¹Department of Microbiology and Biotechnology, Gujarat University, Navrangpura, Ahmedabad, India

²M G Science Institute, Dada Saheb Mavlankar Campus Opposite Gujarat
University Navrangpura, Ahmedabad 380009, Gujarat, India

³Shri P.H.G. Municipal Arts and Science College, Kalol, Gujarat, India

Article Publishing History

INTRODUCTION

The need to save resources, combined with pollution issues from agro-industrial waste and limited disposal options, has encouraged the bioconversion of waste into industrially valuable products (Freitas et al. 2021; Phiri et al. 2024). Considerable amounts of agricultural biomass deemed ‘waste’ is now being explored for the production of biofuels, animal feed, chemicals, and enzymes, among other value-added items (Singh et al. 2021; Velvizhi et al. 2022; Alazaiza et al. 2025).

For example, abundantly and the cheaply available lignocellulosic agrowaste such as vegetable and fruit peels (Panda et al. 2016), rice and wheat husk (Devi et al. 2022; Abena and Simachew 2024), corn cobs (Devi et al. 2022; Joshi et al. 2023), sugarcane bagasse (Devi et al. 2022; Yadav et al. 2022), coconut coir (Khangwal and Shukla 2022), and wood pulp (Walia et al. 2013; Singh et al. 2023) etc. are increasingly being explored for production of important hydrolytic industrial enzymes such as xylanase and cellulase (Sadh et al. 2018; Waheeb et al. 2021; Yafetto 2022).

 The polysaccharide components of lignocellulosic agrowaste are cellulose and hemicellulose. Cellulases consisting of endoglucanase (EC 3.2.1.4), exoglucanase (EC 3.2.1.91) and b-glucosidase (EC 3.2.1.21) act synergistically to convert the cellulose complex of biomass into glucose and oligosaccharide (Fatokun et al. 2016a; Tingthong et al. 2021). Xylanase is the class of enzymes which convert the polysaccharide beta-1,4-xylan into xylooligosaccharide, xylobiose and xylose subunits (Pandey et al. 2022; Chaudhary et al. 2023). Xylanase plays an important role in the conversion of the hemicellulose component of biomass into xylose, (Sarangi and Thatoi 2024).

Xylanases are the enzyme complexes responsible for hydrolysis of xylan, and they include endo-1,4-xylanases (EC 3.2.1.8) and -xylosidases (EC 3.2.1.37), in addition to side-chain-hydrolyzing enzymes (Kumar et al. 2014; Fatokun et al. 2016a). Xylanase and cellulase are important industrial enzyme that have series of applications in food, textile, agriculture, paper pulp and the bioremediation industry (Rodrigues and Odaneth 2021; Basit et al. 2021).The global market for industrially useful enzymes was estimated to be about $ 12.27 billion in the year 2022 and is expected to develop at a compound annual growth rate (CAGR) of approximately 6.5% over the period from 2023 to 2030 (Li et al. 2012; Grand View Research 2023).

Bacteria and fungi can secrete multiple lignocellulolytic enzymes, including xylanases and cellulases (Gudynaite-Savitch and White 2016; Talamantes et al. 2016). However, in recent times, bacterial enzymes for industrial applications are continually increasing due to their rapid growth rate and tenacity to be genetically engineered in contrast to fungi (Danso et al. 2022). Correspondingly, a variety of xylanase and cellulase-producing bacteria have been applied to lignocellulosic biomass for production of enzymes  (Menendez et al. 2015; Chakdar et al. 2016; Kaur et al. 2024).

Streptomyces is one of the most important genera of Actinomycetes involved in fermentation process and it has been widely used for enzyme production (Javed et al. 2021; Khushboo et al. 2022). For example, recently Shrestha et al., reported production of multi-enzyme (pectinase, cellulase, and xylanase) from Streptomyces sp. using agrowaste mixture (Shrestha et al. 2022). Sinjaroonsak et al., recently optimized production of xylanase and cellulase by Streptomyces thermocoprophilus TC13W from pretreated empty fruit bunch of oil palm (Sinjaroonsak et al. 2020).  Advantages of Streptomyces derived enzymes include their high level of extracellular activity, stability across a broad temperature (50–85 °C) and pH (pH 3–13) range (Kumar et al. 2019). Researchers are working to isolate novel Streptomyces strains from unexplored habitats for exploring the potential and application of enzymes secreted by them (Kumar et al. 2020).

