Application of Crude Enzymatic Extract In Mushroom Processing To Recover High Value Products

In the present study, a fungal strain was isolated from mushroom waste dump-site and was described based on the morphological and molecular characteristics. The crude enzymatic extract was prepared by fermenting pineapple peels using the newly isolated fungal strain under solid-state condition. The enzymatic saccharication conditions of mushroom were optimized using the central composite design based on the response surface methodology. The isolate had black colony color, conidial head biseriate and small conidia which are synonymous with Aspergillus niger. The phylogenetic analysis using the rDNA ITS sequencing further revealed that the isolate was identical ( ≥ 99%) to A. niger. The crude extract displayed CMCase, Fpase and xylanase activities of 20.73U/mL, 34.57U/mL and 118.03U/mL respectively. The saccharication using the crude extract at optimal conditions of pH 6.5, temperature 50 o C, enzyme loading of 5% (v/v) and time of 12h achieved maximum glucose yield of 1.639 mg mL -1 which is 1.1 folds higher than the predicted value. This study demonstrated the potential use of crude enzymatic extract from the newly isolated A. niger as a viable and ecient low-cost approach to mushroom processing using enzymes. Bootstrap support of branches indicated on the node was obtained using 500 replicates. Only statistically signicant bootstrap values ( ≥ 50%) are indicated. Branch lengths are indicated as 0.01 substitutions per positions according to the scale bar underneath the tree. Number in parentheses denotes GenBank accession numbers.


Introduction
Edible mushrooms are food items not only rich in nutrients but also other health promoting compounds.
Traditionally, mushrooms were eaten for a various reasons including status in the society, nutritional value, taste and aroma and as well as for the treatment of various illnesses (Kotowski 2019). Currently, mushrooms have received widespread application in the production of conventional medicine because of biologically active substances that they possess (Gasecka et al. 2017). These compounds include hemicelluloses, polysaccharides, lipopolysaccharides, peptides, proteins, glycoproteins, nucleosides, triterpenoids, complex starches, lectins, and lipid derivatives (Kalač 2009). In addition, mushrooms have high content of alkaloids, saponins, avonoids, tannins, sterols, triterpenes, coumarins and cyanogenic glycosides (Lindequist et al. 2005). These compounds have potent immunomodulatory, anticancer, antiproliferative, anti-in ammatory, antiviral, hypotensive and antithrombotic activities (Cheung 2008).
The choice of extraction techniques greatly affects the quality of biologically active compounds from plant or microbial sources including mushrooms, and to that extends, affects their speci c applications. The conventional extraction techniques of bioactive compounds have involved the use of highly toxic and in ammable solvents which have adverse effects not only in the environment but also on the quality of the nal products (Max et al. 2015). Enzyme-based extraction technique has been recently developed and is considered as a viable alternative to the solvent-based extraction methods (Puri et al. 2012). The increasing popularity of enzymes in industrial processing is due to the fact that it does not cause adverse effect on the environment and the quality of the nal product. However, despite many advantages, low product recovery, long extraction period and high cost of commercial enzymes are some of the major bottlenecks associated with enzyme-based processing (Arnau et al. 2019). In addition, it has not been possible to nd microbial strain that meets all the production processes.
In an attempt to improve the commercial viability of enzymes in industrial processing, the use of crude enzymatic extracts from the fermentation of low-cost agro-wastes is increasingly being considered (Dale 1999). This is because crude extracts from the fermented agricultural wastes contain enzyme mixtures capable of hydrolyzing lignocellulosic biomass (Gabriela et al. 2015). In fact, in certain instances, crude enzymatic extracts have proved to be more competitive than their commercial counterparts (Griggs et al. 2012). However, the reaction parameters need to be optimized in order to achieve high e ciency of hydrolysis using crude enzyme extracts. The traditional one-variable-at-a-time method has widely been used in many optimization processes; however, it has certain limitations including need for a number of experiments to be performed which is also time consuming (Singh et al. 2011). A response surface methodology is a mathematical and statistical tool which has the capability of modeling reaction parameters to achieve maximum response (Geiger 2014).
In the present study, a fungal strain was isolated from the mushroom waste dump-site and was characterized using cultural, morphological and molecular markers. The crude enzyme extract obtained by the solid state fermentation of pineapple peels was then used to hydrolyze mushroom biomass into glucose. The central composite design based on the response surface methodology was used to obtain optimal reaction condition for maximum glucose release from mushroom sacchari cation using crude enzyme extract.

