ARTICLE

Respirometric Evaluation and Modeling of GlucoseUtilization by Escherichia coli Under Aerobic andMesophilic Cultivation Conditions

G. Insel,1 G. Celikyilmaz,2 E. Ucisik-Akkaya,2 K. Yesiladali,2 Z.P. Cakar,2

C. Tamerler,2 D. Orhon1*1Department of Environmental Engineering, Istanbul Technical University, Maslak, 34469,

Istanbul, Turkey; telephone: þ90 212 285 38 55; fax: þ 90 212 285 33 36;

e-mail: dorhon@ins.itu.edu.tr2Department of Molecular Biology and Genetics, Istanbul Technical University, Maslak,

34469, Istanbul, Turkey

Received 3 October 2005; accepted 1 August 2006

Published online 25 August 2006 in Wiley InterScience (www.interscience.wiley.com)

. DOI 10.1002/bit.21163

ABSTRACT: The study presents a mechanistic model forthe evaluation of glucose utilization by Escherichia coliunder aerobic and mesophilic growth conditions. In thefirst step, the experimental data was derived from batchrespirometric experiments conducted at 378C, using twodifferent initial substrate to microorganism (S0/X0) ratiosof 15.0 and 1.3 mgCOD/mgSS. Acetate generation, glyco-gen formation and oxygen uptake rate profile were mon-itored together with glucose uptake and biomass increasethroughout the experiments. The oxygen uptake rate(OUR) exhibited a typical profile accounting for growthon glucose, acetate and glycogen. No acetate formation(overflow) was detected at low initial S0/X0 ratio. In thesecond step, the effect of culture history developed underlong-term growth limiting conditions on the kinetics ofglucose utilization by the same culture was evaluated in asequencing batch reactor (SBR). The system was operatedat cyclic steady state with a constant mean cell residencetime of 5 days. The kinetic response of E.coli culture wasfollowed by similar measurements within a complete cycle.Model calibration for the SBR system showed that E. coliculture regulated its growth metabolism by decreasing themaximum growth rate (lower mH) together with anincrease of substrate affinity (lower KS) as compared touncontrolled growth conditions. The continuous low rateoperation of SBR system induced a significant biochemicalsubstrate storage capability as glycogen in parallel togrowth, which persisted throughout the operation. Theacetate overflow was observed again as an importantmechanism to be accounted for in the evaluation ofprocess kinetics.

Biotechnol. Bioeng. 2007;96: 94–105.

� 2006 Wiley Periodicals, Inc.

Correspondence to: D. Orhon

Contract grant sponsor: The Scientific and Technical Research Council of Turkey

(TUBITAK)

Contract grant sponsor: Turkish State Planning Organization (DPT)

Contract grant sponsor: Turkish Academy of Sciences

94 Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

KEYWORDS: Escherichia coli; growth kinetics; acetate gen-eration; glycogen formation; metabolic products; sequen-cing batch reactor; culture history

Introduction

Mechanistic understanding of substrate utilization bymicro-bial cultures and its description in terms of meaningfulprocess rate expressions have always attracted significantresearch effort. Since the pioneering work of Monod (1942),substrate utilization has been associated with biomassgrowth, measured in terms of collective parameters such asvolatile suspended solids, optical density, etc. The growthexpression offered by Monod has been the backbone in themodeling of microbial behavior in many areas and especiallyfor mixed culture systems. Recently, modeling of activatedsludge has been greatly improved by introducing newsubstrate fractions and a number of biomass componentswhich differentiated active biomass, from remaining parti-culate substrate, endogenous residues, etc. (Dold et al., 1980;Henze et al., 1987; Orhon and Artan, 1994). In biologicalwastewater treatment technology today, model evaluation isprovided for the most complex microbial systems definingthe behavior of at least three different groups of micro-organisms under a sequence of anoxic, anaerobic, andaerobic conditions (Gujer et al., 2000). The merit of these

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models depends upon the reliability of the information theyreflect on the substrate to be utilized and the biochemicalmechanisms involved. This information must be experi-mentally determined. In this context, respirometric methodsin these type of evaluations have been a major asset in theaccurate assessment of model coefficients and components(Avcioglu et al., 1998; Ekama et al., 1986; Insel et al.,2006, 2003; Orhon and Okutman, 2003; Spanjers andVanrolleghem, 1995).

Modeling efforts have also led the way to the recognitionof alternative processes for the fate and utilization ofsubstrate. The concept of microbial product generation hasbeen recognized for many years (Hejzlar and Chudoba,1986). It was used in a number of studies proposing differentmechanisms for the formation of microbial products,advocated to be degradable, but much slower compared toinitial substrate (Baskir and Hansford, 1980; Daigger andGrady, 1977). It is also introduced into activated sludgemodeling, mainly to account for soluble and particularresidual products (Orhon and Artan, 1994; Orhon et al.,1999a). Another significant process proposed for substrateutilization is aerobic storage of biopolymers under dynamicconditions imposing a kinetic pressure on the biomass, suchas a concentration gradient of the carbon source. The storedbiopolymers are later utilized for growth in the absence ofexternal substrate (Majone et al., 1999). This mechanism,supported by a number of studies conducted on simplesubstrate like glucose and acetate, serves now as the modelingbasis for mixed culture systems (Gujer et al., 2000).

Modeling requires a continuous research support thatprovides the required insight on fundamental microbialprocesses involved. This support is best achieved throughthe studies conducted on pure cultures using simplesubstrates. In this context, Escherichia coli is one of themost studied organisms among prokaryotes and is usuallyidentified as a member of various mixed culture commu-nities. Various strains of E. coli have been used in manybiotechnological and engineering applications, because oftheir adaptable nature to a wide range of temperature,pH etc. E.coli can easily be cultivated and is alsocommonly found in domestic wastewater. Its behaviorunder predefined conditions can yield important clues onthe fate of mixed cultures within activated sludge systems.E.coli, like other microorganisms in mixed culture systemsunder aerobic conditions, synthesizes pyruvate, which thenis converted to Acetyl-CoA and enters the TCA cycle(Gottschalk, 1985). However, with excess glucose underaerobic conditions, growth of E. coli results in the formationof volatile fatty acids, principally the acetate. In addition, anumber of models have been offered to explain the acetateoverflow and its reuse by E. coli (Ponce, 1999; Varma andPalsson, 1994; Xu et al., 1999).

