4. Results and Discussion

Transcription

1 4. Results and Discussion The results obtained on carrying out the research project entitled Purification and characterization of an alkaline protease from a novel soil isolate, Exiguobacterium acetylicum MTCC 9115 are presented in a chronological succession in this section. Briefly they include isolation and identification of alkaliphilic bacteria with ability to produce alkaline protease, optimization of culture condition for production of the enzyme, purification and characterization of the enzyme and finally applications of the purified enzyme. 4.1 Isolation of alkaliphilic microorganisms from soil samples The first off the objectives of the present study was to isolate an alkaline protease producing microorganism. Soil samples were collected from hide treatment plants and dump yards of dairy industries located in and around Hyderabad, India and from the beach of Visakhapatnam, Andhra Pradesh, India. Totally 10 soil samples were collected in sterile vials and were processed within 24h. Soil samples were serially diluted and plated on modified Horikoshi medium of ph 10.0 (Kimurat and Horikoshi, 1988) by spread plate method. The plates were incubated at 30 o C in an inverted position for 48 h. Totally 17 cultures have been isolated from soil samples. The isolates were repeatedly sub-cultured to obtain pure cultures. The isolated pure cultures were maintained on Horikoshi agar slants of ph 10.0 at 4 o C and were sub-cultured every fortnight.

2 4.2 Screening of isolated cultures for proteolytic activity All the 17 cultures isolated from soil samples were screened for proteolytic activity on casein agar plates at ph A loopful of the 24 h old culture of the each isolate was spotted on sterile casein agar plate and incubated at room temperature for 48 h. The zone of hydrolysis produced around the colonies due to caseinolysis was used to determine the proteolytic activity of the isolated cultures. The ratio of the hydrolysis/growth zone produced around the colonies of soil isolate was calculated. The experiment was conducted in triplicates and an average of the three was taken to determine the soil isolate with maximal protease activity. Since caseinolytic activity was taken as a measure of the proteolytic activity, the culture which has shown maximum caseinolysis was selected for further studies and was designated as A11at our laboratory, CBT, IST, JNTUH. 4.3 Identification of the soil isolate A11 In general a microbial species is identified by its morphological, biochemical and cultural characteristics. The strain A11 with maximal proteolytic activity was chosen from among the isolates and detailed investigations on its morphological, cultural and biochemical characteristics were conducted. The results obtained are as follows: Colony morphology of the Isolate A11 The isolate A11 produced circular colonies with entire margins. The colony was slightly raised and the surface was smooth and shiny. The

3 isolate has produced a light orange colored pigment and the colonies were opaque (Figure 4.1). The isolate A11 is a gram positive oval rod shaped bacterium. The morphological features and colony characteristics of the isolate A11 are presented in the Table 4.1. Table 4.1 Morphological features of the isolate A11 Test Result Colony morphology Configuration Circular Margin Entire Elevation Slightly raised Surface Smooth & Shiny Pigment Light Orange Opacity Opaque Gram s reaction Positive Cell shape Oval Rods Size (µm) Length: 1-2µ Width: < 2µ Arrangement Clusters of 6-10 cells embedded in a common matrix Spore formation - Motility + Arrangement Clusters of 6-10 cells embedded in a common matrix

4 Figure 4.1Culture of the isolate A11 The isolate A 11 streaked on PYE agar ( ph 9.5) and incubated at 35 o C for 24 h Slant of A 11 A diverse range of biochemical tests are usually conducted on a new isolate as a part of its identification process. These biochemical tests provide an insight of the metabolism of the test organism and thus aid in its identification. The results obtained on conducting the biochemical tests on the isolate A11 are listed in detail in the Table 4.2. The strain A11 is methyl red and VP positive where as it has given a negative result for indole and citrate utilization tests. The isolate has hydrolyzed casein, starch, and gelatin but not urea. However the culture was oxidase

5 positive and catalase negative. Further nitrate reduction and H2S production were recorded to be negative. In case of carbohydrate fermentations, the isolate A11 has shown acid production with glucose and lactose but no gas production was observed (Figure 2).