Sampling
The soil sample was obtained from a mushroom waste dumpsite, near a market place in Nairobi, Kenya.
The sterile mushroom-agar media was inoculated with the sampled soil and was incubated at 30 o C for 7 days. Several fungal colonies were formed on the medium; however, only a fungal colony with the largest diameter was selected and sub-cultured on fresh Potato Dextrose Agar media. The pure culture of the selected isolate was stored at 20 o C for future use.

Morphological characterization
The fungal isolate was characterized based on the cultural and morphologies features including colony color, appearance, texture, and colony surface (Klich 2002, Samson et al 2007. Microscopic features including conidial shape, vesicle shape, vesicle arrangement, and appearance of the medulla were also examined by a light microscope after staining with lactophenol cotton blue.

Phylogenetic analysis
The genomic DNA was isolated and ampli ed using methods discussed in Otieno et al. (2015).
Phylogenetic analysis was performed using MEGA® software version 7. Multiple alignment of sequences and calculations of levels of sequence similarity were carried out by using ClustalW algorithm. A phylogenetic tree was built by calculating distance matrices for Maximum-Likelihood analysis with the Tamura 3-parameter model and bootstrapping analysis with 500 replicates to test the robustness of the internal branches for closely related strains (Kumar et al, 2018).

Physicochemical characterization
The ability of the isolate to grow in media with different pH levels, temperature values and salt (NaCl) concentrations was evaluated. For optimum pH elucidation, media was prepared using buffer solutions of pH ranging from 3 to 13. Temperature regime was evaluated by incubating the isolate at a temperature range of between 15 o C and 60 o C. Tolerance to [Na] + was assessed by growing the isolate in media with NaCl concentrations ranging from 0-15% w/v.

Solid-state fermentation of pineapple peels
The dry pineapple peels powder (10g) was put into 250mL Erlenmeyer ask and moistened with basal salt solution and then was autoclaved at 121 o C for 30 min. The sterile powder was inoculated with 1 mL of spore suspension (~1.0x10 7 spores/mL) and then was incubated at 30 o C. After 7 days, the substrate bed was suspended in 50mM phosphate buffer, pH 6.5 and agitated for 1h at 200rpm in an orbital shaker (Gerhardt, GmbH, Germany). The mixture was centrifuged at 5000rpm for 10 min at 4•C and the supernatant was stored at 20 o C for future use. The total protein content of the supernatant was estimated by the method of Lowry et al. (1951) using BSA as a standard.

Enzyme assay
To determine CMCase activity, 1% (w/v) of CMC solution (prepared using crude enzymatic extract, pH 6.0) was incubated at 50 o C for 30 min. Similarly, xylanase activity was determined by incubating 1% (w/v) of xylan solution (prepared using crude enzymatic extract, pH 6.0). Fpase activity was determined by adding small pieces (~50mg) of Whatman lter paper no.1 to crude enzymatic extract. The mixtures were incubated at 50 o C for 60min (Miller 1959). Similarly, the xylose content of the Beechwood xylan degradation was determined. The standard graphs were prepared using 0-500 µg of glucose for CMC and lter paper degradation. The standard graph of 0-500 µg xylose was used for xylan degradation.
One unit of enzyme activity is de ned as the amount of enzyme that catalyzes the release of 1 µmol of reducing sugar equivalent per minute under the speci ed assay conditions. Reaction parameters for mushroom sacchari cation Initial screening of single parameters on enzymatic sacchari cation of mushroom (Pleurotus ostreatus) was conducted using one variable at a time method (data not shown). Higher yields of glucose were recorded between pH 4.5 and pH 6.5, temperature range of 30-60 o C, enzyme loading range of 1-5%, w/v and incubation time of 12h and 60 h. One variable at a time was then optimized by employing response surface methodology based on central composite design to achieve maximum response values.
The range of enzyme loading, reaction pH, incubation time and temperature was determined based on the preliminary experiments shown in Table 1. For each experiment, 1% mushroom powder solution (prepared in phosphate buffer) was mixed with different volumes of crude enzyme extract (1 to 5mL). The pH of the mixtures was varied from pH 4.5 to pH 6.5 and then incubated at different temperatures (30 to 50 ∘C). Aliquots were removed after every 12h and analyzed for changes in glucose concentration using DNS method (Miller 1959).