In biotechnological applications, accurate determinationof each kinetic parameter is of great importance forappropriate reactor design and process control. However,apart from uncertainties associated with experimentalconditions and data properties, the success of unique

parameter estimation may suffer from many factorsreflecting alteration ofmicrobiological properties of themic-robial culture. These factors are namely (1) the culturehistory (2) feeding type/pattern of substrates and (3) failureto recognize other subsidiary microbial processes such asstorage, overflow mechanism etc., taking place simulta-neously together with growth under different environmentalconditions (Beccari et al., 1998; Luli and Strohl, 1990; Xuet al., 1999). The physiological state of the microbialcultures, which is a function culture history (i.e., mean cellresidence time, dilution rate, etc.) involves the regulation ofthe complex biochemical reaction mechanism within thecell. Recent studies have shown that the response of themicrobial culture is highly influenced by r-RNA level of celland the activity of substrate transporting enzymes in termsof substrate utilization (Madigan et al., 2003; Ramarishnaet al., 1996). Basically, the r-RNA level of cell is linked to themaximum growth rate (mH) parameter since it governsthe protein synthesis mechanism. On the other hand, theactivity of substrate transport enzyme is the indication ofsubstrate affinity of the cells. The affinity increases with theelevated activity of transport enzyme(s), which correspondsto low half saturation constant (KS) values (Daigger andGrady, 1982; Ferenci, 1999; Kovarova-Kovar and Egli,1998). Most of the biological systems, such as activatedsludge reactors, are subjected to considerable substrate loadand environmental variations (Majone et al., 1999). In thisrespect, the microbial culture is able to regulate itsmetabolism by promoting substrate utilization and/orstorage during the feast and famine periods (Beun et al.,2000, Dircks et al., 2001).

The metabolic behavior of E. coli is well studied. However,no mechanistic evaluation has been provided using a modelbased approach that individually identifies the mainprocesses and model components affecting substrateutilization with by-product formation, and relies uponrespirometric data reflecting electron acceptor utilizationunder different feed conditions. In this context, the objectiveof the study was to develop a multi-component dynamicmodel for the glucose utilization by E. coli cultivated underaerobic and mesophilic conditions, and to provide amechanistic explanation for major metabolic activities suchas microbial products generation and glycogen formation.The model was calibrated using the oxygen uptake rate(OUR) profiles together with relevant analytical dataderived from batch experiments in a respirometer,conducted at 378C, using two different initial substrate tomicroorganism (S0/X0) ratios of 15 and 1.3 mgCOD/mgSS.

This study also evaluated the effect of limiting growthconditions on the kinetics of glucose utilization by E. coli in acontinuous sequencing batch reactor (SBR) operated withcyclic substrate feeding. The evaluation, similarly involvedmodel calibration of the experimental data obtained atsteady-state, using the same set of model parameters. Theeffects of culture history on growth, storage kinetics andoverflow mechanism were investigated with the aid ofrespirometric and analytical data. Based on the selected

Insel et al.: Modeling of Glucose Utilization by E. coli 95

Biotechnology and Bioengineering. DOI 10.1002/bit

conceptual model, the process kinetics obtained from thisstudy was compared with the uncontrolled growth of E. coli.

Materials and Methods

Bacterial Strain and Growth Medium

E. coli K12 (DSMZ 498) was used throughout this study. Itwas obtained from Deutsche Sammlung von Mikroorganismenund Zellkulturen (Braunschweig, Germany). For all cultiva-tions, a chemically defined medium (M9 minimal medium)was used which contained 8.421 g Na2HPO4(2H2O; 3 gKH2PO4; 0.5 g NaCl; 1 g NH4Cl, 1 ml of 1 M MgSO4 stocksolution and 1 ml of 0.1 M CaCl2 stock solution per 1 L ofdistilled water. Glucose was added to this medium as the solecarbon source. The pH of theM9mediumwas adjusted to 7.4.

Table I. Operational parameters of the SBR system.

Experimental Procedure

Batch Experiments

Two sets of experiments were conducted for modelcalibration and verification at 378C, under differentmesophilic growth conditions of E. coli K12. The preculturewas washed with fresh M9 in order to avoid acetateand glycogen interference to the medium. The initialbiomass (suspended solids) concentration was held around100 mgSS/L for both experiments. The glucose concentra-tions were adjusted to yield two markedly different substrateto microorganism (S0/X0) ratios of 15 and 1.3 mgCOD/mgSS respectively. Respirometric measurements werecarried with the aid of continuous respirometer (RA-ComboLab., Applitek, NV, SA).

The pre-culture used in the respirometer, as inoculation,was grown in 500 mL shake flasks overnight. The flaskswere incubated in orbital shakers at 378C with 250 rpm. Thegrown culture was centrifuged at 5,000 rpm for 15 min. Thesupernatant was disposed and the pellet re-suspended infresh M9 without the carbon source. The resuspendedculture volume was adjusted to supply the adequate biomassin the respirometer reactor. Respirometric measurementswere started prior to the feeding of carbon source in order toobserve the endogenous state of the culture. After theconstant endogeonus level in terms of respiration wasmaintained, carbon source glucose was added to the reactorproviding the selected initial S0/X0 ratios. The preculturestock was kept in �208C prior to cultivation.

