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Ann Microbiol (2017) 67:175–183 DOI 10.1007/s13213-016-1249-8 ORIGINAL ARTICLE Optimization of chitinase production by a new Streptomyces griseorubens C9 isolate using response surface methodology 1,2 1,2 Gasmi Meriem & Kitouni Mahmoud Received: 5 August 2016 /Accepted: 8 December 2016 /Published online: 24 December 2016 Springer-Verlag Berlin Heidelberg and the University of Milan 2016 Abstract The purpose of this article is to use statistical Benner 2008), with at least 10 gigatonnes synthesized and de- Plackett–Burman and Box–Wilson response surface method- graded each year in the biosphere. It is a crystalline polysaccha- ology to optimize the medium components and, thus, improve ride consisting of long linear chains containing more than 1000 chitinase production by Streptomyces griseorubens C9. This units of N-acetyl-β-D-glucosamine linked by β-1,4 glycoside strain was previously isolated and identified from a semi-arid bonds. It may also be related to other structural elements, such as soil of Laghouat region (Algeria). First, syrup of date, colloi- proteins or glucans (Attwood and Zola 1967; Schaefer et al. dal chitin, yeast extract and K HPO ,KH PO were proved to 1987; Merzendorfer and Zimoch 2003). It is widely distributed 2 4 2 4 have significant effects on chitinase activity using the in nature, including eukaryote single-cell (yeast, amoeba, dia- Plackett–Burman design. Then, an optimal medium was ob- toms) and multicellular organisms (filamentous fungi, arthro- tained by a Box–Wilson factorial design of response surface pods, nematodes, snails) (Ehrlich et al. 2007b). It is also present methodology in liquid culture. Maximum chitinase produc- in some marine sponges and algae (Ehrlich et al. 2007a). tion was predicted in medium containing 2% colloidal chitin, However, it is not present in plants, vertebrates or prokaryotes 0.47% syrup of date, 0.25 g/l yeast extract and 1.81 g/l (Funkhouser and Aronson 2007). Chitin can be degraded by K HPO ,KH PO using response surface plots of the chemical, physical or enzymatic methods, but the physical and 2 4 2 4 STATISTICA software v.12.0. chemical methods are limited by their low efficiency, high cost, and lack of specificity, even if they have been industrialized. On the other hand, enzymatic degradation of chitin is much more Keywords Chitinase activity Streptomyces griseorubens eco-friendly but relatively slow in kinetics (Gooday 1990). . . . C9 Plackett–Burman Response surface methodology Therefore, scientists have been interested in improving this en- Box–Wilson zymatic method, in order to find chitinase-producer organisms and enhance their chitinolytic activity. Chitinases (EC 126.96.36.199) belong to the glycosyl hydrolases family and are present in a Introduction wide range of organisms that may not contain chitin but still play an important eco-physiologic role. Many chitinolytic enzymes Chitin is the second most represented polysaccharide in nature have been identified in several Streptomyces species, including after cellulose (Gooday 1990; Whitman et al. 1998;Kaiserand S. antibioticus, S. griseus, S. plicatus, S. lividans, S. aureofaciens and S. halstedii (Narayana and Vijayalakshmi 2009). These enzymes can be used as antibacterial and biocon- * Gasmi Meriem firstname.lastname@example.org trol agents in agriculture and medicine. They can also be used in the fields of industry (Usui et al. 1987) and biotechnology (Radford 1991). Studies on medium optimization for chitinase Laboratoire de Génie microbiologie et applications, Université des production using statistical methods reduce the time and ex- Frères Mentouri Constantine, Campus Chaâbat Erssas, Route Ain El Bey, 25000 Constantine, Algeria pense because they are able to detect the real optimum level of factors in less time. In addition, the