Three-stage fermentation and kinetic modeling of bioflocculant by Corynebacterium glutamicum☆

Liang Shen ,Zhongtao An ,Qingbiao Li,Chuanyi Yao ,Yajuan Peng ,Yuanpeng Wang ,Ruihua Lai,Xu Deng ,Ning He ,*

1 Department of Chemical and Biochemical Engineering,College of Chemistry and Chemical Engineering,Xiamen University,The Key Lab for Synthetic Biotechnology of Xiamen City,Xiamen 361005,China

2 College of Life Science,Shenzhen Key Laboratory of Microbial Genetic Engineering,Shenzhen University,Shenzhen 518060,China

Keywords:Bioflocculant Fermentation Corynebacterium glutamicum Modeling Kinetics

ABSTRACT Fermentation of bioflocculant with Corynebacterium glutamicum was studied by way of kinetic modeling.Lorentzian modified Logistic model,time-corrected Luedeking-Piret and Luedeking-Pirettype models were proposed and applied to describe the cell growth,bioflocculant synthesis and consumption of substrates,with the correlation of initial biomass concentration and initial glucose concentration,respectively.The results showed that these models could well characterize the batch culture process of C.glutamicum atvarious initial glucose concentrations from 10.0 to 17.5 g·L?1.The initial biomass concentration could shorten the lag time of cell growth,while the maximum biomass concentration was achieved only at the optimal initial glucose concentration of 16.22 g·L?1.A novel three-stage fed-batch strategy for bioflocculant production was developed based on the model prediction,in which the lag phase,quick biomass growth and bioflocculant production stages were sequentially proceeded with the adjustment of glucose concentration and dissolved oxygen.Biomass of 2.23 g·L?1 was obtained and bioflocculant concentration was enhanced to 176.32 mg·L?1,18.62%and 403.63%higher than those in the batch process,respectively,indicating an efficient fed-batch culture strategy for bioflocculant production.

1.Introduction

Bioflocculant(microbial flocculant),secreted by certain algae,bacteria,fungias well as yeast,is an extracellular biopolymer,which is able to induce solid particles,cells and colloidal particles in a liquid suspension to flocculate.Contrasted with traditional chemosynthetic flocculant,bioflocculant is harmless and biodegradable with less secondary pollution[1].Bioflocculant can be produced at high rates and the extracellular bioflocculant is easily recovered from the fermentation broth[2,3].Nevertheless,the present reports about bioflocculant are mainly focused on the isolation of bioflocculant-producing microorganisms,chemical structures and properties of bioflocculant,and the mechanisms of flocculation[4-8].Research on the fermentation process of bioflocculant is still quite limited.

For this purpose,some research papers have probed in using the kinetic models to exploitan efficient strategy for bioflocculant production.Kang et al.[9],Liu et al.[10]and Cui[11]proposed the Logistic equation and Luedeking-Piret equation to describe microbial growth and bioflocculant synthesis by Aureobasidium pullulans or Enterococcus cecorum,but these models are not appropriate to predict the fermentation process[12].The Andrews model,describing substrate inhibition effect,could be simplified and employed to modify the Logistic equation.Cheng et al.[13]used the Andrews model modified Logistic equation to describe the growth of 1,3-propanediol-producing microorganism Klebsiella pneumoniae.The modified Logistic equation could well describe the cell growth at a constant initial substrate concentration of 50 g·L?1.In a range of substrate concentrations from 20 to 87 g·L?1,the model was also adapted well.However,the value of Cx,max,the maximum biomass concentration,was constantly yielded by parameter estimation at the constant initial substrate concentration of 50 g·L?1.In fact,Cx,maxvalues are dependenton the initial substrate concentration,so the relationship between Cx,maxvalues and initial substrate concentrations should be investigated.

In our previous study,bioflocculant REA-11,which was proved to be a polymer composed of galacturonic acid,was obtained from the fedbatch fermentation with Corynebacterium glutamicum[14-16].We found that the Logistic equation,time-corrected Gaden's model and two kinetic models in the form of Luedeking-Piret could well describe the cell growth,bioflocculant synthesis,and consumption of glucose and urea,respectively.It seems that these four models could well characterize the batch culture process of C.glutamicum at various initial biomass concentrations.However,they are not applicable as the initial glucose concentration changes.

