Lactic acid production with Lactobacillus casei ... - Wiley Online Library

Eng. Life Sci. 2011, 11, No. 5, 517–527

517

George Kostov1 Mihail Angelov2

Research Article

Zapryana Denkova3 Iliyan Dobrev3

Lactic acid production with Lactobacillus casei ssp. rhamnosus NBIMCC 1013: Modeling and optimization of the nutrient medium

Bogdan Goranov2 1

Department of Wine and Beer, University of Food Technologies Plovdiv, Plovdiv, Bulgaria

2

Department of Biotechnology, University of Food Technologies Plovdiv, Plovdiv, Bulgaria

3

Department of Organic Chemistry and Microbiology, University of Food Technologies Plovdiv, Plovdiv, Bulgaria

The medium needed to perform a fermentation process with viable cells of Lactobacillus casei ssp. rhamnosus NBIMCC 1013 for the production of lactic acid was modeled and optimized. On the basis of single-factor experiments and statistical analysis, the significant factors affecting the fermentation process, i.e. the concentration of carbon source, concentrations of both yeast and meat extracts, and the range of variability of these components were determined. Modeling and optimization of the medium contents were performed using central composite design. The composition of the medium used for the production of lactic acid (g/L) was as follows: glucose 69.8, meat extract 17.07, yeast extract 10.9, CH3COONa 10, K2HPO4 0.25, KH2PO4 0.25, MgSO4 7H2O 0.05, and FeSO4 0.05. The maximum specific growth rate of the lactic acid bacteria (m 5 0.51 h1) and other kinetic parameters were determined during cultivation in a laboratory bioreactor using the logistic equation and the Luedeking–Piret model. The obtained medium allows the production of lactic acid under optimum conditions, at high specific sugar assimilation rates and high lactic acid accumulation rates. The positive results of the paper are the new nutrient medium for lactic acid production and the process kinetic model, enabling scaling up and switching to a continuous process. Keywords: Central composite design / Fermentation medium / Lactic acid / Optimization Received: January 31, 2010; revised: December 27, 2010; accepted: February 20, 2011 DOI: 10.1002/elsc.201000022

1

Introduction

The share of foods containing preservatives increases rapidly in the nutrition of contemporary people. Although they are hardly toxic, they directly affect the gastrointestinal microflora, destroying its development. Therefore, microbial metabolites are applied, to achieve biopreservation on the one hand and a beneficial influence on the gastrointestinal tract on the other hand. Many chemical substances are continually involved in the biochemical processes going on in living systems. Among these, lactic acid serves as an important metabolite of an equally important energy-yielding process [1]. Lactic acid is a carboxylic acid with the chemical formula CH3CHOHCOOH and is a colorless liquid organic acid [2]. Lactic acid has a mild

Correspondence: Dr. George Kostov ([email protected]), Wine and Beer Department, University of Food Technologies, 26 Maritza blvd., 4002 Plovdiv, Bulgaria Abbreviations: CCD, central composite design; DW, Durbin–Watson

& 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

flavor and is applied in the preservation of foods or as an additive to them. It has other applications in other fields of industry, e.g. in the pharmaceutical industry as a disinfecting solution, for the production of biodegradable polymers, polyesters, and different inks and paints, as well as in the furriery industry [2–8]. Lactic acid is also used as an acidulate, as flavoring or pH-buffering agent, or as inhibitor of bacterial spoilage in many processed foods. The esters of lactic acid are used in baking foods, as emulsifying agents [2, 9]. Production of lactic acid can be carried out in two ways: chemical synthesis and carbohydrate fermentation [2]. Chemical synthesis in most cases leads to the production of a racemic mixture of the L- and D-forms of the acid. The method of carbohydrate fermentation is relatively cheaper and thus preferable. Lactic acid is an organic acid that is produced as a result of the fermentation metabolism of lactic acid bacteria. Lactic acid bacteria of the genera Pediococcus, Lactobacillus, and Leuconostoc are used as producers of lactic acid. The homofermentative lactic acid bacteria are suitable for the industrial production of lactic acid. Other producers of lactic acid are molds, e.g. of the genera Mucor and Rhizopus. The choice of

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G. Kostov et al.