6 Table 4.2 Biochemical characteristics of the strain A11 Biochemical Test Result Growth on MacConkey - agar Indole test - Methyl red test + Voges Proskauer test + Citrate utilization - H 2S production - Casein hydrolysis + Esculin hydrolysis + Gelatin hydrolysis + Starch hydrolysis + Urea hydrolysis - Catalase test - Oxidase test + Nitrate reduction - Arginine dihydrolase - Ornithine decarboxylase + Lysine decarboxylase - Tween 40 hydrolysis - Tween 80 hydrolysis - Acid from glucose + Acid from lactose + Gas from glucose - Phosphatase - Hippurate hydrolysis - DNase test + ONPG +

7 Figure 4.2 Biochemical characteristics of the isolate A11 Starch hydrolysis Methyl Red test Zone of clearance indicating Positive result on addition of iodine solution to starch agar medium Control Test Indicating positive result with formation of red color on addition of methyl red indicator Caseionlysis Zone of clearance on 1% casein agar plates of ph 9.5

8 4.3.2 Study of the cultural characteristics of the strain A Culturing of the strain A11 and protease assay of the crude enzyme The test strain A11 was cultured in sterilized PYE medium at ph 9.5 (Figure 3). A 5% inoculum of the 24 h old culture was inoculated into fermentation broth and was incubated at 30 o C for 24 h. The culture was harvested by centrifugation at rpm for 10 min at 4 o C. The cell free supernatant was used as the crude enzyme. Protein concentration of the crude enzyme was estimated by Lowry et al method (1951). The crude enzyme was assayed for protease activity with casein as substrate according to the modified method of Mc Donald and Chen (1965) described in earlier sections. One unit of alkaline protease activity (U) was defined as the amount of enzyme liberating 1µg of tyrosine per min under the standard assay conditions Determination of optimal Temperature for the growth of A11 Optimal temperature for the growth of the isolate A11 was studied by culturing the organism at different temperatures in the range of 10 o C - 60 o C. A graphical representation of the effect of temperature on the growth of the culture is presented in the Figure 4.3. The culture has shown growth at temperatures of 15 o C to 55 o C. However, the optimum temperature for growth of the strain A11 was observed at 35 o C.

9 Optical Density (600nm) Figure 4.3 Effect of temperature on the growth of A Temperature ( o C) The isolate A11 cultured at different temperatures in the range of o C in PYE broth at ph 9.0 has shown maximum growth at 35 o C Determination of optimal ph for the growth of A11 The strain A11was cultured at different ph values in the range of 4-12 in PYE medium at 30 o C for 24 h at 120 rpm on an orbital shaker. A graph was plotted with ph on X-axis and optical density culture broth at 600nmof the on Y-axis to depict the effect of ph on the growth of the strain under study (Figure 4.4). The study indicates that the culture has shown growth at ph values in the range of 4-12 whereas the optimum ph for growth was recorded as 9.0.

10 Optical Density (600nm) Figure 4.4 Effect of ph on the growth of the strain A ph The strain A11 on culturing at varying ph values in the range of 4-12 has shown optimal growth at ph Determination of the effect of NaCl on the growth of A11 The effect of NaCl on the growth of A11 was studied by culturing the organism at varying concentrations of NaCl in the range of 0.1%-15% (w/v) at a temperature of 30 o C. The culture has shown growth within the concentrations of 0-15% of NaCl but maximum growth was observed at 0.1% of NaCl (Figure 4.5). Hence the strain A11 can be considered as halotolerant (Ventosa et al, 1998).

11 Optical density (600nm) Figure 4.5 Effect of NaCl on the growth of A NaCl (%) Halotolerance of the isolate A11 was studied by culturing the organism at different NaCl concentrations in the range of 0.1 to15% [w/v]. The isolate has shown growth at NaCl concentrations in the range of 0.1%-11% Taxonomic identification of the isolate A11 Finally the results obtained from morphological, biochemical and cultural characterization studies were compared with Bergey s manual of Determinative Bacteriology (1986) for identification of the test strain. The soil isolate designated as A11 at our laboratory is identified as Exiguobacterium acetylicum. Moreover the isolate was sent to IMTech (Institute of Microbial Technology), Chandigarh, India where the test strain A11 was authentically confirmed as Exiguobacterium acetylicum MTCC 9115.

