|Year : 2020 | Volume
| Issue : 1 | Page : 7-17
Optimizing the production of rice straw hydrolytic cellulase under solid-state fermentation using Aspergillus terreus RS2
Shaymaa A Ismail, Amira A Hassan
Department of Chemistry of Natural and Microbial Products, Division of Pharmaceutical and Drug Industries, National Research Centre, Dokki, Giza, Egypt
|Date of Submission||05-Sep-2019|
|Date of Decision||24-Nov-2019|
|Date of Acceptance||04-Feb-2020|
|Date of Web Publication||24-Mar-2020|
Shaymaa A Ismail
Department of Chemistry of Natural and Microbial Products, Division of Pharmaceutical and Drug Industries, National Research Centre, El Bohouth Street, Dokki, Giza 12622
Source of Support: None, Conflict of Interest: None
Background The enzymatic hydrolysis of lignocelluloses into fermentable sugars is the key step in biorefining, and cellulases are the key enzymes. The low titer of cellulase production and their high cost remain the most significant barriers to their industrial applications. The aim of this study was the economic production of cellulase by an Egyptian fungal isolate under solid-state fermentation by using rice straw as a carbon source. Additionally, the produced enzyme can be applied in the hydrolysis of rice straw and production of free sugars that can be used in several biotechnological industries.
Materials and methods The isolated fungus was identified according to its cultural and morphological features followed by 18S rDNA sequencing. Optimization of the enzyme productivity was performed by applying Plackett–Burman and Box–Behnken designs. Finally, the hydrolysis of rice straw for the production of fermentable sugars using the produced enzyme was carried out, confirmed by scanning electron microscope and thin-layer chromatography analysis.
Results and conclusion The optimum cellulase activity produced by the isolated fungus Aspergillus terreus RS2 was 124.94 U/g dry substrate. It was achieved at the optimum conditions that were conducted to be as follows: 3.75 g (1.5%w/v) of rice straw moistened with 11.25 ml (1 : 3 biomass to moistening agent) of modified Mandel’s medium [1% (NH4)2SO4 was the only constituent nitrogen source] of pH 7, incubated at 30°C for 8 days. Finally, the activity of the produced enzyme in the degradation of rice straw indicated the release of reducing sugars of 343.98 mg/g dry substrate with a saccharification percentage of 34.4% recorded after 4-h hydrolysis period.
Keywords: Aspergillus terreus RS2, carboxymethyl cellulase, rice straw, saccharification, solid-state fermentation
|How to cite this article:|
Ismail SA, Hassan AA. Optimizing the production of rice straw hydrolytic cellulase under solid-state fermentation using Aspergillus terreus RS2. Egypt Pharmaceut J 2020;19:7-17
|How to cite this URL:|
Ismail SA, Hassan AA. Optimizing the production of rice straw hydrolytic cellulase under solid-state fermentation using Aspergillus terreus RS2. Egypt Pharmaceut J [serial online] 2020 [cited 2020 Jul 11];19:7-17. Available from: http://www.epj.eg.net/text.asp?2020/19/1/7/281014
| Introduction|| |
The overall energy shortage and the environmental problems enforce global concerns for the development and utilization of renewable energy sources . Lignocellulosic biomass is one of the most abundant but underutilized biomass that is considered to be an attractive option for the development of today’s biorefineries from the perspective of its low cost, renewability, and its minimal effect in food production . It consists of ∼35–50% cellulose, ∼20–35% hemicelluloses, and ∼5–30% lignin of the plant dry weight . The conversion of the polysaccharide constituent of this biomass to its constituent fermentable sugars is a crucial step in the commercial success of biorefineries . The use of enzymes in the conversion process is the most convenient, desirable, and ecofriendly method, with a satisfactory yield of free sugars .
Cellulolytic enzymes are the biorefineries key enzymes, as they are the enzymes that catalyze the hydrolysis of cellulose. They are produced naturally by wood-degrading fungi and bacteria as a part of the energy transfer and the carbon cycle. Commercially, filamentous fungi of Trichoderma spp. and Aspergillus spp. are the main source for their production ,, but their high cost is still the most significant barrier to their industrial applications , reflecting the importance of their low-cost production.
The production of cellulase using fungi via solid-state fermentation (SSF) is one of the most desirable and cost-effective techniques . SSF is an old technology that has been emphasized to be efficient in the production of hydrolytic enzymes in which the cultivating conditions of the fungi simulate the natural environment . The selection of the substrate for SSF processes that can facilitate the anchorage of fungi, along with providing sufficient nutrients, remained a subject of intense research for many decades . Rice straw is one of the most abundant lignocellulosic crop residue that is generated and collected directly from the fields . According to the Food and Agriculture Organization of the United Nations points system, the annual global production of rice straw is ∼600–900 million tons . The low bulk density and high silica and mineral contents are characteristics that limited its application . So the burning of rice straw in open fields is a common practice for its disposal all over the world, leading to air pollution that consequently affects public health . The utilization of rice straw as a carbon source for the production of cellulase instead of using the refined cellulosic carbon source can decrease the total cost of the enzyme and increases its economic viability.
