the conditions reported in this paper, theglucose concentration was maintained at the set point withless than a 0.003 standard error (e.g., 0.27 + 0.01, 0.49 ±0.01, 0.70 ± 0.02, and 1.5 + 0.03 g. liter-'; Table 1) duringsteady-state growth. Although there was some fluctuation ofdilution rates during these experiments, turbidity (data notshown) and biomass measurements revealed that the cul-tures were in steady state for over 10 residence times (Table1) and in some cases for up to 24 residence times (Fig. 2).Equations governing the glucose-stat. Figure 1 shows the

generalized setup of the glucose-stat used in these experi-ments. The equation governing the accumulation of biomassin the glucose-stat is the same as that used for the chemostat(31):

dxldt = (F,/V) * X-(F0/V) X + p.X-cxX (1)

where dx/dt equals the accumulation of biomass (in gramsper liter) with time, F1 and F, are the flow rates (in liters perhour) into and out of the vessel, respectively; V is volume (inliters); [L is the specific growth rate (per hour); cx is the deathrate (per hour); and X is the biomass (i.e., dry cell weight).With a sterile feed, (F1/V) would equal 0, thus dropping outof the equation. Since F/V equals the dilution rate (D [perhour]) and since the growth rate (p.) is usually orders of

-i -.-j

Cm?- 1.5--4-

:- 1.0-

>.< 0.5-o

a)

cc-C,o t

.2

2.0-

1.0

c 0.5-E^O E 0.1-Q) 1--8 Cm005-

s

a)U)0C.)

1.5

1.0-

Q5-tKc changed

10 20 30Time (hours)

40 50

FIG. 2. Glucose-stat of E. coli B grown at a controlled constantsoluble-glucose concentration of 0.50 g. liter-1 (fermentation B ofTable 1). The period of steady-state growth and the residence times(each equaling 1.12 h) are indicated in panel A. (A) Dry weight of (-)and acetate produced by (A) E. coli B versus time of fermentation.(B) Dilution rate of glucose-stat versus time based on the flow rate(liters per hour) of the nutrient solution. (C) Glucose demand of theculture as a function of time. (D) Concentration of soluble glucose inglucose-stat versus time of fermentation. The continuous flow wasstarted after 5 h, with an initial Kc setting of 0.5. At the point markedKc changed, the gain setting was lowered to 0.2 to decrease thefluctuation in the glucose concentration.

A

.10

C

I.I?=qm 17%m.,rn:JpJ~*72

D

Steady StateContinuousFlow Begun

W.&-- -2.&..am -0 N Ab-*Wjpwo-,Wwlor --- -0 -Z-74, -

920 KLEMAN ET AL.

00

0 0 0 0 00 90 * 0 06

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from

GLUCOSE-STAT 921

magnitude greater than the death rate (oa), this equation canbe rearranged as follows (31):

dxldt = X(>L - D) (2)

At steady state, dxldt equals 0, so ,u and D must be equal, asshown in equation 2. The substrate balance would be de-scribed by the following equation:

dSvIdt = FIV(Sf) - FIV(Sj) - (>XIY) (3)

where Sf and Sv are the glucose concentrations in the feedand vessel, respectively; Y is the cell yield (in grams [DCW]per gram of glucose consumed). By substituting D (per hour)for FIV and assuming steady-state growth where dSvldtwould equal 0, then

0= D(Sf-SV) - 1iXIY (4)

Also, at steady state, from equation 2, where p. = D, therelationship would be described as

X' = Y(Sf - SO) (5)

where X' equals the steady-state cell concentration (in gramsper liter) and Sv, is the steady-state glucose concentration (ingrams per liter) for the vessel. For the reactor, the hourlyglucose demand (GD') is

GD' = ,uX/Y (6)

expressed in grams of glucose consumed per liter per hour.To obtain the specific glucose consumption rate (SGCR),equation 6 is divided by the steady-state biomass concentra-tion, X' (g [DCW]Iliter), to get

SGCR = ,u/Y (7)

which would be expressed in grams of glucose consumed pergram ofDCW per hour. Therefore, SGCR divided by D (= p.)gives 1IY.