culture medium components Present address: Department of Biochemistry and Cellular Biology, University of Mentouri Brothers, Constantine, Algeria have a major influence on the microbial production of 176 Ann Microbiol (2017) 67:175–183 extracellular chitinases. For this, Plackett–Burman design experiment (Plackett and Burman 1946). The variables con- (PBD) and response surface methodology (RSM) are the most sidered for the design are listed in Table 1. A total of 19 widely used statistical approaches (Montgomery 2008). In this variables (15 real and 4 dummy) in 20 different combinations study, we evaluate the effects of 15 factors on the production of were selected for this study. Table 2 shows the design matrix, chitinase enzyme by S. griseorubens C9. The variables that including the 19 variables, to assess their effect on chitinase could affect the production of chitinase were identified statisti- production; it also gives the response evaluated as a chitinase cally by PBD and central composite designs (CCD). activity. All experiments were carried out in duplicate. Each independent variable was explored at high (+1) and (−1) low level. The PBD is based on the first-order model: Materials and methods Y ¼ β þ Σβ X þ ε ð1Þ 0 i Microorganism and culture conditions Where Y is the experimental response (chitinase activity), β the main effects of the factors, β is the regression coefficient, X is i i The chitinase-producing bacterial strain C9 was isolated from the level of the independent variable, and ε is a random error. a semi-arid soil surrounding the region of Laghouat (Algeria) This model does not describe the interaction between factors. It and was identified as a member of the Streptomyces genus by is only used to screen and evaluate the significant factors which 16S rDNA sequencing (GenBank accession no. LN864570). have a great influence on the response (chitinase production). Colloidal chitin medium (CCM) was used for growth and After regression variables analysis, these most significant factors chitinase production, containing the following constituents were then optimized by response surface method (RSM) using −1 (g. l ): 1 g colloidal chitin, 0.7 g KH PO ,0.3gK HPO , 2 4 2 4 central composite design (CCD) of Box-Wilson. 4gNaCl,and0.5 gMgSO •7H O,1mgFeSO •7H O, 4 2 4 2 0,1 mg ZnSO •7H O, 0,1 mg MnSO •7H O, and 20 g agar. 4 2 4 2 Optimization of medium with the response surface method Colloidal chitin broth (50 ml) in 250-ml capacity Erlenmeyer flasks was inoculated with a 1% (v/v) spore suspension (ad- A CCD (Box and Wilson 1951) matrix was developed under justed to 0.8 OD ) of the strain and incubated at 40 °C in a the RSM to optimize the levels of the four most significant rotary incubator (150 rpm) for 7 days. After centrifugation factors identified by PBD. Each factor in the design was (10,000g, 4 °C, for 20 min), the supernatant was collected for measurement of chitinase activity. Table 1 Variables in real values, for screening by Plackett–Burman design Chitinase assay Variables Levels Units Chitinase activity was determined by a dinitro-salicylic acid +1 −1 (DNS) method (Miller 1959). This worked on the concentra- A:pH 5 9 tion of N-acetylglucosamine (NAG), which is released as a B : Colloidal chitin 1 3 % result of enzymatic action (Ulhoa and Peberdy 1991; Fenice C : Date syrup 0 2 % et al. 1998). The 2-ml reaction mixture contained 1 ml of 0.1% D : Dummy ––– colloidal chitin in acetate buffer (50 mM, pH 5.0) and 1 ml of E : Lactoserum 0 2 % crude enzyme extract. The mixture was then incubated in a water bath shaker at 50 °C for 1 h. The reaction was stopped F : Peptone 10 15 g/l G : Casein 0.1 0.4 g/l by the addition of 3 ml DNS reagent to 1 ml of the filtrate, followed by heating at 100 °C for 5 min, and the absorption H : Dummy ––– was measured at 540 nm using UV spectrophotometer. One