The conditions of the fermentation processes have a crucial effect on the growth of the microorganisms and their released metabolic products as well as the cost of the production process. For multivariable processes, statistical optimization is advantageous to save time and effort, decrease the number of the required experiments, and consequently, decrease the total cost of the process . Response surface methodology was originally described by Box and Wilson , and in the past few years, it has been applied in the optimization processes in various microbiological and biotechnological fields ,. It has been successfully applied in the optimization of the microbial production of cellulase ,,.
The current study concerned with the production of cellulase by SSF of rice straw using locally isolated fungus in addition to the identification of the isolated fungus on the basis of its cultural and morphological features followed by 18S rDNA sequencing. Optimization of the enzyme productivity by applying Plackett–Burman and Box–Behnken designs was performed. Finally, the ability of the produced enzyme for rice straw hydrolysis and production of free sugars was examined.
| Materials and methods|| |
Carboxymethyl cellulose (CMC) and glucose standard were purchased from Sigma-Aldrich, (Saint Louis, MI, USA). Potato dextrose agar (PDA) and thin-layer chromatography (TLC) plates were purchased from Merck (Darmstadt, Germany). Dinitrosalicylic acid (DNS) was obtained from Panreac (Barcelona, Spain). All other chemicals were of analytical or high-performance liquid chromatography grade.
Rice straw was collected after air drying from fields situated in Al Sharqiya, Egypt, which was then cut into pieces, grounded using a standard grinder, and used directly without any further processing.
The fungus used in this study was previously isolated during the intensive course of the screening program concerned with the isolation of microorganisms from the soil secreting nonstarch hydrolyzing enzymes (unpublished data). It was identified according to its cultural and morphological features. Molecular identification of the strain was carried out by 18S rDNA sequencing performed in Sigma Scientific Services Co.
Culture conditions and enzyme production
The fungus was cultivated on PDA slants and incubated at 30°C for 7 days unless other conditions were described. After cultivation, spore suspension was prepared by scratching of each slant with 10 ml distilled water containing 0.1% tween 80. SSF was initially performed, in which 2 ml of the spore suspension was used to cultivate 250 ml Erlenmeyer flask containing 5 g of rice straw (with 0% of initial moisture content) moistened with 10 ml tap water then incubated at 30°C for 7 days. At the end of the fermentation process, extraction was performed by adding 50 ml of distilled water to each flask, shaken at 150 rpm and 30°C for 1 h, and then centrifuged at 5000 rpm for 10 min. The resulted supernatant was subjected to further analysis.
Enzyme activity and protein content assays
The cellulolytic activity in terms of carboxymethyl cellulase (CMCase) activity was determined by DNS method  in a reaction mixture consisted of 500 μl of 1% CMC (dissolved in 0.05 mol/l acetate buffer, pH 5) and 500 μl of the culture supernatant incubated at 50°C for 30 min. At the end of the assay time, 2.5 ml of DNS was added to stop the reaction, and the color developed after boiling for 10 min was measured at 540 nm. One unit of the enzyme was defined as the amount of enzyme that released 1 µmol of glucose per minute under the assay conditions. The amount of the produced enzyme was expressed as units per gram dry substrate (U/gds).
The protein content was determined as described by Lowry et al. , using bovine serum albumin as a standard.
Effect of pretreatment of rice straw
The effects of microwave heating for 1 min and alkaline (soaking in 5% NH4OH for 24 h at 4°C  and in 2.75% NaOH for 3 h at 55°C  in the ratio 1 : 20 w/v) pretreatments of rice straw were investigated.
Effect of moistening agent
Overall, 10 ml of Mandel’s medium [composed of (g/l) (NH4)2SO4 1.4, KH2PO4 2, urea 0.63, CaCl2 0.3, MgSO4.7H2O 0.3, peptone 0.75, and 1 ml of trace element solution]  at pH 5 was used as a moistening agent instead of tap water. After that the constituent mixture of nitrogen sources was replaced by equivalent nitrogen content of each nitrogen source separately (peptone, urea, and (NH4)2SO4), and then the most suitable concentration of the selected nitrogen source was examined in the range of 0.1–2%.
Statistical optimization of cellulase production
In this study, two-step optimization approaches were carried out to enhance cellulase production. Initially, the variables that influence cellulase production were selected by applying Plackett–Burman design. In the second step, Box–Behnken design was applied to optimize the selected variables.
Selecting the variables that influenced cellulase production
For multivariable processes, the screening of the variables that influenced any process is the initial step of its optimization. To identify the variables that have the highest influence on cellulase production, Plackett–Burman design , including seven variables, was applied, in which the experimental runs were calculated as n+1, where n is the number of the selected variables. The seven independent variables were substrate concentration (% w/v), moisture level (biomass to moistening agent ratio), pH of the moistening agent, time of autoclaving (min), age of the fungus (days), temperature (°C), and fermentation period (days); each variable has been represented in terms of high (+1) and low (−1) levels, as shown in [Table 1].
|Table 1 The levels of the independent variables screened in Plackett–Burman design|
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Each generated response was calculated according to the first-order linear equation:
where Y is the response (cellulase production), B0 is the model intercept, Bi is the linear coefficient, and Xi is the level of the independent variable.