microorganism for industrial uses depends on the type of the carbon source and on the productivity of the selected strain [2–8]. Fermentative production of lactic acid is advantageous over its synthetic production in that, by choosing a stream of lactic acid bacteria that produces only one isomer of lactic acid, an optically pure product can be obtained. Microorganisms need a carbon source for their growth and development. All microorganisms, including Lactobacillus delbrueckii ssp. delbrueckii, assimilate glucose. This specific microorganism also assimilates sucrose; therefore, molasses are the most appropriate raw material. L. delbrueckii ssp. bulgaricus metabolizes lactose but does not metabolize sucrose. The most suitable raw material for it is whey. L. casei ssp. rhamnosus and Lactobacillus helveticus ssp. rhamnosus transform both glucose and lactose. Also for these two strains, the most suitable raw material is whey. L. delbrueckii ssp. lactis metabolizes glucose, lactose, and sucrose. Starch is another potential carbon source. The choice of a strain depends on how it performs hydrolysis. In hydrolysis with malt a- and b-amylases, the result is mostly maltose. Microorganisms that assimilate maltose are L. delbrueckii ssp. lactis, some strains of L. delbrueckii ssp. delbrueckii, and others. When a-amylases and glucoamylase are used, the result is glucose and some glucose oligosaccharides. The strains mentioned above are suitable in this case. The strains Lactobacillus amylovarus and Lactobacillus amylophilus hydrolyze starch and, at the same time, ferment it to lactic acid. Starch raw materials can be fermented by some mold species, e.g. Rhizopus sp., and most often by Rhizopus oryzae [2–8]. The second significant organogenic element is nitrogen. Both organic and inorganic substances (NH3, NH4OH, (NH4)2SO4, (NH4)2HPO4) are used as nitrogen sources for lactic acid fermentation. Organic nitrogen sources are yeast extract, meat extract, peptone, and malt rootlets. Amino acids and B vitamins are needed for lactic acid biosynthesis. When the amount of biotin (vitamin H) is insufficient, the bacteria need different amino acids. In media rich in vitamin H, it is not necessary to add aspartate. There is a similar relationship between folic acid (vitamin B9) and the synthesis of lactic acid. There are a few irreplaceable amino acids specific for each representative of the lactic acid bacteria. It is obligatory for mineral salts to be added to the medium as they serve as sources of macro- and microelements. These include MgSO4, MnSO4, and FeSO4. Phosphorus is necessary for the development of lactic acid bacteria. NH1 4 cannot be used as only nitrogen source, but its presence influences the assimilation of amino acids. Fatty acids also influence the development of lactic acid bacteria, although the mechanisms of their effect have not yet been well studied [3, 4]. The diversity of combinatorial interactions of the medium components with the metabolism of the cells and the large number of medium constituents necessary for cellular growth and production do not permit a satisfactorily detailed modeling. For this reason, experimental search procedures in simultaneous shaking flask experiments are used to optimize the fermentation media. As an alternative to the methods of statistical experimental design employed in this field for many decades, the use of stochastic search procedures has recently been evaluated, since these require neither the unimodality of the response surface nor limitations in the number of medium components under


consideration. Response surface methodology (RSM) is an efficient experimental strategy to seek optimal conditions for a multivariable system [10]. It has been successfully employed for optimization of the medium composition and the operating conditions in many bioprocesses [10–14]. The use of various supplements (yeast extract, meat extract, peptone) improves the quality of the culture medium, by stimulating the growth of lactic bacteria and enhancing the lactic acid yield. However, the use of these substances in large quantities is very expensive and can reach about 30% of the total cost of lactic acid production. High concentrations of these components can lead to an inhibition of the bacterial growth and a reduction of the metabolic product yield. Therefore, it is necessary to develop an industrially acceptable process with increased productivity and optimal composition of the nutrient medium. These requirements can be achieved by different methods: development of continuous fermentation for the production of lactic acid with immobilized cells, optimization of the culture medium composition, exploration of the fermentation process kinetics, or development of control systems for the fermentation process. Optimization of the medium composition for higher yields of lactic acid by using statistical methods has been the subject of several publications. Since there is a specific link between the strain and the medium for its cultivation, the authors have worked in different directions: optimization of cultivation conditions to increase the yield of lactic acid [14–20], studying various substrates for lactic acid production [16, 21–25], and optimization of the nutrient media for lactic acid production by different types of microorganisms [16, 18–21, 26–33]. Our previous works have focused on the exploration of the possibilities of obtaining lactic acid from immobilized lactic acid bacteria and on the feasibility to carry out a continuous fermentation process for lactic acid production [34, 35]. The purpose of the present work was to optimize the culture medium composition for lactic acid production by Lactobacillus casei ssp. rhamnosus NBIMCC 1013. The aim of the study was to use a combination of strain-specific culture media to achieve maximum yields of lactic acid. The design of an experiment was performed and the results were statistically processed in order to achieve the aim. This is the initial step in the development of a continuous fermentation system for obtaining lactic acid from free and immobilized cells. It is known that the yield of a metabolite product is related to the specificity of each strain to be cultivated on a suitable cultural medium. Therefore, the optimization of these media is an important milestone in the development and implementation of every process in the biotechnology industry. Finally, the kinetic parameters of the fermentation process were identified with regard to the possibilities for its control and the shift to a continuous fermentation system.