Experimental design and data analysis
Response surface methodology was employed in determining the optimum reaction parameters for the enzymatic sacchari cation of mushroom biomass. After determining the initial range of the reaction parameters, a ve-level, four-factor CCD with 31 experiments was used in this study ( Table 1). The Minitab® software 17 was used to perform experimental design and statistical analysis. The key independent variables optimized were: reaction pH(x 1 ), incubation time(x 2 ), reaction temperature (x 3 ) and enzyme loading(x 4 ). The design had 16 factorial points, eight axial points, and seven replicates of the center point. The 31 runs were randomized and the response (glucose yield) was recorded in Table 2. The CCD data was analyzed by multiple regression to t the quadratic polynomial model. The analysis of variance and the effect and regression coe cients of individual linear, quadratic and interaction terms were determined as shown in Table 3. Signi cant levels were determined at p-values ≤0.05. The model was veri ed and validated by running con rmatory experiment in triplicate using the optimum reaction conditions generated by the RSM. The experimental and predicted values were compared and tested for statistical differences.

Morphological characteristics
The culture morphology of the isolate is illustrated in Figure 1.
The fungal isolate exhibited colony color black, reverse colony yellow, colony appearance spread spores, colony texture uffy, colony surface smooth; conidial head present; vesicle shape ovoid; vesicle arrangement biseriate; the appearance of metula entirely covering medulla; medulla shape oval; exudate absent; decumbent vegetative hyphae thin-walled, hyaline. The culture of the fungal isolate has been deposited at the NRRL Microbial Culture Collection under the voucher number Aspergillus niger NRRL 61452.

Phylogenetic relationships
The isolate had an ITS rDNA sequence length of 572 base pair. The BLAST search against the NCBI database revealed >99% maximum homology of the fungal isolate with the GenBank Aspergillus niger. The matrix for this analysis had 562 characters, 560 characters were conserved and only 2 were variable while none was phylogenetically informative. The phylogenetic relationship of this isolate with the GenBank homologs is shown in Figure 2. The sequence was deposited in GenBank under the accession number: MW237706. The isolated fungal strain was designated as A.niger KWM.
Bootstrap support of branches indicated on the node was obtained using 500 replicates. Only statistically signi cant bootstrap values (≥50%) are indicated. Branch lengths are indicated as 0.01 substitutions per positions according to the scale bar underneath the tree. Number in parentheses denotes GenBank accession numbers.

Physico-chemical characteristics
The isolate exhibited good growth at temperature range of 25-30 o C with optimal growth recorded at 30 o C; however, extreme temperatures of 20 o C or 40 o C highly restricted growth. Growth was recorded in media with pH range of 5 and 11 with the optimal growth being exhibited at pH 6 to 8; the growth was greatly limited at extreme pH≤4 or 12. Similarly, good growth rate was exhibited at 0-10% (w/v) NaCl concentration; best growth was recorded at 3-5 % (w/v) NaCl concentration. The growth was slow between 6-10 % (w/v) salt concentrations for the rst 5 days, but then highly improved after 7 days of growth. However, growth was extremely restricted beyond10% (w/v) NaCl concentration.

Enzyme activities
The crude extract was obtained from solid-state fermentation of pineapple peels by the fungal isolate. The enzyme activities of 20.73U/mL, 54.57U/mL and 118.03U/mL for CMCase, Fpase and xylanase respectively were displayed in the crude enzymatic preparations.