The main effect of each variable was determined by the following equation:
where E(Xi) is the effect of the tested variable. Mi+ and Mi− represent cellulase production from the experimental runs where the independent variable (Xi) measured was present at high and low values correspondingly, and N is the number of runs.
In the second step of optimization, Box–Behnken design  was applied to determine the optimum level of the selected variables. In this model ([Table 3]), an experimental design of 15 runs and three central points was constructed with three independent variables. Each variable was examined at three different levels: low (−), high (+), and control or basal (0). The second order polynomial equation used for the interpretation of the correlation between the variables and the response (cellulase production) was as follows:
where Y is the predicted cellulase production, ß0 is the model intercept, ßi is linear coefficient, ßii is quadratic coefficient, and ßij is cross-product coefficient, where Xi and Xj are the coded levels of the independent variables.
Hydrolysis of rice straw
Saccharification activity of the produced enzyme
Initially, the filter paper hydrolyzing (FPase) activity was determined according to Ghose , in which 0.5 ml of the culture supernatant was incubated with a 1×6 cm (5 mg) rolled filter paper strip (Whatman No.1) in 0.5 ml of 0.05 mol/l acetate buffer, pH 5, at 50°C for 30 min. In addition xylanase, mannanase, and pectinase activities of the produced enzyme were estimated using xylan, locust bean gum, and citrus fruit pectin, respectively, as substrates. The amount of the released reducing sugars was determined by DNS method .
The saccharification of rice straw using the produced enzyme was examined in a 50 ml screw-capped bottle, in which 10 ml of the enzyme was added to 1 g of rice straw in 10 ml of 0.05 mol/l acetate buffer at pH 5 and incubated at 50°C for different incubation periods (1–6 h). The amount of the released reducing sugars was determined using DNS. The percentage of saccharification was calculated as follows :
Thin-layer chromatography analysis
The rice straw-resulted hydrolyzate with the maximum amount of released reducing sugars was analyzed by TLC using a mixture of propanol : water : ammonia (7 : 2 : 1 v/v) as a mobile phase . The resulted sugars were visualized with diphenyl amine-aniline reagent .
Scanning electron microscope
The rice straw before and after enzymatic treatment was examined by field emission high-resolution scanning electron microscope (Quanta 250; FEI, Czechoslovakia, Czech Republic).
The experiments were carried out in triplicates, with three measurements per replicate, and the results were reported as average±SD.
| Results|| |
Cultural and morphological features of the isolated fungus
The cultural feature of the used fungus on PDA is shown in [Figure 1]a, indicating that the fungus colonies were cinnamon to brown in color. Morphological features of the isolate in terms of sporangia were examined under scanning electron microscope, as shown in [Figure 1]b, indicating that the fungus is Aspergillus spp. Moreover, the culture of the isolated fungus in the optimized fermentation medium containing rice straw as a carbon source was examined under scanning electron microscope ([Figure 1]c), manifesting the ability of the isolated fungus for the utilization of rice straw for growth.
|Figure 1 Cultural and morphological features of the used fungus. (a) The culture on potato dextrose agar; (b) scanning electron microscopy of the fungus cultured on potato dextrose agar; (c) scanning electron microscopy of the fungus cultured on rice straw (c).|
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The confirmation for the isolate identification was performed on the basis of 18S rDNA nucleotide sequencing, and the phylogenetic analysis was performed using MEGAX and neighbor-joining method . The phylogenetic tree is shown in [Figure 2], and the data of the partial sequence were submitted under the name Aspergillus terreus strain RS2 to NCBI and received accession number of MN368221.
Rice straw pretreatment effect
The effect of pretreatment of rice straw either by microwave heating or by soaking in alkaline solutions did not improve the productivity of the enzyme. The alkaline pretreatment led to almost 50% decrease in the total protein content and enzyme activity, as shown in [Figure 3]a.
|Figure 3 The effect of (a) rice straw pretreatment (b) different moistening agent and (c) different concentration of (NH4)2SO4.|
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Effect of moistening agent
The substitution of tap water with Mandel’s medium as a moistening agent improved the productivity from 37.481 to 54.536 U/gds and increase the total protein content from 42.676 to 47.776 mg/gds.
On replacement of the constituent mixture of nitrogen source with the equivalent nitrogen content of each individual nitrogen source, the highest productivity was observed by using (NH4)2SO4 only, in which the productivity increased to 62.149 U/gds, with a slight increase in total protein content (48.551 mg/gds) ([Figure 3]b). By using different concentrations of (NH4)2SO4 (0.1–2%), the productivity increased as the concentration increased to reach 76.828 U/gds by using (NH4)2SO4 of concentration 1%. After that, no increase in productivity was observed by increasing the concentration. Although the total protein content increased as the concentration increase from 0.1 to 0.2%, the overincrease in concentration did not increase the total protein content ([Figure 3]c).
