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KH2PO4 improves cellulase production of Irpex lacteus and Pycnoporus sanguineus
⁎Corresponding author. inbiomis@gmail.com (María Daniela Rodríguez)
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Received: ,
Accepted: ,
This article was originally published by Elsevier and was migrated to Scientific Scholar after the change of Publisher.
Abstract
Abstract
The optimization of cellulase production by Irpex lacteus and Pycnoporus sanguineus was investigated. Fractional factorial design was conducted to determine significant variables and interactions. Response surface methodology was applied through Box-Behnken design to determine the optimum level of each factor on cellulase production. The optimal conditions of culture media were (g/L): for I. lacteus CaCl2.2(H2O) 0.3, MgSO4.7(H2O) 0.3 and KH2PO4 3, while for P. sanguineus was CaCl2.2(H2O) 0.1, MgSO4.7(H2O) 0.2 and KH2PO4 9. This optimized medium improved cellulase production, especially β-glucosidase activity values for I. lacteus. KH2PO4 was found in this work to be a useful mineral compound for cellulolytic production.
Keywords
Cellulase
Optimization
Response surface methodology
Mineral medium
1 Introduction
The availability of fossil fuel resources and the increasing energy demand are the main driving forces in the search for alternative energy sources. The large-scale replacement of petroleum fuels by biofuels, such as bioethanol from lignocellulosic materials (bioethanol 2G) appears to be a powerful approach to meet the growing energy demands (Abril and Abril, 2009). Increasing the use of bio-fuels for energy generation purposes is of particular interest nowadays because they allow mitigation of greenhouse gases (Balat and Balat, 2009). Bioethanol 2G is particularly promising because it can use the power of biotechnology to reduce production costs, employ abundant and low cost raw materials, has a higher octane rating and is an environmentally clean product. Lignocellulosic residues from wood, grass, agricultural and forestry wastes are particularly abundant in nature and have a potential for bioconversion. Wood sawdust from pine and eucalyptus are the most abundant lignocellulosic residue in forest regions. The lignocellulosic material from softwood source contains about 44% cellulose, 21% hemicellulose and 28% lignin (Galbe and Zacchi, 2002), while hardwood has 40% cellulose, 17% hemicellulose and 21% lignin (Lima et al., 2014). Coniferyl alcohol is the principal component of softwood lignins, whereas guaiacyl and syringyl alcohols are the main constituents of hardwood lignins. The principal component of hardwood hemicellulose is glucuronoxylan, whereas glucomannan is predominant in softwood (Pérez et al., 2002).
Sawdust constitutes a renewable resource from which many useful biological and chemical products can be derived. Accumulation of lignocellulose materials in large quantities in places where agricultural and forest residues present a disposal problem results not only in deterioration of the environment but also in loss of potentially valuable material that can be used in biomass fuel production (Sánchez, 2009).
Ethanol production from lignocellulosic materials comprises the following main unit operations: pretreatment, hydrolysis of cellulose and hemicellulose, sugar fermentation and bioethanol separation (Alvira et al., 2010; Balat and Balat, 2009). To breakdown polymeric sugars in an environmental friendly process, it is necessary to decrease the cost of cellulases production involved in hydrolysis of cellulose, to increase volumetric productivity, to use cheaper substrates and to produce enzymes with high stability (Percival Zhang et al., 2006).
White-rot fungi have the ability to degrade most of wood components due to their capacity to synthesize hydrolytic extracellular enzymes that recognize the links between the components of both lignin (polyphenolic oxidases) and hemicellulose (hemicellulases). Potential applications of lignocellulolytic enzymes in industrial and environmental biotechnology require huge amounts of these enzymes at the lowest cost possible (Elisashvili et al., 2008). The enzyme cost is one of the factors determining the economics of a biocatalytic process and it can be reduced with optimum conditions for their production and low-cost substrates (Ayishal et al., 2015; Lynd et al., 2002; Prasad et al., 2014).
