Low cost feedstock for the production of endoglucanase in solid state fermentation by Trichoderma hamatum NGL1 using response surface methodology and saccharification efficacy

2.1 Cellulase-producing fungi from plantain field

About 10 g of soil was collected from the banana plant root tip from the agricultural field. Suitable dilutions (10 ^-4 to 10^-8) were made and the fungi were isolated using potato dextrose agar (PDA) medium. The morphologically variant isolates were isolated by continuous streaking on PDA agar medium and subjected for EGase screening.

2.2 Screening of the fungal isolates for EGase activity

Twenty morphologically variant isolates were grown in culture medium for 72 h. Then the cow dung was extracted as described by Vijayaraghavan et al. (2012) by simple filtration and centrifugation. The culture supernatant was restraining by centrifugation and the cell free extract was loaded on CMC - agarose plates (0.9% agarose, 1% CMC, pH 6.0) and incubated for 5 h at room temperature (30 ± 2 °C). Then the plates were flooded with Congo red (1%, (w/v) an incubated for 15 min at 30 ± 2 °C, followed by 1 M of NaCl (10 mL) to stain the plate. Appearance of clear zones around sample wells indicated EGase hydrolysis.

2.3 Identification of the organism

In our study, potent amylase producing fungal isolate was subjected for molecular characterization. The PCR protocol was carried out using the forward primer, ITS1 (5′TCCGTAGGTGAACCTGCGG3′) and a reverse primer, ITS4 (5′TCCTCCGCTTATTGATATGC3′). The resulted PCR amplicon was sequenced and 18S rDNA partial sequence obtained from this study was submitted to NCBI with accession number, KX424842.

2.4 Inoculum preparation

T. hamatum NGL1 was culture into the medium consists of sucrose – 30; NaNO₃^- 3.0; and K₂HPO₄-0.5 and the medium pH was maintained as 6.0. Experiment was performed in 100-mL Erlenmeyer flask containing culture medium and incubated in static condition at room temperature (30 ± 2 °C) for 5 days.

2.5 Substrate

Saw dust, paddy straw, cow dung, banana peel and wheat bran were used as the substrate for the production of EGase. Cow dung was collected from a farm house and dried under sunlight for a week. The dried cow dung and other substrates were finely powdered.

2.6 Solid state fermentation

Two gram of substrate (Saw dust, paddy straw, cow dung, banana peel and wheat bran was taken in 100-ml Erlenmeyer flask and initial moisture content was adjusted using Tris-HCl buffer (pH 8.0, 0.05 M) as 60% (v/w). The content was sterilized at 121 °C for 20 min. After sterilization, a density of 2 × 10⁶ spores was inoculated on the substrate aseptically and incubated for 6 days at 37 °C. EGase was extracted as described previously by Vijayaraghavan and Vincent (2012). One-way analysis of variance (ANOVA) was used to find the potent substrate for optimization studies.

2.7 Enzyme assay

Endoglucanase activity was estimated from the crude extract as described by (Irfan et al., 2013).

2.8 Screening of process parameters

The process parameters such as, carbon, nitrogen, and ionic sources were screened by supplementing solitarily along with substrate. To evaluate the optimum pH on EGase production, the culture substrate pH value was adjusted from pH 3.0 to 8.0 using various buffers. To anzlyze the optimum moisture level, the moisture level was adjusted between 40% and 80%. One-way analysis of variance (ANOVA) was used to analyze the significance of process variables (P < 0.05).

2.9 Screening the significant process parameters by statistical approach

In our study, important process parameters influencing EGase production in SSF was screened. Totally five variables were selected for this study. The experiment involved pH, moisture, maltose, oat meal and magnesium based on initial screening experiments. Each of the process parameters was analyzed at two different levels (low and high). The actual values corresponding to the coded levels were shown in Table 1a. For five variables, a total experimental run was 32. About 5 g of substrate was weighed and transferred into all 32 Erlenmeyer flasks and the process variables were adjusted as described in Table 1b. Design Expert 9.0, StatEase Inc., Minneapolis, Minnesota was used to design the experiment and to analyze the experimental data. Eq. (1) gives the first order polynomial equation that governs the response (Y) of the enzyme bioprocess.

2.10 RSM for optimizing the parameters

The three most significant factors which influence on EGase production were selected from two level full factorial design for optimization of EGase production in SSF (Table 2a). Design Expert 9.0, StatEase Inc., Minneapolis, Minnesota has been used to design the experiment and to analyze the experimental data. The experiment involved a central composite design with 20 randomized experimental runs for the selected three variables. In our experiment, 5.0 g of solid substrate was added into the Erlenmeyer flask and the other variable levels were maintained as described in Table 2b. All Erlenmeyer flasks were sterilized as described earlier and inoculated with a density of 2 × 10⁶ spores and incubated for 6 days and enzyme was extracted and assayed as described earlier. The model was built using the data and the same was subjected for analysis of variance (ANOVA) to check for statistical significance (Table 2c). The second order polynomial equation describing the response (Y) of the process is given as:

The designed statistical model was experimentally validated by carrying out SSF using the predicted levels of parameters and the response was compared.