Parameter Unit Value

Substrate to microorganism ratio (F/M) gCOD/gSS�day 0.9

Number of cycle, m — 4

Maximum volume, VT mL 1,500

Initial volume, V0 mL 1,425

Wasted volume per cycle, VSL mL 75

Continuous SBR Experiment

Sequencing batch reactor (SBR) is basically a fill and drawreactor with sequential feeding and withdrawal, as the unit

96 Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

processes involved in SBR and continuous bioreactors areidentical. SBR is a widely used reactor-system both inexperimental and modeling studies to understand thephysiology and kinetics of mixed culture systems (Artan andOrhon, 2005). In this study, 2-L Biostat1 B (Braun,Germany) bioreactor was operated as a sequencing batchreactor (SBR) with a cycle length of 6 h and each cycleconsisting of five process operation phases (Ucisik Akkaya,2004). The oxygen was always provided together withmixing (250 rpm) during all stages of the cycle. The totalvolume of the reactor was set to 1.5 L and a hydraulicretention time of 5 days was adjusted for the system bywithdrawing 0.075 L aliquots from the end of each 4 cycle.For each cycle, feeding and withdrawing ended in 1 and 3min, respectively for each cycle. The operational data of SBRsystem is given in Table I. Feeding and withdrawing wereperformed with two parallel pumps connected to timers.Microorganisms were pulse-fed with 75 mL/cycle ofmedium containing 4,300 mgCOD/L glucose as the solecarbon source to achieve substrate to microorganism ratio(F/M) of 0.9 gCOD/gSS�day for 5 days. The bioreactor wasoperated at 378C and 250 rpm.

Sampling was carried out with appropriate intervals forthe analysis of intracellular and extracellular growthmetabolites and the intracellular storage polymers in orderto obtain the previous history of the cellular metabolites andthe storage polymers of E. coli at steady-state conditions.

Analytical Measurements and Modeling

Acetate concentration was determined using a gas chro-matograph (HP-Agilent Technologies 6890N GC Systems,USA). Agilent Technologies 125-3232 DB-FFAP (J & WScientific, HP, USA) capillary 30.0 m� 0.53 mm� 1 mmnominal column was used for the measurements. Data wereanalyzed by ChemStation Software, Agilent Technologies,HP. The injector (split-splitless) and flame ionizationdetector (FID) temperatures were set at 2608C and 3008C,respectively. Cell growth was monitored spectrophotome-trically at 600 nm wavelength (UV 1601, Shimadzu, Japan).Glycogen measurements were determined using an HPLCsystem (Shimadzu), equipped with a refractive indexdetector and a HPX-87 H column (Biorad, USA) at 608C.The mobile phase was HPLC grade distilled water with aflowrate of 0.6 L/min. Data were analyzed by a Shimadzu VP

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computer program. Prior to residual glucose analysis,samples were centrifuged at 14,000 rpm for 2 min andfiltered through 0.22 mm Millipore filters. Samples foracetate measurements were also treated the same as residualglucose samples, after which 0.3 mL, 3 M H3PO4 was addedto acetate samples to prevent the evaporation of acetate.Acetate and PHB measurements were carried out by using agas chromatography (GC) system (Agilent Technologies,USA), as described previously (Akar et al., 2005; UcisikAkkaya, 2004). The respirometric analyses were carried outby a continuous respirometer with a sampling frequency ofsample per minute (RA-Combo Lab., Applitek, NV, SA). Itwas equipped with a peristhaltic pump and solenoid valves(Spanjers, 1993). A water jacket was used to keep thetemperature of the culture at constant level. The tempera-ture and dissolved oxygen concentrations were continuouslymeasured in a separate 750 mL respirometric chamberequipped with a single WTW type dissolved oxygenelectrode. Air was introduced to 4-L reactor by acompressor, through a sparger. A working volume of 3 Lwas put into the jacketed vessel. Respiration measurementswere started prior to feeding of batch and SBR system untilthe culture showed the same respiration rate as before thesubstrate addition.

Samples were withdrawn from the reactor regularly inorder to determine the residual glucose concentrations,acetate concentration and optical density (OD600) values inlag, log and stationary phases, and also for glycogen andPHB measurements. Time series data of OUR, glucose,glycogen, acetate profiles were used in parameter estimationprocedure. During the minimization of total sum of squarederrors, the absolute errors pertaining to OUR and otheranalytical data (glucose, glycogen, acetate) were accepted as�1.0 mgO2/L and �10 mgCOD/L, respectively. The opticaldensity (OD600) data were used for the comparison ofsimulated active biomass concentration, XH. The SIMPLEXsearch algorithm was used for the estimation of the modelparameters for batch experiments (Nelder and Mead, 1965).The AQUASIM software was used for model simulation andestimation of model parameters using respirometric andanalytical data (Reichert et al., 1998). The analyticalmeasurements of chemical oxygen demand (COD) andsuspended solids (SS) can be found in StandardMethods forthe Examination of Water and Wastewater (1998). TheCOD equivalence of glucose can be calculated as 1.066 gCOD/g glucose.

Table II. Model matrix for the utilization of glucose by E. coli.

Process/states SO SS

1 Growth on SS � 1�YH�aYH

YH� 1

YH

2 Storage of SS �ð1� YSTOÞ �1

3 Growth on SA � 1�YHYHA

4 Growth on XSTO � 1�YHYH

5 Decay of XH 1�fpComposition (unit) O2 COD

Model Description

The proposed model for evaluating glucose utilization byE. coli is structured to be limited, for simplicity, with fivemodel components or state variables, namely active biomass(XH), glycogen stored in biomass (XSTO), glucose (SS),acetate (SA), and dissolved oxygen (SO). It basically involvessix microbial processes; growth on glucose; storage ofglucose as glycogen; generation of acetate; growth onacetate; growth on glycogen and biomass decay due toendogenous respiration. Related process kinetics andstoichiometry describing interactions and transformationsamong model components are expressed in a way that iscompatible with previous mathematical models that havebeen proposed to formulate biochemical reactions ofmicrobial populations fed with different type of substrates(Dold et al., 1980; Henze et al., 1987; Orhon and Artan,1994; Wentzel et al., 1992). For a mechanistic model of thissize, failure to grasp the basic interactions between modelcomponents and processes often leads to serious misinter-pretations. In order to overcome this problem, the structureof the proposed model is presented in a matrix format(Henze et al., 1987; Peterson, 1965) reflecting the basicstoichiometric relationships constituting the backbone ofthe model. This matrix format is outlined in Table II, wheremodel components are listed in the upper row; therightmost column gives the process rate expressions andrelevant stoichiometric coefficients are incorporated inappropriate cells of the matrix.