Selecting of the variables that influenced cellulase production
By applying PBD, seven variables were screened for their influence on cellulase production, and the mean value of the observed enzyme activity is illustrated in [Table 2]. A wide variation in the results ranging from 64.07 to 116.898 U/gds was observed, reflecting the importance of the initial screening of the variables that influenced the enzyme productivity. The maximum activity was observed at run number 7, with 116.898 U/gds by applying fermentation conditions of substrate concentration, 2%; moisture level; 1 : 3 biomass to moistening agent ratio; pH: 7; time of autoclaving: 15 min; age of the fungus: 7 days; temperature: 30°C; and fermentation period: 5 days.
The main effects of the examined variables were calculated and are presented graphically in [Figure 4]. The calculated values indicated that the highest main effects were investigated with the substrate concentration, moisture level, and fermentation period, in which both the substrate concentration and the fermentation period had negative values, whereas the moisture level had positive value.
|Figure 4 The independent variables main effects on cellulase production.|
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The analysis of the data by multiple regression ([Table 3]) indicated that all of the tested variables except the time of autoclaving significantly affected the enzyme productivity. The highest confidence level was observed to be with the substrate concentration, moisture level, and fermentation period. The coefficient values were used to estimate the effect of the seven independent variables on the enzyme production. The variable that possessed positive effect was maintained at positive level whereas the one that possessed negative effect was maintained at negative level to achieve maximum production of the enzyme in the second phase of optimization. The first-order equation that described the correlation between the selected seven variables and the enzyme activity could be presented as follows:
where Y is the cellulase activity, and X1, X2, X3, X4, X5, X6, X7 are substrate concentration, moisture level, pH of the moistening agent, time of autoclaving, age of the fungus, temperature, and fermentation period, respectively.
The coefficient of determination (R2) value of the selected model was 0.991, and the calculated analysis of variance indicated the overall high significant of the model since the model terms had probability greater than F value of 4.12 E−15 (<0.05).
From the aforementioned results of PBD, the substrate concentration, moisture level, and fermentation period were the variables with the highest main effect and the highest confidence level, so they were selected for the second phase of optimization.
The observed and predicted mean values of Box–Behnken design results are represented in [Table 4]. The second-order polynomial equation, concluded from the multiple regression analysis ([Table 5]), was used in the prediction of the enzyme activity as follows:
where Y is the cellulase activity and X1, X2 and X3 are the substrate concentration, moisture level, and fermentation period, respectively.
The R2 value of the applied model was 0.86, indicating that 86% of the variation in the cellulase activity was owing to the selected independent variables. The absolute average deviation (AAD) was calculated to be 10.938% by Eq. 7.
where P, Yexp, and Yprd are the number of the experiment, observed, and predicted cellulase activity, respectively.
The analysis of variance of the regression indicated that the model terms used in this study are highly significant, as the model terms had F value of 24.242 and P value of 1.64 E−12 (<0.05). Moreover, the residual analysis ([Figure 5]) obtained by plotting of the observed–predicted values (residuals) vs the response (observed cellulase activity) indicated that the residuals were symmetrically and constantly spread throughout the range.
The validation of the applied model was confirmed by performing an experiment under the optimized conditions. The result indicated that the experimental cellulase activity (120.18 U/gds) was in accordance with the predicted value 112.183 U/gds.
Hydrolysis of rice straw
Initially, the FPase activity of the produced enzyme under the optimized culture conditions was determined as described previously in the material and method section. The result demonstrated that the produced enzyme possessed 1.1 U/gds Fbase activity at 50°C. Moreover, it possessed 2.3 U/gds mannanase activity, without the determination of any xylanase and pectinase activity.
The saccharification of untreated rice straw was carried out using the produced enzyme for different incubation periods, and the amount of the released reducing sugars was determined then the calculated saccharification percentage was represented in [Figure 6]a. It was observed that the saccharification percentage increased up to 4 h, recording 34.4% with 343.98 mg reducing sugars/gds, and then by increasing the time, there was no improvement in the saccharification percentage.
|Figure 6 Hydrolysis of rice. (a) Saccharification percentage; (b) thin-layer chromatography analysis of the resulted hydrolyzate after saccharification of untreated rice straw by using the produced enzyme for 4 h at 50°C in which S1, S2, S3, and A are mannose, glucose, cellobiose standards, and the resulted hydrolyzate, respectively.|
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The resulted reducing sugars were analyzed by TLC ([Figure 6]b), and the results indicated that glucose is the main constituent followed by mannose without the detection of cellobiose, confirming the ability of the produced enzyme to hydrolyze rice straw to its constituent monosugars.