Irpex lacteus and Pycnoporus sanguineus, white-rot fungi native from Misiones (Argentina), have potential for cellulase production when growing on wood flour as a carbon source (Rodríguez et al., 2015). However, there is a need to develop strategies to achieve overproduction (Elisashvili et al., 2008). Optimization of growth conditions and the evaluation of effects and interactions to find optimal conditions, have been used successfully in improving cellulase production, and it can be used to optimize the culture medium with a minimum number of experimental trials (Dave et al., 2013; Hoa and Hung, 2013; Huang et al., 2015; Oberoi et al., 2014; Sadhu et al., 2014; Shajahan et al., 2017; Shashidhar et al., 2013; Singh and Kaur, 2012; Sukumaran et al., 2005; Trinh et al., 2013). Combinatorial interactions of medium components with the production of the desired compound are numerous and the optimum processes may be developed using an effective experimental design procedure (Hao et al., 2006). Response surface methodology is a common statistic method, which is very useful in the optimization of biotechnological processes (Govarthanan et al., 2015; Tan et al., 2016). The statistical design and the development of culture conditions for increase cellulase production is the key issue to improving the implementation of enzymes in bioconversion of biomass (Padilha et al., 2015; Valencia and Chambergo, 2013).
In this study, I. lacteus and P. sanguineus were utilized for cellulase production and the optimization of the mineral medium was investigated for the enhancement of cellulase production by submerged fermentation. This work focused on cellulases, and as the polyphenolic oxidases and hemicellulases were not evaluated, as a carbon source was used eucalyptus and pine flour as a 50:50 mix. Fractional factorial design was conducted to determine significant variables and interactions. Then, response surface methodology was applied to determine the optimum level of each factor on cellulase production.
2 Material and methods
2.1 Microorganisms
I. lacteus BAFC 1171 and P. sanguineus BAFC 2126 were provided by the Mycological Culture Collection of the Department of Biological Sciences, Faculty of Exact and Natural Sciences, University of Buenos Aires, Argentina. Strains were maintained on malt extract agar at 4 °C.
2.2 Raw material
Sawdust from Pinus sp. and Eucalyptus sp. were collected from sawmill near to Posadas (Misiones, Argentina). Both materials were air-dried until 10% moisture content, ground in a hammermill and sieved. Pinus sp. wood flour (PWF) and Eucalyptus sp. wood flour (EWF) were classified by screening on a 40 mesh sieve.
The raw materials were characterized following analytical methods described in a previous work (Rodríguez et al., 2015). PWF contained 65.17 ± 0.74 (%w/w) carbohydrates, 24.45 ± 1.31 (%w/w) lignin and 1.82 ± 0.29 (%w/w) extractives; while EWF contained 69.9 ± 2.11 (%w/w) carbohydrates, 12.01 ± 0.93, (%w/w) lignin and 1.27 ± 0.13 (%w/w) extractives.
2.3 Inoculum
Strains were first cultured on malt extract agar for 5 days at 28 °C. To prepare the inoculum, eight 28 mm2 agar-plugs from each strain were cut and transferred to 500 mL Erlenmeyer flasks containing 100 mL of the following medium (g/L): ammonium sulphate 1.4, yeast extract 0.25, urea 0.3, glucose 5, MgSO4.7(H2O) 0.1, CaCl2.2(H2O) 0.1 and KH2PO4 5. The medium was adjusted at pH 5 and incubated at 29 °C in static conditions for 216 h.
2.4 Culture media and growth conditions
The inoculum was washed with sterile distilled water and homogenized with 50 mM acetate sodium buffer pH 4.8 and 0.1% (v/v) tween 80 until DO600 = 0.9. To each experiment, 14% (v/v) of inoculum was added to 250 mL Erlenmeyer flasks containing 50 mL of the following components (g/L): ammonium sulphate 1.4, yeast extract 0.25, urea 0.3, EWF 5, PWF 5.
MgSO4.7(H2O), CaCl2.2(H2O), KH2PO4, ZnSO4.7(H2O), CoCl2.6(H2O) and FeSO4.7(H2O) were added according to each experimental design. Flasks were incubated in a reciprocal shaker at 80 rpm and 30 °C for 360 h. The culture was maintained for so long time to be able to detect each maximum enzyme activity, since these may or may not coincide over time. Samples of culture supernatants were stored at −20 °C.