2

Materials and methods

2.1

Microorganisms

Lactic acid bacteria from the strain L. casei ssp. rhamnosus NBIMCC 1013 were used. They were obtained from the


Eng. Life Sci. 2011, 11, No. 5, 517–527

Nutrient medium optimization for lactic acid production

collection of the Department of Organic Chemistry and Microbiology at the University of Food Technologies in Plovdiv.

2.3

2.2

Medium and cultivation conditions

MRS broth (g/L): glucose 20, peptone 10, meat extract 8, yeast extract 4, CH3COONa 5, tri-ammonium citrate 2, MgSO4 7H2O 0.2, MnSO4 7H2O 0.05, KH2PO4 2, Tween80 1 mL. Fermentation media (g/L) for L. casei ssp. rhamnosus NBIMCC 1013: (i) glucose 20, meat extract 12.5, yeast extract 5.5, CH3COONa 10, K2HPO4 0.25, KH2PO4 0.25, MgSO4 7H2O 0.1, MnSO4 7H2O 0.05, FeSO4 0.05, (ii) lactose 20, yeast extract 5.5, peptone 12.5, CH3COONa 10, K2HPO4 0.25, KH2PO4 0.25, MgSO4 7H2O 0.1, MnSO4 7H2O 0.05, FeSO4 0.05, (iii) fermentation media according to the plan of the experiment. All media were sterilized for 20 min at 1211C. Cultivation was conducted in flasks under static conditions in a thermostat at 371C. The accumulation of lactic acid was measured after 24 and 48 h from the beginning of the experiment, for all preliminary experiments. The accumulation of lactic acid for the design experiment was measured after 12 h from the beginning of the experiment, in order to make correct conclusions. All flasks are inoculated with 1% inocula of L. casei ssp. rhamnosus NBIMCC 1013 (24-h culture).

2.3.1

519

Analysis Titratable acidity

For the determination of the acid-forming ability of the lactic acid bacteria, the titratable acidity (expressed as Toerner degree, 1T) was determined by titration of 10 mL sample with 0.1 N sodium hydroxide to a pink endpoint using phenolphthalein as the indicator (11T 5 0.009 g lactic acid) [36, 37].

2.3.2

Determination of the viable counts of lactobacilli

The samples were diluted tenfold according to the method of serial dilution in a saline solution. Later, they were spread onto petri dishes with MRS medium and incubated for 3 days at 371C, until single colonies were formed [36, 37].

2.4

Bioreactor and cultivation conditions

Batch cultivation of L. casei ssp. rhamnosus NBIMCC 1013 was carried out in a laboratory bioreactor with a geometric volume of 2 L and the control device Applikon ADI 1020 (Fig. 1). The reactor is equipped with a six-blade turbine stirrer and four blades. There are two orifices on the lid: one for feeding and the other for the installation of heat exchangers and sensors. The installation includes sensors and mechanisms for monitoring and control of the main bioprocess variables: pH, redox potential (Eh, mV), temperature (1C), dissolved oxygen (%, optional). The sterilized cultural medium and inocula are inserted into the apparatus using a peristaltic pump. The temperature of cultivation was 371C. The time of cultivation was 24 h.

Figure 1. Scheme of the laboratory bioreactor. (1) Apparatus with geometric volume of 2 L, (2) blades, (3) thermo-strength Pt100, (4) heater, (5) heat exchanger for cold water, (6) stirrer, (7) pH electrode, (8) flask for fermentation medium and inoculum, (9) filter, (10) peristaltic pump, (11) motor, (12) control device, (13) lid.



520

2.5

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G. Kostov et al.

Mathematical analysis and processing of the experiment results

Table 1. Acid-producing ability of L. rhamnosus 1013 in medium containing glucose and lactose during 48 h

Central composite design (CCD) was used for optimization of the medium composition. The mathematical processing of the results from the experiments is accomplished using Microsoft Excel and Statgraphics Centurion XV (trial version) [5, 38]. The values of the coefficients in Eq. (3) are calculated in accordance with the dependence [5, 38] bji ¼

N X

Xji Yi =

N X

i

bjj ¼

N X i

Xj0 Yi =

N X

ðX 0 Þ2j ;

Xji2

Cultivation under static Cultivation in bioreactor conditions with stirring Strain Substrate

1013 1013

Glucose Lactose

Titratable acidity (1T)

Titratable acidity (1T)

24 h

48 h

24 h

48 h

156.1 83

220 120

110.6 61.8

200 120

ð1Þ

i

Xj0

¼

Xj2

i

N X

! Xij2 =N

ð2Þ

i¼1

where Xji is the coded value of the experimental factor (i 5 1, 2, 3; j 5 1, 2, 3), Yi is the observed value of the test function (titratable acidity) at the corresponding point, and n is the number of experimental factors. The calculation of the values of the coefficients in the regression equation is carried out with the presented dependencies and using the algorithm of Statgraphics Centurion XV (trial version). The optimization of the target function is performed by the gradient method, with fixing of some factors of a certain level. The desirability function for optimization d(y) expresses the desirability of a response value equal to y on a scale of 0–1. This function takes one of the three forms, depending on whether the response is to be maximized, minimized, or a target value hit [5, 38]. The optimization is performed by an algorithm embedded in the used software.