Parameters of culture growth in glucose-stats. Figure 2shows the results of a steady-state glucose-stat fermentationin which the residual glucose concentration was set to becontrolled at a set point of 0.50 g liter-'; the actual(measured) glucose concentration at steady state (from 21 to58 h; 24 residence times) averaged 0.49 + 0.01 g of glucoseper liter (Table 1, fermentation B). D, and hence also pu, ofthe E. coli B culture at this set point was 0.89 + 0.07 h-(generation time, 47 min). This growth rate correspondedfavorably with the initial growth rate (0.90 h-1) of E. coli Bgrown in glucose-controlled fed-batch cultures at 37°C (9),even though the glucose-stats were carried out using adefined medium. This glucose-stat was in steady state for 23residence times, during which time the culture turbidity (notshown), biomass, dilution rate, glucose demand, and solubleacetate were constant (Fig. 2).To calculate the SGCR of the culture, equation 7 is

rewritten as follows:

SGCR = [(Sf - SvIX] D (8)

where Sf is the glucose concentration (in grams per liter) inthe feed medium, Sv is the glucose concentration (in gramsper liter) in the vessel, X is biomass (i.e., DCW [in grams perliter]), and D is dilution rate (1/h). The specific glucoseconsumption rate at a residual glucose concentration of 0.49g. liter-' was found to be 2.8 g of glucose consumed per g ofDCW. h. This value is ca. 35% higher than glucose con-sumption rates obtained with comparably run fed-batchcultures (i.e., at 37°C) (9). This was expected because theglucose-stat fermentations contain defined medium, whereas

the fed-batch cultures also contained casein hydrolysate (9).The SGCR of the E. coli B glucose-stat cultures (averaging2.9 g of glucose consumed per g of DCW h, which equals16.1 mmollg of DCW- h) is also considerably higher than theSGCR values reported for chemostat-grown E. coli (ca. 1.25to 9.12 mmol of glucose consumed per g of DCW - h) byTempest and Neijssel (28). Tempest and Neijssel (28), how-ever, showed that the SGCR increased linearly with dilutionrate. The glucose-stat-grown E. coli cultures were growing atRmax, so the values we obtained likely represent the maximalSGCR of which E. coli B is capable.Table 1 compares the results obtained with steady-state

glucose-stat fermentations run at 0.25 (actual, 0.27 + 0.01),0.50 (actual, 0.49 + 0.01), 0.70 (actual, 0.70 + 0.02), and 1.5(actual, 1.5 + 0.03) g of residual glucose per liter. Fermen-tations A, C, and D were continued for ca. 11 residencetimes after steady state had been achieved; in each case, thecultures were ended because of depletion of medium ratherthan loss of steady state. Fermentation B (Fig. 2) was carriedout for 24 residence times (ca. 35 generations) after steadystate had been achieved to demonstrate the long-term sta-bility of the glucose-stat.We had discovered in preliminary experiments that the

concentration of glucose in the feed dictated the cell biomassin the fermentors at steady state, which is borne out byequation 5. In each of these fermentations, we chose to havebiomass remain constant (see Materials and Methods forprotocol), and the data reflect this, with an average of 0.91 +

0.09 g of DCW per liter (Table 1). Under the conditions usedin this study (e.g., when the Sf was set so that a constant X'would be obtained), the values for D (0.86 + 0.04 h-1), P'max(=D), SGCR (2.9 + 0.2 g of glucose per g ofDCW h), yield(0.30 + 0.02 g of DCW per g of glucose utilized), and acetateproduced (0.27 + 0.01 g of acetate produced per liter) weresimilar, independent of the set point concentration of glu-cose (Table 1). Thus, whether S, was 0.27 or 1.5 g. liter-',the cells appeared to be in approximately the same physio-logical states.