2.5 Enzyme assays
The FPcellulase activity (FPA) and endo-1,4-β-glucanase activity (EGs – EC 3.2.1.6) were determined according to International Union of Pure and Applied Chemistry (Ghose, 1987). The cellobiohydrolase activity (CBHs – EC 3.2.1.91) was determined according to Wood and Bhat (Bhat and Wood, 1988). FPA was assayed by measuring the release of reducing sugars in a reaction mixture containing 0.1 mL of crude enzyme, 10 mg of Whatman No. 1 filter paper as substrate and 0.2 mL of 50 mM sodium acetate buffer (pH 4.8) at 50 °C for 60 min. EGs activity was assayed by measuring the release of reducing sugars in a reaction mixture containing 0.1 mL of crude enzyme and 0.1 mL of 2% (w/v) of carboxymethylcellulose solution in 50 mM sodium acetate buffer (pH 4.8) incubated at 50 °C for 30 min. CBHs activity was assayed by measuring the release of reducing sugars in a reaction mixture containing 0.1 mL of crude enzyme and 0.1 mL of 1% (w/v) of cellulose in 50 mM sodium acetate buffer (pH 4.8) incubated at 50 °C for 60 min and 125 rpm. Reducing sugars were assayed by dinitrosalicyclic acid method (Miller, 1959). One unit of FPA, EGs and CBHs activity were defined as the amount of enzyme required to liberate 1 µmol of glucose per min from the particular substrate under the assay conditions.
The β-glucosidase activity (BGLs – EC 3.2.1.21) was measured using p-nitrophenyl-β-d-glucopyranoside (Bailey, 1981). The release of p-nitrophenol was measured at 400 nm from a reaction mixture containing 0.9 mL of 0.03 M p-nitrophenyl glucopyranoside in 50 mM acetate buffer (pH 4.8) and 0.1 mL of suitably diluted enzyme, incubated at 50 °C for 15 min and 125 rpm. One unit of BGLs activity was defined as the amount of enzyme required to liberate 1 µmol of p-nitrophenol per min under the assay conditions.
2.6 Fractional factorial design
To optimize the concentration of the mineral medium for I. lacteus and P. sanguineus, the mineral sources that had a significant effect on cellulases activities were identified by a 26-1 fractional factorial design (FFD). Experimental variables and levels in the FFD are shown in Table 1. In this design, six components were chosen from Mandels medium (Mandels and Reese, 1956). Each component was set into two levels: low (−1) and high (+1) level. The factors with a confidence level at or above 95% were selected to be optimized later.
Variables [g/L]
Symbol
Coded factor level
−1
+1
MgSO4·7 H2O
X1
0.1
0.5
KH2PO4
X2
1
5
FeSO4·7 H2O
X3
0
0.05
CaCl2 2 H2O
X4
0.1
0.5
ZnSO4·7 H2O
X5
0
0.002
CoCl2·6 H2O
X6
0
0.004
2.7 Box-Behnken design
Box-Behnken design (BBD) was performed to optimize the statistically significant variables with positive influence on cellulolytic production from FFD results. The independent variables for each strain (X1, X2, X3 and X4) were evaluated at three different coded levels: −1, 0 and +1 (Table 2).
Variable [g/L]
Symbol
I. lacteus
P. sanguineus
Coded factor levels
Coded factor levels
−1
0
+1
−1
0
+1
MgSO4 7 H2O
X1
0
0.3
0.6
0
0.2
0.4
KH2PO4
X2
0.5
3
5.5
0
3
6
FeSO4 7 H2O
X3
0
0.05
0.1
0
0.05
0.1
CaCl2 2 H2O
X4
0
0.3
0.6
The minimum and maximum ranges of variables were investigated. Response surface methodology (RSM) was used to analyse the results. Each enzyme activity was taken as the response (Y). The quadratic polynomial regression model was assumed for predicting response. The empirical formula to find the optimal cellulolytic yield was given by the Eq. (1):
2.8 Effect of KH2PO4 on cellulolytic production
Based on the Box-Behnken experimental design results, it was necessary to evaluate higher levels of KH2PO4 for P. sanguineus, so new concentrations were studied (6, 9 and 12 g/L). CaCl2.2(H2O) and MgSO4.7(H2O) were maintained constant at their optimum values (0.1 and 0.2 g/L, respectively).
These assays were performed in triplicate. The culture media and growth conditions employed were described above.
2.9 Statistical analysis
The statistical software package Statgraphic Centurion (StatPoint, Inc., version 15.2.05) was used for the experimental design matrix, regression analysis of the experimental data, and optimization procedure.