3

Results and discussion

3.1

Choice of carbon source and investigation on the correspondence between the amount of carbon source and the accumulation of lactic acid

The influence of the carbon source on the production of lactic acid was studied. The titratable acidity is measured after 24 and 48 h in media containing glucose (fermentation medium (a) in Section 2.2) and lactose (fermentation medium (b) in Section 2.2). The results are given in Table 1. The results are the average of four measurements for each experimental variant. The data show that more lactic acid is accumulated in the medium containing glucose. It also shows that lactic acid fermentation is performed better under static conditions and that the titratable acidity is nearly twice as high in the medium containing glucose as in the medium containing lactose. The lower production of lactic acid under dynamic conditions (cultivation in a bioreactor) can be explained by the non-optimized culture conditions. Therefore, all experiments to optimize the composition of the culture medium were performed in flasks. The other main reason to choose the static experiments in


optimizing the composition of the medium is the ability to optimize all versions of the environment to be set in the same initial conditions. On the basis of these experiments, glucose was used as the carbon source in the next series of experiments. The accumulation of lactic acid by lactobacilli is both a substrate- and product-inhibited process, which means that the amount of the metabolites in the medium is strongly influenced by the initial concentration of the carbon source. For this purpose, it is necessary to determine the concentration of the sugars in the medium at which the inhibition is observed. The experiments are conducted using fermentation medium (a) with varying concentrations of the substrate. Data from these experiments are given in Fig. 2. The results are the average of four measurements for each point, which guarantees the accuracy of this research. It is proven by analysis of variance (ANOVA). The value of Kohren’s criterium G 5 0.375 is lower than the critical value Gcrit 5 0.4169 (n 5 4, k 5 3, and a 5 95%), which shows that the dispersion values of the experiments in each point are homogenous. As can be seen in Fig. 2, the optimal value of glucose concentration is between 4 and 6%. At higher concentrations of the carbon source, the titratable acidity of the medium starts to decrease.

3.2

Influence of the concentration of yeast extract and meat extract on the accumulation of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013

Lactic acid bacteria need additives in the medium in order to produce lactic acid. The additives promote the growth and development of the microbial culture and allow an increase in the amount of the final product. The effects of the concentrations of yeast extract and meat extract as complex raw materials on the growth of L. caseissp. rhamnosus NBIMCC 1013 and the production of lactic acid were studied (Figs. 3 and 4). The studied medium components increase the amount of lactic acid produced. As can be seen in Figs. 3 and 4, the titratable acidity of the medium increases to a certain value; then, the lactic acid accumulation rate decreases, i.e. meat extract and yeast extract lead to substrate inhibition after reaching a certain value. For meat extract, this value is 1%; for yeast extract, it is 0.55%. Slight accumulation of lactic acid was observed at meat extract concentrations above 1% (Fig. 3). This accumulation of


Eng. Life Sci. 2011, 11, No. 5, 517–527


are most frequently used whereas third-power models are rarely used. A second-power model can be obtained using CCD [5, 38].

180 160 Titratable acidity, 0T

521

140

Y ¼ b0 1

k X

bi Xi 1

i¼1

120 100

k X

bij Xi Xj 1

n X

bii Xi2

ð3Þ

i¼1

1ojoiok

The data for the limits of variability of the medium components are given in Table 2. For the right performance of the experiment, star point a 5 71.4214 is chosen. The value of

80 60

240

40 4

6 8 Glucose, %

10

12

Figure 2. Influence of the concentration of the carbon source on the accumulation of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013.

product is within the error of the experiment (which for this study is about 4%). Therefore, 1% can be considered as the optimal concentration of meat extract in the medium. At a concentration of yeast extract in the medium of 40.8%, a reduction in the concentration of formed lactic acid was observed. This reduction is relatively small and within the experimental error (5%). Therefore, 0.8% yeast extract in the medium can be considered as optimal for the development of the microbial population and accumulation of lactic acid. The studied two factors – yeast extract and meat extract – showed that increasing their amounts in the medium leads to an increase in the lactic acid production up to a certain concentration in the cultural medium. Above this concentration, slightly decreased or constant levels of the titratable acidity of the medium were observed. In the single-factor experiments, the other factors are fixed at a defined level. Thus, it is difficult to determine the optimal value of the investigated factors since the interaction between the components in the medium is not taken into account. It is necessary to increase this interaction and to determine accurately the optimal values of the component in the middle. Single-factor experiments are the basis for determining the limits of variation of the tested components in the construction of the matrix of the planned experiment.