Enzyme activity is influenced by numerous parameters such as pH, temperature, inducers, medium additives, and type of fermentation (Bhardwaj et al. 2019).

 Furthermore, enzyme activation is dependent on various metal ions as activators or inhibitors. For this reason, optimization and in-depth analysis of these parameters are a must for maximizing enzyme activity. Here, we have employed submerged fermentation processes (SmF) for the production of xylanase and cellulase. Advantages of SmF include homogeneous conditions in the media, better biomass utilization, and easy scale-up. It has been reported that SmF enables better biomass utilization and therefore results in higher enzyme production (Hansen et al. 2015; Joshi et al. 2023).

This study aimed to study the influence of parameters such as pH, temperature, substrate and enzyme concentration for optimum enzyme production using response surface methodology (Siwach et al. 2024). Enzyme activity of crude and purified xylanase and cellulase produced from indigenously isolated Streptomyces lividans was studied using one factor at a time approach. Cultured broth media was filtered and taken as crude enzyme. Enzyme purification was carried out from broth media using spin column and gel electrophoresis (Boucherba et al. 2014; Joshi et al. 2023).

MATERIALS AND METHODS

Optimization using Response Surface Methodology :Response surface methodology was employed to get optimum conditions of significant variables. Three independent variables, namely, ammonium sulphate (g) and dextrose (g), and substrate (g) were assessed for the dependent response variable e., cellulase and xylanase enzyme production (U/mL), Table 1. State Ease Design-Expert V 10.0.1 software was used for multiple non-linear regression of response for each run to obtain the coefficient of the polynomial equation. Response surface methodology processed by use of central composite design (CCD). Statistical analysis of the model was performed to evaluate the analysis of variance (ANOVA). The statistical significance of the model was determined by the F-test and the goodness of fit of the estimated polynomial equation was assessed based upon the coefficient of determination (R2), response surface and contour plots (Vaishnav et al. 2022).

Table 1. RSM experimental runs and response

		Factor 1	Factor 2	Factor 3	Response 1	Response 2
Standard	Run	A: Ammonium sulphate (g)	B: Dextrose (g)	C: Substrate concentration (g)	Cellulase (U/mL)	Xylanase (U/mL)
15	1	2.25	2.75	2	425.13	423.09
10	2	4.35224	2.75	2	356.06	364.08
1	3	1	1.5	1	372.09	305.79
16	4	2.25	2.75	2	429.45	419.98
6	5	3.5	1.5	3	418.42	438.84
8	6	3.5	4	3	453.55	460.32
13	7	2.25	2.75	0.318207	247.58	158.29
3	8	1	4	1	398.52	346.6
17	9	2.25	2.75	2	432.19	428.14
2	10	3.5	1.5	1	220.48	158.07
9	11	0.147759	2.75	2	393.47	396.11
20	12	2.25	2.75	2	421.78	417.69
14	13	2.25	2.75	3.68179	412.89	433.27
7	14	1	4	3	390.06	390.1
12	15	2.25	4.85224	2	471.02	428.95
5	16	1	1.5	3	430.38	432.79
18	17	2.25	2.75	2	440.52	432.28
4	18	3.5	4	1	353.64	297.28
19	19	2.25	2.75	2	423.98	420.34
11	20	2.25	0.647759	2	426.13	384.31

Bacterial strain: From our previous work we screened bacteria efficient in production of cellulase and xylanase using agricultural waste as substrate. Based on 16S rRNA analysis the indigenously isolated bacterium was identified as Streptomyces lividans. Gram’s staining was carried out to study cultural and morphological characteristics. Nutrient agar was used to study colony characteristics. The strain was maintained on nutrient agar slant and stored at 4 ^o

Crude enzyme and Purified enzyme: Sterilized basal salt media (yeast extract, K₂HPO₄, KH₂PO₄, MgSO₄.7H₂O, (NH₂)₂SO₄, NaCl, CaCO₃) containing 2 g of corn cob for xylanase or coconut husk for cellulase was inoculated with Streptomyces lividans and incubated for 72 hours at 37 ^o The broth was filtered and taken as crude enzyme. 100 mL of crude xylanase/cellulase enzyme was concentrated by spin column chromatography to give 10 mL of purified enzyme.

