To evaluate the incidence of fungal cellulase production from some sources collected from different locations in Alexandria-Egypt, a survey study was conducted during 2018 using PDA plats with 1% carboxymethyl cellulose and 0.2% Congo red used as an indicator. A total of 122 fungal cellulase producers were isolated from various locations (cellulase producers showed a clear zone around the colonies) and were distributed as follows: waste materials, soil, wood, orange, bread, and eggplant (28.68, 25.4 percent, 14.75 percent, 12.2 percent, 11.47 percent, and 7.38 percent, respectively). The cellulosic waste materials were found to be high in fungal cellulose decomposers (28.68%), followed by soil (25.4%). The other tested sources were low in fungal cellulose decomposers, with prevalence reductions of approximately 50%.
Quantitative cellulase detection
The cellulase activity of the most promising selected fungal isolates was measured quantitatively (which showed the largest cleared zones) as presented in Table 1. The basal salt medium was prepared, inoculated with the most promising fungal cellulase producers and incubated for 7 days under shaken conditions at 28°C. The requisite analyses were evaluated at the termination of the incubation period. The results revealed that acetate buffer at pH 5 and 50°C was the most efficient buffer used for the estimation of cellulase activity with isolates. Carvalho et al [29] reported that Aspergillus niger, optimum conditions for complete cellulase synthesis, were reached after 74.27 hours of fermentation at 31.22°C, and cellulase enzymes were extremely resistant to a broad range of temperatures and pH values, indicating that they may be useful in industrial settings [29].
Identification of the most promising fungal isolate
The most promising cellulase producer (isolate 3SAZ) was developed on PDA plates. The cultural features on PDA plates revealed the filamentous characteristics of the promising fungi (as illustrated in Fig. 2). Light microscopic preparations of isolate 3SAZ revealed the morphological features of Aspergillus niger with a black spore arrangement [30].
Table 1 Isolate code, source of isolation, the zone size, and the cellulase activity of the most promising isolates.
Isolation code
|
Source of isolation
|
Zone size
|
Cellulase activity (U/ml/ml)
|
ASZ1
|
Waste materials
|
3.6
|
4
|
ASZ2
|
Waste materials
|
3.5
|
3.6
|
ASZ3
|
Waste materials
|
3.9
|
4.41
|
ASZ4
|
Waste materials
|
2.1
|
2.9
|
ASZ5
|
Soil
|
1.8
|
2.8
|
ASZ6
|
Soil
|
3.1
|
3.89
|
ASZ7
|
Orange
|
2.4
|
2.5
|
ASZ8
|
Wood
|
2.8
|
2.9
|
ASZ9
|
Wood
|
1.9
|
2.5
|
ASZ10
|
Bread
|
2.7
|
2.3
|
ASZ11
|
Bread
|
2.6
|
2.5
|
Molecular identification
DNA was successfully extracted using a GenJET genomic DNA extraction kit. DNA purity were noticed in the range of 1.8- 2 and concentration was 1023.3 ng/µl. Molecular identification of isolate-coded 3ASZ was performed using PCR-amplified 18S rDNA genes. The products of the PCR analyzed by 1% agarose gel. The use of phylogenetic tools has permitted the grouping of several genera and species according to conventional taxonomic techniques [31]. The sequence was submitted to the BLAST database to find homologies with other 18S rDNA sequences. The similarity percentages and accession numbers obtained after comparing the sequence of the tested strain to the submitted sequences in GenBank. The results showed that the isolate code 3ASZ was correlated to Aspergillus niger with 100% similarity. The sequence of isolate 3ASZ was submitted to the BLAST database to find homologies with other 18S rDNA sequences. A phylogenetic tree was created using the Mega 5 program (Fig. 2) and indicated that isolate 3ASZ is more related to the Aspergillus niger strain (GenBank accession no. MN535797.1).