Statistical analysis and model tting
In the present study, a total of 31 runs were employed for optimizing the four independent variables. The CCD and their coded, experimental and predicted values are shown in Table 2. The results showed that the glucose yield ranged from 0.00 to 1.046 mg mL −1 . The experimental maximum glucose yield (1.046 mg mL −1 ) was found in conditions of pH 5.5, temperature 40 o C, time 36h and enzyme loading 5%. The model predicted maximum glucose yield of 0.934mg/mL in conditions of pH 6.0, temperature 45 o C, enzyme loading 4% (v/v) and time 48h. The results were tted with a second-order polynomial model described in equation 1: Y (Glucose yield) = β 0 + β 1 x 1 + β 2 x 2 + β 3 x 3 + β 4 x 4 + β 11 + β 22 + β 33 + β 44 + β 12 x 1 x 2 + β 13 x 1 x 3 + β 14 x 1 x 4 + β 23 x 2 x 3 + β 24 x 2 x 4 + β 34 x 3 x 4 (1) Where Y is the measured response; β 0 is the intercept term; β 1 , β2, β 3 , and β 4 are linear coe cients; β 11 , β 22 , β 33 , and β 44 are quadratic coe cients; β 12 , β 13 , β 14 , β 23 , β 24 , and β 34 are interaction coe cients; and x 1 , x 2 , x 3 , and x 4 represent the independent variables: temperature, pH, time and enzyme loading respectively. Table 2 Matrix of CCD for evaluation of effect of independent variables on the glucose yield The model expressed by equation (2) represents glucose yield (Y) as a function of pH (X 1 ), time (X 2 ), temperature (X 3 ), and enzyme loading (X 4 ). Y (Glucose yield) = 0.367714 + 0.044625x 1 + 0.062208x 2 +0.117292x 3 + 0.147958x 4 − 0.041085 -0.019710 + 0.022290 +0.081415 -.028438x 1 x 2 +0.025438x 1 x 3 +0.012062x 1 x 4 -0.005563x 2 x 3 + 0.052563x 2 x 4 -0.094938x 3 x 4 (2) The statistical signi cance of the regression model was evaluated by the P-value and F-test, and the ANOVA for the response surface quadratic model ( Table 3). The coe cient of determination was (R 2 ) was 0.87. The linear and quadratic terms in second order polynomial model (Eq. 2) were highly signi cant (p<0.01). The t and p-values for linear, quadratic and combined effects of the variables are given in Table 4. The time, temperature, pH and enzyme loading were linear variables which had signi cant (p<0.05) positive effects on mushroom hydrolysis. With regard to the quadratic terms, the medium pH and reaction time had negative effect on the glucose levels obtained. The temperature and enzyme loading positively affected mushroom hydrolysis. The effect of enzyme loading on glucose yield was signi cant (p < 0.05). Table 3 Analysis of variance of second order polynomial model for optimization of enzymatic sacchari cation of mushroom.

Analysis of response surface plots
Three-dimensional contour plots were used to visualize the interaction effect of the dependent and independent variables on the response while keeping the other two factors constant (Fig. 2a-f). The validity of the model equation for predicting the optimum response value was evaluated under the following optimal model conditions: pH 6.5, temperature 50 ∘C, time 12h and enzyme loading 5% (v/v). This set of optimum conditions was determined by a response optimizer ( Figure 3) and was used to validate the experimental and predicted yields of the responses using the model equation. A mean value of 1.639 ±0.04 mg mL −1 (n = 3) was obtained from the experiment which is 1.1 folds higher than the predicted value.