Acetate production in glucose-stats. It is now known that acombination of high specific growth rate and the presence ofexcess glucose substrate causes the bacterial Crabtree ef-fect, in which the substrate is converted to oxidized organicacids such as acetate (13). There appears to be a linkbetween the accumulation of acetate caused by the bacterialCrabtree effect and decreased growth rate and final cellconcentration (13, 20), and acetate accumulation has beenshown to decrease the formation of recombinant DNAproducts (2, 7, 14, 17). Therefore, the ability to study theresponse of E. coli to given glucose concentrations understeady-state conditions, such as are found in the glucose-stat, may lead to important discoveries about the metabolismof cultures in response to glucose.Meyer et al. (18) reported that chemostat cultures of E.

coli K-12 Dl produced increasing concentrations of acetatein direct proportion to the dilution rate. At the highestdilution rate they used, just slightly lower than D, (criticaldilution rate; 0.56 h-1), they found that E. coli producednearly 0.45 g of acetate per liter. Similarly, Doelle et al. (3,5) suggested that both rapid growth and high glucose levelscontributed to the bacterial Crabtree effect. Using tur-bidostat cultures at constant biomass, Doelle et al. (3) foundthat switchover from normal coupled respiration to thebacterial Crabtree effect occurred at 1.5 to 2 g of glucose perliter. In the glucose-stat cultures, on the other hand, E. coliB achieved an average dry weight of 0.91 + 0.9 g liter-',with a growth rate of 0.86 + 0.04 h-1, and produced 0.32 +

VOL. 57, 1991

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from

APPL. ENVIRON. MICROBIOL.

TABLE 2. Comparison of glucose-stat with chemostats"

Parameter Chemostat Glucose-stat

Dilution rate (D) Calculated from F/V Calculated from F/VFlow rate (liters/h) Set by operator Dependent on SGCRGlucose consumption rate Depends on D and Sf Depends on cell requirement aloneSoluble concn of limiting nutrient (Sj) Essentially O* Controlled at a set point >0Biomass concn Depends on Sf onlyb Depends on difference between [S,] and [Sf]Operation at PL..ax Unstable Normal, stable operation

" Abbreviations and definitions: F, flow rate; V, volume of glucose-stat (in liters); glucose consumption rate, grams glucose consumed per liter per hour;S,, glucose concentration (in grams per liter) in the vessel; Sf, glucose concentration (in grams per liter) in the feed.b As interpreted from Wang et al. (31).

0.08 g of acetate per liter in the presence of differentbackground glucose concentrations (Table 1). Thus, theresults of our glucose-stat runs appear to conflict with theresults of Doelle et al. (3). This is probably because theCrabtree effect is apparently much more pronounced underconditions in which yeast extract is present, as it was in theturbidostat cultures of Doelle et al. (3) and is usually also infed-batch cultures (9, 13). Brown et al. (2) and Luli (11) haveshown that the production of acetate by E. coli is greater inmedia containing rich nutrients (e.g., yeast extract or cornsteep liquor) than in defined media. Moreover, the concen-tration of cells in fed-batch cultures is much higher than inglucose-stat cultures. Therefore, the low production of ace-tate in the glucose-stats, which were run using definedmedium, compared with production in fed-batch culturesgrown in glucose plus casein hydrolysate medium (9) is notsurprising. Also, the E. coli B cultures grown in the glucose-stat would be growing at P'max values ranging from 0.81 to0.90 h-1 (Table 2), which suggests that E. coli B producesless acetate in response to glucose and growth rate than E.coli K-12 strains (18) do. We also observed this phenomenonin batch and fed-batch cultures (13).