Scanning electron microscopy
The examination of the surface of rice straw before and after enzymatic treatment by scanning electron microscope (SEM) is shown in [Figure 7], indicating that the morphology of rice straw was greatly altered after enzymatic hydrolysis.
|Figure 7 SEM of rice straw. (a) Untreated; (b) enzymatically treated using the produced enzyme.|
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| Discussion|| |
The utilization of lignocellulosic biomass for the production of value-added compounds in biorefineries depends mainly on their hydrolysis to its constituent soluble sugars . Cellulases are the biorefineries key enzymes , and the production cost of the enzyme is the first crucial step in the determination of the economic feasibility of its industrial application. The cost of the enzyme production can be reduced by using crude substrates instead of using the purified substrates . In the current study, cellulolytic potential in terms of CMCase activity of A. terreus RS2 isolated from soil was evaluated under SSF of 5 g rice straw moistened with 10 ml of tap water. The produced enzyme showed activity of 37.481 U/gds (3.7481 U/ml) after 7 days of fermentation period, which was further optimized to reach 124.94 U/gds. A. terreus has been previously reported as CMCase producers by SSF of different crude substrates, such as banana peels, with the production of maximum activity of 1.11 and 1.5 U/ml in mono and in co-culture with Aspergillus niger MS23, respectively ; sugarcane-bagasse with maximum activity of 13.83 U/gds ; and sweet sorghum bagasse with the production of 105.2 U/gds . Rice straw has been also used as a carbon source for the production of 96.6  and 141.29 U/gds  CMCase after optimization of the cultural conditions of SSF using A. terreus. The productivity of the enzyme using the locally isolated strain in the current study is comparatively high, indicating the efficiency of the isolated strain to utilize rice straw as a carbon source for the production of cellulase. The utilization of rice straw as the fermentation carbon source in the fungal production of cellulase attracted the research focus from the perspective of its low cost and reliable supply and to reduce its disposal environmental pollution hazards ,,,,.
The conditions of the fermentation process have a crucial effect on the yield of the produced enzyme. Initially, the effects of microwave and alkaline pretreatment of rice straw were investigated. Although the use of microwave heating was reported by Hassan et al.  as one of the solutions to overcome the intrinsic recalcitrant nature of lignocellulosic biomass before the production of valuable compounds, the use of microwave pretreatment of rice straw in the current study did not achieve any improvement in the productivity of the enzyme. In addition, alkaline pretreatments did not improve the productivity, but they decreased the total protein content and consequently decreased the activity of the enzyme. This decrease may be attributed to the excess decomposition of the constitutional sugars and/or the release of compounds that inhibit the fermentation process . In the present study, an overall increase of 3.3-fold was achieved in which the optimum conditions were conducted to be as follows: 3.75 g (1.5%w/v) of rice straw moistened with 11.25 ml (1 : 3 biomass to moistening agent) of modified Mandel’s medium [1% (NH4)2SO4 was the only constituent nitrogen source] of pH 7, incubated at 30°C for 8 days. Ammonium salts as the nitrogen sources were favorable for the production of cellulase as reported by Aggarwal et al. , whereas Narra et al.  reported that the use of inorganic nitrogen sources led to poor production of the enzyme. Nguyen et al. , reported that both organic and inorganic nitrogen sources can be optimally utilized for the production of CMCase. In this study, the stimulation of cellulase production in the presence of ammonium salts may be attributed to their direct entry in the synthesis of protein .
The optimization of the fermentation process is necessary to increase the yield of the enzyme that consequently decreases the total cost of the enzyme. For the optimization of multivariable process, statistical techniques are advantageous as they save time and reduce the number of the required experiments, resulting in a decrease in the overall cost of the process. Several statistical techniques have been successfully employed in the fermentation technology for the optimization of the production of various enzymes ,,. In the current study, PBD was initially applied, in which seven variables were screened for their influence on the production of the enzyme. The R2 value of the selected model was 0.991, indicating the high accuracy of the model, as it suggested that a variation of 99.1% occurs owing to the independent variables. Joglekar and May  reported that the R2 value should be at least 80% to indicate the good fitness of the applied model. The analysis of PBD results indicated that the substrate concentration, moisture level, and fermentation period were the highest significant influencing variables. The substrate concentration and fermentation period exerted negative effects on the enzyme production (the enzyme productivity increased when the values of the variables changed from high to low), whereas moisture level exerted positive effect. The second step of optimization included the application of Box–Behnken design to determine the optimum level of the highest significant three variables, in which the R2 and AAD values were 86.2 and 10.938%, respectively. Yolmeh and Jafari  and Ghorbannezhad et al.  reported that the suitable values of R2 and AAD indicated that the applied model depicts the correct behavior, and it can be successfully used in the optimization process. Moreover, the residual analysis confirms that the model is correct on average for all the observed results.