Titratable acidity, 0T

2

220 200 180 160 140 0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

Meat extract, %

Figure 3. Influence of the concentration of meat extract on the accumulation of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013.

210 200

Titratable acidity, 0T

0

190 180 170 160 150 140 130 0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

Yeast extraxt, %

3.3

Optimization of the medium composition using CCD

Single-factor experiments are conducted in order to determine the limits of variability of the chosen components in the medium, and to select a proper type of the mathematical model. The area where the optimum of the regression mathematical model is located is called almost stationary. Its characteristic feature is that it is nonlinear. For an adequate description of this area, it is necessary to look for models from a higher level. In the scientific literature, second-power models


Figure 4. Influence of the concentration of yeast extract on the accumulation of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013. Table 2. Limits of variation of the medium components Component (%) a

Lower level Basic level Upper level 1a

0.9 3 Glucose (X1) Yeast extract (X2) 0.1 0.25 Meat extract (X3) 0.292 0.5

8 0.6 1

13 0.95 1.5

15.1 1.09 1.707


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Table 3. Plan of the experiment and results from the experiments for variation of lactic acid accumulation by L. casei ssp. rhamnosus NBIMCC 1013 after 12 h since the beginning of the process Row

X1

X2

X3

Observed value

Fitted value

Lower 95.0%

Upper 95.0%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

1 1 0 1 1 1.41421 0 0 0 1 1 0 1.41421 0 0 1 0 1

1 1 0 1 1 0 1.41421 1.41421 0 1 1 0 0 0 0 1 0 1

1 1 1.41421 1 1 0 0 0 1.41421 1 1 0 0 0 0 1 0 1

115.2 140.0 143.9 122.0 145.8 80.0 158.0 140.1 122.5 128.3 109.3 125.0 109.2 136.1 135.0 138.0 136.1 85.5

111.28 133.954 144.975 116.621 150.748 83.1358 165.494 134.189 121.225 128.612 111.818 133.1 107.648 133.1 133.1 133.415 133.1 94.4855

103.955 126.629 137.65 109.296 143.423 74.1647 156.523 125.218 113.9 121.287 104.493 127.921 98.6765 127.921 127.921 126.09 127.921 87.1606

118.604 141.279 152.3 123.946 158.073 92.1069 174.465 143.16 128.55 135.937 119.143 138.279 116.619 138.279 138.279 140.74 138.279 101.81

Table 4. ANOVA for the target function ‘‘Lactic acid’’ Source

Sum of squares

Df

Mean square

F-ratio

p-Value

Significance

Before excluding the insignificant coefficients (primary analysis) A: Glucose 901.247 1 B: Yeast extract 1469.97 1 C: Meat extract 846.118 1 AA 2843.84 1 AB 15.4013 1 AC 54.6012 1 BB 560.571 1 BC 90.4512 1 CC 1.59027 1 Total error 244.832 8 Total (corr.) 7028.62 17

901.247 1469.97 846.118 2843.84 15.4013 54.6012 560.571 90.4512 1.59027 30.6039

29.45 48.03 27.65 92.92 0.50 1.78 18.32 2.96 0.05

0.0006 0.0001 0.0008 0.0000 0.4982 0.2184 0.0027 0.1239 0.8254

Significant Significant Significant Significant Insignificant Insignificant Significant Insignificant Insignificant

After excluding the insignificant coefficients (primary analysis)b) A: Glucose 901.247 1 B: Yeast extract 1469.97 1 C: Meat extract 846.118 1 AA 2843.84 1 BB 560.571 1 Total error 406.876 12 Total (corr.) 7028.62 17

901.247 1469.97 846.118 2843.84 560.571 33.9063

26.58 43.35 24.95 83.87 16.53

0.0002 0.0000 0.0003 0.0000 0.0016

Significant Significant Significant Significant Significant

a)

a) R2 5 96.5166%; R2 (adjusted for d.f.) 5 92.5979%; standard error of estimate 5 5.53208; mean absolute error 5 3.11081; DW statistics 5 1.83193 (p 5 0.3667); lag 1 residual autocorrelation 5 0.0762662. b) R2 5 94.2112%; R2 (adjusted for d.f.) 5 91.7991%; standard error of estimate 5 5.82291; mean absolute error 5 4.06315; DW statistics 5 1.75818 (p 5 0.4169); lag 1 residual autocorrelation 5 0.00280266.

the star arm depends on the number of input factors n 5 3 and of replicates in the design center n0 5 4. It is selected from the tables and is set in the algorithm of the used software [5, 38]. The plan of the experiment and the results from the experiments are shown in Table 3. The accumulation of lactic acid is measured after 12 h from the beginning of the process, so that the influence of the different components of the medium on the accumulation of lactic acid can be determined accurately.