Protein (enzyme) characterization: Crude and purified protein (enzyme) was characterised for molecular weight by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) using 3 mm gel slab. Coomassie brilliant blue G-250 was used as a stain. Broad range molecular weight marker was used for molecular weight determination. Crude and purified enzyme was characterised using SLS One Stop Protein Purification mini prep protocol.

The 10 mL of crude supernatant after xylanase/cellulase production was incubated at 37°C for 30 minute and mixed with equal volume of precipitation and binding buffer. The system was incubated on ice for 2-5 minute and then centrifuged for 10, 000 RPM for 5 minute.

The supernatant was removed and the pellet was resuspended in 500μl of resuspension buffer. The solution was transferred to SLS One-step protein Spin Column and centrifuged at 10,000 RPM for 1 minute.

The spin column was placed into a brand-new collecting tube, and 100μl of elution buffer was added to it. The tube was incubated at room temperature for 1 minute. and then centrifuge at 10,000 RPM for 1 minute. The eluted protein (1 mL) was collected for further analysis.

Effect of influencing parameter The effects of influencing parameters, such as temperature, pH, substrate concentration, and enzyme amount, were investigated. Enzyme activity of parameters was assayed by measuring released sugar using DNSA reagent (Miller 1959). Briefly, 1 mL of crude/purified enzyme was mixed with 1 mL of 1 % substrate (CMC for cellulase and Xylan for xylanase) in addition to 2 mL of buffer. After 10 minutes of incubation at ambient room temperature (̴ 30 + 3 ^oC), 1 mL DNSA was added Enzyme activity (µmol/minute) was calculated using equation 1.

Here, incubation time was 10 minutes. Molecular weight of xylose and cellulose is 150.13 g/mol and 162.14 g/mol, respectively.

Enzyme activity was investigated for influencing parameters such as temperature, pH, substrate concentration and enzyme amount.

RESULTS AND DISCUSSION

Cultural and Morphological Characteristics

Table 2. Cultural Characteristics on Nutrient agar.

Shape	Size	Colony appearance	Margin	Elevation	Texture	Gram’s reaction	Pigment
Round	Medium	Rough	Entire	Slightly Raised	Dry	Gram Positive	Nil

Figure 1: Colony characteristics of KJB17 on A. Nutrient Agar plate, B. Basal Salt Agar plate

To verify the phenotypic characteristics of the KJB17 strain, the bacteria was grown on Nutrient Agar plate. The resulting colony was slightly raised, colourless colony with rough appearance on Nutrient Agar, Figure 1 A. Additionally, the KJB17 strain colony was also grown on Basal Salt Agar plate on which it gave distinctly pink colonies as can be seen in Figure 1 B. Furthermore, on Nutrient agar as well as Basal salt agar media plate, the KJB17 strain gave luxurious growth, Figure 1.

Based on microscopic observation of Gram staining, KJB17 strain is Gram positive, long rod and non-capsulating, Figure 2, based on Bergey’s Manual of Systematic Bacteriology (Beg et al. 2001; Abdulkhair et al. 2025).

Response surface methodology : For RSM analysis, twenty different experimental runs were design to study enzyme production response according to runs provided by minimum and maximum value of ammonium sulphate, dextrose, and substrate concentration, as listed in Table 1. Table 3 represents experimental design matrix with actual and predicted values of xylanase and cellulase production. Increasingly, RSM optimization is being studied for optimum enzyme production (Amadi et al. 2020; Siwach et al. 2024).