Optimization of the nutritional requirements affecting Aspergillus niger 3ASZ cellulase production using a multifactorial statistical design
-Plackett-Burman design
A Plackett–Burman experimental design was used to optimize the medium composition for maximum cellulase output by Aspergillus niger 3ASZ and to evaluate the factors that significantly influenced its production. The Plackett–Burman design was used for 20 trials with double concentration levels for eleven separate variables (illustrated data in Table 2), as presented in the experimental matrix (Table 3). The corresponding results for the fifteen examined variables were summarized. A large variation in the results of the Plackett-Burman design experiments was observed. The cellulase activity from the different trials varied (3.5-29.5 U/ml/min). The main effects of the premeditated variables on cellulase activity were measured as presented in (Fig. 3). Soluble starch, ZnSO4 and CaCl2 were the most significant variables affecting cellulase production. Peptone, sodium carbonate and KH2PO4 were the most significant variables decreasing production, as presented in Table 4. The quality of the conventional model was indicated by the purpose of R2 (0.883295). Accordingly, the insignificant variables for the production of cellulase were discounted. According to Gautam et al [32], a concentration of 1.0% yeast extract, beef extract and peptone resulted in the highest cellulase production, with peptone producing the most cellulase followed by ammonium nitrate and beef extract, while yeast extract and sodium nitrate minimized the production of cellulase by Aspergillus niger. However, Abdullah et al [33] reported that urea increases cellulase yield. Carvalho et al [29] described that the incubation time resulted in a high income of cellulase by Aspergillus niger, which was also in contrast with the results of the current study that showed that incubation time was a nonsignificant factor in enzyme productivity. Similarly, Verma et al [34] reported that soluble starch increased the enzyme yield. Wu et al [35] found that MgSO4, K2HPO4, and peptone increased enzyme activity, contrary to the current findings. Although Gautam et al [32] found that peptone and yeast extract resulted in the highest cellulase production, the findings were strikingly different.
Table 2 Experimental variables at different levels used for cellulase production, using Plackett-Burman design
Variable code.
|
Variable %
|
Experimental values
|
Lower
|
Higher
|
X1
|
FeSO4.7H2O
|
0.0
|
0.0005
|
X2
|
Tween 80
|
0.0
|
0.1
|
X3
|
Soluble starch
|
0.0
|
0.004
|
X4
|
Peptone
|
0.4
|
2.00
|
X5
|
CaCl2
|
0.001
|
0.01
|
X6
|
Yeast extract
|
0.1
|
1
|
X7
|
KH2PO4
|
0.0001
|
0.05
|
X8
|
MgSO4.
|
0.001
|
0.05
|
X9
|
(NH4)2SO4
|
0.001
|
0.05
|
X10
|
MnSO4
|
0.0
|
0.002
|
X11
|
ZnSO4.7H2O
|
0.0001
|
0.003
|
X12
|
Urea
|
0.001
|
0.1
|
X13
|
Sodium acetate dehydrogenate
|
0.0
|
0. 1
|
X14
|
Sodium carbonate anhydrous
|
0.0
|
0. 1
|
X15
|
Incubation time
|
5 days
|
7 days
|
Table 3 Plackett-Burman design matrix for fifteen variables with coded levels
Trail
no.
|
Variables
|
Cellulase activity
(U/ml/min)
|
X1
|
X2
|
X3
|
X4
|
X5
|
X6
|
X7
|
X8
|
X9
|
X10
|
X11
|
X12
|
X13
|
X14
|
X15
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
4.5
|
2
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
19.5
|
3
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
9.5
|
4
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
7.5
|
5
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
21.5
|
6
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
7
|
7
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
21.5
|
8
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
5.5
|
9
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
24.5
|
10
|
-1
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
3.5
|
11
|
1
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
9.5
|
12
|
-1
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
10.5
|
13
|
-1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
4.5
|
14
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
13.5
|
15
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
20.5
|
16
|
1
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
20
|
17
|
1
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
22.5
|
18
|
-1
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
4
|
19
|
-1
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
29.5
|
20
|
1
|
1
|
-1
|
-1
|
1
|
1
|
1
|
1
|
-1
|
1
|
-1
|
1
|
-1
|
-1
|
-1
|
14.5
|
* -1; low level, +1; high level.