Glucose-stat versus other types of continuous cultures.Continuous cultures are valuable tools for studying, understeady-state conditions, the effect of growth parameters onbacterial metabolism. Examples include the effects of carbonversus nitrogen substrate limitations or the effects of variousgrowth rates on enzyme specific activities, stability of plas-mids, production of primary or secondary metabolites, andso forth. The chemostat, in which one nutrient is limiting andthe dilution rate is predetermined (Table 2), is the mostwidely used type of continuous fermentation. Two signifi-cant limitations to the use of chemostats, however, mayinfluence results under given circumstances: (i) growth near[Lmax is unstable, and (ii) the organisms are essentiallystarved for the limiting nutrient, which can be seen in theiruptake kinetics and cell membrane protein composition (30).Also, nutrient limitation in chemostats can lead to resultsthat may not reflect optimal growth conditions for theorganism. For example, a stringent strain of E. coli overgrewand displaced a relaxed strain in a carbon- and energy-limited chemostat, indicating that chemostat-grown E. coli isunder stringent response conditions (22). This suggests thata chemostat-grown E. coli culture is responding to a starva-tion-induced "survival mode" rather than to optimal cultureconditions. Because of these two limitations, researchershave developed various feedback-controlled fermentationsin which nutrient feed rates are based on the measurement ofculture parameters rather than being preset. Under feedbackcontrol, the continuous cultures can operate stably at theP'max of the organism (Table 2). A simple example of afeedback-controlled continuous culture is the turbidostat, in

which the nutrient feed rate is based on the turbidity (opticaldensity) of the culture (1). The rate of nutrient addition iscontrolled to maintain a constant optical density (cell mass),and because there is no apparent limiting nutrient, theorganisms grow at P'max-

Auxostats are feedback continuous cultures in which thenutrient feed rate is based on the control of a particulargrowth-associated parameter (e.g., pH [21, 24], dissolved 02[32], Eh [6], H2S [23], NH3 [10, 27], ethanol production [8],CO2 production [16], or specific ions [4]) around a set point.Auxostats, however, which regulate substrate feed indi-rectly, are subject to physical and chemical variances in themedium which somewhat limit their usefulness (4).

Nutristats, on the other hand, are feedback-controlledcontinuous cultures in which control is based directly on thecontrol of residual substrate (1, 4, 10, 19, 26, 27) (Table 2). Amajor advantage to nutristats is that one can determine theeffects of different nonlimiting substrate concentrations onthe metabolism of an organism. There have only been a fewapplications of nutristat (10, 15, 19, 27), however, probablybecause of the limited availability of sterilizable on-lineprobes which can measure substrate concentration (1, 4) andthe inability to maintain a constant substrate concentration(1). Fraleigh et al. (4) discussed the difficulty in constructinga properly tuned controller which can handle changes indifferent parameters, e.g., set point or media. In preliminaryexperiments, we found that a proportional controller was notsufficient to control the nutristat. Our system, however,which utilizes a predictive control algorithm (9) and isfine-tuned by a feedback control utilizing a proportionalgain, was found to maintain glucose at the set point within a0.003 standard error for 11 to 24 residence times. Thus, thepredictive controller appears to be an optimal control mech-anism for nutristat cultures. Our algorithm would also workto control other substrate concentrations that are measura-ble by systems similar to ours, such as lactate, ethanol, andsucrose. Moreover, this predictive control algorithm alsoshould work well to control nutristats in which the substrateconcentrations are determined by high-pressure liquid chro-matography, quadrupole mass spectrometers, and otherdevices.There are many possible uses of a glucose-stat and other

predictive-controlled nutristats. These types of cultures mayprove invaluable in the study of stability of product forma-tion and plasmids in recombinant continuous cultures. Un-der glucose-stat conditions, the organisms are growing atImax but are relieved from the glucose-limited (i.e., starved)conditions found in chemostats. Moreover, glucose metab-olism by organisms growing in steady-state environments inwhich background glucose can be controlled at variousconcentrations may provide insight into the regulation ofglucose assimilation and catabolism.