Table 3. Experimental design matrix of RSM with experimental and predicted values of xylanase and cellulase enzyme

	Xylanase		Cellulase
Run	Actual Value	Predicted Value	Actual Value	Predicted Value	Standard
Order					Order
1	423.09	423.6934	425.13	428.9125	15
2	364.08	356.7232	356.06	347.927	10
3	305.79	301.1914	372.09	366.268	1
4	419.98	423.6934	429.45	428.9125	16
5	438.84	442.9705	418.42	423.1065	6
6	460.32	467.5572	453.55	461.124	8
7	158.29	161.3139	247.58	251.9438	13
8	346.6	345.1081	398.52	395.5854	3
9	428.14	423.6934	432.19	428.9125	17
10	158.07	166.6463	220.48	228.2753	2
11	396.11	399.7353	393.47	399.1254	9
12	417.69	423.6934	421.78	428.9125	20
13	433.27	426.5145	412.89	406.0486	14
14	390.1	384.1623	390.06	384.0167	7
15	428.95	433.5664	471.02	475.647	12
16	432.79	440.8606	430.38	437.0892	5
17	432.28	423.6934	440.52	428.9125	18
18	297.28	291.848	353.64	348.6827	4
19	420.34	423.6934	423.98	428.9125	19
20	384.31	375.9621	426.13	419.0253	11

Table 4. Analysis of variance (ANOVA) table for Response Surface Quadratic model for Xylanase enzyme

	Sum of		Mean	F	p-value
Source	Squares	df	Square	Value	Prob > F
Model	141127.8	9	15680.86	236.0699	1.90209E-10	Significant
A-Ammonium sulphate	2233.191	1	2233.191	33.61992	0.000173366	Significant
B-Dextrose	4005.483	1	4005.483	60.30115	1.52675E-05	Significant
C-Substrate	84897.47	1	84897.47	1278.102	6.96241E-12	Significant
AB	3303.626	1	3303.626	49.73493	3.48902E-05	Significant
AC	9337.295	1	9337.295	140.5697	3.27184E-07	Significant
BC	5061.689	1	5061.689	76.20196	5.44057E-06	Significant
A2	3723.496	1	3723.496	56.05593	2.09372E-05	Significant
B2	645.4682	1	645.4682	9.717298	0.010924847	Significant
C2	30340.5	1	30340.5	456.7656	1.12078E-09	Significant
Residual	664.2466	10	66.42466
Lack of Fit	509.3735	5	101.8747	3.288972	0.108646708	Not significant
Pure Error	154.8731	5	30.97463
Cor Total	141792	19

Table 5. Analysis of variance (ANOVA) table for Response Surface Quadratic model for Cellulase enzyme

Source	Sum of Squares	Df	Mean Square	F Value	p-value Prob > F
Model	74609.29	9	8289.921	109.0996	8.64E-09	Significant
A-Ammonium sulphate	3164.153	1	3164.153	41.64189	7.32E-05	Significant
B-Dextrose	3870	1	3870	50.9312	3.15E-05	Significant
C-Substrate	28666.7	1	28666.7	377.2686	2.86E-09	Significant
AB	4148.694	1	4148.694	54.59896	2.34E-05	Significant
AC	7689.24	1	7689.24	101.1944	1.51E-06	Significant
BC	3394.056	1	3394.056	44.66753	5.48E-05	Significant
A2	5526.093	1	5526.093	72.72623	6.7E-06	Significant
B2	611.4555	1	611.4555	8.047071	0.017647	Significant
C2	17983.98	1	17983.98	236.6785	2.74E-08	Significant
Residual	759.8486	10	75.98486
Lack of Fit	524.6043	5	104.9209	2.230041	0.199675	Not significant
Pure Error	235.2443	5	47.04886
Cor Total	75369.14	19