Table 4 ANOVA and Statistical analysis of Plackett–Burman design results on cellulase production by Aspergillus niger 3ASZ.
|
Coefficients
|
Standard Error
|
t Stat
|
P-value
|
Intercept
|
13.675
|
1.349911
|
10.1303
|
0.000535
|
x1
|
1.072552
|
2.055128
|
0.521891
|
0.629312
|
x2
|
0.979646
|
1.688569
|
0.580163
|
0.592917
|
x3
|
5.151386
|
1.671816
|
3.081312
|
0.036884
|
x4
|
-2.92405
|
1.657891
|
-1.76372
|
0.152554
|
x5
|
2.428271
|
1.678734
|
1.446489
|
0.221581
|
x6
|
0.088005
|
1.653485
|
0.053224
|
0.960105
|
x7
|
-1.68019
|
1.869237
|
-0.89886
|
0.419543
|
x8
|
1.31371
|
1.744133
|
0.753217
|
0.493226
|
x9
|
1.595513
|
1.869237
|
0.853564
|
0.441447
|
x10
|
2.064414
|
1.653485
|
1.248523
|
0.279926
|
x11
|
3.160842
|
1.678734
|
1.882872
|
0.13284
|
x12
|
-0.32071
|
1.657891
|
-0.19344
|
0.856038
|
x13
|
2.076034
|
1.671816
|
1.241784
|
0.282154
|
x14
|
-2.2994
|
1.688569
|
-1.36175
|
0.244928
|
x15
|
-0.31812
|
2.055128
|
-0.15479
|
0.884482
|
-Box-Behnken Design (BBD)
Box-Behnken design (BBD) and response surface methodology (RSM) were used to determine the optimal conditions for the production of cellulase enzymes. Relationships between the response of cellulase activity and independent variables were profits for manipulating the optimal state. Soluble starch, ZnSO4 and CaCl2 (independent significant variables) were exposed to the optimum response state for cellulase production. The quality of the conventional model of the Box–Behnken design was indicated by the purpose of R2 (0.92576). Table 5 symbolizes the matrix of the design, and Fig. 4 shows the surface plot results. The normality test is a crucial graphical tool for identifying and explaining whether the generated data set is normal or not. The residuals were displayed against the model's anticipated normal values in this investigation, as shown in Fig. 4. The residuals were distributed normally, as shown by the normal probability chart, with points dispersed close to the diagonal line. This meant that the anticipated cellulase productivity matched the experimental data rather well. A confirmation experiment was carried out to test the accuracy of PBD. The optimum environments recognized from the design were confirmed and paralleled the optimal activity predicted after the design. The predictable cellulase activity was 79.42231436 U/ml/min, where the actual activity after optimal conditions was 76.4 U/ml/min; therefore, accuracy grade (96.2%) established the strength of the ideal matrix under the following optimum conditions: (%) CMC, 0.3; FeSO4.7H2O, 0.0005, Tween 80, 0.1; Soluble starch, 0.005402; CaCl2, 0.029214; Yeast extract, 1; MgSO4, 0.05; (NH4)2SO4, 0.05; MnSO4, 0.002; ZnSO4.7H2O, 0.003301; Urea, 0.001 and Sodium acetate, 0. 1 at pH 5.5 with a cultivation temperature of 28°C and incubation time of 5 days under shaken conditions. Under these ideal circumstances, the maximum cellulase activity was 76.4 U/ml/min, which was over 18 times that of the basal medium.