Optimum concentration of the substrate in SSF is an essential requirement to ensure the appropriate growth of microorganisms . In the present study, the production of the enzyme increased by decreasing the concentration of rice straw from 2 to 1.5%. This may be attributed to the fact that increasing the substrate concentration led to a decrease in the enzyme yield owing to the inhibitory effect of the increased amount of the released byproducts . This result was in contrast with the result reported by Aggarwal et al. , in which increasing the concentration to 6% of alkali-assisted acid pretreated rice straw was the optimum concentration for maximum CMCase production by using A. niger BK01.The fungal production of cellulase by SSF generally starts by the fungal colonization of the substrate to ensure its depolymerization for the induction of the production of enzymes . Accordingly, the optimal incubation period varied based on the type of the used substrate and the species of the fungus employed in the fermentation process. The result of the current study (8 days) was in accordance with that reported by Sohail et al. , in which 240 h was indicated as the optimum period for the production of the enzyme by the fermentation of sugarcane-bagasse using A. terreus MS105.
In SSF, moisture is the most significant variable. Behnam et al.  and Vu et al.  reported that the increase in the moisture content results in a decrease in the porosity of the substrate and consequently reduces the oxygen transfer. On the contrary, the decrease in the moisture content leads to poor accessibility to nutrients and consequently poor microbial growth. Therefore, estimating the suitable moisture content for the optimum production of the enzyme is necessary. Fatma et al.  estimated a ratio of 1 : 3 (substrate: moistening agent) as an optimal ratio for maximum enzyme production by Trichoderma reesei. Similar result was achieved in the current study, whereas Aggarwal et al.  reported a ratio of 1 : 2 to be the best for the optimal production of the enzyme by A. niger BK01. Moisture contents of 50, 70, 75, and 80% were also reported for optimum fungal production of the enzyme ,,,,,.
The produced enzyme at the optimized culture conditions was used for the hydrolysis of untreated rice straw for different incubation period, and the results demonstrated a saccharification percentage of 34.4% with released reducing sugars of 16.9 mg/ml (343.98 mg reducing sugars/gds) recorded after 4 h of hydrolysis period. Aggarwal et al.  reported 35.96% as the highest saccharification value of alkali-assisted acid pretreated rice straw using crude A. niger BK01 cellulase for 2.5 h. Kobkam et al.  reported maximum yield of sugars of 0.54 g/g ds achieved by the enzymatic hydrolysis of hydrothermal-alkali pretreated rice straw using commercial cellulase after 120 h of hydrolysis period. Prajapati et al.  reported the production of 131 mg reducing sugar/g by the hydrolysis of hydrothermal-alkali pretreated rice straw using crude Aspergillus tubingensis cellulase. Chang et al.  reported 8.88 mg/ml as the highest amount of the released sugars resulting from the hydrolysis of TiO2/UV/H2O2 pretreated rice straw by cellulase. The result of the current study suggests that the produced enzyme can be efficiently used in the hydrolysis of rice straw without the need of pretreatment.
| Conclusion|| |
This study demonstrated an economically and ecofriendly approach for rice straw discard valorization. Untreated rice straw was efficiently used as a carbon source for the production of cellulase by SSF using locally isolated A. terreus RS2. The production of the enzyme was statistically optimized to reach 124.94 U/gds. Moreover, the produced enzyme was efficiently used for rice straw hydrolysis without any pretreatment. Hence, the results obtained in this study hold promise in bio-processing industrial applications.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Cai C, Bao Y, Zhan X, Lin X, Lou H, Pang Y et al.
Recovering cellulase and increasing glucose yield during lignocellulosic hydrolysis using lignin-MPEG with a sensitive pH response. Green Chem 2019; 21:1141–1151.
Kamel S, El-Sattar HA, Vera D, Jurado F. Bioenergy potential from agriculture residues for energy generation in Egypt. Renew Sustain Energy Rev 2018; 94:28–37.
Zabed H, Sahu JN, Boyce AN, Faruq G. Fuel ethanol production from lignocellulosic biomass: an overview on feedstocks and technological approaches. Renew Sustain Energy Rev 2016; 66:751–774.
Shuddhodana XX, Munishwar NG, Virendra SB. Stable cellulolytic enzymes and their application in hydrolysis of lignocellulosic biomass. Biotechnol J 2018; 13:1700633.
Chandel AK, Chandrasekhar G, Silva MB, Silvério da Silva S. The realm of cellulases in biorefinery development. Crit rev biotechnol 2012; 32:187–202.
Xue Y, Wang X, Chen X, Hu J, Gao MT, Li J. Effects of different cellulases on the release of phenolic acids from rice straw during saccharification. Bioresour technol 2017; 234:208–216.
Srivastava N, Srivastava M, Gupta VK, Ramteke PW, Mishra PK. A novel strategy to enhance biohydrogen production using graphene oxide treated thermostable crude cellulase and sugarcane bagasse hydrolyzate under co-culture system. Bioresour technol 2018; 270:337–345.
Tai WY, Tan JS, Lim V, Lee CK. Comprehensive studies on optimization of cellulase and xylanase production by a local indigenous fungus strain via solid state fermentation using oil palm frond as substrate. Biotechnol prog 2019; 35:2781.