For determining regression model fitting was significant or not significant, ANOVA analysis was conducted for xylanase and cellulase which is summarised in Table 4 and Table 5, respectively. ANOVA of regression model demonstrated model was highly significant based on Fisher’s F-test with high F-value and p-value. The p-value checks significance of each coefficient, and indicates interaction strength between each independent parameter.  F-value of 236.07 and 109.10 implies model is significant for xylanase and cellulase, respectively. Smaller p-value (here, p < 0.05 for xylanase and cellulase) indicates higher significance of corresponding coefficient.  As can be seen from Table 4 and Table 5, A, B, C, AB, AC, BC, A², B², and C² are significant for xylanase and cellulase production, respectively. The “Lack of Fit F-value” of 3.29 with corresponding p-value of 0.10 for xylanase (Table 4) and 2.23 with corresponding p-value of 0.19 for cellulase (Table 5) implies the Lack of Fit is not significant relative to the pure error. Insignificant lack of fit confirmed the validity of model.

Table 6. Statistical calculation of RSM experimental design for xylanase and cellulase

	Xylanase	Cellulase
Std. Dev.	8.150132	8.716929
Mean	376.816	395.867
C.V. %	2.162894	2.201984
PRESS	4321.114	4515.445
R-Squared	0.995315	0.989918
Adj R-Squared	0.991099	0.980845
Pred R-Squared	0.969525	0.940089
Adeq Precision	53.13943	40.13299

Furthermore, statistical calculation to determine the goodness of the model for experimetal desgin of xylanse and cellulase are depicted in Table 6. For xylanase, “Pred R-Squared” of 0.9695 is in reasonable agreement with the “Adj R-Squared” of 0.9911, i.e. the difference is less than 0.2. Likewise, for cellulase, “Pred R-Squared” of 0.9401 is in reasonable agreement with the “Adj R-Squared” of 0.9808, i.e. the difference is less than 0.2. “Adeq Precision” measures the signal to noise ratio and ratio greater than 4 is desirable. Adeq Precision value of 53.13943 and 40.13299 for xylanase and cellulase reveal an adequate signal. Thus, based on all these results, this model can be used to navigate xylanase and cellulase production.

Zhang et al. 2016 studied optimisation of xylanase and cellulase from Streptomyces griseorubens JSD-1 using RSM for improved enzymatic saccharification efficiency. Walia et al., 2015 (Walia et al. 2015) studied xylanase from Cellulosimicrobium cellulans CKMX1 and its improvement using RSM.

Figure 3: Esponse surface plots of xylanase and cellulase showing interaction of three
variables (Ammonium sulphate, dextrose, and, substrate concentration).

The three-dimension (3D) contour plots were prepared to understand the effect of three variables, i.e., ammonium sulphate, dextrose, and substrate concentration on xylanase and cellulase production, Figure 3. 3D contour plots visual interaction between two variables by fixing third variable at zero level. All graphs clearly reveal influence of substrate concentration is major contributor for xylanase and cellulase production.

Molecular identification by 16s rRNA gene technology

Figure 4: Phylogenetic tree of KJBs17 (Streptomyces lividans)

ABI 3730xl Genetic Analyzer was used to carry out the DNA sequencing reaction of the PCR amplicon with prime r27F using BDT v3.1 Cycle sequencing kit for molecular identification. The BLAST search of 16S rRNA gene sequence against sequences in nucleotide database showed 100% homology with Streptomyces lividans strain, Fig. 4. Thus, the new indigenously isolated strain was identified as Streptomyces lividans (Thomas et al. 2013). The genomic sequence is uploaded on National Center for Biotechnology Information (NCBI) portal with accession number of PP528163. The genomic sequence of identified Streptomyces lividans is

TGCTGGCAACACGGGACAAGGGTTGCGCTCGTTGCGGGACTTAACCCAACATCTCACGACACGAGCTGACGACAGCCATGCACCACCTGTACACCGACCACAAGGGGGGCACCATCTCTGATGCTTTCCGGTGTATGTCAAGCCTTGGTAAGGTTCTTCGCGTTGCGTCGAATTAAGCCACATGCTCCGCCGCTTGTGCGGGCCCCCGTCAATTCCTTTGAGTTT.

