A Shortcut to the Optimization of Cellulase Production Using the Mutant Trichoderma reesei YC-108

Abstract

Trichoderma reesei YC-108, a strain isolated by a kind of newly invented plate was found to over produce cellulase and it was then used as a cellulase producer. To get the maximum amount of cellulase, the combination of the medium ingredients, which has a profound influence on metabolic pathway was optimized using response surface methodology. The optimum composition was found to be 24.63 g/L wheat bran, 30.78 g/L avicel, and 19.16 g/L soya-bean cake powder. By using the optimized medium, the filter paper activity (FPA) increased nearly five times to 15.82 IU/mL in a 30 L stirred fermenter, carboxymethyl cellulase activity (CMCase) was increased from 83.02 to 628.05 IU/mL and the CMCase/FPA ratio was nearly doubled compared with the parent strain at initial medium.

Introduction

Cellulose is a renewable carbon source that is available in large quantities, and can be a solution to the problems of ethanol [1], organic acids [2], and other chemicals [3]. The major problem is cost factor of exploitation of cellulase, with contribute as much as 50 % to the overall cost [4]. In order to improve the yields of cellulase, lots of work has been made in developing new strains, optimizing culture conditions [5–8], and cultivation mode [9–11].

In the present work, strain Trichoderma reesei RUT C-30 was conducted by using a combination of UV light and N-methyl-N′-nitro-N-nitrosoguanidine (NTG), a cellulase hyperproducing strain T. reesei YC-108 was obtained, whose CMCA/FPA ratio is much higher than parent strain. It is helpful to improve the application value. In process of optimizing the medium ingredients, we found that one kind of nitrogen source, soya-bean cake powder, could enhance cellulase activity significantly. And then we optimized the three most important medium ingredients using response surface methodology (RSM). To our knowledge, it has not yet been reported to study and optimize conditions of a medium for cellulase production. Finally, the process was scaled up in a 30 L stirred fermenter.

Materials and Methods

Microorganisms

Strain T. reesei RUT C-30 was purchased from China centre of industrial culture collection (CICC); T. reesei YC-108, a mutant derived from T. reesei RUT C-30, was an active producer of cellulase.

Plate-clearing Assay

A kind of convenient and high efficiency screening plate invented by the authors was used to screen for hyper cellulase-producing mutants. The basic medium consists of 2 % cellulose specially treated by homogenizing in a ball mill for 15 min and 2 % agar. Especially, 0.5 % l-sorbose with effect of inhibiting mycelium growth and inducing production of cellulase was added to this plate [12]. The plates were seeded with irradiated spores and incubated at 28° C for 2–3 days, a clear zones would be observed only around colonies of the mutant strains.

Cellulase Production

For inoculum preparation, 5.0 mL of a spore suspension (containing 10⁸ conidia/mL) of T. reesei YC-108 was inoculated into 100 mL of the seed medium in a 250 mL conical flask, and cultured at 30 °C, 180 rpm for 2 days. Small scale experiments were carried out in 500 mL conical flasks with 100 mL of fermentation medium. The inoculum ratio was 10 % (v/v), and the flasks were shaken at 29 °C, 150 rpm for 7 days.

A 30 L stirred-tank fermenter with a working volume of 22 L was used for large scale production of cellulase. The fermentation temperature was 28–30 °C, the agitation speed and air flow rate were kept at 150 rpm and 0.8 vvm, respectively. During the whole fermentation process, samples were periodically withdrawn for detection.

Enzyme Assay

Filter paper activity (FPA) and carboxymethyl cellulose (CMC) activity of the produced cellulase were determined according to the method of the International Union of Pure and Applied Chemistry (IUPAC) [13]. Filter paper was from Xinhua company, and the degree of substitution (DS) and polymerization (DP) of CMC from Noviant Inc used in the study were 0.65 and 750, respectively.

Experimental Design and Optimization

Response surface methodology consists of a group of empirical techniques devoted to the evaluation of relations existing between a cluster of controlled experimental factors and the measured responses, according to one or more selected criteria [14–16]. A prior knowledge and understanding of the process and the process variables under investigation are necessary for achieving a more realistic model [17]. The production medium contained wheat bran, avicel, soya-bean cake powder, potassium (KH₂PO₄), magnesium (MgSO₄·7H₂O) and trace metals. The significant independent variables of the medium components are wheat bran and avicel [8]. During our previous studies, we also tried many other cheap carbon and nitrogen sources. We found that soya-bean cake powder is a very efficient nitrogen source which can enhance the production of cellulase significantly. So we also select soya-bean cake powder as an significant independent variable. The concentration of other components was kept constant throughout the investigation since they had no significant effect on cellulase production.