The analysis of variance (ANOVA) was used for data analysis, the least significant difference test (LSD test) was performed to establish differences among levels of a factor and standardized through Pareto charts. Differences were considered to be significant at p-value <0.05.
3 Results
3.1 Fractional factorial design
Initial screening of the most important mineral compounds (MgSO4.7(H2O), CaCl2.2(H2O), KH2PO4, ZnSO4.7(H2O), CoCl2.6(H2O), FeSO4.7(H2O)) and their interactions affecting cellulolytic production by I. lacteus and P. sanguineus was performed employing the FFD. Table 3 represented the FFD for thirty-five run experiments with two levels of values for each variable and the results with respect to cellulolytic production. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O), X4: CaCl22(H2O), X5: ZnSO47(H2O), X6: CoCl26(H2O). −1 low level, +1 high level.
Run
Variables
I. lacteus [U/L]
P. sanguineus [U/L]
X1
X2
X3
X4
X5
X6
EGs
CBHs
BGLs
FPA
EGs
CBHs
BGLs
FPA
1
−1
−1
−1
−1
−1
−1
481
18
58
86
122
16
156
138
2
1
−1
1
−1
−1
−1
421
24
77
86
113
14
62
79
3
−1
−1
1
1
−1
−1
549
26
68
81
148
18
58
72
4
1
−1
−1
1
−1
−1
542
18
60
75
207
22
110
101
5
−1
1
1
−1
−1
−1
169
18
66
44
233
51
207
103
6
1
1
−1
−1
−1
−1
588
44
70
96
219
40
207
124
7
−1
1
−1
1
−1
−1
507
37
79
94
220
38
211
110
8
1
1
1
1
−1
−1
361
22
51
59
233
22
134
93
9
−1
−1
1
−1
1
−1
308
24
64
106
152
10
116
62
10
1
−1
−1
−1
1
−1
219
28
73
100
187
16
160
86
11
−1
−1
−1
1
1
−1
204
18
57
76
204
23
125
123
12
1
−1
1
1
1
−1
300
37
77
78
154
34
65
80
13
−1
1
−1
−1
1
−1
657
51
53
81
230
58
225
117
14
1
1
1
−1
1
−1
355
41
61
82
226
33
209
111
15
−1
1
1
1
1
−1
427
29
62
45
224
34
181
109
16
1
1
−1
1
1
−1
293
40
79
94
202
38
203
113
17
−1
−1
1
−1
−1
1
381
24
67
78
196
19
120
86
18
1
−1
−1
−1
−1
1
211
19
63
31
131
25
149
51
19
−1
−1
−1
1
−1
1
239
29
84
79
176
6
126
62
20
1
−1
1
1
−1
1
505
31
67
81
167
9
57
66
21
−1
1
−1
−1
−1
1
411
49
49
75
67
0
44
43
22
1
1
1
−1
−1
1
167
20
47
28
204
36
177
116
23
−1
1
1
1
−1
1
204
42
67
73
202
42
182
118
24
1
1
−1
1
−1
1
259
43
49
95
207
34
109
112
25
−1
−1
−1
−1
1
1
338
30
89
93
206
32
195
92
26
1
−1
1
−1
1
1
599
34
64
82
215
22
85
95
27
−1
−1
1
1
1
1
818
43
69
82
163
20
107
76
28
1
−1
−1
1
1
1
499
36
54
83
183
17
98
73
29
−1
1
1
−1
1
1
396
55
73
94
267
6
209
101
30
1
1
−1
−1
1
1
960
44
71
80
261
39
217
108
31
−1
1
−1
1
1
1
503
35
75
98
224
45
195
119
32
1
1
1
1
1
1
170
43
52
98
263
29
155
99
33
0
0
0
0
0
0
720
44
63
119
222
34
136
101
34
0
0
0
0
0
0
714
46
62
100
256
37
184
103
35
0
0
0
0
0
0
740
45
64
94
222
31
154
98
The effect of each mineral source and their interactions were standardized to determine the positive or negative influence on cellulolytic production, and the significant parameters (p-value <0.05) are shown in Table 4. The p-value was used as an indicator of analysis and is important for understranding the pattern of mutual interactions between the variables. A negative effect means that there is a decrease in the response parameter for every increase in the variable, and vice versa. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O), X4: CaCl22(H2O), X5: ZnSO47(H2O), X6: CoCl26(H2O). +: positive influence, −: negative influence.