Streptomyces is described as a Gram positive, spore-forming, and aerobic actinobacterium, which has a high guanine-cytosine (GC) content in the genome and contains LL-diaminopimelic acid in the cell wall. Streptomyces are reported to produce amylase (Al-Dhabi et al. 2020; Lakshmi et al. 2020), protease (Sarkar and Suthindhiran 2020), cellulase (Danso et al. 2022), xyalanase (Porsuk 2013; Danso et al. 2022), nitrate reductase (Zhang et al. 2021), and catalase (Kim et al. 2013) to hydrolyze starch, protein, cellulose, xylan, nitrate, and hydrogen peroxide, respectively.

Crude and purified protein was characterised using the SLS one-stop Nontagged protein purification column per standard protocol. The column is specifically designed with combination of immobilized metal affinity chromatography and boronic acid-based resins for efficient protein purification.  The molecular weight of crude and purified enzyme was determined using SDS-PAGE. As can be seen from Figure 5, there are several fragments of crude and purified protein. Molecular mass of denatured protein was between 66.4 to 20.1 kDa as measured by comparative movement of proteins on SDS-PAGE (Wu et al. 2018). The obtained results are in consistent with that obtained by (Waheeb et al. 2021b; Abdulkhair et al. 2025).

Figure 5: Electrophoresis on agar gel

Enzyme activity and its influencing parameter

Enzyme activity was investigated for influencing parameters such as temperature, pH, substrate concentration and enzyme amount. Enzyme activity was measured using DNSA method (Miller 1959; Islam and Roy 2018). Several studies have studied optimization of influencing parameters for enzyme activity for xylanase (Techapun et al. 2002; Khurana et al. 2007; Fatokun et al. 2016b; Sinjaroonsak et al. 2020)  and cellulase (Fatokun et al. 2016b; Sinjaroonsak et al. 2020).

Figure 6: Temperature effect on enzyme activity of crude and purified enzyme. A. Xylanase B. Cellulase

The effect of temperature in the range of 20 to 60 ^oC on enzyme activity of crude and purified xylanase and cellulase was determined, Figure 6. As can be seen purified enzyme of xylanase and cellulase reported higher activity than crude enzyme for all studied temperature, Figure 6 Xylanase and cellulase show good activity at within temperature range of 20 to 40^oC, Figure 5. Maximum activity of 419.6 µmol/mL (Figure 6A) and 339.2 µmol/mL (Figure 6B) for purified xylanase and cellulase respectively was reported at 30^oC. Maximum activity for crude xylanase of 337.07 µmol/mL (Figure 6A) and cellulase of 245.51 µmol/mL (Figure 6B) was reported at 20^oC and 30^oC, respectively. Similar results have been reported by Leya et al., for Streptomyces sp. (Thomas et al. 2013; Sinjaroonsak et al. 2020). Temperature is important parameter for optimum enzyme production due to alterations in microbial protein structure and its properties with variations in temperature (Juturu and Wu 2014; Li et al. 2025).

Cellulase: The effect of initial pH in the range of 2 to 10 were investigated to understand its influence on enzyme activity of crude and purified xylanase and cellulase, Figure 7. pH of growth media was regulated with 0.1 N HCl/NaOH. From the results it can be seen that pH 8 and 10 are optimum for xylanase, Figure 7 A and cellulase, Figure 7 B, with respect to crude as well as purified. In addition, clearly for all pH studied crude for cellulase reported better activity than purified, Figure 7 B. Interestingly for xylanase, no significant change in enzyme activity of crude and purified was reported, Figure 7 A. It is noted that synthesis and expression of certain genes, and microbial metabolic activities, are influenced by the internal pH, in response to that of the external environment (Fatokun et al. 2016b). In addition, many enzyme systems and the transport of several enzyme species across the cell membrane are influenced by the initial pH of the cultivation medium (Fatokun et al. 2016b). Thus, it is crucial to maintain optimum pH.