Discussion
The identity of the fungal isolate was determined based on the cultural and morphological characteristics ( Figure 1). The black colony color, conidial head biseriate and small conidia 2.7-3.5µm exhibited by this isolate are typical of Aspergillus niger as reported previously by Klich (2002) and Samson et al. (2007). The phylogenetic analysis using rDNA ITS sequences and the BLAST search against the GenBank reference strains revealed that the isolate was a close relative of Aspergillus species with the closest sister being the Aspergillus niger (MT620753). Pineapple peels are produced in high quantities across many fruit processing factories worldwide and their disposal still remain a great challenge. Their utilization as raw materials for the production of value added products such as enzymes may be a welcome move by the bioprocessing companies. In the present study, the fermentation of pineapple peels proved to be a viable cost-effective strategy of producing enzymes with widespread industrial applications. Crude enzymatic extract displayed strong cellulolytic and xylanolytic activities of 20.73U/mL, 34.57U/mL and 118.03U/mL for CMCase, Fpase and xylanase respectively. The cellulolytic and xylanolytic activity of crude extract from this isolate was higher than most lamentous fungi reported in the literature (Jampala et al. 2017). Similarly, xylanase and CMCase activities of 91.9 U/mL and 5.61 U/mL respectively were reported in fermentation broth of barley straw. In this study, the pineapple peels substrates must have in uenced the high enzyme activities displayed in the fermentation broth. Elisashvili et al (2008) had previously reported that the growth substrate have great in uence on the production enzyme production and activities.
The response surface methodology was used to develop the experimental design for evaluating the optimum conditions and the interaction effects of the process parameters on the response. The probability (p) F<0.05, the F-value = 7.39 and a low p-value (p=0.000) suggested that the model terms were signi cant. The coe cient of determination (R 2 =0.87) indicated that the experimental and predicted values were in good agreement, and that the model can well be used to predict process performance and optimization. The lack-of-t (F-value of 1.1) for regression of Eq. 2 was not signi cant (p-value=0.475). Non-signi cant lack-of-t is a good proof that the model equation is adequate to predict the response under any combination of values of the variables. Non-interactive effect of the variables (p > 0.05) on mushroom hydrolysis (Table 3) implies that these variables had additive effects on mushroom hydrolysis. Similar results had been reported by de Almeida et al. (2016) where non-interactive effect of reaction variables resulted in additive effects on the enzymatic sacchari cation of pineapple peels.
The effect of independent variables and their interaction on mushroom sacchari cation were visualized using three dimensional response surface plots (Figure 3). The interaction effect of temperature, incubation time, pH and enzyme loading had in uence on glucose yield. In a similar study, Sattler et al. The reported glucose yield (1.639 ±0.04 mg mL −1 ) in the present study is above glucose yields obtained from Pleurotus species previously reported (Sławińska et al. 2020, Zhou et al. 2912). This could have resulted from the e cient hydrolysis of mushroom biomass and the presence of adequate balance between different enzymes in the crude extract. Van Dyk and Pletschke (2012) noted that biomass degradation is a function of a balanced enzyme proportions that act in synergy to breakdown the complex structure of the lignocellulose. The accessory enzymes that are important in mushroom cell-wall degradation include glucanases, chitinases and proteases (Harman et al. 2004, Kubicek et al. 2014). These enzymes are also important during mushroom pathogenesis by the pathogenic fungi such as Trichoderma harziunum (Wang et al. 2016). The extract contains antifungal properties that may be employed in the management of many fungal related complications.
Enzymes have been used in mushroom processing to recover high value products. Banjongsinsiri et al.
(2016) used commercial bromelain and papain enzymes to enhance recovery of protein from mushroom biomass. Similarly, Poojary et al (2017) digested mushroom biomass with commercial enzymes to recover amino acids responsible for umami taste. However, for a long time, the cost of commercial enzymes has remained a major bottleneck in industrial bioprocesses. Increasing research into the applications of the crude enzyme extracts in the bioconversion processes is being driven majorly by the need to make enzyme-based processing more competitive. Mahamud and Gomes (2012) applied crude enzymes in sacchari cation of sugarcane bagasse for the production of bioethanol production; the crude enzyme extract of Trichoderma sp. displayed CMCase, Fpase and xylanase activities of 0.977, 0.110 and 9.280 U/ml which had overall degree of sacchari cation 45.71%. Similarly, Kumar and Sharma (2012) used crude enzyme extract in juice clari cation. In the same study, the crude enzymatic extract was more competitive compared to commercial enzymes and the combination of crude and commercial enzymes produced even better results. However, despite potential of crude enzymes as a viable approach to lowering the cost of bioprocessing, limited or probably no study is available on its application in mushroom processing. This study therefore provides baseline information necessary for the application of crude enzymatic extracts in mushroom processing.

Declarations
Tables      Effect of reaction variables on glucose yield during mushroom sacchari cation using crude enzymatic extract.

Figure 3
Optimization plot for enzymatic sacchari cation of mushroom A response optimizer (Figure 4) was used to create optimum conditions of temperature 50oC, incubation time of 12h, pH 6.5 and enzyme loading of 5% (v/v) with predicted yield of 1.494 mg mL-1