Variable
I. lacteus
P. sanguineus
EGs
CBHs
BGLs
FPA
EGs
CBHs
BGLs
FPA
X1
+
+
+
X2
+
+
+
+
+
+
+
+
X3
+
+
X4
+
X5
−
X6
−
−
−
−
Interactions
X5-X3
X2- X3
−
+
−
X1- X6
−
−
X1- X3
−
−
X2- X5
−
−
X4- X2
+
X4- X3
−
Table 4 shows that the cellulolytic production was positively influenced by KH2PO4; while CoCl2.6(H2O), affected in a negative manner. For I. lacteus, FPA was positively influenced by CaCl2.2(H2O) and FeSO4.7(H2O), and negatively influenced by the interaction MgSO4.7(H2O)-FeSO4.7(H2O) and MgSO4.7(H2O)-CoCl2.6(H2O).
For P. sanguineus, EGs activity was positively influenced by the interaction KH2PO4-FeSO4.7(H2O), whereas BGLs activity was negatively influenced. FPA and EGs activity were negatively influenced by KH2PO4-ZnSO4.7(H2O). For I. lacteus, EGs activity was positively influenced by the interaction KH2PO4-CaCl2.2(H2O). The EGs production by P. sanguineus was negatively influenced by ZnSO4.7(H2O). Therefore, the optimization scheme was continued with KH2PO4, FeSO4.7(H2O) and MgSO4.7(H2O), without ZnSO4.7(H2O) and CoCl2.6(H2O). The optimization procedure included CaCl2.2(H2O) only for I. lacteus because this factor and its interactions were significant (positively or negatively) only for this strain.
3.2 Optimization of mineral medium by RSM
Based on the above results, an optimization design was carried out. The mineral compounds MgSO4.7(H2O), CaCl2.2(H2O), KH2PO4 and FeSO4.7(H2O) for I. lacteus; and MgSO4.7(H2O), KH2PO4 and FeSO4.7(H2O) for P. sanguineus resulted to be significant for cellulolytic production by the FFD and was optimized by the BBD to determine their effects and interactions on cellulase production.
The concentration of these components was varied to determine the optimal concentration of each one that produced maximum cellulolytic activities. Variables from the FFD that did not significantly influenced in the enzymatic activities were maintained at the minimum level (Table 1). The experimental design matrix, with a total of 24 combinations and 3 replicates at the center points, was performed as shown in Table 5 for I. lacteus. The results showed that the mineral medium constituted in trial 22 gave maximal cellulase production. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O), X4: CaCl22(H2O). Activities are expressed on U/L.
Runs
X1
X2
X3
X4
Experimental
Predicted
EGs
CBHs
BGLs
FPA
EGs
CBHs
BGLs
FPA
1
−1
0
0
−1
929
34
60
78
845
42
66
88
2
1
0
0
−1
527
36
58
88
573
36
49
89
3
−1
0
0
1
842
36
55
106
778
44
63
98
4
1
0
0
1
842
50
80
109
907
50
73
92
5
0
−1
−1
0
682
24
46
77
627
23
38
72
6
0
1
−1
0
421
41
64
101
507
45
60
95
7
0
−1
1
0
585
19
21
68
481
23
23
67
8
0
1
1
0
851
31
70
100
887
41
77
98
9
−1
0
−1
0
580
36
46
81
577
42
53
97
10
1
0
−1
0
739
36
50
93
816
42
62
99
11
−1
0
1
0
829
48
70
97
1004
40
66
100
12
1
0
1
0
368
47
49
101
623
40
51
94
13
0
−1
0
−1
450
22
27
65
509
23
32
68
14
0
−1
0
1
421
18
22
45
641
27
38
60
15
0
1
0
−1
617
49
72
85
650
39
65
79
16
0
1
0
1
592
53
78
97
785
51
81
103
17
−1
−1
0
0
559
26
40
65
604
16
27
49
18
1
−1
0
0
641
31
34
75
476
28
31
79
19
−1
1
0
0
759
53
76
114
690
48
72
108
20
1
1
0
0
954
33
57
60
675
36
62
74
21
0
0
−1
−1
525
43
46
91
562
39
49
83
22
0
0
−1
1
1044
62
89
114
901
51
79
112
23
0
0
1
−1
977
37
66
103
885
41
69
104
24
0
0
1
1
1084
48
70
83
813
45
60
89
25
0
0
0
0
726
44
49
94
845
49
53
96
26
0
0
0
0
935
56
55
88
845
49
53
96
27
0
0
0
0
874
46
55
106
845
49
53
96
For P. Sanguineus, the design resulted in 12 combinations with 3 central points (Table 6). Results showed that the combination number 2 yielded the highest cellulolytic production. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O). Activities are expressed on U/L.