Figure 8: Substrate concentration effect on enzyme activity of crude and purified
enzyme. A. Xylanase B. Cellulase

Effect of substrate concentration in the range of 5 to 25 mg was studied on enzyme activity of crude and purified xylanase and cellulase, Figure 8. As can be seen for xylanase optimum enzyme activity of 486.2 µmol/mL was reported for crude and purified enzyme at substrate concentration of 20 mg and 25 mg, Figure 8 A. Interestingly, for purified cellulase optimum enzyme concentration of 400 µmol/mL was reported at 25 mg and crude cellulase enzyme activity of 395 µmol/mL was optimum at 20 mg and 25 mg of substrate concentration, Figure 8 B. Since xylanase and cellulase are inducible extracellular enzyme, substrate concentration plays an important role (Ortiz-Cortés et al. 2021). Overall, substrate concentration exhibited positive linear behaviour on enzyme activity as expected. However, higher concentration of substrate is also reported to adversely affect the growth and enzyme activity as seen in case of purified cellulase enzyme at 25 mg (Bajar et al. 2020).

Figure 9: Enzyme volume effect on enzyme activity of crude and purified enzyme. A. Xylanase B.

Cellulase : The effect of enzyme amount in the range of 0.5 to 2.5 mL was studied on enzyme activity of crude and purified xylanase and cellulase, Figure 9. As can be seen, Figure 9 A and B, enzyme activity of crude was optimum than purified for xylanase as well as cellulase at enzyme amount of 2.5 mL. Enzyme activity of 510.87 µmol/mL was optimum for xylanase and enzyme activity of 449.5 µmol/mL was optimum for cellulase. The results are as expected that with increase in enzyme amount enzyme activity would show an increase.

Figure 10: Influence of optimized parameters on enzyme activity of
crude and purified Xylanase and Cellulase

From the above results (Figure 10), optimized parameters for xylanase were 30^oC temperature, 10 pH, 20 mg substrate concentration, and 2.5 mL enzyme volume. These parameters reported enzyme activity of 510 µmol/mL and 499.56 µmol/mL for crude and purified xylanase respectively. Likewise, optimised parameters for cellulase were 30^oC temperature, 8 pH, 20 mg substrate concentration, and 2.5 mL enzyme volume. These optimized influencing parameters reported enzyme activity of 405.6 µmol/mL and 467.22 µmol/mL for crude and purified enzyme respectively. By exploiting the potential of Streptomyces lividans and optimizing the fermentation process, we can enhance the production of cellulase and xylanase for its applications.

CONCLUSION

Overall, we used response surface methodology to investigate the influence of three variables (ammonium sulfate, dextrose, and substrate concentration) on the activity profile of xylanase and cellulase production. Through experimental design and three-dimensional contour plots, we found that substrate concentration was the major contributor to the production of both enzymes (xylanase and cellulase). We evaluated the potential of indigenous Streptomyces lividans isolated from agrowaste for xylanase and cellulase production using substrate fermentation. Furthermore, we examined the influence of various parameter, i.e., temperature (20-60^oC), pH (2-8), substrate concentration (5-25 mg), and enzyme volume (0.5-2.5 mL) on enzyme activity of xylanase and cellulase. The specific enzyme activity under optimum parameters conditions was found to be 4.21 µmol/mg-minute for xylanase and 3 µmol/mg-minute for cellulase, respectively. By exploring the potential of Streptomyces lividans and optimizing the fermentation process, we can enhance the production of these important industrial enzymes. Furthermore, future research should focus on the potential enhancement of enzyme activity through genetic manipulation, thereby improving the applicability of xylanase and cellulase.

ACKNOWLEDGMENTS

We extend our heartfelt gratitude to Dr. Meenu Sarraf, Head Department of Microbiology M G Science Institute, DadaSaheb Mavlankar Campus Opposite Gujarat University, Navrangpura, Ahmedabad 380009, Gujarat.

Author conflict statement: All authors confirm that there are no known conflicts of interest associated with this publication.

Funding: Research work received no external funding. Kinjal Joshi received financial support from SHODH fellowship

Data Availability Statement:  Data will be made available on request

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