The range and the levels of the variables investigated in this study are given in Table 1. The central values (zero level) chosen for experimental design were (g/L): wheat bran = 25, avicel = 30, soya-bean cake powder = 20. In developing the regression equation, the test variables were coded according to the equation

1

where X_j is the independent variable coded value, Z_j is the independent variable real value, Z_0j is the independent variable real value on the centre point and Δ_j is the step change value. The response variable was fitted by a second order model in order to correlate the response variable to the independent variables. The general form of the second degree polynomial equation is

where Y is the predicted response, X_i, X_j are input variables which influence the response variable Y; b₀ is the intercept; b_j is the linear coefficient; b_jj is the quadratic coefficient and b_ij is the interaction coefficient.

Table 1.

Experimental range and levels of the independent variables

Variables (g/L)	Symbol		Range and levels
	Real	Coded	−1	0	1
Wheat bran	Z1	X1	20	25	30
Avicel	Z2	X2	25	30	35
Soya-bean cake powder	Z3	X3	15	20	25

The SAS software, version 8.0 was used for regression and graphical analyses of the data obtained. The optimal concentrations of the critical medium components were obtained by Ridge Analysis and contour plots. The statistical analysis of the model was performed in the form of analysis of variance (ANOVA).

Results and Discussion

Obtain the Mutant

After conducted by 254 nm UV light with distance of 15 cm for 3–5 min, the mutant named as UV-5 was isolated with higher cellulase activity. And then the UV-5 was treated by 0.2 mg/mL NTG in pH 8.0 Tris buffer for 0.5–1.5 h, the cellulase activity of the mutant named as NTG-2 increased 1.46 times.

The combination of UV light and NTG was more efficient to get the mutants with increased cellulase activity of 1.16 times than NTG-2. The cellulase hyperproducing mutant was isolated and named as T. reesei YC-108.

Optimization of Medium

In order to find the optimum combination of major components of the medium, experiments were performed according to the Box–Behnken experimental plan (Table 2).

Table 2.

Box–Behnken plan in coded value and observed response (FPA)

Runs	X1	X2	X3	Y(FPA)
1	−1	−1	0	8.40
2	−1	1	0	9.59
3	1	−1	0	9.83
4	1	1	0	7.07
5	0	−1	−1	6.87
6	0	−1	1	9.75
7	0	1	−1	10.15
8	0	1	1	6.36
9	−1	0	−1	8.15
10	1	0	−1	9.75
11	−1	0	1	9.14
12	1	0	1	7.38
13	0	0	0	10.39
14	0	0	0	10.46
15	0	0	0	10.26

In order to check the adequacy of the model to represent the system further, an ANOVA table was constructed (Table 3). The results demonstrate that the model is highly significant, as is evident from the Fisher’s F test (Fmodel, mean square regression/mean square residual = 36.18) with a very low probability value [(Pmodel > F) = 0.0005]. The goodness of fit was checked by determination coefficient (R² = 0.985) which indicates that only 1.5 % of the total variations are not explained by the model. The value of the adjusted determination coefficient (Adj R² = 0.9577) is also very high to advocate for a high significance of the model [17, 18]. A higher value of the correlation coefficient, R = 0.992, justifies an excellent correlation between the independent variables [19]. At the same time, a relatively lower value of the coefficient of variation (CV = 3.27 %) indicates a better precision and reliability of the experiments carried out [17, 19].

Table 3.

ANOVA for the quadratic model

Source	DF	SS	MS	F value	P > F
Model	9	27.531	3.059	36.177	0.0005
Residual	5	0.423	0.085
Lack of fit	3	0.402	0.134	13.015
Pure error	2	0.021	0.01
Total	14	27.954

DF Degrees of freedom, SS Sum of squares, MS Mean of squares

The application of RSM yielded the following regression equation which is empirical relationship between cellulase activity (Y) and the test variables in coded unit.

where Y is the response and X₁, X₂ and X₃ are the coded values of the test variables respectively.

The significance of each coefficient was determined by P values which are listed in Table 4. The smaller the P-value, the more significant is the corresponding coefficient [17, 18]. The result suggest that these three components can act as limiting nutrients and a little variation in their concentration will alter the product formation rate.

Table 4.

ANOVA for Y(FPA)

Term	Estimate	Std err	t	Pr > |t|
X1	−0.156	0.103	−1.520	0.189025
X2	−0.21	0.103	−2.043	0.096542
X3	−0.286	0.103	−2.784	0.038703
X1X1	−0.663	0.151	−4.378	0.007169
X1X2	−0.988	0.145	−6.792	0.001053
X1X3	−0.84	0.145	−5.778	0.002185
X2X2	−0.985	0.151	−6.509	0.001279
X2X3	−1.668	0.145	−11.469	0.0001
X3X3	−1.103	0.151	−7.285	0.000762

The 2D contour plots are generally the graphical representations of the regression equation, they are presented in Figs. 1, 2 and 3 from which the values of FPA for different concentrations of the variables can be predicted. Each contour curve represents an infinite number of combinations of two test variables with the other one maintained at its zero level, and the maximum predicted value is indicated by the surface confined in the smallest ellipse in the contour diagram.