Sukumaran RK, Singhania RR, Mathew GM, Pandey A. Cellulase production using biomass feedstock and its application in lignocellulosic saccharification for bioethanol production. Renew Energy 2009; 34:421–424.
Yoon LW, Ang TN, Ngoh GC, Chua ASM. Fungal solid-state fermentation and various methods of enhancement in cellulase production. Biomass Bioenergy 2014; 67:319–338.
Jain RK, Ghosh D, Agrawal D, Suman SK, Pandey D, Vadde VT et al.
Ethanol production from rice straw using thermotolerant Kluyveromyces
sp. IIPE453. Biomass Convers Biorefin. 2015; 5:331–337.
Desai KM, Survase SA, Saudagar PS, Lele SS, Singhal RS. Comparison of artificial neural network (ANN) and response surface methodology (RSM) in fermentation media optimization: case study of fermentative production of scleroglucan. Biochem Eng J 2008; 41:266–273.
Box GE, Wilson KB. On the experimental attainment of optimum conditions. J Royal Stat Soc 1951; 13:1–38.
Astray G, Gullón B, Labidi J, Gullón P. Comparison between developed models using response surface methodology (RSM) and artificial neural networks (ANNs) with the purpose to optimize oligosaccharide mixtures production from sugar beet pulp. Ind Crop Prod 2016; 92:290–299.
Yolmeh M, Jafari SM. Applications of response surface methodology in the food industry processes. Food Bioproc Tech 2017; 10:413–433.
Behnam S, Karimi K, Khanahmadi M. Cellulase production under solid-state fermentation by ethanolic Zygomycetes
fungi: application of response surface methodology. NFSR 2019; 6:27–34.
Ratnakomala S. Enhancement of Cellulase (CMCase) production from marine actinomycetes Streptomyces
sp. Bse 7-9: optimization of fermentation medium by Response Surface Methodology. EES 2019; 251:12005.
Miller GL. Use of dinitrosalicylic acid reagent for determination of reducing sugars. Anal Chem 1959; 31:426–428.
Lowry OH, Rosebrough NJ, Farr AL, Randall RJ. Protein measurement with folin phenol reagent. J Boil Chem 1951; 193:265–275.
Kogo T, Yoshida Y, Koganei K, Matsumoto H, Watanabe T, Ogihara J et al.
Production of rice straw hydrolysis enzymes by the fungi Trichoderma reesei
and Humicola insolens
using rice straw as a carbon source. Bioresour technol 2017; 233:67–73.
Maftukhah S, Abdullah A. Cellulase enzyme production from rice straw using solid state fermentation and fungi Aspergillus niger
ITBCC L74. MATEC Web Conferences 2018; 156:01010.
Mandels M, Hontz L, Nystrom J. Enzymatic hydrolysis of waste cellulose. Biotechnol Bioeng 1974; 16:1471–1493.
Plackett B. The design of optimum multifactorial experiments. Biometrika 1946; 33: 305–325.
Box GE, Behnken DW. Some new three level designs for the study of quantitative variables. Technometrics 1960; 2:455–475.
Ghose TK. Measurement of cellulase activities. Pure Appl Chem 1987; 59:257–268.
Baig MMV, Biag MLB, Baig MIA, Yasmeen M. Saccharification of banana agro-waste by cellulolytic enzymes. Afr J Biotechnol 2004; 3:447–450.
Cabrera JC, Cutsem PV. Preparation of chitooligosaccharides with degree of polymerization higher than 6 by acid or enzymatic degradation of chitosan. Biochem Eng J 2005; 25:165–172.
Tanaka T, Fujiwara S, Nishikori S, Fukui T, Takagi M, Imanaka TA. Unique chitinase with dual active sites and triple substrate binding sites from the hyperthermophilic Archaeon Pyrococcus Kodakaraenis
KODI. Appl Env Micro 1999; 15:5338–5344.
Kumar S, Stecher G, Li M, Knyaz C, Tamura K. MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 2018; 35:1547–1549.
Lakshmi GS, Rao CS, Rao RS, Hobbs PJ, Prakasham RS. Enhanced production of xylanase by a newly isolated Aspergillus terreus
under solid state fermentation using palm industrial waste: a statistical optimization. Biochem Eng J 2009; 48:51–57.
Rahnama N, Foo HL, Rahman NAA, Ariff A, Md Shah UK. Saccharification of rice straw by cellulase from a local Trichoderma harzianum
SNRS3 for biobutanol production. BMC Biotechnol 2014; 14:1–12.
Sohail M, Ahmad A, Khan SA. Production of cellulase from Aspergillus terreus
MS105 on crude and commercially purified substrates. 3 Biotech 2016; 6:103.
Sharma R, Kocher GS, Bhogal RS, Oberoi HS. Cellulolytic and xylanolytic enzymes from thermophilic Aspergillus terreus
RWY. J Basic Microbiol 2014; 54:1367–1377.