I : Tryptone 10 15 g/l unit of enzyme activity was defined as the amount of enzyme J : Yeast extract 0.1 0.4 g/l that catalyzed the release of 1 μmol of N-acetylglucosamine K : Ammonium sulfate 0.1 0.4 g/l per ml in 1 min. The colloidal chitin was prepared as described L:Dummy ––– by Hsu and Lockwood (1975). M:PO 12g/l N : Trace elements 0.5 1.5 ml/l Screening of critical media components using O : Crayfish shell 0 20 g/l a Plackett–Burman design P : Dummy ––– Q : Mushroom 0 20 g/l The PBD was used to select significant medium components R : Shrimp shell 0 20 g/l affecting the production of chitinase. It is a two-factorial de- S : NaCl 5 10 g/l sign that allowed the screening of n variables in an n+1 Ann Microbiol (2017) 67:175–183 177 Table 3 Coded and real values of variables selected for CCD studied at five different levels, Table 3 gives the actual and the coded levels of the variables tested. The factors were coded Variables Unit Levels according to the following equation: −2 −1 0 +1 +2 X −X i 0 X ¼ ð2Þ d A: colloidal chitin (%) 1 1.5 2 2.5 3 B: Syrup date (%) 0 0.5 1 1.5 2 Where X is the coded level, X is the real value, X is the real R i 0 C: Yeast extract (g/l) 0.05 0.15 0.25 0.35 0.45 value of central point, and d is the value of step change of D: PO (g/l) 1 1.25 1.5 1.75 2 variable. Table 4 gives the design matrix and the response evaluated (the averages of duplicate experiments) in terms of chitinase included in the final models. The statistical significance of activity. Chitinase activity can be expressed as a function of the polynomial model equation was carried out by an F test independent variables by the polynomial equation of the second and the significance of the regression coefficients was tested order: 2 by t tests. In addition, the coefficient of determination R of the equation and the analysis of variance (ANOVA) were de- Y ¼ β þ ∑β x þ ∑β x þ ∑β x x ð3Þ j j2 j k 0 j jj jk termined. STATISTICA software v.12.0 (Dell) was used for the experimental design and analysis of the experimental data. Where Y is the response here in terms of chitinase activity, β is the intercept, β , β , β are linear, quadratic and interactive j jj jk coefficients, respectively. Results Statistical analysis Chitinase production The responses obtained were subjected to multiple non-linear regression analysis to obtain the coefficients. Estimates of Initially, basal medium (CCM) was used for the production of coefficients with levels higher than 95% (P <0.05) were chitinase. From the shake flask fermentation, S. griseorubens Table 2 Plackett–Burman experimental design matrix with the observed response (chitinase activity) Run Variables Chitinase activity AB C DE F GH I J K L M N OP Q R S (U/ml) 11 −11 1 −1 −1 −1 −11 −11 −11 1 1 1 −1 −1 1 7.476 21 1 −11 1 −1 −1 −1 −11 −11 −1 1 111 −1 −12.239 3 −11 1 −11 1 −1 −1 −1 −11 −11 −1 111 1 −17.053 4 −1 −11 1 −11 1 −1 −1 −1 −11 −11 −1 11 117.043 51 −1 −11 1 −11 1 −1 −1 −1 −11 −11 −1 1 116.544 61 1 −1 −11 1 −11 1 −1 −1 −1 −11 −11 −1 111.799 71 1 1 −1 −11 1 −11 1 −1 −1 −1 −11 −11 −1 1 1.973 81 1 1 1 −1 −11 1 −11 1 −1 −1 −1 −11 −11 −11.116 9 −1 1 111 −1 −11 1 −11 1 −1 −1 −1 −11 −1 1 7.049 10 1 −1 111 1 −1 −11 1 −11 1 −1 −1 −1 −11 −13.244 11 −11 −11 1 1 1 −1 −11 1 −11 1 −1 −1 −1 −1 1 1.861 12 1 −11 −1 1 111 −1 −11 1 −11 1 −1 −1 −1 −16.527 13 −11 −11 −1 111 1 −1 −11 1 −11 1 −1 −1 −11.934 14 −1 −11 −11 −11 1 1 1 −1 −11 1 −11 1 −1 −17.033 15 −1 −1 −11 −11 −1 1 111 −1 −11 1 −11 1 −11.986 16 −1 −1 −1 −11 −11 −1 111 1 −1 −11 1 −1 111.924 17 1 −1 −1 −1 −11 −11 −11 1 1 1 −1 −11 1 −1 1 2.042 18 1 1 −1 −1 −1 −11 −11 −1 1 111 −1 −11 1 −12.062 19 −11 1 −1 −1 −1 −11 −11 −1 111 1 −1 −1 116.639 20 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −1 −12.134 178 Ann Microbiol (2017) 67:175–183 Table 4 Central composite design of variables (in coded levels), with the response could be