Fig. 1.

Contour plot of FPA (IU/mL): the effect of wheat bran and avicel on cellulase production. The concentration of soya-bean cake powder is held at zero level

Fig. 2.

Contour plot of FPA (IU/mL): the effect of wheat bran and soya-bean cake powder on cellulase production. The concentration of avicel is held at zero level

Fig. 3.

Contour plot of FPA (IU/mL): the effect of avicel and soya-bean cake powder on cellulase production. The concentration of wheat bran is held at zero level

Figures 1, 2 and 3 depict that there are significant mutual interactions among these three components. Avicel works as a carbon source for the growth of fungi and an inducer for the production of cellulase, when the concentration of it increased to 30 g/L or higher level, a decrease in FPA resulted as shown in Figs. 1 and 3, partly due to the pH decreased to <3.0. Sternberg reported that the loss of cellulase activity due to a decrease in medium pH was not recoverable after the pH was adjusted upward [20]. So the optimum avicel concentration is around 27.1–31.6 g/L (Figs. 1, 3). Wheat bran, on the one hand, is a good substrate for cellulase production, because of its nutrients, starch, proteins, and lignocellulosic materials for microbial growth and cellulase synthesis [21], on the other hand, addition of wheat bran can alleviate pH decrease during growth on avicel and resulted in the increase of cellulase activity. So there is a significant mutual interaction between avicel and wheat bran in accordance with Fig. 1. Soya-bean cake powder firstly used as an medium ingredient for cellulase production could increase cellulase activity remarkably. In addition to acting as a nitrogen source, it might also contain some inducers or activators responsible for the biosynthesis of cellulase. There are significant mutual interactions between soya-bean cake powder and other two components, and an optimal concentration of soya-bean cake powder is around 18.3–20.6 g/L (Figs. 2, 3).

Ridge Analysis was used to obtain the optimal values of the test variables, in coded unit they are as follows: X₁ = −0.075, X₂ = 0.078, X₃ = −0.168, with the corresponding Y = 10.44 IU/mL. The natural values obtained by putting the respective values of X_i in Eq. (1) are (g/L): wheat bran = 24.63, avicel = 30.78 and soya-bean cake powder = 19.16.

The model predicts that the maximum cellulase activity obtained is 10.44 IU/mL (a variation of 9.92–10.96 IU/mL being possible) in confidence range of 95 %. Verification of the results using the optimized medium was accomplished by carrying out shake-flask experiments. The maximum FPA obtained experimentally was found to be 10.66 IU/mL obviously in close agreement with the model prediction. After optimization, the production of cellulase was enhanced nearly five times experimentally (Table 5).

Table 5.

Cellulase activity before and after optimization produced by T. reesei Rut C-30 and T. reesei YC-108

Microorganism	Before optimization			After optimization			In 30 L stirred fermenter after optimization
	FPA	CMCase	CMCase/FPA	FPA	CMCase	CMCase/FPA	FPA	CMCase	CMCase/FPA
T. reesei Rut C-30	3.24	83.02	25.62	5.60	156.02	27.86	9.68	276.07	28.5
T. reesei YC-108	8.40	289.38	34.45	10.66	385.55	36.18	15.82	628.05	39.70

Cellulase Production in a 30 L Fermenter

The process of cellulase production was scaled up in a 30 L stirred fermenter with the optimized medium. The time course and pH value on cellulase production were shown in Fig. 4. Since the dissolved oxygen and mass transfer conditions were improved in the stirred fermenter, the fermentation time was reduced to 5 days, and the maximum FPA, CMCA, the CMCA/FPA ratio reached 16.23, 631.45 IU/mL and 38.91, respectively. The results showed that the cellulase production of T. reesei YC-108 was increased at large scale by using this optimized medium.

Fig. 4.

The time course of cellulase production by T. reesei YC-108 in a 30 L stirred fermenter at the optimum medium

Conclusions

Three variables, the composition of medium, wheat bran, avicel, and soya-bean cake powder were designed using RSM for FPA. The values of these components to obtain the maximum enzyme activity were found, and scaled up in a 30 L fermenter. The mutation and the optimization of the medium not only resulted in increasing the cellulase activity of the mutant T. reesei YC-108 up to nearly fivefolds, and the CMCA/FPA ratio two times, but also reducing the cost of the medium by using simple, cheap and efficient medium ingredients. This study could be one of the effective approaches to reduce the cost of cellulase production.

Nomenclature

X_i, X_j

Independent variable coded value

Z_j

Independent variable real value, g/L

X₁

Coded value of wheat bran concentration

X₂

Coded value of avicel concentration

X₃

Coded value of soya-bean cake powder concentration

Y

Predicted response (cellulase activity), IU/mL

Greek Symbols

b₀

Intercept term

b_j

Linear effect coefficient

b_ij

Interaction effect coefficient

b_jj

Squared effect coefficient

Δ_j

Step change value