This way, the rate of change (generation or utilization) ina model component for a given biochemical process isobtained by multiplication of related process stoichiometryand kinetics (Gujer and Larsen, 1995). In the model,biomass growth (E. coli) is defined by a hyperbolic Monod-type expression as commonly adopted in other models. Thisrate expression stops growth when external substrate(glucose) is depleted by means of a substrate switchfunction controlled by the half saturation constant, KS. Thisway, growth on glucose (SS) ceases upon complete depletionof glucose, itself. According to the model, when one unit ofsubstrate is consumed, its YH fraction is converted intobiomass and the remaining stoichiometric fraction (1�YH)is used for energy, consuming an equivalent amount ofdissolved oxygen, SO.

Simultaneous to growth on glucose, acetate is produced inthe bulk as a microbial by-product (Johnston et al., 2003;

SA XSTO XH Rate equation

a 1 mH1SS

KSþSSXH

YSTO kstoSS

KSTOþSSXH

� 1YHA

1 mH2SA

KSAþSA

KS

KSþSSXH

� 1YH

1 kglyKS

KSþSS

KSA

KSAþSAXSTO

�1 bHXH

COD COD COD

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Luli and Strohl, 1990; Shimizu et al., 1988). As proposed inthe literature, acetate generation is considered as a growth-associated process (Luedeking and Piret, 1959; Ponce, 1999;Xu et al., 1999) which is activated by an a fraction of thegrowth mechanism on primary substrate (Orhon and Artan,1994). In other words, acetate generation occurs as a YSPfraction of the primary substrate, where YSP¼a �YH. In thiscase, the acetate generation is not expressed as anindependent process, but as part of growth on glucose:

dSAdt

¼ amH1

SSKS þ SS

XH (1)

Accordingly, dissolved oxygen consumption associated withgrowth on glucose is defined with a stoichiometriccoefficient of (1�YH�YSP)/YH to maintain the basic massbalance (Gujer and Larsen, 1995). The model proposes asequential growth mechanism, where acetate is used up assecondary external substrate after the depletion of glucose.In this rate expression, biodegradation of acetate is activatedby the inverse Monod switch function defined for SS.

dSAdt

¼ � mH2

YH

SAKSA þ SA

KS

KS þ SSXH (2)

Recently, the microbial storage concept was discovered andincorporated in microbial population modeling (Gujeret al., 1999). This concept can be explained in such way thatheterotrophic biomass is capable of storing the externalsubstrate (i.e., volatile fatty acids) within the cell in apolymeric form (polyhydroxybutyrate, glycogen etc.). Thesestored materials are then consumed for growth and cellmaintenance (Beccari et al., 1998; Beun et al., 2000; vanLoosdrecht et al., 1997). Experimental results showed thatglycogen is formed parallel to the degradation of glucose stillpresent in the bulk (Krishna and van Loosdrecht, 1999).According to the microbial storage concept, oxygen isconsumed via (i) the storage and (ii) the utilization ofinternally stored material for cell growth and maintenance(Gujer et al., 1999). A storage process is added to the secondline of the matrix (Table II). Thus, glucose (SS) is stored asglycogen (XSTO) with a stoichiometry of YSTO. Theremaining part indicated by (1�YSTO) is consumed asoxygen during the active transport of glucose.

After the consumption of all external substrates (glucoseand acetate), the internal storage polymer, glycogen, isconsumed for cell growth. As a simplification, the processrate for degradation of glycogen (XSTO) is formulated by afirst order reaction rate, kgly�XSTO (Dircks et al., 2001). Inthe model matrix (Table II), two inverse switch functions areincorporated in order to activate glycogen consumptionwhen external substrates (SS and SA) are exhausted (see line4 in Table II). Finally, the biomass decay takes place and itconsumes oxygen to provide maintenance energy. The(1�fP) portion is produced in the system as a particulateinert product composed of inert materials, cell debris etc.

98 Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

during the decay process (van Loosdrecht and Henze, 1999;Orhon et al., 1999b).

Results and Discussion

Batch Experiments

High Initial S0 /X0 Ratio

The experiment carried out at S0/X0 ratio of 15 mgCOD/mgSS was started with an initial glucose concentration of1,530 mgCOD/L, which exhibited a rapid decrease and wascompletely removed within 270min. Glucose utilization wascoupled with an exponential biomass increase reaching itsmaximum OD600 of 1.45 as shown in Figure 1a. Parallel toglucose removal from the bulk, acetate accumulation wasobserved to a level of 350 mg/L (Fig. 1b). In experimentsusing glucose as external carbon source under mesophilicconditions, acetate (SA) generation is commonly observed asa by-product in parallel to the growth of E. coli (Belo andMota, 1998; Cockshott and Boyle, 1999; Luli and Strohl,1990). After the depletion of glucose (SS), produced acetatewas removed within 2 h (Fig. 1b). Glycogen (XSTO)formation was also detected during the experiment,simultaneously with glucose utilization, at a much lowerlevel of 42 mgCOD/L compared to acetate generation. Asshown in Figure 2, glycogen consumption was triggered afterremoval of external substrate (i.e., glucose and acetate). PHBwas monitored in the study, to explore the possibility ofintracellular polymer formation (PHB) from acetate leakedout during the utilization of glucose. PHB was not detectedin collected samples. As shown in Figure 1a, the OUR profileexhibited an exponential increase to a maximum level of236 mgO2/L/h with a sharp decrease at complete depletionof glucose. A second increase in the OUR rate was observedin parallel to the acetate (SA) utilization, with a lower slopeupto a maximum level of 92 mgO2/L/h. The second peakended with a smoother decrease, which may be attributed toconsumption of internal glycogen (XSTO) pool (Fig. 1b).