On the basis of the results (Table 3), an analysis of the proposed CCD was conducted and a mathematical model was obtained (Eq. 4). The results from the analysis of the proposed mathematical model are given in Table 4. In accordance with the data in Table 4 and the Pareto diagram (Fig. 5), all insignificant factors were excluded from the mathematical model. Figures 6–8 show the graphic interpretations of the obtained mathematical model (3).


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Standardized Pareto Chart for Lactic acid AA B:Yeast extract A:Glucose C:Meat extract BB BC AC + -

AB CC 0

2

4

6

8

10

Standardized effect

Figure 5. Pareto diagram for the significance of the coefficients in the mathematic model.

Table 5. Optimum value of the mathematical model Factor

Low

High

Optimum

Optimum (%)

Glucose Yeast extract Meat extract

1.41421 1.41421 1.41421

1.41421 1.41421 1.41421

0.202704 1.41421 1.41421

6.98 1.09 1.707

Estimated Response Surface Meat extract=1,41421

Lactic acid, oT

Lactic acid 120,0

180 170 160 150 140 130 120 110 100 90 80

130,0 140,0 150,0 160,0 1,4 0,7 -1,4

-0,7

0 Glucose

0,7

1,4

170,0

0 -0,7 Yeast extract -1,4

Figure 6. Influence of glucose and yeast extract on the production of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013.

LA ¼ 133:1 8:67X1 111:07X2 18:40X3 18:85X12 18:37X22 ð4Þ ANOVA (Table 3) partitions the variability in lactic acid into separate pieces for each of the effects. It then tests the statistical significance of each effect by comparing the mean square against an estimate of the experimental error. In this case, five effects have p-values of less than 0.05, indicating that they are significantly different from zero at the 95.0% confidence level. Using observation and the estimated value, the correlation coefficient R2 is calculated. The statistical value R2


523

indicates that the model as fitted explains 94.21% of the variability in lactic acid. The adjusted R2 statistical value, which is more suitable for comparing models with different numbers of independent variables, is 91.79%. The standard error of the estimate shows the standard deviation of the residuals to be 5.82. The mean absolute error (MAE) of 4.06 is the average value of the residuals. The Durbin–Watson (DW) statistical model tests the residuals, to determine whether there is any significant correlation based on the order in which they occur in your data file. Since the p-value is greater than 5.0%, there is no indication of serial autocorrelation in the residuals at the 5.0% significance level [5, 38]. All three studied factors significantly influence the accumulation of lactic acid, but the most influential among them is the carbon source. As seen from the coefficients of the model (Eq. 3) and the Pareto diagram (Fig. 5), the increase in the concentration of the carbon source leads to a decrease in the product yield. This indicates substrate inhibition after growth of the microbial culture, meaning that the increase in the concentration above the optimum value (Table 5) leads to a decrease in the product yield. The strong negative influence of the carbon source on the production of lactic acid is proven by the value of the coefficient of X12 . This coefficient (b11 5 18.85) serves as a proof for substrate inhibition of the process. The other two factors have a positive influence on the target function and, to a certain extent, compensate for the substrate inhibition. The increase in their concentration in the medium leads to an increase in the concentration of lactic acid in the medium. The concentration of yeast extract in the medium has a stronger influence on the target function. In this case, there is some influence on the effect of second power, i.e. the increase in the concentration of the yeast extract provides the microbial population with the needed amino acids, vitamins, and other microcomponents that compensate for the influence of the substrate inhibition (Fig. 6). The influence of the meat extract on the concentration of lactic acid is relatively poor (Fig. 7). Nonetheless, this component has a positive influence on the production of the final product. The combined influence of the chosen factors does not significantly influence the production of lactic acid, which means that, besides substrate inhibition, there are no other factors that lead to a decrease in the production of lactic acid (Fig. 8). The optimum values of the three components are given in Table 5. The optimization of the obtained model is executed using special software. The maximum titratable acidity according to the mathematical model is 178.351T (16.05 g/L lactic acid). The obtained values of the concentrations of the yeast and the meat extract represent the optimum level in order to minimize the influence of substrate inhibition on the microbial population.