12 Further 16S rrna analysis of the isolate A11 has also been conducted to understand its phylogeny SrRNA analysis The most conserved or least variable genes in all cells are those of rrna. The sequence of 16S rrna or small ribosomal subunit is used for determination of Taxonomy and Evolutionary relationships or Phylogeny of an organism. Whole genomic DNA of the test organism A11 was extracted by high salt method. The genomic DNA was amplified with universal primers 27F and 1489R. The amplified PCR product was subjected to agarose (1%w/v) gel electrophoresis for analysis. The amplified product was purified by QIAGEN purification kit and sequenced by cycle sequencing method with SequiTherm sequencing kit (Biozym) and the chain termination reaction (Sanger et al., 1997) (Figure 4.6). The 762 bp PCR product was sequenced and the BLAST analysis of the sequence was performed (Table 4.3). Phylogenetic tree was constructed by the CLUSTAL_W algorithm of MEGA 4 for sequence alignments and MEGA 4 (Tamura et al. 2007) software for phylogenetic analyses (Figure 4.7)

13 Figure S rdna Analysis Agarose gel electrophoresis of purified DNA sample Chromatograms of the 16SrDNA sequence analysis

14 Table 4.3 BLAST analysis of the 16SrDNA sequence in NCBI-BLAST search engine Accession Description Max score Total score Query coverage E value Max ident Bacterium RBA S AY ribosomal RNA gene, partial % % sequence Exiguobacterium sp. M527 AB gene for 16S rrna, partial % % sequence, strain: M527 Uncultured bacterium clone EU A 16S ribosomal RNA % % gene, partial sequence Bacillaceae bacterium NR184 DQ S ribosomal RNA gene, % % partial sequence Exiguobacterium acetylicum strain DSM DQ % S ribosomal RNA % gene, partial sequence Links Figure 4.7 Dendrogram depicting the phylogenetic relationship of strain with all valid species of the genus Exiguobacterium

15 The 16SrRNA analysis of the test species has been in complete consent with the physiological and biochemical identification of the test strain under study. Hence the strain under study is conclusively identified as Exiguobacterium acetylicum Growth vs Protease activity The strain Exiguobacterium acetylicum MTCC 9115 was cultured in PYE broth at 30 o C for 48h at 120 rpm on an orbital shaker. Samples of culture broth were withdrawn for determination of growth at regular 4 h intervals from the time of inoculation. Growth was measured by reading the absorbance at 600nm with uninoculated broth taken as a blank. Simultaneously, the samples were also assayed for protease activity and growth vs protease activity of the culture Exiguobacterium acetylicum MTCC 9115 was plotted (Figure 4.8). Growth curve studies have revealed that the strain Exiguobacterium acetylicum MTCC 9115 has an exponential growth phase till 20 h. The strain has entered the stationary phase at 24 h. Maximum protease production was recorded at 24 h of growth that is during the early stationary phase.

16 Optical density (600nm) Protease activity (U/ml) Figure 4.8 Growth vs Protease activity Growth Time (h) Protease activity Study of Growth versus protase activity has shown that maximal production of alkaline protease by the strain A11 occurs at 24 hours, i.e during the early stationary phase of growth. 4.4 Submerged fermentation Effect of the size of inoculum over enzyme production by Exiguobacterium acetylicum MTCC 9115 The effect of inoculum percentage over alkaline protease production was studied by inoculating the PYE broth with different percentages of inoculum of 24 h old culture of Exiguobacterium acetylicum MTCC 9115 with in the range of 2%-20% [v/v]. The study has indicated 10% [v/v] inoculum of the culture as optimum inoculum percentage (Figure 4.9). The impact of the percentage of inoculum over alkaline protease

17 Protease activity (U/ml) production has been reported earlier (Sinha and Satyanarayana, 1991). An optimal inoculum of 10% (v/v) was reported by Mizusawa et al (1969) for Streptomyces rectus var proteolyticus. Falahatpishe et al in 2007 reported an inoculum size of 10% inoculum for protease production by an alkaliphilic Bacillus sp El-Shafei et al (2010) also reported an inoculum size of 10% for alkaline protease production by Streptomyces albidoflavus. Figure: 4.9 Effect of inoculum percentage over alkaline protease production % 4% 6% 8% 10% 12% Inoculum percentage The culture was inoculated with different inoculum sizes in the range of 2-12% (v/v) and optimum inoculum size was found to be 10% (v/v) Determination of the effect of induction over alkaline protease production Induction with catalytic substrates is an efficient strategy to improve the production of many enzymes (Pan and Xu, 2003). Hence in the present study effect of