Modeling study involved primarily the calibration of themodel on the oxygen uptake rate (OUR) curve together withglucose (SS), acetate (SA), glycogen (XSTO) concentrationprofiles obtained from experiments at two different initialS0/X0 ratios. Estimatedmodel parameters are summarized inTable III. At high initial S0/X0 ratio of 15.0 mgCOD/mgSS,the first increase in the OUR profile could be attributedto the exponential growth of E. coli defining amaximum growth rate (mH1) around 15.5 day�1 and a halfsaturation coefficient, KS of 16 mgCOD/L. The maximumgrowth rate could be estimated separately from theinitial active heterotrophic biomass, XH0 as proposed byDochain et al. (1995) as exponential growth occurs at theexpense of unlimited substrate. The magnitude of themaximum growth rate used in calibration is in conformitywith the range from 11 to 34 day�1 reported in the literature(Ponce, 1999; Van de Walle and Shiloach, 1998). Model

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Figure 1. Batch experimental and modeling results for (a) OUR, XH, and Optical Density; (b) substrate concentrations at high initial S0/X0 ratio of 15 mgCOD/mgSS.

interpretation of the glucose concentration parallel togrowth also accounted for acetate generation with a¼ 0.58and formation of glycogen with kSTO¼ 1.4 day�1. Thesecond peak in the OUR curve corresponded to secondarygrowth on generated acetate (SA) at a lower maximumgrowth rate of 2.5 day�1 after glucose removal from the bulkliquid. The lower maximum growth rate on acetate ðmH2Þ ismainly attributed to the inhibitory effect of high acetateconcentration on growth-associated processes (Luli andStrohl, 1990; Shimizu et al., 1988). As indicated in Table III,much higher maximum growth rate ðmHÞ and halfsaturation constant (KS) for glucose were found ascompared to the growth on acetate. This kinetic differencehas been explained with the argument that the high capacity-low affinity enzymes utilized for glucose could be substitutedby low capacity-high affinity enzymes used for acetatedegradation during the same experiment (Grady et al., 1996;Kovarova-Kovar and Egli, 1998).

As shown in Figure 1a and b, the sharp decline after thefirst peak indicates the transition from the utilization ofone simple substrate, glucose directly to another, acetate.The smoother OUR decline after the second peak is due to

Figure 2. Experimental and modeling results for (a) OUR, XH, and Optical Den

growth on stored glycogen, well predicted by modelsimulation, practically taking place after consumption ofacetate following a slower start to the extent that is allowedby the switch function KSA/(KSAþ SA). The heterotrophicyield, YH is one of the most significant parameters for modelevaluation; it can be computed using the area below theOUR profile indicating the oxygen consumption for growth,provided that the amount of substrate utilized for growth isknown (Sollfrank and Gujer, 1991). This way, the averageyields of YH and YHA were estimated to be 0.45 and0.67 gcellCOD/gCOD for glucose and acetate, respectively.These values are in agreement with the range of 0.27–0.67 mgcellCOD/mgCOD given in the literature (Henzeet al., 1987; Paalme et al., 1997; Shiloach et al., 1996). Ahigher heterotrophic yield for acetate was required in orderto simulate the consumption of oxygen under the OURcurve corresponding to acetate degradation (second OURhump in Fig. 1a). The OUR curve is also sensitive to initialactive biomass concentration, XH0; nearly identical XH0

values of around 60 mgCOD/L were estimated for bothexperiments since they were started with nearly the sameinitial biomass levels in dry weight basis. The XH0 profiles

sity; (b) substrate concentrations at low initial S0/X0 ratio of 1.3 mgCOD/mgSS.

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Table III. Estimated stochiometric and kinetic parameters for model evaluation.

Model parameters Unit

Batch

Continuous SBRHigh S0/X0 Low S0/X0

Stoichiometry

Biomass yield on glucose, YH gcellCOD/gCOD 0.45 0.47 0.40

Biomass yield on acetate, YHA gcellCOD/gCOD 0.67 0.67 0.35

Acetate generation coefficient, a — 0.58 0.00 0.60

Kinetics

Maximum storage rate, ksto day�1 1.4 1.4 2.0

Maximum growth rate on SS, mH1 day�1 16.2 15.1 4.0

Maximum growth rate on SA, mH2 day�1 2.50 2.50 0.36

Half saturation constant for growth on SS, KS mgCOD/L 16.0 16.0 2.0

Half saturation constant for growth on SA, KSA mgCOD/L 4.7 4.7 0.5

Rate constant for XSTO consumption on SA, kgly day�1 9.8 9.8 0.8

Biomass

Active biomass concentration, XH0 mgcellCOD/L 60 66 1,050

Default model parameters: YSTO: 0.9 gCOD/gCOD; bH¼ 0.15 day�1, fP¼ 0.2.

obtained by model simulations were in conformity with theOD600 measurements during growth phases as shown inFigure 1a. However, the OD600 values obtained during thegrowth on acetate under higher S0/X0 do not reflect thesecondary exponential growth of heterotrophic biomass,signaling the danger of directly using index values such asOD600 for the assessment of active biomass in modelingstudies.

Low Initial S0 /X0 Ratio

The second batch respirometric experiment was started witha substantially lower glucose concentration of 120 mgCOD/L to sustain an initial S0/X0 ratio of 1.3 mgCOD/mgSS. Theoxygen uptake rate (OUR) exhibited a typical profile, totallydifferent from the one obtained at high S0/X0 ratio, with apeak value of around 50 mgO2/L/h after 50 min, graduallydecreasing to 5 mgO2/L/h (Fig. 2a). As illustrated inFigure 2b. Glucose (SS) was rapidly consumed within 120min with a parallel biomass increase to an optical density(OD600) of only 0.34 (Fig. 2a). Neither acetate, norappreciable glycogen production was detected during theexperiment. The overall evaluation of the experimental datashowed that when E. coli is exposed to an excessive glucoselevel, it utilizes external substrate for growth, with simul-taneous acetate generation as microbial metabolic productand internal glycogen storage. After complete depletion ofglucose, a secondary growth takes place at the expense ofacetate, which allows when decreased to a sufficiently lowlevel, subsequent utilization of glycogen storage. Whenpresent at a much lower level, glucose utilization is solelydirected to growth mechanism.