2.11 Enzymatic hydrolysis of paddy straw

In this study, saccharification analysis was performed in 100 mL Erlenmeyer flask containing paddy straw and crude enzyme mixture. The initial substrate concentration was kept as 1.0% and the reaction was performed (30–60 °C) under shaking condition at 150 rpm for 72 h as suggested by (Selig et al., 2008). To the control reaction, commercial enzyme (150 U) was added (Novozymes A/S, Denmark). After the saccharification process, enzyme was inactivated by boiling the tubes for about 10 min. Further reducing sugar of the sample was measured using DNA method (QI et al., 2004) and saccharification rate (%) was calculated.

3.1 T. Hamatum NGL1 as the best isolate capable of EGase production by utilizing cow dung as solid waste

Twenty fungi were subjected for EGase screening which was isolate from the vicinity of banana root tip. Among the isolates, NGL1 emerged as the potent EGase producing organism. The fungus produced a clear zone of 7.5 mm on the CMC agar plate. It was cultured in SSF for the EGase production and the yield was 39.8 ± 2.7 U/g solid substrate in cow dung substrate. Enzyme production was 12.4 ± 1.2 U/g, 17.1 ± 2.2 U/g, 10.1 ± 0.7 U/g, 30.3 ± 2.1 U/g for saw dust, paddy straw, banana peel and wheat bran, respectively (P < 0.05). Since SSF medium such as, cow dung resembles the natural environment of the organism; increased enzyme production can be expected than submerged fermentation. The cost of the culture medium reflects on the final product cost of enzymes. Hence, use of a low cost substrate is always desired in a commercial point of view. Cow dung is an easily available, cheap, tail end waste which may cause environment pollution if left unutilized. It can be effectively utilized as a solid medium in SSF process for enzymes production. (Bansal et al., 2012) earlier applied kitchen waste residues for cellulose production by Aspergillus niger NS-2 in SSF. Trichoderma sp. is one of the important fungi which were widely used to produce cellulases commercially (Nathan et al., 2014). In recent years, cellulase has been produced by Trichoderma sp. using various substrates, including lignocellulose waste from vinegar industry (Liu and Yang, 2007). These substrates are available in seasonal basis and some substrates are not available in very large quantity. Considering its low cost and availability, cow dung is highly effective for EGase production.

3.2 Selection of best yielding medium components

The production of enzyme can be further improved by supplementing additional nutrient sources in some cases. Also, each bacterium is unique and each organism requires its own nutrients composition based on its original environmental conditions. Hence many solid substrates were tested to choose the best yielding medium components using OVAT approach. Maltose emerged as the suitable carbon source for EGase production from hamatum NGL1 (51 ± 4.7 U/g) (Fig. 1a). These carbon sources induce the production of EGase (P < 0.05). In Aspergillus hortai, lactose induced cellulase production (El-Hadi et al., 2014). Oat meal led to maximum enzyme activity (43.5 ± 3.1 U/g), followed by skimmed milk (41.3 ± 3.5 U/g) (P < 0.05) (Fig. 1b). The organic nitrogen sources supplemented with cow dung showed better yield than the inorganic nitrogen sources. The supplementation of magnesium ions gave maximum enzyme activity (37.5 ± 3.5 U/g) compared to other ions (P < 0.05) (Fig. 1c). EGase production was found to be high at 70% moisture (54 ± 2.3 U/g). Enzyme production was 13.7. ± 1.8, 37.5 ± 1.1, 42.4 ± 1.9%, 23.8 ± 3.1%, respectively at 40, 50, 60 and 80% respectively (P < 0.05). Also enzyme activity was high at pH 6.0 (55.3 ± 2.8 U/g). Enzyme production was 11.3 ± 2.1, 18.2 ± 3.8, 37.5 ± 1.95, 46.8 ± 2.7 and 31.4 ± 3.3 U/g substrate at pH 3.0, 4.0, 5.0, 7.0 and 8.0, respectively (P < 0.05).

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Fig. 1

A–c. Effect of various carbon sources (a), nitrogen sources (b) and ions (c) on production of EGase in solid state fermentation by T. hamatum NGL1.