Runs
X1
X2
X3
Experimental
Predicted
EGs
CBHs
BGLs
FPA
EGs
CBHs
BGLs
FPA
1
0
−1
−1
11
6
40
7
29
9
50
12
2
0
1
−1
133
18
94
31
120
17
94
27
3
0
−1
1
4
14
54
3
17
15
54
7
4
0
1
1
63
11
46
19
45
8
36
14
5
−1
0
−1
56
3
57
15
61
3
56
14
6
1
0
−1
56
3
80
19
46
2
71
19
7
−1
0
1
6
0
35
13
16
1
44
13
8
1
0
1
9
1
28
3
4
1
29
4
9
−1
−1
0
9
6
37
9
0
4
28
5
10
1
−1
0
2
3
42
9
0
2
41
4
11
−1
1
0
61
1
53
12
69
3
54
17
12
1
1
0
9
2
31
11
32
4
40
15
13
0
0
0
57
5
29
19
52
3
39
16
14
0
0
0
43
2
49
10
52
3
39
16
15
0
0
0
44
2
38
19
52
3
39
16
Results obtained from the BBD, were examined by analysis of variance and the effects were standardized in Pareto charts. For I. lacteus, the results are shown in Fig. 1. These Pareto charts show the variables in descending order of importance with the estimated effect. The bars that cross the vertical line indicate that these variables significantly influenced at the confidence level studied. For EGs no factor or interaction was statistically significant.
Pareto charts with the estimated effect of the variables tested for (A) CBHs activity, (B) BGLs activity and (C) FPA in I. lacteus. The confidence level was 95%.
Results for P. sanguineus are shown in Fig. 2. For BGLs and FPA no factor or interaction was statistically significant.
Pareto charts with the estimated effect of the variables tested for (A) EGs activity and (B) CBHs activity in P. sanguineus. The confidence level was 95%.
The FPA, CBHs, BGLs (I. lacteus) and EGs activities (P. sanguineus) were positively influenced by X2 (KH2PO4).
Equations describing the model obtained for each enzyme studied were obtained. The optimal medium can be achieved from the model. Eqs. (2–5) correspond to I. lacteus, while Eqs. (6–9) correspond to P. sanguineus were Y1 and Y5 represent EGs activity, Y2 and Y6 CBHs activity, Y3 and Y7 BGLs activity, Y4 and Y8 to FPA [U/L].
The fitness of the model can be checked by the coefficient of determination (R2). The R2 value is always between 0 and 1. As R2 reaches close to 1, the model becomes stronger and it predicts the response better (Jung et al., 2015). Results showed that R2 were between 83 and 96%, which indicated that the model could explain these percentages of variability in the response. Regression equation can describe the real relationship between each variable and the response value. Eqs. (2–9) show that the cellulolytic production was positively influenced by KH2PO4.
The three-dimensional response surfaces were plotted to investigate the interaction between the variables and to determine the optimum concentration of each factor for maximum cellulase production. The contour plots of enzyme activities are shown in Figs. 3 and 4. The peaks and curvature indicated the maximum enzyme activity in the response surface plots. The shapes of the surfaces, circular (or) elliptical indicated remarkable interaction between the independent variables.
Response surface plots of the Box-Behnken design to optimize the mineral medium for cellulolytic production by I. lacteus. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O), X4: CaCl22(H2O).
Response surface plots of the Box-Behnken design to optimize the mineral medium for cellulolytic production by P. sanguineus. X1: MgSO47(H2O), X2: KH2PO4, X3: FeSO47(H2O).