18 induction over alkaline protease production was studied. Sterile PYE broth inoculated with 24h old culture of E. acetylicum MTCC 9115 was induced with 0.1% (v/v) sterile casein solution at regular 4h intervals from 4 to 24 h of growth of the culture. The study has indicated 16h of growth as the optimum time period for induction. Induction has increased the production by 24%. The induction protease production by protein was reported in Neurospora crassa (Drucker, 1972). Negi and Banerjee (2006) have reported 1% starch and 1% casein as good inducers for production of both amylase and protease enzymes in Aspergillus awamori. Dey and Chaphalkar (1998) have reported a 46.2% increase in protease production by thermophilic Streptomycete flora of a meteroritic crater on induction with casein Media optimization studies Alkaline proteases are enzymes of high commercial value. It is very important to develop a cost-effective method for production of the enzyme since it determines the commercial viability of the strain. Optimization of media plays an important role in developing an economically feasible bioprocess. Initially media optimization studies have started with screening of various carbon sources, nitrogen sources and mineral salts to define the medium components that are critical for the maximal production of alkaline protease enzyme by Exiguobacterium acetylicum MTCC 9115 by submerged fermentation. An efficient culture medium producing high yields of the enzyme was developed by conducting further

19 optimization by response surface methodology (RSM) on critical parameters selected from preliminary screening Screening studies Firstly screening studies were carried out on a set of carbon sources, nitrogen sources and mineral salts to define the critical medium components for protease production by Exiguobacterium acetylicum MTCC The effect of each component was tested by supplementing the basal media with a fixed concentration of each component at a time. The results of the screening studies are presented below in detail Effect of carbon source on growth and protease production by submerged fermentation Screening studies conducted on different carbon sources have indicated Glucose as the best carbon source for growth followed by Dextrose (Figure 4.10). However dextrose at 2% concentration has given maximum protease yield. Hence Dextrose has been chosen as the carbon source of choice for protease production by Exiguobacterium acetylicum MTCC Least growth and protease production have been recorded by Lactose and Xylose. The studies conducted by Venil and Lakshmanaperumalsamy (2009) also have shown Dextrose as the carbon source of choice for protease production by Bacillus subtilis HB04. Das and Prasad (2010) have also reported dextrose as the best carbon source for alkaline protease production by Bacillus subtilis.

20 OD (600nm) Protease activity (U/ml) Figure 4.10 Effect of carbon sources on growth and protease activity Carbon source (2%w/v) Protease activity (U/ml) Effect of carbon sources (2.0% w/v)) on growth and protease production was studied and the study has indicated Glucose as the best carbon source for growth and Dextrose for protease production Effect of nitrogen sources over growth and protease production by submerged fermentation The study of the effect of different nitrogen sources on growth and protease production has indicated Peptone as the best nitrogen source. Peptone at 2 % (w/v) concentration has resulted in maximum growth and as well protease production. Followed by peptone was soyabean meal which also has shown good growth and protease production. However the Urea has shown least growth and production. The effect of different nitrogen sources on growth and protease production is presented in the Figure Peptone has been reported as the best nitrogen source for

21 OD 600 (nm) Protease activity (U/ml) protease production by Pseudomonas Fluorescens by Kalaiarasi and Sunitha (2009). Figure 4.11 Effect of nitrogen sources on growth and protease production Nitrogen source (2% w/v) Protease activity Growth The study of the effect of different nitrogen sources (2.0% w/v) has indicated peptone as the best source nitrogen for growth and protease production by Exiguobacterium acetylicum MTCC Effect of Mineral salts over growth and protease production The studies on mineral salts have indicated NaCl as the best mineral salt for growth and protease production followed by K2HPO4 and KCl. The one with lowest influence has been MgCl2. The mineral salt NaCl has been