Table 5 Box-Behnken design matrix and results for the most significant three Variables that affect Aspergillus niger 3ASZ celllase production
Trail
|
Soluble starch
|
ZnSO4
|
CaCl2
|
Cellulase activity (U/ml/min)
Measured Predicted
|
1
|
0
|
-1
|
-1
|
19.4
|
21.431
|
2
|
0
|
1
|
-1
|
18.1
|
19.875
|
3
|
0
|
-1
|
1
|
27.9
|
26.125
|
4
|
0
|
1
|
1
|
51.2
|
49.236
|
5
|
-1
|
-1
|
0
|
29.8
|
30.347
|
6
|
-1
|
1
|
0
|
34.6
|
35.347
|
7
|
1
|
-1
|
0
|
33.4
|
32.653
|
8
|
1
|
1
|
0
|
49.8
|
49.208
|
9
|
-1
|
0
|
-1
|
52.3
|
49.778
|
10
|
-1
|
0
|
1
|
60.0
|
61.194
|
11
|
1
|
0
|
-1
|
53.4
|
52.250
|
12
|
1
|
0
|
1
|
72.3
|
74.889
|
13
|
0
|
0
|
0
|
75.6
|
75.556
|
Effect of chemical compounds on produced cellulase
The tested crude Cellulase was tested against 1 mM of different compounds (CaCl2, NaCl, MgCl2, ZnCl2, FeSO4, MgSO4, MnSO4, CuSO4, EDTA, SDS, DMSO, glycerol, isopropanol, methanol, ethanol), as illustrated in (Fig. 5). Its activity was stable at different tested compounds, as presented.
Purification of produced enzyme
Cellulases are a widely and clinically used enzyme that requires high purity and yield. Purification and description are required steps in the development of the enzyme's performance and function. Ammonium sulfate precipitation was used to treat the crude enzyme, followed by sequential fractionation with the Amicon method. The concentrated ammonium sulfate fraction was transferred to an Amicon system (3 KDa), and the reported total activity was 29560 U/ml/min; volume, 20 ml with purification fold, 6.734 and yield of enzyme, 93.54. Using the Amicon system (partially purified enzyme, final volume, total enzyme activity, specific activity, purification fold and yield of cellulase) are illustrated in Table 6. The purification profile verified the effectiveness of the method, which could be used as a novel tool in the purification of cellulase enzymes. The strategy of enzyme purification depends on choosing a good source for enzyme production, a good method of homogenization and a perfect method of separation [36, 37]. The crude extract from the culture medium was taken through the two-step purification of gel filtration and ion-exchange chromatography [38]. After concentration of enzyme by ammonium sulphate, followed by protein fractionation using Amicon®Ultra filters, which has been the most widely used method to extract proteins, one of the big advantages of this method is a rapid sample preparation which only requires an ultrafiltration step with centrifugal filter devices [35].
Table 6 Purification profile of Aspergillus niger 3ASZ cellulase
Purification steps
|
Volume (ml)
|
Activity (U/ml/min)
|
Protein (mg/ml)
|
Total activity (U)
|
Specific activity (u/mg)
|
Purification fold
|
Yield of Enzyme loss (%)
|
Crude enzyme
|
400
|
79
|
1.119
|
31600
|
70.6
|
1
|
100
|
(NH4)2SO4 (40-70%)
|
20
|
1489.45
|
3.812
|
29789
|
390.73
|
5.534
|
94.27
|
Amicon system cut of 3 kDa
|
20
|
1478
|
3.109
|
29560
|
475.394
|
6.734
|
93.54
|
Amicon system cut of 100 kDa
|
20
|
1398
|
1.921
|
20970
|
545.8
|
7.797
|
66.36
|
Amicon cut off 10KDa
|
15
|
1388.6
|
1.450
|
20829
|
957.655
|
13.56
|
65.91
|
Amicon 20 KDa
|
10
|
2069.5
|
1.211
|
20695
|
1708.91
|
24.2
|
65.49
|
Amicon 30KDa
|
10
|
1898
|
0.899
|
18980
|
2111.23
|
29.9
|
60.06
|
Amicon 50KDa(50-100KDa)[Upper filter]
|
5
|
2284
|
0.601
|
11420
|
3800.33
|
53.83
|
36.13
|
Amicon 50KDa (30-50 kDa)[lower filter]
|
5
|
1399
|
0.201
|
6995
|
6960.2
|
98.58
|
22.14
|
Amicon 70KDa (70-100KDa) [Upper filter]
|
5
|
1791.8
|
0.492
|
8959
|
4570.91
|
51.58
|
28.35
|
Amicon70KDa(50-70KDa))[lower filter]
|
5
|
480
|
0.101
|
2400
|
4752.47
|
67.31
|
7.6
|
This technique allows the removal of high-molecular-weight solutes (i.e., proteins), retaining solutes of low-molecular-weight, including the analysis, after centrifugation over and done with a membrane with a suitable molecular weight cutoff with different molecular weights based on a size-exclusion filtration mechanism [40], At this step, fractions exhibiting cellulase activity were pooled and concentrated using Amicon®Ultra filters with different molecular weight cut off protein (3, 10, 30, 50 and 100 KDa) followed by characterization of the enzyme by determination of optimum temperature and pH required to reveal its possible industrial applications. Nasir et al [41] found that the enzyme was purified 2.33-fold with a yield