The optimum concentration of MgSO4.7(H2O) coincided with the central point which corresponded to 0.2 g/L in P. sanguineus and 0.3 g/L in I. lacteus. For I. lacteus, the optimal concentration of KH2PO4 and CaCl2.2(H2O) coincided with the central point corresponding to concentrations of 3 g/L and 0.3 g/L respectively, except for BGLs, where the optimum concentrations corresponded to +1 levels of both salts. For P. sanguineus, the highest level (+1) of KH2PO4 gave the maximum enzymatic activities. So, to find the optimum cellulolytic activities it was necessary to increase its concentration. The optimum concentration of FeSO4.7(H2O) corresponded to −1 level (absence) for both strains.
3.3 Validation of experimental model
For I. lacteus, the maximum enzyme activities predicted by the RSM model were 1004 U/L for EGs, 51 U/L for CBHs, 81 U/L for BGLs and 112 U/L for FPA, while for P. sanguineus were 120 U/L for EGs, 17 U/L for CBHs, 94 U/L for BGLs and 27 U/L for FPA.
In order to verify the model, the optimal conditions were applied to three independent replicates for cellulolytic production. For I. lacteus, the average EGs activity was 808 U/L, for CBHs activity was 40 U/L, for BGLs was 82 U/L and for FPA was 87 U/L, whereas for P. sanguineus the EGs activity was 105 U/L, CBHs 10 U/L, BGLs 88 U/L and FPA was 29 U/L. The experimental values were in agreement with the predicted response.
3.4 Effect of KH2PO4 on cellulolytic production of P. Sanguineus
For P. sanguineus, the enzyme activities were positive influenced by KH2PO4 and the levels tested in the BBD were not high enough to find the optimum concentration, hence a new experiment was performed testing higher concentrations of this compound and the results are shown on Fig. 5.
Effect of KH2PO4 on cellulolytic production of P. sanguineus.
Cellulolytic activities showed differences among the levels of KH2PO4 studied. In the case of EGs, CBHs and FPA, the activities values were similar for 9 and 12 g/L of KH2PO4, and higher than that produced with 6 g/L. For BGLs, the higher activities obtained corresponds to 9 g/L of KH2PO4 (155 U/L), so the appropriate concentration of KH2PO4 was 9 g/L.
The increase of 6–9 g/L of KH2PO4 involved, for example, an increase of 30 U/ L of BGLs (125–155 U/L). The gram of KH2PO4 costs 0.048 U$S, therefore, increasing from 6 to 9 g/L of KH2PO4 costs 0.144 U$S per liter of culture medium. 1 U of BGLs costs approximately 0.0245 U$S, so the increase of 30 U generated by the increment from 6 to 9 g/L of KH2PO4 corresponds to 0.651 U$S. Therefore, 0.144 U$S is invested to produce 30 U/L more, which in the market costs 0.651 U$S. The same occurs to the other cellulases.
4 Discussion
4.1 Determination of significant variables for cellulolytic production by 26-1 fractional factorial design
Analyzing the activity of each enzyme, it was found that the KH2PO4 positively influenced cellulolytic production on both strains. KCl had an increase of 12% in the production of EGs by Peniophora sp. (Trinh et al., 2013). Other authors have found that cellulase production by Trichoderma reesei, measured as FPA, was markedly reduced in the absence of KH2PO4 (Li et al., 2011; Wen et al., 2005). As regard to FeSO4.7(H2O), a positive influence on CBHs activity of P. sanguineus and FPA of I. lacteus was observed. Other authors found that FeSO4.7(H2O) at concentrations between 0.05 and 0.2% negatively influenced in EGs (Trinh et al., 2013) and CBHs production by Trametes versicolor (Shah et al., 2010). The CoCl2.6(H2O) negatively influenced most of the cellulolytic enzymes (Table 4). For T. reesei, it was found that cobalt was not crucial for cellulolytic production (Wen et al., 2005). With respect to CaCl2.2(H2O), its influence was positive, and its interaction with KH2PO4 was also positive in I. lacteus. CaCl2.2(H2O) maximized the production of cellulases secreted by Chaetomium sp. (Kapoor et al., 2010) and Bacillus licheniformis NCIM 5556 (Shajahan et al., 2017). The MgSO4.7(H2O) had a positive influence, but its interaction with other minerals was negative. The positive influence of MgSO4.7(H2O) in the production of EGs is in agreement with similar behavior found by other authors (Singh and Kaur, 2012).