explained by this model. The P values extracellular chitinase activity as response of the important variables in the PBD as given below were the most significant variables affecting chitinase production by Run Level Chitinase activity (U/ml) S. griseorubens C9 (Table 5): syrup of date (P = 0.000552), A B C D Observed Predicted yeast extract (P = 0.003029), K HPO ,KH PO (P = 2 4 2 4 0.016506) and colloidal chitin (P = 0.015921). From the ex- 1 −1 −1 −1 −1 7.421 6.368 perimental data, these four variables could clearly affect the 21 −1 −1 −1 9.226 7.061 production of chitinase. Among them, syrup of date and 3 −11 −1 −1 9.358 8.204 K HPO ,KH PO had a positive effect on chitinase produc- 2 4 2 4 41 1 −1 −1 9.785 8.758 tion, while the other two variables exerted negative effects. 5 −1 −11 −1 6.987 5.908 These optimum variables were further evaluated by RSM 61 −11 −1 6.206 5.837 using the Box–Wilson design. Considering the results 7 −11 1 −1 9.752 7.944 displayed in Table 5 and after exclusion of the insignificant 81 1 1 −1 9.456 7.732 model terms (based on their insignificant P values > 0.02) the 9 −1 −1 −1 1 1.855 1.426 reduced polynomial Eq. (1) may be written as follows: 10 1 −1 −1 1 1.786 1.884 11 −11 −1 1 6.051 4.710 Y ¼ 3:984−1:22B þ 3:06C−1:95J þ 1:21M ð4Þ 12 1 1 −1 1 6.104 5.029 Where B = Colloidal chitin, C = syrup of date, J = yeast extract 13 −1 −1 1 1 1.487 0.804 and M = K HPO ,KH PO . 2 4 2 4 14 1 −1 1 1 1.497 0.497 15 −1 1 1 1 4.275 4.287 16 1 1 1 1 4.498 3.841 Optimization using RSM 17 −2 0 0 0 1.471 3.306 18 2 0 0 0 1.527 3.553 Based on the identification of variables by PBD, a CCD ex- 19 0 −2 0 0 1.763 3.171 perimental plan was carried out for variables that affected 20 0 2 0 0 5.897 8.351 significantly chitinase production. Table 3 shows the real 21 0 0 −2 0 2.948 5.089 and the coded values of the levels of variables selected in 22 0 0 2 0 1.720 3.442 the CCD. The predicted and observed values of the response 23 0 0 0 −2 7.775 11.033 (chitinase activity) generated in CCD are described in Table 4. 24 0 0 0 2 1.596 2.200 A multiple regression analysis was applied to the experimental 25 0 0 0 0 1.546 1.557 data, and a second order polynomial equation was found to explain the chitinase production by S. griseorubens C9. Only 26 0 0 0 0 1.563 1.557 27 0 0 0 0 1.582 1.557 significant variables are shown in this equation as below: 28 0 0 0 0 1.537 1.557 Y ¼ 2:93 þ 1:295B−2:208D þ 0:362B*D þ 0:822B þ 1:035D ð5Þ C9 had maximum chitinase production of 0.058 U/ml after 6 days of fermentation time at 40 °C (Fig. 1). Where B = syrup of date and D = PO (K HPO ,KH PO ). 4 2 4 2 4 The experimental results revealed that this polynomial equa- Evaluation of significant variables using Plackett-Burman tion could satisfactorily explain the effects of the most signif- design icant variables concentration in chitinase production of S. griseorubens C9. Analysis of variance (ANOVA) for the Fifteen variables supposed to affect chitinase production were reduced model of most significant variables with chitinase evaluated under 20 experiments for the PBD (Table 1). Table 2 production as responses was generated. The Fisher’s F test shows the responses obtained in terms of chitinase activity, revealed a very low P value (P < 0.0001) which indicated that estimated by DNS method. The responses were statistically the model was highly significant (Table 6). The robustness of evaluated and the variables with P value less than 0.02 and the model was determined by calculating the determination confidence levels above 98% were considered to have a sig- coefficient R (0.7323), which suggested that it is a reliable nificant effect on chitinase production. The regression coeffi- model and that it is able to explain more than 73.23% of the cients and determination coefficients (R )forthelinearregres- total variations. Only 26.77% of