Therefore,in this paper,kinetic models are constructed at different initial glucose concentrations for the batch fermentation process of bioflocculant by C.glutamicum.Based on the dynamic analysis,a novel three-stage fed-batch fermentation strategy is proposed to improve the bioflocculant production.

2.Materials and Methods

2.1.Materials

2.1.1.Microorganism

The strain used in this study was C.glutamicum,presently preserved at the China Center for Type Culture Collection(CCTCC 201005,Wuhan,China).

2.1.2.Media

The medium for slant consisted of(per liter):5 g glucose,1 g yeast extract,1 g beefextract,2 g tryptone,trace FeSO4and 15 g agar.The initial pH was adjusted to 7.2.

The seed medium consisted of(per liter):10 g glucose,0.5 g yeast extract,0.5 g urea,0.1 g KH2PO4,0.1 g K2HPO4,0.1 g NaCl,and 0.2 g MgSO4.The initial pH was adjusted to 8.0.

The fermentation medium consisted of(per liter):1 g yeast extract,1 g urea,0.1 g KH2PO4,0.1 g K2HPO4,0.1 g NaCl,and 0.2 g MgSO4.In carbon source single-factor experiments,the glucose concentration was 10,12.5,15,16.25,and 17.5 g·L?1.In fed-batch culture process,the initial glucose was 16.22 g·L?1.The initial pH of all media was adjusted to 8.0.

2.1.3.Cultivation conditions

The slants were incubated at 28°C for 16 h.For seed preparation,two loops of cells were inoculated into 100 ml of seed medium in a 250-ml flask and incubated at28°C,120 r·min?1on a reciprocal shaker until the optical density at 600 nm of seed culture reached 0.6-0.8.

For batch fermentation,the seed culture was inoculated at 5%(by volume)into 100 ml of the fermentation medium in a 250-ml flask.The inoculated flask was kept on a rotary shaker at 28°C,120 r·min?1for 48 h.

The fed-batch fermentation was performed on a 2-liter fermentor(Applikon Biotechnology Applikon BioBundle,Netherlands).5%(by volume)of seed culture was inoculated into 1400 ml fermentation culture.The three-stage fed-batch strategy was applied:(1)feeding with 60 g·L?1glucose solution(28.5 ml)and 32 g·L?1urea solution(14.25 ml)at the 6th hour;(2)feeding with 60 g·L?1glucose solution(95 ml)and 32 g·L?1urea solution(47.5 ml)at the 10th hour;(3)feeding with 60 g·L?1glucose solution(95 ml)and 32 g·L?1urea solution(47.5 ml)at the 19th hour.In this process,the agitation was stopped after 31 h till the culture finished and the aeration rate was kept at 2 L·L?1·min?1throughout the process.

2.2.Analytical methods

2.2.1.Determination of biomass

Cell growth was measured by dry cell mass(DCM).A total of 5 ml of fermented medium was centrifuged at 10000 g for 15 min,washed twice with distilled water,and dried at 105°C until a constant mass was achieved.

2.2.2.Determination of glucose

Glucose was determined according to the reference[17].Standard sucrose solutions were prepared at concentrations of 0,0.08,0.16,0.24,0.32 and 0.4 mg·ml?1separately.Each of the standards was mixed with 1.5 ml 3,5-dinitrosalicylic acid reagent.The optical density of the solutions was measured at 520 nm and the standard curve was obtained.Then 1 ml of cell-free culture broth was treated in the same way as described above.The sucrose concentration of the culture broth was calculated according to the standard curve.

2.2.3.Determination of urea

Urea concentration was measured by paradimethylaminobenzaldehyde(PDAB)method[18].A series of standard urea solutions at concentrations of 0,0.04,0.1,0.15,0.2,0.3 and 0.4 mg ·ml?1were prepared;5.0 ml PDAB solution(0.03 g·ml?1)and 3.0 ml HCl(10 mol·L?1)were added into each of the standard solutions,mixed and left standing for 15 min.The optical densities of the standard urea solutions were measured at446 nmand the standard curve was obtained.Then 1 ml of cell-free culture broth was treated in the same way as described above.The urea concentration of the culture broth was calculated according to the standard curve.