In this study a unified model structure was conceived in away that would be applicable for the two sets of experimentsconducted under different initial conditions (Table III). Inthis framework, the OUR profile of low S0/X0 ratioexperiment smoothly increased up to 55 mgO2/L and wasfollowed by a gradual decline parallel to glucose consump-

100 Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

tion without yielding any acetate generation, which could beinterpreted by microbial growth alone, simply using similarstoichiometric and kinetic coefficients estimated for theevaluation of the results in the first experiment. Since therewas no volatile fatty acid generation at this S0/X0 ratio,the value of a was set to zero. This means that glucose isconsumed for growth process without any acetate produc-tion with an average yield coefficient of 0.47 gcellCOD/gCOD. However, the shape of the OUR profile exhibiting asmooth decline required incorporation of a slight glycogenformation mechanism of around 5 mgCOD/L, which wasnot measured during the experiment, with subsequentutilization for growth for appropriate evaluation of the OURdata, as shown in Figure 2a.

Short-term batch respirometry has become a conven-tional tool for extracting important model parameterstogether with the active biomass fraction for a selectedmodel. The oxygen uptake rate profile provides a fingerprintof biomass activity and the biodegradability of substrate fedto the system (Ekama et al., 1986; Spanjers and Vanrolle-ghem, 1995). The observation of complete degradation ofsubstrate with the aid of oxygen uptake rate measurementsallowed in this study, as in many others (Insel et al., 2003;Sozen et al., 1998; Spanjers and Vanrolleghem, 1995) toderive process stoichiometry and kinetics in terms ofmeaningful processes. The ratio of initial substrate tobiomass (S0/X0) was the key parameter for respirometricexperiments directly effecting the shape and the order ofmagnitude of the respirometric profile (Ekama et al., 1986;Insel et al., 2002).

Description of biomass growth on glucose with the samekinetics coefficients of mH1 ¼ 15-16 day�1 and KS¼ 16mgCOD/L at two significantly different S0/X0 ratios may beregarded as another key feature of the study. This findingdoes not support the arguments in the literature (Chudobaet al., 1992; Grady et al., 1996) that the amount of subs-trate provided to cells in a batch kinetic test will affect thephysiological state of cells during the assay and hence theresulting growth kinetics. In most related studies however,

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experimental justification has been limited to the measure-ment of substrate and particulate matter (dry weight)interpreted to represent active biomass, with a pre-conceived idea that growth is the only biochemicalmechanism responsible for substrate utilization, thusignoring parallel mechanisms, such as biochemical storageand microbial products generation observed in this study,likely to occur to a variable extent together with growth,depending on experimental conditions. This type of anevaluation is bound to lump all parallel processes ontogrowth, with the net effect of a distorted growth kineticsresulting in variable kinetic coefficients for each experi-mental condition, depending on the relative impact of theoverlooked processes. The model evaluation in this studyclearly indicated that, when all significant biochemicalprocesses are considered and incorporated into a conceptualmodel, microbial growth, assuming a variable role in theutilization of the initial substrate, is defined in terms ofsimilar process kinetics in two batch experiments conductedwith different initial substrate to biomass (S0/X0) ratios.

It should be noted however that precultivation of E. coli atthis stage imposed no growth restriction, allowing themicrobial culture to develop and sustain the full comple-ment of its protein synthesis system. Most engineeredsystems however, such as biological treatment processes,exert a kinetic pressure on the microbial culture as they areoperated at a given (often low) net growth rate, at steady-state. It is argued that in such systems, the culture historyaffects the protein synthesis system which would adapt itselfto imposed environmental conditions and yields a variablegrowth kinetics under different S0/X0 ratios (Grady et al.,1996; Sokol, 1987).

Continuous SBR Experiments

Experimental data on glucose utilization by E. coli werederived using a sequencing batch reactor system operated

Figure 3. Experimental and modeling results of (a) OUR profile

with four cycles a day and pulse feeding of glucose at thebeginning of each cycle. The start-up of the SBR wascontinued until steady state where the biomass concentra-tion was observed to stabilize around 1,000 mg/L cell dryweight (cdw) at a mean cell residence time of 5 days. Duringsteady-state operation, the transient response of the systemwas monitored throughout the process phase of a selectedcycle by measuring concentration profiles of glucose,glycogen and acetate together with the complete OURprofile. Based on the measurement campaign summarized inFigure 3, following cases were observed to characterize thecyclic performance of the SBR system at steady-state: (i) theinitial glucose at a concentration of approximately 250 mg/Lat the start of the cycle was rapidly depleted within 20 min;(ii) acetate generation occurred concurrently with glucoseutilization, up to a peak level of 50 mgCOD/L, followed by agradual removal pattern within the first 60 min of the cycle;(iii) steady-state SBR operation induced glycogen build-upfluctuating around 80 mgCOD/L within biomass, partlyconsumed in the later phase of the cycle after depletion of allexternal substrate; (iv) OUR exhibited, as shown in Figure3a, a doubled-peak profile, where the initial OUR peak ofaround 170 mgO2/L/h could be explained by the growthresponse of E. coli, as supported by OD600 measurements(Fig. 4a), during the consumption of glucose, together withstorage of part of the glucose as glycogen (XSTO) as shown inFigure 3b. Subsequently, the OUR dropped to second lowerpeak around 50 mgO2/L/h, which corresponded to acetateconsumption. After the consumption of acetate, smootherdecrease in the OUR profile could be attributed to thedegradation of storage products and the endogenous decayof active biomass.

The experimental data in this study, summarized inFigure 3 justifies the selection of the adopted model, whichdefines, aside from microbial growth, other relevantprocesses such as acetate generation and glycogen forma-tion, again. In the model calibration study, the parameterswere manually selected and optimized by trial and error to

and (b) substrate concentrations for continuous SBR system.