the total variation of chitinase sion model of the chitinase production were represented in production was not explained by the model. The relatively Table 5. The model was highly significant (P <0.02) and high adjusted determination coefficient (R Adj = 0.6714) ac- R = 0.98429, meaning that 98.4% of the total variability in counts for the significance of the model. Tests for the lack-of- Ann Microbiol (2017) 67:175–183 179 0.07 Fig. 1 The time-course of chitinase production by Streptomyces griseorubens C9 0.06 before optimization 0.05 0.04 chitinolytic activity 0.03 0.02 0.01 02 468 10 Incubation time (days) fit of the model showed that the results were significant expected to increase the syrup of date concentrations and de- (Table 7). The 3D response surface plot described by the re- crease the K HPO ,KH PO concentrations. 2 4 2 4 gression model was drawn to illustrate the effects of the most important independent variables, and their combined effect, upon the response variable (Fig. 2). The response surface Validation of the experimental design showed a curvature along the syrup of date and PO . The concave shape of the plot indicated that we can find an opti- Optimum levels of the tested factors were obtained by apply- mum value for the response in the range of the studied vari- ing a regression analysis on Eq. 5 using STATISTICA soft- ables, which could be due to the statistical significance of the ware v.12.0 (Dell). The coded values of the most important quadratic coefficients of these variables. The response is factors were as follow: B = −1.064 and D = 1.252. When translating these coded values, the concentrations of syrup of date and K HPO ,KH PO were calculated as 0.47%, and Table 5 Effect estimates for chitinase activity from the result of the 2 4 2 4 Plackett–Burman design 1.81 g/l, respectively, for the maximum chitinase activity of the 0.902 U/mL, produced by S. griseorubens C9 and predict- Factors Effect t value p value Coefficient ed by the mathematical model. The study of chitinase production by S. griseorubens C9 Intercept 3.98400 26.15835 0.000013 3.984000 was performed on the optimized medium in shaken A:pH −0,96300 −3.16146 0.034136 −0.481500 Erlenmeyer flasks (250 ml). The practical response of B : Colloidal chitin −1.22320 −4.01567 0.015921 −0.611600 chitinase production was 1.53 U/ml (Fig. 3), which is in agree- C : Date syrup 3.06060 10.04772 0.000552 1.530300 ment with the model prediction. The yield of the chitinase D : Dummy ––– – production was enhanced 26.38 times using RSM optimiza- E : Lactoserum 1.08560 3.56394 0.023503 0.542800 tion, in comparison with the basal medium (0.058 U/ml). This F : Peptone −.087400 −2.86928 0.045502 −0.437000 result showed that the experimental values obtained were in G : Casein −0.36480 −1.19761 0.297183 −0.182400 accordance with those predicted statistically and confirmed H : Dummy ––– – the authenticity of the model. I : Tryptone −0.67400 −2.21269 0.091352 −0.337000 J : Yeast extract −1.95500 −6.41812 0.003029 −0.977500 Table 6 Effect estimates and regression coefficient for chitinase K : Ammonium sulfate −0.14760 −0.48456 0.653326 −0.073800 activity from the result of CCD L:Dummy ––– – M:PO 1.21000 3.97234 0.016506 0.605000 Model term Effect t value P value Coefficient N : Trace elements 0.96360 3.16343 0.034072 0.481800 Intercept 2.93170 5.0909 4.229e-05 2.93170 O : Crayfish 0.88980 2.92115 0.043194 0.444900 B 2.59024 3.4841 0.002103 1.29512 P: Dummy ––– – D −4.41633 −5.9403 5.602e-06 −2.20816 Q : Mushroom 1.03940 3.41227 0.026971 0.519700 B × D 0.72402 0.7952 0.435014 0.36201 R:Shrimp −0.08680 −0.28496 0.789822 −0.043400 B × B 1.64410 2.3311 0.029313 0.82205 S : NaCl 0.90320 2.96514 0.041343 0.451600 D × D 2.07161 2.9372 0.007624 1.03580 2 2 R = 0.98429, Adj R = 0.92537 Chitinolytic activity U/ml K HPO , KH PO 2 4 2 4 180 Ann Microbiol (2017) 67:175–183 Table 7 Analysis of variance (ANOVA) of chitinase activity for the known that the conventional method for medium optimization reduced model like the one-factor-at-a-time approach is time-consuming, ex- pensive and difficult when a large number of variables must be Model term SS df MS F value P value explored and the interactions between multiple factors in- B 40.2562 1 40.2562 12.13898 0.002103 volved cannot be detected. On the other hand, optimizing B × B 18.0203 1 18.0203 5.43391 0.029313 the parameters by statistical experimental design can eliminate D 117.0238 1 117.0238 35.28771 0.000006 these limitations. The statistical tool is used in many biotech- D × D 28.6104 1 28.6104 8.62727 0.007624 nological processes, i.e. optimization of culture conditions B × D 2.0968 1 2.0968 0.63228 0.435014 (Huang et al. 2010), production of biomass (Yu et al. 1997), Residual 72.9581 22 3.3163 and ethanol (Ergun and Mutlu 2000); enzymes (Treichel et al. Lack of fit 63.193 3 21.064 40.9865 1.708e-08 2010) and also for optimizing the yield of recombinant prod- Pure error 9.765 19 0.514 ucts such as actinorhodin (Elibol 2004), lysozyme (Gheshlaghi et al. 2005), the alkaline protease (Adinarayana 2 2 R = 0.7323; Adj R =0.6714 and Ellaiah 2002) and hirudin (Rao et al. 2000). In our study, df degrees of freedom; SS sum of squares; MS mean square; the optimization of culture media was carried out in two stages: the first step was the selection of variables having a Discussion positive effect on the production of chitinase using PDB (Khan 2010), and the second step determined the optimum This study noted that the composition of the culture medium variables values selected by PBD, using central composite can significantly affect the production of chitinases. Similar design. However, few studies were conducted for the produc- studies were conducted for Pseudomonas fluorescens where tion of chitinase using PBD and RSM (Singh et al. 2009). changes in clear zones on chitin medium with variable com- PBD is well established and widely used in the selection of positions were distinguished (Nielsen and Sørensen 1999). culture medium components. It can also screen the important Studies performed on Streptomyces sp. (Reynolds 1954)gave variables as well as their significance levels (Box 1952). The maximum activity after 6 days of incubation and decreased results of PBD experiments revealed that colloidal chitin, syr- thereafter, which is consistent with our observations. It is well up of date, PO (K HPO ,KH PO ) and yeast extract had 4 2 4 2 4 Fig. 2 Surface plot of chitinase activity of Streptomyces griseorubens C9 as a function of syrup date and K HPO ,KH PO 2 4 2 4 Syrup of date Chitinolytic activity Ann Microbiol (2017) 67:175–183 181 1.535 Fig. 3 The time-course of chitinase production by 1.53 Streptomyces griseorubens C9 after optimization 1.525 1.52 1.515 1.51 Chitinolytic activity 1.505 1.5 1.495 1.49 1.485 02468 10 incubation time (days) significant effects on the production of chitinase by S xylosoxydans and Paenibacillus sabina Strain JD2 (Vaidya griseorubens C9. Studies proved that colloidal chitin is the et al. 2001; Patel et al. 2007). The addition of peptone and whey best substrate for chitinase production by Microbispora sp. showed no significant effect on the production of chitinase. (Nawani and Kapadnis 2005), Andronopoulou and Vorgias This is in agreement with the work of Singh et al. (2009), (2004) also reported that colloidal chitin was the best chitin who discovered that the production of chitinase by source for chitinase production by Thermococcus Paenibacillus sp. D1 was reduced in the presence of peptone chitonophagus (Andronopoulou and Vorgias 2004), which is (Singh et al. 2009). Similar observations have also been de- in agreement with our observations. However, in the case of scribed by