Kumar AK, Parikh BS. Cellulose-degrading enzymes from Aspergillus terreus
D34 and enzymatic saccharification of mild-alkali and dilute-acid pretreated lignocellulosic biomass residues. BIOB 2015; 2:7.
Narra M, Dixit G, Divecha J, Kumar K, Madamwar D, Shah AR. Production, purification and characterization of a novel GH 12 family endoglucanase from Aspergillus terreus
and its application in enzymatic degradation of delignified rice straw. Int Biodeterior Biodegradation 2014; 88:150–161.
Aggarwal NK, Goyal V, Saini A, Yadav A, Gupta R. Enzymatic saccharification of pretreated rice straw by cellulases from Aspergillus niger
BK01. 3 Biotech 2017; 7:158.
Zheng W, Chen X, Xue Y, Hu J, Gao MT, Tsang YF. The influence of soluble polysaccharides derived from rice straw upon cellulase production by Trichoderma reesei
. Process Biochem 2017; 61:130–136.
Kaur J, Sandhu A, Soni R, Soni SJ. Valorisation of rice straw by using it as a substrate for production of cellulolytic-hemicellulolytic enzyme cocktail and second generation ethanol. J Fundam Renewable Energy Appl 2018; 8.
Hassan SS, Williams GA, Jaiswal AK. Emerging technologies for the pretreatment of lignocellulosic biomass. Bioresour Technol 2018; 262:310–318.
Rahnama N, Mamat S, Shah UKM, Ling FH, Rahman NAA, Ariff AB. Effect of alkali pretreatment of rice straw on cellulase and xylanase production by local Trichoderma harzianum
SNRS3 under solid state fermentation. Bio Resources 2013; 8:2881–2896.
Nguyen KA, Penkhrue W, Lumyong S. Production of high cellulase yields from polypore fungi in solid-state fermentation using green tea waste. bioRxiv 2019; 612093.
Mandels M. Microbial source of cellulose. Biotechnol Bioeng 1975; 5:81–105.
Hashem AM, Ismail SA, Hosny AED, Awad G, Ismail SA. Optimization of Dothideomycetes
spp.NRC-SSW chitosanase productivity and activity using response surface methodology. Egypt J Chem 2018; 61:973–987.
Ismail SA. Microbial valorization of shrimp byproducts via the production of thermostable chitosanase and antioxidant chitooligosaccharides. Biocatal Agric Biotechnol 2019; 20:101269.
Ismail SA, Serwa A, Abood A, Fayed H, Ismail SA, Hashem AM. Study the use of deep artificial neural network in the optimization of the production of antifungal exochitinase in comparison with the response surface methodology. JJBS 2019; XX:XX. (in press).
Joglekar AM, May AT. Product excellence through design of experiments. Cereal Foods World 1987; 32:857–868.
Ghorbannezhad P, Bay A, Yolmeh M, Yadollahi R, Moghadam JY. Optimization of coagulation-flocculation process for medium density fiberboard (MDF) wastewater through response surface methodology. Desalin Water Treat 2016; 57:26916–26931.
Ramos LP, Beruil C, Saddler JN. The use of enzyme recycling and the influence of sugar accumulation on the cellulose hydrolysis by Trichoderma
cellulases. Enzyme Microb Technol 1993; 15:19–25.
Vu VH, Pham TA, Kim K. Improvement of a fungal strain by repeated and sequential mutagenesis and optimization of solid state fermentation for the hyper-production of raw starch digesting enzyme. J Microbiol Biotechnol 2010; 20: 718–726.
Fatma H, El-Zaher Abd A, Fadel M. Production of bioethanol via enzymatic saccharification of rice straw by cellulase produced by Trichoderma reesei
under solid state fermentation. N Y Sci J 2010; 3:72–78.
Ilyas U, Majeed A, Hussain K, Nawaz K, Ahmed S, Nadeem M. Solid state fermentation of Vigna mungo for cellulase production by Aspergillus niger
. World Appl Sci J 2011; 12:1172–1178.
Trinh DK, Quyen DT, Do TT, Nguyen TTH, Nghiem NM. Optimization of culture conditions and medium components for carboxy methyl Cellulase (CMCase) production by a novel Basidiomycete strain Peniophora sp
.NDVN01. Iranian J Biotechnol 2013; 11:251–259.
Kobkam C, Tinoi J, Kittiwachana S. Alkali pretreatment and enzyme hydrolysis to enhance the digestibility of rice straw cellulose for microbial oil production. KMUTNB Int J Appl Sci Technol 2018; 11:XX.
Prajapati BP, Suryawanshi RK, Agrawal S, Ghosh M, Kango N. Characterization of cellulase from Aspergillus tubingensis
NKBP-55 for generation of fermentable sugars from agricultural residues. Bioresour technol2018; 250:733–740.
Chang KL, Wang XQ, Han YJ, Deng H, Liu JY, Lin YC. Enhanced enzymatic hydrolysis of rice straw pretreated by oxidants assisted with photocatalysis technology. Materials 2018; 11:802.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]