and specific activity of 2.11% and 105 U/mg, respectively, using a Sephadex-G-100 gel column. While Imran et al [42] reported that the purified cellulase activity using a Sephadex-G-100 gel filtration column was increased by 5.14-fold with a yield and specific activity of 151.6% and 61.21 U/mg, respectively, Sulyman et al [43] observed that Aspergillus sp. cellulase specific activity (13.71 U/mg) increased 32-fold with DEAE-cellulose chromatography. On the other hand, Emmanuel and Queen [44] reported that Aspergillus niger cellulase activity was decreased during the purification steps, probably because fungi secrete a variety of digestive enzymes that can decompose lignin and other cellulosic materials; hence, the specific activity in the crude preparation of cellulase using ion exchange followed by Sephadex G-200 decreased from 12.50 to 5.18 μmol/ml/min/mg. However, Prajapati et al [45] reported that the highly active fraction obtained from cellulase purification from Aspergillus niger after anion exchange chromatography was 55 kDa, and it was found that when crude Aspergillus niger cellulase was subjected sequentially to six different treatments, the purified enzyme reported 245-fold increases in specific activity with 26.16% yield with 270-fold increases in activity and 22.11% yield were achieved [36]. An important implication of the results of purification of Aspergillus niger 3ASZ cellulases was high yield of pure cellulases with high enzyme activities due to application of Amicon®Ultra filters with different molecular weight cut off protein (3, 10, 30, 50 and 100 KDa), this sequential ultrafiltration was designed according to molecular weight of cellulase enzyme which was reported by many studies is below 100 KDa [46]. On the other hand, using Amicon®Ultra filters for molecular sieving was considered one of the most advantageous as it is time consuming, where each cut off takes approximately 30 minutes, so all the processes take approximately 5 hours, where the main studies used the Sephadex-G-100 gel filtration column in molecular sieving [36, 42, 46].
Effect of temperature and hydrogen ion concentration on the enzyme activity (crude and purified fractions)
-Effect of temperature
In a trial to standardize the optimum temperature of Aspergillus niger 3ASZ cellulase activities of the obtained purified fractions from Amicon Pro-purification system, the fractions were subjected to different temperatures (35-700C) for 30 min. Data in Fig. 6 revealed that the optimum temperature of protein extracted from Aspergillus niger3ASZ (50-100 KDa) showed two optimal temperature at 45 and 55 0C (indicating the presence of two enzymes), on the other hand the optimum temperatures of cellulase fractions (70-100 KDa), (50 -70 KDa), (30 -50 KDa) were 45 & 55 and 600C. It was reported that temperatures over 40°C decrease the activity of most enzymes, but the optimum temperature required for the activity of Aspergillus sp. cellulase was found to be approximately 60°C. Even at 90°C, which is near the boiling point, the activity of the enzyme was more than 80% [47]. It was reported that the optimum temperature of purified cellulase was 50°C at pH 6.0, and the enzymatic hydrolysis efficiency was maintained with more than 80% of the maximum efficiency over temperatures of 45 to 55°C and pH values of 4.0 to 7.0 [48].
-Thermal stability
To determine the current stability for the tested enzyme fractions, the residual Aspergillus niger 3ASZ cellulase activities of all fractions of the purified cellulases were plotted against exposure time at various temperatures (35, 40, 45, 50, 55, 60 and 65°C). The residual activities were measured under the reaction conditions of each fraction that had different optimum temperatures using acetate buffer at pH 5 (Table 7). All fractions were stable at 35 and 40 °C for 4 hrs. The thermal stability of cellulase was studied by treating the enzyme at 60, 65 and 70°C for up to 180 min and measuring the residual enzyme activity [45]. The optimum temperature of the purified enzyme was 50°C, and the enzyme was active over a range of pH 3.5-5 with optimal activity at pH 4.8. Narra et al [49] reported that the enzyme retained 99% of its maximum activity after 150 min of cultivation at 50°C. At 60°C, the purified enzyme retained 90% activity for 1 hour and more than 75% activity for 2 h followed by activity loss.