Insel et al.: Modeling of Glucose Utilization by E. coli 101

Biotechnology and Bioengineering. DOI 10.1002/bit

Figure 4. Simulation graphs for (a) Active biomass-XH, Optical Density-OD600 measurements; (b) OUR profile and AR-sensitivity trajectories for KS and KSA parameters in SBR

cycle.

get best fit on experimental data as shown in Figure 3a and b.The model parameters used in calibration were listed inTable III together with the parallel results obtained frombatch experiments as mentioned above. The active biomass(XH) was calculated by model as an outcome of thesimulation. While it is rather difficult to determine activebiomass from the experiments conducted under low initialsubstrate to microorganism (S0/X0) ratio (Dochain et al.,1995; Insel et al., 2002), the continuous nature of the SBRsystem allows calculating active biomass at steady state if theparameter values are appropriately assigned. A typicalmodeling result of the OUR curve can be observed in Figure3a, where the initial high OUR reflects the growth responseof 900 mgCOD/L of active biomass (XH) after the spike ofsubstrate that sustains an initial glucose concentration of250 mgCOD/L (Table III). Figure 4a shows that the trendof active biomass is in good agreement with OD600

measurements within one SBR cycle.The important feature of model simulation exercise is the

significantly low values of 4.0 day�1 for the maximumgrowth rate, mH1 and 2.0 mg/L for the half saturationconstant for growth, KS providing appropriate calibration ofthe experimental data for the SBR system operated at steady-state at a mean cell residence time of 5 days (Table III). Thebatch experiments conducted under different conditionsreveals that the biomass, with no growth limitations yieldedmuch higher maximum growth rate of around 16.0 day�1

together with a relatively higher KS value of 16 mgCOD/L(Table III). It is interesting that the acetate was alwaysgenerated with relatively similar stoichiometry (approxi-mately the same a values around 0.60) for both batch andcontinuous experiments. In this respect, it can be concludedthat the acetate generation phenomena (Shiloach et al.,1996; Xu et al., 1999)—which is linked to primarygrowth—occurs independently from the culture history.

In this study, aside from lower maximum growth rates aswell as half saturation constants obtained compared to the

102 Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

batch experiment results, the same findings hold true for therates of acetate (SA) kinetics. However, the maximumstorage rate, ksto was estimated to be 2.0 day�1, which isslightly higher than 1.4 day�1. This may be due to theincreased storage capacity of biomass since the maximumgrowth rate is reduced. Thus, the biomass might promote itsstorage process rather than consuming the external substratein TCA via growth (Daigger and Grady, 1982; Dircks et al.,2001; Gottschalk, 1985). The yield on glucose was found tobe around 0.4, which falls within the range of 0.27–0.67 gcellCOD/gCOD given in literature (Henze et al., 1987;Paalme et al., 1997; Shiloach et al., 1996).

A simulation study was conducted to visualize thesensitivities of half saturation parameters of KS and KSA onthe OUR profile obtained for SBR system. Figure 4b showsthe experimental OUR profile (left y-axis) together withabsolute-relative (AR) sensitivity trajectories (right y-axis)for half saturation parameters of KS and KSA (Reichert et al.,1998). The AR sensitivity function is commonly used tocalculate the absolute changes in the OUR profile per unitchange in envisaged parameters—KS and KSA in this case.According to the simulation results, a 100% change in KS

causes a positive shift of 90 mgO2/L�h in OUR between thefirst and second plateaus (Fig. 4b). However, a similarchange in KSA only induces a 20 mgO2/L�h shift occurring atthe end of the second OUR tailing. Since the sensitivitytrajectories (i) have different order of magnitudes, (ii)influence different sectors of OUR profile, and (iii) are notsymmetrical along time axis, KS and KSA can be extractedusing the same respirogram.

The metabolic pathways and processes regarding glucoseutilization leading to glycogen formation from glucose 6-P,or acetate generation through pyruvate and acetyl-CoAprior to TCA cycle are well studied and documented. Whenthe carbon input exceeds the capacity of the centralpathways, metabolism is known to be balanced in eitherof the following ways: (i) metabolic intermediates are

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converted to (storage) polymers, (ii) substrate oxidation andenergy generation are uncoupled, (iii) low-molecular weightcompounds are excreted to the medium (El-Mansi andHolms, 1989). Thus, Dedhia et al. (1994) argued that itshould be possible to eliminate acetate production(strategy—iii) by directing carbon flux to a storage polymer.It was found that glycogen overproduction in wild-typeE. coli did not significantly reduce acetate excretion, whichwas explained by the low levels of glycogen produced thatcould not efficiently divert carbon away from glycolysis(Dedhia et al., 1994). This may also explain the simultaneousacetate and glycogen formation observed in our study. Themaximum concentration of acetate produced was aboutsevenfold of that of glycogen. The E. coli K12 strain used inthe experiments is also known as an acetate producer evenunder fed-batch conditions with low glucose concentra-tions, thus its metabolism has been studied and comparedwith those strains with efficient glucose utilization usingmicroarrays and Northern blot analyses (Phue et al., 2005).Former genetic studies also revealed a global regulatorygene, csrA, which represses gluconeogenesis, glycogenbiosynthesis, and glycogen catabolism, but activatesglycolysis (Wei et al., 2000). It was also found that csrAgene positively regulates the acetyl-CoA synthetase (Acs)pathway which produces acetyl-CoA directly from acetate(Wei et al., 2000). A detailed metabolic interpretation ofsimultaneous glycogen and acetate formation is clearlybeyond the scope of our study. The maximal handlingcapacity and overloading of the TCA cycle and relative rateof formations of glucose 6-P and acetyl Co-A towardsglycogen formation and/or acetate generation certainlyrequire further research.

The results of model evaluation provides support to thefindings of Daigger and Grady (1982) who stated that inpure cultures, physiological adaptation of microbial culturesto environmental conditions triggers the regulation ofcomplex biochemical components directly affecting thespecific growth rate. They further suggested that inmicrobial cells, the protein synthesis system, which isdirectly related to RNA levels in the cells, plays importantrole on the bacterial anabolism/catabolism during cultiva-tion. The maximum growth conditions are a direct measureof the RNA level of the cell which trigger the proteinsynthesis mechanism. Accordingly, a decrease in RNAcontent indicates a reduction of protein synthesis, thus aparallel reduction in the maximum growth rate (Daiggerand Grady, 1982).