922 KLEMAN ET AL.

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from

GLUCOSE-STAT 923

ACKNOWLEDGMENTS

This work was partially funded by a grant from YSI, Inc., YellowSprings, Ohio.We thank Don Ordaz for his technical assistance during these

investigations.

REFERENCES1. Agrawal, P., and H. C. Lim. 1984. Analyses of various control

schemes for continuous bioreactors, p. 61-90. In A. Fiechter(ed.), Advances in biochemical engineering/biotechnology.Springer-Verlag, Berlin.

2. Brown, S. W., H.-P. Meyer, and A. Fiechter. 1985. Continuousproduction of human leukocyte interferon with Escherichia coliand continuous cell lysis in a two stage chemostat. AppI.Microbiol. Biotechnol. 23:5-9.

3. Doelle, H. W., N. W. Hollywood, and A. W. Westwood. 1974.Effect of glucose concentration on a number of enzymes in-volved in the aerobic and anaerobic utilization of glucose inturbidostat-cultures of Escherichia coli. Microbios 9:221-232.

4. Fraleigh, S. P., H. R. Bungay, and L. S. Clesceri. 1989. Contin-uous culture, feedback control and auxostats. Trends Biotech-nol. 7:159-164.

5. Hollywood, N., and H. W. Doelle. 1976. Effect of specific growthrate and glucose concentration on growth and glucose metabo-lism of Escherichia coli K-12. Microbios 17:23-33.

6. Jee, H. S., T. Mano, N. Nishio, and S. Nagai. 1988. Influence ofredox potential on methanation of methanol by Methanosarcinabarkeri in Eh-stat batch cultures. J. Ferment. Technol. 66:123-126.

7. Jensen, E. B., and S. Carlsen. 1990. Production of recombinanthuman growth hormone in Escherichia coli: expression ofdifferent precursors and physiological effects of glucose, ace-

tate, and salts. Biotechnol. Bioeng. 36:1-11.8. Karim, M. N., and G. Traugh. 1987. Data acquisition and

control of a continuous fermentation unit. J. Ind. Microbiol.2:305-317.

9. Kleman, G. L., J. J. Chalmers, G. W. Luli, and W. R. Strohl.1991. A predictive and feedback control algorithm maintains a

constant glucose concentration in fed-batch fermentations.Appl. Environ. Microbiol. 57:910-917.

10. Kole, M. M., D. Ward, and D. F. Gerson. 1986. Simultaneouscontrol of ammonium and glucose concentrations in Escherichiacoli fermentations. J. Ferment. Technol. 64:233-238.

11. Luli, G. W. 1988. Ph.D. dissertation. The Ohio State Univer-sity, Columbus.

12. Luli, G. W., S. M. Schlasner, D. Ordaz, M. Mason, and W. R.Strohl. 1987. An automatic, on-line glucose analyzer for feed-back control of fed-batch growth of Escherichia coli. Biotech-nol. Tech. 1:225-230.

13. Luli, G. W., and W. R. Strohl. 1990. Comparison of growth,acetate production, and acetate inhibition of Escherichia colistrains in batch and fed-batch fermentations. Appl. Environ.Microbiol. 56:1004-1011.

14. MacDonald, H. L., and J. 0. Neway. 1990. Effects of mediumquality on the expression of human interleukin-2 at high celldensity in fermentor cultures of Escherichia coli K-12. Appl.Environ. Microbiol. 56:640-645.

15. Meschke, J., H. Bennemann, H. Herbst, S. Dormeier, and D. C.Hempel. 1988. On-line HPLC-measurement and control of sub-strate in a continuously operated biological tank reactor. Bio-

process Eng. 3:151-157.16. Meyer, C., and W. Beyeler. 1984. Control strategies for contin-

uous bioprocesses based on biological activities. Biotechnol.Bioeng. 26:916-925.