-Effect of hydrogen ion concentration on the enzyme activity (crude and purified fractions)
Different fractions of Aspergillus niger 3ASZ cellulases were recognized for enzyme activity as a function of pH ranging from 3 to 9 using acetate buffer (pH 3-5.5), phosphate buffer (pH 6-7.5) and tris-HCl (pH 8-9), and the optimum temperature for each fraction was used. There are variation in enzyme activities in relation to hydrogen ion concentrations. The optimum pH values of the purified Aspergillus niger 3ASZ enzyme fractions (50-70 KDa), (70-100 KDa), (50- 70 KDa) and (30-70 KDa) were 5, 5, 5 and 7, respectively. The optimum activity of cellulases pH 4.6 and a temperature of 45°C were discovered to be ideal. A wide optimum range of temperatures and pH values were reported for maximum cellulase activity that led to cellulase efficiency being active at diverse pH and temperature conditions, which could reflect the ability of the enzyme to degrade cellulosic material in a large variety of environmental conditions and thereby allow fungi to grow widely in diverse conditions. Hafiz et al [50] reported that the cellulase assay revealed that the enzymes were fully active over a broad pH range (5-8) with an optimum activity of 155 U/ml at pH 8. As the pH was increased above the optimum value (pH, 8), cellulase activity decreased. However, Megha et al [36] reported that fungi showed the best enzyme production at a pH range of 4-7 and temperatures range of 40-50°C. Prajapati et al [45] reported that purified cellulase had optimum activity at 70°C and pH 5.0, while the optimum pH, temperature, incubation time of the enzyme were 7.0, 35°C and 24 h, respectively [51]. Bano et al [47] reported that the optimum pH is 10, which renders the enzyme more alkalophilic for use in industrial applications. In conclusion, it was revealed that there is no specific pH or temperature for optimization of purified cellulase production, and it is correlated with many factors, namely, cellulase producer, pH, temperature, thermal stability of enzyme, etc.). These findings urge the need for a more in-depth study, that is, further given credence to the hypothesis that Aspergillus sp. are good sources of a variety of cellulolytic enzymes. All the obtained results indicated that Aspergillus sp. could serve as a good source of commercially and industrially viable cellulases.
Table 7 Thermal stability of the residual activities of the purified cellulase fractions at 45°C
|
A.niger 3ASZ cellulase fractions residual activity (%)
|
TIME
(min.)
|
(50-100 KDa)
|
(30-50 KDa)
|
(70-100KDa)
|
(50-70 KDa)
|
Crude enzym
|
15
|
100
|
100
|
100
|
100
|
100
|
30
|
100.2
|
100.4
|
100.1
|
100.9
|
100
|
45
|
110.1
|
100.2
|
100.2
|
101.8
|
100
|
60
|
100
|
99.8
|
100.4
|
101.9
|
100
|
75
|
100.3
|
97.5
|
100.9
|
102.3
|
100
|
90
|
101
|
94.89
|
101.3
|
103.9
|
100
|
105
|
102.1
|
93.2
|
101.7
|
102.2
|
100
|
120
|
100.5
|
92.55
|
100.9
|
101.9
|
100
|
135
|
100.2
|
91.5
|
100.89
|
101.6
|
98.2
|
150
|
100.1
|
90.6
|
100.67
|
101.4
|
97.8
|
165
|
99.98
|
89.5
|
100.49
|
100.6
|
96.4
|
180
|
99.69
|
87.3
|
100.3
|
100.2
|
95.9
|
195
|
99.06
|
86.8
|
100.1
|
99.9
|
95.1
|
210
|
98.97
|
85.9
|
100.06
|
99.58
|
94.5
|