3.4

Cultivation in bioreactor with optimum medium

On the basis of the executed optimization, the composition of the optimal medium was determined (g/L): glucose 69.8, meat extract 17.07, yeast extract 10.9, CH3COONa 10, K2HPO4 0.25, KH2PO4 0.25, MgSO4 7H2O 0.1, MnSO4 7H2O 0.05, FeSO4


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G. Kostov et al.

Estimated Response Surface Yeast extract=1,41421

Lactic acid, oT

Lactic acid 120,0

180 170 160 150 140 130 120 110 100 90 80 -1,4

130,0 140,0 150,0 160,0 170,0

1,4

-0,7

0

0,7

1,4

Glucose

0,7 0 Meat extract -0,7 -1,4

Figure 7. Influence of glucose and meat extract on the production of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013.

Estimated Response Surface Glucose=-0,202704

Lactic acid, oT

Lactic acid 120,0

180 170 160 150 140 130 120 110 100 90 80

130,0 140,0 150,0 160,0 1,4

170,0

0,7 -1,4

-0,7

0 0,7 Yeast extract

1,4

0 Meat extract -0,7 -1,4

Figure 8. Influence of meat extract and yeast extract on the production of lactic acid by L. casei ssp. rhamnosus NBIMCC 1013.

1000

65

800

60

600

55

400

50

200

45

0

pH

70

The lactic acid bacteria grew with a high specific growth rate mm 5 0.511 h1. The proposed mathematical model shows a relatively low coefficient of internal population competition b 5 2.6 1016 mL/CFU h. At the same time, more lactic acid is accumulated in comparison to the primary experiments. This shows that the culture developed under optimum conditions and under minimum influence of product and substrate inhibition. The culture entered relatively fast into the stationary phase, and during the exponential phase, the redox potential remained at the same value. This allowed the continuous accumulation of lactic acid. On entering the stationary phase, the redox potential changed its value and allowed the accumulation of the maximum amount of lactic acid in the medium. After 24 h, product inhibition occurred. It is known that lactic acid is a final product of the microbial metabolism and it is expected to be accumulated by the cells in the stationary phase. In the equation of the product

5,6

240

5,4

220

5,2

200

5,0

180

4,8

160

4,6

140

4,4

120

4,2

100

4,0

80

3,8

60

15,5 15,0

o

1200

Eh, mV

Glucose (S), g/l

75

obtained from the optimization procedures must be confirmed experimentally in a greater volume. In order to finish the present study, cultivation in a bioreactor with mechanical stirring was performed under the optimum conditions for the microbial culture. The accumulation of product in the medium and the development of the culture were measured. During cultivation for 24 h, the changes in the redox potential values of the medium were also measured. The results are given in Fig. 9. The survey results shown in Fig. 9 are the average of five independent cultures in optimized nutrient medium. Identification of the kinetics parameters of batch cultivation was executed on the basis of the conducted experiment according to the logistic equation (Eq. 5) [5, 19]. In this study the biomass concentration for the determination of the kinetic parameters in the growth equation was replaced by the number of viable cells in the culture medium. The number of viable cells was determined according Section 2.3. The parameters are given in Table 6. The identification was performed according to the algorithm given in [39]. dX dt ¼ ½mm bXX dP ¼ qp0 X1K dX ð5Þ dt dt dS ¼ g dX 1dX dt dt

3,6

40 0

5

10

15

14,5 14,0 13,5

logN (X), CFU/ml

0.05. The medium is characterized by optimum concentrations of the carbon source and the additives allowing accumulation of the maximum amount of lactic acid in the medium. The introduction of laboratory research in the industry is related with the scaling of the process. The optimization of the cultural medium was made in flasks; therefore, the results

Lactic acid (P), T

524

pH Eh Lactic acid Viable cells Glucose Viable cells - model Glucose - model Lactic acid - model

13,0 12,5

20

Time, h

Figure 9. Batch cultivation of L. caseissp. rhamnosus NBIMCC 1013 in optimum medium in a bioreactor with mechanic stirring, for 24 h.



Eng. Life Sci. 2011, 11, No. 5, 517–527


525

Table 6. Kinetic parameters of the fed-batch process of lactic acid fermentation for lactic acid accumulation lm (h1) 0.511