Complex substrates such as lignocellulosic residues induce the co-production of substrate degrading enzymes. For applications, improvement and modification of the complex molecular structure of lignocellulosic materials, the synergistic action of substrate degrading enzymes is required and crude enzymes can be more efficient than purified enzymes, decreasing total production cost considerably (Moteshafi et al., 2016; Yennamalli et al., 2013). For these reasons, it is important to study conditions in order to promote the production of cellulolytic cocktail.
4.2 Optimization of mineral medium using Box-Behnken design
After FFD experiments, the components of the mineral medium with significant influence on cellulolytic production were identified, and the concentration thereof was optimized by an optimization design.
For P. sanguineus, the optimal concentration of CaCl2.2(H2O) was 0.1 g/L, value corresponding to an optimized composition for T. reseei using manure as the carbon source (Wen et al., 2005). For I. lacteus, the optimal concentration of CaCl2.2(H2O) was 0.3 g/L. Regarding to MgSO4.7(H2O), the optimal concentrations were 0.2 g/L and 0.3 g/L for P. sanguineus and I. lacteus, respectively. For Penicillium echinulatum, the optimum value of MgSO4.7(H2O) and CaCl2.2(H2O) were 0.375 g/L for each mineral, maximizing EGs, BGLs and FPA activities (dos Reis et al., 2015).
Through the BBD, it was found that the optimum concentration of KH2PO4 was 3 g/L for I. lacteus, but for P. sanguineus it was necessary a further experiment to find the right concentration of the mineral, corresponding to 9 g/L. For T. reesei the maximum production of EGs and total cellulases was achieved with 4 g/L, after optimizing the concentration of KH2PO4 (Hao et al., 2006).
Regard to each particular cellulase, higher EGs activities were obtained with I. lacteus (808 U/L). Aspergillus niger and T. reesei employing carboxymethylcellulose as carbon source produced 70 and 90 U/L respectively while A. ochraceus produced 225 U/L cultivated on rice straw (Lee et al., 2011). EGs activity was improved in both strains, with 800 U/L by I. lacteus and 145 U/L by P. sanguineus against 500 y 80 U/L in Mandels medium without optimization (Rodríguez et al., 2015).
Optimized medium improved cellulase production, especially BGLs activity values for I. lacteus (81 U/L), which were found to be 40-fold higher than conventional Mandels medium. For P. sanguineus the increase was 8-folds, 155 U/L in optimized medium against 19 U/L in traditional Mandels medium, however, this value was low compared with those reported by other authors using lignocellulosic substrates and synthetic medium (Lee et al., 2011; Yoon et al., 2013).
Regarding to FPA, increasing was not significant, however, for CBHs activity, in both strains were obtained 2-folds higher activity respect to traditional Mandels medium (27 U/L for I. lacteus and 14 U/L for P. sanguineus) (Rodríguez et al., 2015). The major CBHs activity corresponded to I. lacteus (40 U/L). This result was similar that produced by P. sanguineus employing corncob as carbon source (Falkoski et al., 2012). I. lacteus also produced the higher FPA (87 U/L) and this result was comparable as that obtained by T. reesei employing synthetic medium (Ezekiel et al., 2010).
5 Conclusions
Important variables of culture media for cellulase production were investigated by FFD. From results, the significant variables were investigated on BBD. Optimal conditions of culture media for cellulase production were (g/L): for I. lacteus CaCl2.2(H2O) 0.3, MgSO4.7(H2O) 0.3 and KH2PO4 3, while for P. sanguineus was CaCl2.2(H2O) 0.1, MgSO4.7(H2O) 0.2 and KH2PO4 9. KH2PO4 was found in this work to be a useful mineral compound for cellulolytic production. Therefore, the model was reliable for maximizing cellulase production of I. lacteus and P. sanguineus. Thus, this study demonstrated that RSM with appropriate experimental design can be effectively applied for the optimization of the variables of culture media in microbial fermentation. For these strains, however, remain to study the operational parameters such as culture temperature, pH and speed of agitation.
Acknowledgments
This work was supported by the Ministry of Science, Technology and Productive Innovation; and General Secretariat of Science and Technology [gran numbers 16Q477]. MDR and MLC have fellowships from National Council of Scientific and Technical Research (CONICET).
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