2.2.4.Determination of bioflocculant

Bioflocculant concentration was measured according to the methods described by Wang et al.[19]and Dische[20]through the detection of galacturonic acid,which was determined by carbazole colorimetry after eliminating sugar with ethanol.

3.Results and Discussion

3.1.Cell growth in the batch culture of C.glutamicum

The cell growth curves of C.glutamicum at various initial glucose concentrations from 10 to 17.5 g·L?1are shown in Fig.1.The results show that the highest biomass concentration appears at the initial glucose concentration of 16.25 g·L?1in the stationary phase while the lowest biomass is observed at initial glucose concentration of 10.0 g·L?1.

Fig.1.The cell growth in the batch culture of Corynebacterium glutamicum atvarious initial glucose concentrations.(■10 g·L?1; ●12.5 g·L?1; ▲15 g·L?1; ▼16.25 g·L?1;?17.5 g·L?1).

3.2.Logistic model and description of cell growth of C.glutamicum

Logistic equation was created by Verhulst for human population growth modeling and rediscovered by Pearl and Reed for the same purpose[21].The Logistic equation is a substrate independent model.It can well describe the inhibition of biomass on growth,existing in many batch fermentations[22].

The Logistic equation is

where Cx,0is the initial biomass concentration(g·L?1),Cx,maxis the maximum biomass concentration(g·L?1),μmis the maximum specific growth rate(h?1),and t is the fermentation time(h).

Curve fittings with Logistic model for cell growth were established according to our previous research( figure not shown)[12].The parameter values of the Logistic equation are given in Table 1.The maximum biomass concentration could be achieved at the initial glucose concentration of 16.25 g·L?1.Since the model parameter in Table 1 and the batch culture results in Fig.1 are in a good agreement,it could be assumed that the growth of C.glutamicum is a substrate independent and biomass self-inhibition process.This assumption is in conflict with most reports for C.glutamicum to produce organic acids,in which the fermentation performance was largely dependent on the substrate[23,24].In this meaning,Logistic model could not describe precisely the C.glutamicum culture for bioflocculant REA-11 production.

Table 1 Parameter values of the Logistic equation

3.3.Modified Logistic equation and description of cell growth of C.glutamicum

In a microbial growth medium,the maximum biomass concentration is closely related to the concentration of carbon source.Thus the relationship between Cx,maxand initial glucose concentration should be reflected in the Logistic equation.

The relationship between Cx,maxand initial glucose concentration is assumed as a peak-shaped function(data not shown).The peakshaped curves are in different forms,each with its own characteristics such as Gaussian,Logistic peak equation and Lorentzian equation[25].Fitted with the three models,R2were calculated to be 0.9944,0.9956 and 0.9993,respectively,indicating that Lorentzian equation achieved higher accuracy.Thus the Lorentzian equation is chosen to describe the peak-shaped curve,described as

where Cx,max0is the lowest maximum biomass concentration(g·L?1),Cs,0is the initialglucose concentration(g·L?1),Cs,cis the initialglucose concentration with the highest maximum biomass concentration(g·L?1),μmis the maximum specific growth rate(h?1),A and w are constant.The parameter values of the equation are calculated as Cx,max0=1.4612,Cs,c=16.2246,w=2.3072,A=0.6884,according to the least squares fitting by Matlab software.Thus the Lorentzian model is established as

The optimal initial glucose concentration for cell growth is calculated to be 16.22 g·L?1.The Lorentzian modified Logistic model is also established.

where μmis the mean of maximum specific growth rate,μm=0.2045,with SD=0.0075.

As shown in Fig.2,the modified Logistic model could well describe the cell growth at various initial glucose concentrations.