As further support to variable maximum specific growthrate, Kovarova-Kovar and Egli (1998) stated that themicrobial cells could adjust their kinetic properties within awindow of mH-KS plane depending upon the type of thebacteria having oligotrophic and copiotrophic properties.The oligotrophic properties correspond to lower maximummH-KS domain, however, the copiotrophic propertiesindicates higher mH-KS levels. For instance, microorganismsare able to increase their affinity (<<KS) during long-termadaptation from high to low substrate concentration in such

way that glucose is transported via high affinity galactosebinding protein/maltose system rather than the glucosephosphotransferase system (Lengeler, 1993; Kovarova-Kovar and Egli, 1998). Simultaneously, when long termadapted cells are removed from chemostat to batch reactorsat high glucose concentrations, the maximum growth rateare reduced by the factor of 60%. Feast and famine periodsalso play an important role on the selection of kineticproperties due to the adjustment of substrate transportsystem(s) as well as variations in catabolic/anabolicproperties (Dircks et al., 2001; Kurlandzka et al., 1991).The polymer synthesis can also be observed when thecarbohydrate and lipid content of the cell increases undercertain feeding conditions. For this study, corresponding to2.0 day�1 maximum storage rate (ksto), the maximumglycogen level reached to 100 mgCOD/L within the cyclewhich is 60 mgCOD/L higher compared to the previousresults obtained for the batch experiments as summarized inTable III.

Conclusions

In this study, glucose utilization and resulting kineticbehavior of a pure culture of E. coli was first evaluated inbatch reactors and then in a continuous sequencing batchreactor system operated at steady state with the aid of multi-component model calibration. The evaluation underlinedthe need of accounting for all major biochemical mechan-isms likely to occur under different conditions, so that anacceptable model simulation and calibration could be made.Accordingly, the model structure included the kinetic andstoichiometric description of acetate generation as amicrobial product and glycogen formation as a storagebiopolymer together with sequential growth of E. coli onthese substrates. Evaluation of the oxygen uptake rate profilewas adopted as an integral component of model evaluation,which enabled to interpret experimental data obtained atsignificantly different initial substrate to biomass (S0/X0)ratios of 15.0 and 1.3 mgCOD/mgSS, with a set ofstoichiometric and kinetic model parameters. The modelevaluation in this study clearly indicated that, when parallelmechanisms of acetate generation and glycogen formationare incorporated into a conceptual mechanistic model,microbial growth while exerting a variable impact in theutilization of the initial substrate, may be defined in terms ofthe same process kinetics in two experiments conducted atdifferent initial S0/X0 ratios. These experiments weredesigned to impose no growth restrictions on the E. coliculture, with the net result that the biomass was able tomanipulate and adjust its protein/enzyme synthesismechanism to primarily secure microbial growth. Growthon glucose was immediately increased and sustained atmaximum level in the experiment with high initial S0/X0

ratio and was practically the only mechanism of substrateutilization at low initial S0/X0 ratio.

Insel et al.: Modeling of Glucose Utilization by E. coli 103

Biotechnology and Bioengineering. DOI 10.1002/bit

However, in continuous SBR experiments the kineticresponse of the E. coli culture in the biodegradation ofglucose was found to be dependent upon the culture history.Under controlled conditions, during continuous operationof SBR system at steady-state, the microorganisms regulatedtheir growth metabolism by decreasing their maximumgrowth rate (lower mH) together with increasing of substrateaffinity (lower KS) leading to state that microbial growth canbest be described by a variable kinetics most suited to thespecific operating conditions. This result has significantimplications, especially for environmental biotechnology,against the adoption of constant mH and KS valuessuggesting that they should be determined for each caseunder experimental condition approximating the selectedmode of operation. Furthermore, the glycogen storagecapability slightly increased under controlled growthconditions. The overflow mechanism for acetate wasobserved and could be modeled for both cultures, whichare subjected to controlled and uncontrolled growthconditions.

The results of this study provided strong evidence for thesignificant role of the respirometric data in facilitating areliable kinetic comparison of different experimental setswith a comprehensive modeling study. They furtherindicated that the decision on appropriate model structurerequires collecting information on the overall fate ofsubstrate under study, involving all major biochemicalmechanisms and parameters. In this respect, besides therespirometric data, other measurements of substrate, by-products and internally stored materials are strictly requiredfor an accurate interpretation of the real mechanism ofsubstrate utilization and corresponding growth kinetics.

Nomenclature

bH e

104

ndogenous decay rate (dayS1)

COD c

hemical oxygen demand (mg/L)

fP p

articulate inert fraction of endogenous biomass (S)

KS h

alf saturation constant for growth on glucose (dayS1)

KSA h

alf saturation constant for growth on acetate (dayS)

kgly ra

te constant for XSTO consumption (dayS1)

kSTO m

aximum storage rate (dayS1)

OD o

ptical density

OUR o

xygen uptake rate (mgO2/L/h)

PHB p

olyhydroxybutyrate

SS su

spended solids (mg/L)

SA a

cetate concentration (mgCOD/L)

S0/X0 in

itial substrate to microorganism ratio

SS g

lucose concentration (mgCOD/L)

TCA tr

icarboxylic acid

XSTO st

orage polymer as glycogen (mgCOD/L)

XH0 in

itial active biomass concentration (mgCOD/L)

YH h

eterotrophic yield on glucose (gcellCOD/gCOD)

YHA h

eterotrophic yield on acetate (gcellCOD/gCOD)

a a

cetate generation coefficient (S)

mH m

aximum heterotrophic growth rate (dayS1)

The contribution of Prof. D. Orhon was partly sponsored by the

Turkish Academy of Sciences.

Biotechnology and Bioengineering, Vol. 96, No. 1, January 1, 2007

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