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3.3 Elucidation of significant process parameters using statistical method

The randomized trial involved 32 experimental runs for five variables as shown in Table 1b and a regression model was built based on the results. The enzyme activity ranged from 0.9 U/g to 102.6 U/g. ANOVA was performed on the results was tabulated (Table 1c). The F value of the model was 25.92 and was statistically significant. The model had an R² value of 0.9845. The predicted R² value was found to be 0.8036 and the adjusted R² value was 0.9465. The equation in terms of the coded factors can be given as

EGase activity = + 24.08 + 7.78A – 4.95B + 4.59D + 3.98AB – 5.85AC + 6.17AE + 8.75BC + 3.25BE + 3.62CD + 2.98DE + 9.90ABC – 3.16ABE + 5.55ACD – 5.83ACE + 9.77BCD – 3.04BDE + 4.37CDE + 2.74ABCD – 4.50ABDE – 4.42ACDE + 3.05BCDE + 10.77ABCDE

In the equation, the process variables were included in coded levels. Hence the coefficients of results of each model terms could be considered as a measure of the relative impact of each term on the process conditions. The negative coefficient for parameter B (moisture content of the medium) indicates that the EGase activity could be further improved by decreasing the moisture content of the substrate. Based on these results, pH, moisture and oat meal were the medium components that appeared as the important process parameters and were considered for RSM. Recently, (Bagewadi et al., 2018) used Plackett–Burman design for optimizing cellulase production.

3.4 Response surface methodology using central composite design

The interaction effects between the significant process parameters were analyzed using the central composite design and the pinnacle of EGase activity was explored using response surface plots. The surface plot implied the interactions of variables on EGase production (Fig. 2a-c). Table 2b shows the three process parameters (pH, moisture and oat meal) in their response (−α, −1, 0, +1, +α) for the CCD experimental design. ANOVA was performed on the results and the quadratic equation obtained was given as, $$\text{EGase}\text{activity}=+\text{11}0.\text{15}+\text{11}.\text{12A}+\text{15}.\text{58B}-\text{18}.\text{38C}-\text{1}0.\text{49AB}+\text{28}.\text{49AC}-\text{13}.\text{19BC}-\text{1}0.\text{38}{\text{A}}^{\text{2}}-\text{15}.\text{98}{\text{B}}^{\text{2}}-\text{12}.\text{55}{\text{C}}^{\text{2}}$$

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Fig. 2

Three dimensional response surface plots depicting the interactive effect between moisture and pH (a), oat meal and pH (b) and oat meal and moisture (c) on production of EGase by T. hamatum NGL1.

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The model F value of 42.84 indicated the statistical significance of the experimental model and was statistically significant (p < 0.0001). The model terms having a probability less than 0.05 can be considered as statistically significant (Table 2c). The lack of fit F-value was 0.54 and it was not significant indicated goodness of fit. The predicted R² value of this model was 0.9085, and the adjusted R² value was 0.9520. The model had an R² value of 0.9747. The R² value of the design could be at least 0.8 to fit the model. So, our designed model is best fit with R² value 0.9747. CCD and RSM are used to provide optimum concentration of selected factors. In an enzymatic bioprocess enhanced enzyme production can be frequently achieved by means of statistical optimization design. Response surface plot generally helps to visualize the interactive effect of selected factors on EGase production. In our study, a three-fold increase in the EGase activity was obtained in SSF using cow dung substrate by T. hamatum NGL1 than unoptimized medium. Medium optimization by employing RSM showed that the SSF medium containing oat meal (0.2%), pH 6.14 and moisture (66.49%) helps the maximum amount of EGase production. In this study, the increase of moisture content and pH of the medium enhanced EGase production at certain level and enzyme production was further decreased. The predicted value for the SSF process parameters were 151.3 U/g solid waste the observed activity and the experimental response was 148 ± 3.5 U/g. Recently, (Bagewadi et al., 2018) used statistical approach to optimize the medium components for enzyme production and reported 2.31-fold increase on EGase production. Likewise, (Lee et al., 2015) optimized EGase production from Trichoderma harzianum KUC1716 using response surface methodology and the reported optimized independent factors were 1.85% cellulose, 0.48% soy peptone and 0.10% thiamine.

3.5 Hydrolysis of paddy straw using EGase from T. Hamatum NGL1

The saccharification efficacy of EGase from T. hamatum NGL1 and commercial EGase was described in Fig. 3. In this study, paddy straw was used as the substrate to evaluate the efficacy of sacchairification. According to Maeda et al. (2011) no microorganism produces cellulases with desirable properties for biomass hydrolysis. Hence, saccharification process on lignocellulostic materials using enzymes is interesting. In this study, saccharification process was maximum at 60 °C than other temperatures and saccharification efficacy was significant (p < 0.05) at optimized temperature. The cellulose content of paddy straw positively correlated with saccharification process during this study. However, lignin content of paddy straw negatively correlated in this experiment.

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Fig. 3

Saccharification process of paddy straw at various temperature after 72 h of incubation. Error bar represents standard deviation (n = 3).

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