3.4.Modified Luedeking–Piret equation and description of bioflocculant production process

A delay of bioflocculant production was found compared with the cell growth in our previous study[12].Therefore,a parameter of the lag time,td,is introduced to modify the Luedeking-Piret model,called mixed model or part-growth-associated model.This modified Luedeking-Piret equation can be described as

where Yp/xis the product yield coefficient on biomass(mg·g?1),βis the non-growth-associated product formation coefficient(g·g?1·h?1),and tdis the lag time(h).

The integrated form of Eq.(5)is given by

The parameter values of the equation are as follows:td=?9.4056,Yp/x=9.0898,and β=0.3556,with R2=0.9738.

Eq.(6)is applied to simulate the experimental results at initial glucose concentration of 15.00 g·L?1and initial biomass concentration of 0.03 g·L?1[Fig.3(a)].The time-corrected Luedeking-Piret model fits the bioflocculant synthesis very well.

Fig.2.Experimental data(■)and simulation(-)of biomass concentration with modified Logistic equation in the batch culture of C.glutamicum.[Initial glucose concentration/initial biomass concentration,g·L?1/g·L?1:(a)10.00/0.03;(b)12.50/0.03;(c)15.00/0.02;(d)16.25/0.03;(e)17.50/0.03].

3.5.Substrate consumption models

Carbon substrate such as glucose is used to form cell structures and metabolic products as well as the maintenance of cell metabolism[12,22].The glucose consumption modelis a Luedeking-Pirettype equation as follows,in which the amount of carbon substrate used for product formation is assumed to be negligible.

where Yx/sis the biomass yield coefficient on glucose(g·g?1)and m is the maintenance coefficient(g·g?1·h?1).

Integrating Eq.(7)gives Eq.(8),

The values of parameters are estimated to be Yx/s=0.5264 and m=0.0835,with R2=0.9635.

Besides,the urea consumption in the batch fermentation of bioflocculant is proposed as

where Yx/uis the biomass yield coefficient on urea(g·g?1).

The integrated form of Eq.(9)is

The parameter value is calculated to be Yx/u=3.1983,with R2=0.9745.

Eqs.(8)and(10)are used to simulate the experimental results at initial glucose concentration of 13 g·L?1and initial biomass concentration of 0.03 g·L?1[Fig.3(b,c)].The results show that the Luedeking-Piret type equation successfully described glucose and urea consumption in the batch culture process of C.glutamicum.

3.6.Prediction of batch fermentation process of bioflocculant by C.glutamicum

As suggested by the above results,the four models could describe the batch fermentation process of bioflocculant REA-11 by C.glutamicum quite well.For further verification of the application of the models,we investigate their prediction potentials.

Fig.3.Experimental data(■)and simulation(-)of bioflocculant production with time-corrected Luedeking-Piret model and substrate consumption with Luedeking-Piret type models.(a)Bio flocculant production;(b)glucose consumption;(c)urea consumption.

Fig.4.Biomass prediction by Lorentzian modified Logistic equation in the batch culture of C.glutamicum at various initial biomass and glucose concentrations.(IBC:initial biomass concentration,g·L?1;IGC:initial glucose concentration,g·L?1).

Fig.4 gives the prediction curves for cell growth of C.glutamicum with the Lorentzian modified Logistic equation.The cell growth is accelerated at high initial biomass concentration from 0.01 to 0.05 g·L?1[Fig.4(a)].Meanwhile,glucose exhibits an inhibition on the cell growth at concentrations above 16.225 g·L?1[Fig.4(b)],which is consistent with the optimal batch culture condition of glucose concentration.Regarding the comprehensive effect of these two factors as shown in Fig.4(a,b),it seems that the high initial biomass concentration could shorten the lag phase,but the maximum biomass concentration is reached only at the optimal initial glucose concentration of 16.225 g·L?1.Similarly,Fig.5 gives the prediction curves of bioflocculant production and substrate consumption with the time-corrected Luedeking-Piret model and Luedeking-Piret type models at various initial biomass and glucose concentrations.Results also indicate that the yield of bioflocculant is dominant by the optimized initial glucose concentration,and the high initial biomass concentration could increase the production rate in the first stage of fermentation.

Kinetic modeling is an essential step in developing a fermentation process since the models can be used to determine the optimal operation condition for the production of a target metabolite[26-28].Therefore,a new technical process could be designed based on the models proposed here for the bioflocculant fermentation with C.glutamicum.