b (mL/CFU . h) 2.6 10

16

qpo (1T/CFU . h) 3.94 10

16

K (1T/CFU . h) 1.3 10

accumulation, the coefficient K represents the accumulation of product by the cells in the exponential phase. On the other hand, qpo describes the accumulation of product by the cells in the stationary phase. From the conducted mathematical modeling, it can easily be seen that lactic acid is accumulated mainly by the cells in the stationary phase, which is clearly seen by the extremely low value of K. In the equation for substrate consumption, g and d parameters are summarized for the substrate consumption for cell growth and product formation. They show that glucose is consumed with a high specific rate g 5 14.34 g(glucose)/CFU h and d 5 2.33 1016 g(glucose)/CFU h and confirm the observations that glucose is an appropriate substrate for the selected strain. The optimized medium allows the consumption of substrate with high specific speed, at which lactic acid accumulates at high specific speed, especially from cells in the stationary phase. The obtained mathematical model shows the change in the concentration of microbial cells in the medium, the accumulation of lactic acid, and the assimilation of the substrate. It is a useful tool to determine the parameters for the production of lactic acid using immobilized cells, by giving the starting point for determining the dilution rate during continuous fermentation [39, 40]. In the following, the dynamics of the pH change during cultivation is described. It was found that, in the first 12 h, the pH decreases from an initial value of 5.5 to 4.1. The rate of change of this parameter is relatively high, but after 12 h, a slow rate of change was observed due to product inhibition. The results show (Fig. 9) that, at pH values in the range of 5–5.5, maximum specific growth rates and high specific rates of product accumulation and substrate consumption were observed. Therefore, it is appropriate to carry out the cultures at these pH values. Initial studies were conducted for the application of the pH-stat to lactic acid fermentation with immobilized cells in Ca-alginate at two pH values, 5 and 5.2. High dilution rates of 0.32 (pH 5) and 0.47 h1 (pH 5.2) were observed, showing the potential for developing a system of pH-stat cultivation for continuous lactic acid fermentation. These studies will be discussed with regard to future developments and publications. The obtained results from the optimization of the medium are comparable with results obtained by other authors. Lima et al. [19, 30] obtained a culture medium with 55 g/L lactose and complex sources of nitrogen and phosphorus, with a final yield of lactic acid of 18.68 g/L. By additional optimization of the cultivation conditions, a final yield of 52.37 g/L lactic acid was reached. In another study, Lima et al. [20] reached a lactic acid yield of 41.42 g/L. These results were obtained from batch processes in flasks. In the cultivation of L. casei ssp. rhamnosus NBIMCC 1013 in a laboratory bioreactor and under standard conditions for lactic acid bacteria without pH adjustment, a yield of lactic acid of 20.7 g/L was reached.


d (g (glucose)/CFU . h)

27

2.33 10

16

c (g (glucose)/CFU . h) 14.34

For the pH-stat cultivation, we achieved a yield of 6.4 g/L h and 70% substrate utilization. These results are comparable with those obtained by Venus and Richter [40] who reported a productivity of 8 g/L h Lei et al. [41], after optimization of the culture medium, reached a glucose concentration of 118.2 g/L and a lactic acid yield of 4.58 g/L h. Hujanen et al. [29] achieved a concentration of glucose in the medium of 120 g/L and a volumetric productivity of 3.5 g/L h. Mel et al. [31], using CCD, developed a culture medium with a glucose concentration of 9.8%, where the specific growth rate of the lactic acid bacteria was 0.341 h1 and the lactic acid concentration was about 20 g/L. A detailed comparison of the results is difficult to make due to the specificities of the strains used. However, we can say that our results are comparable with those in literature.

4

Concluding remarks

Design of experiment and statistical processing were conducted in order to model and optimize the composition of the medium for lactic acid fermentation. Using CCD, a mathematical model was developed to determine the influence of the concentrations of glucose, yeast extract and meat extract on the production of lactic acid. Cultivation in a laboratory bioreactor was conducted using the obtained medium, and the kinetic constants of the process were determined using the logistic equation and the Luedeking–Piret model. The obtained medium allows the performance of the lactic acid production process under optimum conditions, at high specific sugar assimilation rates and a high lactic acid accumulation rate

Symbols used bi K

[] [1T/CFU h]

LA n N qpo

[g/L] [] [] [1T/CFU h]

R2 Xji

[] []

Yi

[]

Greek symbols a [] b [mL/CFU h] d [g/CFU h]

coefficient in the regression equation specific rate of accumulation of lactic acid by the cells in the exponential phase concentration of lactic acid in Eq. (3) number of experimental factors number of experiments (in Eqs. 1 and 2) specific rate of accumulation of lactic acid by the cells in the stationary phase correlation coefficient coded value of the experimental factor (i 5 1, 2, 3; j 5 1, 2, 3) observed value of test function (titratable acidity) at the corresponding point star point arm coefficient of internal population competition glucose consumption rate by the cells in the exponential phase


526 mm g

Eng. Life Sci. 2011, 11, No. 5, 517–527

G. Kostov et al. [h1] [g/CFU h]

maximal specific growth rate glucose consumption rate by the cells in the stationary phase

[17]

The authors have declared no conflict of interest. [18]

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