17. Meyer, H.-P., H.-J. Kuhn, S. W. Brown, and A. Fiechter. 1984.Production of human leukocyte interferon by Escherichia coli,p. 499-505. In Proceedings of the Third European Congress onBiotechnology, vol. 1. Verlag Chemie GmbH, Weinheim, Ger-many.

18. Meyer, H.-P., C. Leist, and A. Fiechter. 1984. Acetate formationin continuous culture of Escherichia coli K12 Dl on defined andcomplex media. J. Biotechnol. 1:355-358.

19. Mori, H., T. Yamane, T. Kobayashi, and S. Shimizu. 1983. Newcontrol strategies for continuous cultures based upon a micro-computer-aided nutristat. J. Ferment. Technol. 61:305-314.

20. Pan, J. G., J. S. Rhee, and J. M. Lebeault. 1987. Physiologicalconstraints in increasing biomass concentration of Escherichiacoli B in fed-batch culture. Biotechnol. Lett. 9:89-94.

21. Rice, C. W., and W. P. Hemphling. 1985. Nutrient-limitedcontinuous culture in a phauxostat. Biotechnol. Bioeng. 27:187-191.

22. Riesenberg, D., and F. Bergter. 1984. Mixed culture kinetics ofstringent and relaxed Escherichia coli cells in glucose-limitedchemostat. Z. Allg. Mikrobiol. 24:113-117.

23. Rogerson, A. C. 1980. Nitrogen-fixing growth by nonheterocys-tous cyanobacterium Plectonema boryanum. Nature (London)284:563-564.

24. Sowers, K. R., M. J. Nelson, and J. G. Ferry. 1984. Growth ofacetotrophic, methane-producing bacteria in a pH auxostat.Curr. Microbiol. 11:227-230.

25. Strohl, W. R., P. L. Lorensen, and S. M. Schlasner. 1986.Microcomputer-control of fermentation processes. Biotech-niques 4:336-343.

26. Suzuki, T., T. Yamane, and S. Shimizu. 1986. Mass productionof poly-f3-hydroxybutyric acid by fed-batch culture with con-trolled carbon/nitrogen feeding. Appl. Microbiol. Biotechnol.24:370-374.

27. Suzuki, T., T. Yasuda, T. Yamane, and S. Shimizu. 1986.Detection and automatic control of ammonium ion concentra-tion in microbial culture with an ammonium ion selectiveelectrode. J. Ferment. Technol. 64:63-70.

28. Tempest, D. W., and 0. M. Neijssel. 1987. Growth and energydistribution, p. 797-806. In F. C. Neidhardt, J. L. Ingraham,K. B. Low, B. Magasanik, M. Schaechter, and H. E. Umbarger(ed.), Escherichia coli and Salmonella typhimurium: cellularand molecular biology, vol. 1. American Society for Microbiol-ogy, Washington, D.C.

29. Titus, J. A., G. W. Luli, M. L. Dekleva, and W. R. Strohl. 1984.Application of a microcomputer-based system to control andmonitor bacterial growth. Appl. Environ. Microbiol. 47:239-244.

30. Villarejo, M., J. Stanovich, K. Young, and G. Edin. 1978.Differences in membrane proteins, cyclic AMP levels, andglucose transport between batch and chemostat cultures ofEscherichia coli. Curr. Microbiol. 1:345-348.

31. Wang, D. I. C., C. L. Cooney, A. L. Demain, P. Dunnill, A. E.Humphrey, and M. D. Lilly. 1979. Fermentation and enzymetechnology. John Wiley & Sons, Inc., New York.

32. Yano, T., T. Kobayashi, and S. Shimizu. 1981. Control system ofdissolved oxygen concentration employing a microcomputer. J.Ferment. Technol. 59:295-301.

VOL. 57, 1991

on April 19, 2021 by guest

http://aem.asm

.org/D

ownloaded from