3.7.Three-stage fed-batch culture of C.glutamicum for bioflocculant production

Fig.5.Prediction of bioflocculant production and substrate consumption with modified Luedeking-Piret model and Luedeking-Piret type models.(IBC:initial biomass concentration,g·L?1;IGC:initial glucose concentration,g·L?1).

According to the prediction results from the kinetic models,a threestage fed-batch strategy was presented for bioflocculant production by C.glutamicum,as described in the Materials and Methods section.16.22 g·L?1was chosen as the initial glucose concentration based on the modified Logistic model calculation.As shown in Fig.6,the first stage(0-6th hour)was determined by the lag time from the prediction curve in Fig.4.For the second stage(6th-31th hour),glucose was fed to maintain the concentration about 16 g·L?1to continuously benefit the cell growth,at the 6th,10th and 19th hour.The biomass concentration was quickly increased to a high level about 1.6 g·L?1,which was close to the maximum biomass concentration from the model prediction value(Fig.4)at the end of the second stage.The third stage(after 31th hour)was thereafter designed to harvest bioflocculant by manipulating dissolved oxygen(DO).During this process,the agitation was stopped after 31 h till the culture finished and the aeration rate was kept at 2 L·L?1·min?1throughout the process.This is ascribed to the important role of DO in bioflocculant production.Our previous study showed that bioflocculant REA-11 was a polygalacturonic acid biosynthesized from phosphate-1-glucose[29].The metabolic flux to Pentose pathway increased nearly 80%with DO increased from 10%to 70%.The metabolic flux in Embden-Meyerh of-Parnas(EMP)pathway almost remained the same while those with the acetic acid and lactic acid synthetic pathway increased and that with REA-11 synthesis decreased.This result is consistent with the conclusion that adenosinetriphosphate(ATP) flux is more favorable for cell growth but is unfavorable for the synthesis of REA-11[14].

Fig.6.Time courses for bioflocculant production with the three-stage fed-batch culture strategy by C.glutamicum.

The results of the overall three-stage fermentation showed that a biomass of2.23 g·L?1was obtained and the bioflocculant concentration was enhanced to 176.32 mg·L?1,18.62%and 403.63%higher than those in the batch process,respectively,indicating an effective fed-batch strategy for bioflocculant production by C.glutamicum(Fig.6).The results suggest the rationality and practicability of the kinetic models.

4.Conclusions

Lorentzian modified Logistic model was constructed to describe the cell growth in the batch culture of C.glutamicum with correlation of initial glucose concentration.Time-corrected Luedeking-Piret model and Luedeking-Piret type models were employed to characterize bioflocculant production and substrate consumption.All the four models fit the batch process very well.Model prediction results show that the initial biomass concentration could shorten the lag time of cell growth,while the maximum biomass concentration is achieved only at the optimal initial glucose concentration,i.e.16.22 g·L?1in this study.

Based on the dynamic data from the kinetic models,a three-stage fed-batch strategy was investigated,in which the fermentation process sequentially passed through the lag phase,quick biomass growth and bioflocculant production stages with adjustment of the glucose concentration and DO.Higher yields of biomass(2.23 g·L?1)and bioflocculant(176.32 mg·L?1)were obtained through this new strategy,implying an applicable bioflocculant production.

Nomenclature

A constant

Β non-growth-associated product formation coefficient,g·g?1·h?1

Cs,0initial glucose concentration,g·L?1

Cs,cinitial glucose concentration with the highest maximum biomass concentration,g·L?1

Cu,0initial urea concentration,g·L?1

Cx,0initial biomass concentration,g·L?1

Cx,maxmaximum biomass concentration,g·L?1

Cx,max0lowest maximum biomass concentration,g·L?1

m maintenance coefficient,g·g?1·h?1

t fermentation time,h

tdlag time,h

w constant

Yp/xproduct yield coefficient on biomass,mg·g?1

Yx/sbiomass yield coefficient on glucose,g·g?1

Yx/ubiomass yield coefficient on urea,g·g?1

μmmaximum specific growth rate,h?1