Han et al. (2009)in Streptomyces sp. Da11 (Han Metarrhizium anisopliae, good chitinase production was et al. 2009), while Gohel and Naseby (2007) reported a signif- found using chitin flakes rather than colloidal chitin (St icant effect of urea, yeast extract and peptone on the production Leger et al. 1986). The importance of the nature of chitin in of chitinase by Pantoea dispersa (Gohel and Naseby 2007). obtaining higher yields of chitinase was documented by Concentrations of PO (KH PO ,K HPO )positively reg- 4 2 4 2 4 Monreal and Reese (1969)in Seratia marcescens, and low ulated the production of chitinase by S. griseorubens C9. chitinase production was seen on a mushroom or beetle chitin K HPO was identified as the best phosphorus source for 2 4 contrary to colloidal and swollen chitin. Syrup of date was chitinase production by Paenibacillus sp. D1 (Singh et al. used as another carbon source in this study and showed a 2009). Nawani and Kapadnis (2005) described that low PO significant positive effect on the production of chitinase. levels were more favourable to the production of chitinase in Dates were reported to be rich in carbohydrates (predominant- Streptomyces when compared to high PO levels, which were ly glucose and fructose) along with a range of minerals and demonstrated in the CCD design in this study. The above vitamins, but low in protein content (1.5–3%, w/w) (Kamel results indicated that the PBD is an appropriate tool to exam- 1979;Nancibet al. 2001). It was previously used to increase ine the effect of culture medium constituents on the produc- production of citric acid by fermentation (Roukas and tion of chitinases. Components with maximum contribution Kotzekidou 1997), but never in chitinase production. effects were then selected for RSM using Box–Wilson design. Nitrogen sources may also affect the production of RSM improved the development process and significantly chitinases. In our study, the addition of ammonium sulfate to used at an industrial level, among which Box–Wilson design the culture medium had no effect on the production of methodology considers the interaction effects between the chitinases. However, the addition of yeast extract in the culture variables (Vaidya et al. 2003). The role of RSM in optimizing medium significantly affected the production of chitinase by culture media is to define the optimal concentrations of sig- S. griseorubens C9. In Streptomyces sp., Nawani and nificant variables previously determined by PBD and to find Kapadnis (2005) reported that decreased yeast extract and am- the relationship between more than one variable and a given monium sulfate concentrations may promote chitinase produc- response (Wang and Liu 2008;Heetal. 2009). The RSM was tion (Nawani and Kapadnis 2005). Other studies showed that used for the optimization of culture media for Haematococcus the production of chitinases can be improved by adding yeast pluvialis growth (Gong and Chen 1997). It was also used for extract to Serratia marcescens (Monreal and Reese 1969), the production of hirudin from Saccharomyces cerevisiae Aspergillus carneus (Sherief et al. 1991), Alcaligenes (Rao et al. 2000). chitinolytic activity (u/ml) 182 Ann Microbiol (2017) 67:175–183 Andronopoulou E, Vorgias CE (2004) Multiple components and induc- The P value is used as a tool to determine the significance of tion mechanism of the chitinolytic system of the hyperthermophilic each factor, which in turn is required to understand the structure archaeon Thermococcus chitonophagus. Appl Microbiol Biotechnol of interactions between variables. The lower the P value, the 65:694–702. doi:10.1007/s00253-004-1640-4 more significant is the corresponding coefficient. 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Annals of Microbiology – Springer Journals
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