22 OD (600nm) Relative activity (%) chosen for further optimization studies. The effect of mineral salts is presented in the Figure Figure 4.12 Effect of mineral salts over growth and protease production Mineral salts (0.1%w/v) Growth Different mineral salts (0.1%w/v) were tested for their effect on growth on protease production by the strain Exiguobacterium acetylicum MTCC The study has indicated NaCl as the mineral element with strong influence over protease production. Screening studies have indicated Dextrose, peptone and NaCl as the best sources of carbon, nitrogen and mineral salts respectively for production of protease enzyme. Induction of the culture with casein at 16 hours of growth has shown a strong positive impact on enzyme production. The components that have been chosen from screening for further optimization studies include Dextrose, 2g/100ml (x1);, Peptone

23 2g/100ml (x2) and NaCl 0.1g/100ml (x3) and induction 10ml/100ml with 1% [w/v] casein(x4) Multiple responses optimization and model building A multiple response optimization (MRO) was performed to enhance the production of an alkaline protease by Exiguobacterium acetylicum MTCC 9115 with the nutritional factors selected from screening studies. Optimization of the medium constituents was carried out by applying Central composite design (CCD) and response surface methodology (RSM) which is an effective, sequential and stepwise procedure. The lead objective of RSM is to run rapidly and efficiently along the path of improvement towards the general vicinity of the optimum (Myers and Montgomery, 1995). It becomes appropriate on identification of optimal region for running the process. The four independent variables, Dextrose, 2g/100ml (x1);, Peptone 2g/100ml (x2) and NaCl 0.1g/100ml (x3) and induction 10ml/100ml with 1% [w/v] casein(x4) were chosen for optimizing the maximal production of alkaline protease (Y) by submerged fermentation. To search for the optimum combination of components of the medium and induction factor, experiments were performed according to the given CCD experimental design and the response was recorded (Table 4.4). The model summary is presented in the Table 4.5.

24 Table: 4.4 Experimental design matrix and results of CCD of media optimization for submerged fermentation Run Number Factors x1 x2 x3 x4 Protease measured U/ml Protease Predicted U/ml The coefficient of determination (R 2 ) was calculated for alkaline protease production by submerged fermentation (0.891) indicating that the statistical model can explain 89.1% of variability in the response.

25 Table 4.5 Model summary Model R R 2 Adjusted Standard Error of the R 2 Estimate The R 2 value is always between 0 and 1. The closer the R 2 is to 1.0, the stronger the model and the better it predicts the response (Khuri and Cornell, 1987). In this case, the value of the determination coefficient, R 2 indicates that only 10.9% of the total variations for alkaline protease production by submerged fermentation are not explained by the model. The adjusted R 2 value corrects the R 2 value for the sample size and for the number of terms in the model. The value of the adjusted determination coefficient (Adj R 2 ) for alkaline protease production (0.789) is also very high to advocate for a high significance of the model (Box and Hunter, 1978; Cochran and Cox 1957). If there are many terms in the model and if the sample size is not very large, the adjusted R 2 may be noticeably smaller than the R 2. Here in this case the adjusted R 2 value is which is lesser than the R 2 value of By applying multiple regression analysis on the response, the experimental results of the CCD design was fitted with a second order full polynomial equation. The empirical relationship between alkaline protease production by submerged fermentation by Exiguobacterium acetylicum MTCC 9115 (Y) and the four test variables in coded units obtained by the application of RSM is given by equation 4.

26 Y = * x * x * x * x * x1x * x1x * x1x * x1x * x2x * x2x * x2x * x3x * x3x * x4x4 The F-values of model (Table 4.5) and values of prob > F (<0.05) indicated that the model terms are significant. ANOVA has been conducted for the second order response surface model and the results are given in Table 4.6. Table: 4.6 Analysis of Variance (ANOVA) for the Quadratic Models Model Sum of Squares Degree of freedom Mean Square F Significant Probability (p) Regression E-5 Residual Total The significance of each coefficient was determined by Student s t-test and p-values (Table 4.7). The larger the magnitude of the t-value and smaller the p-value, the more significant is the corresponding coefficient (Myers and Montgomery, 1995; Khuri and Cornell, 1987; Box and Hunter, 1978). This implies that the values of factors having p values lesser than 0.05 are statistically more significant.

27 Table: 4.7 Model Coefficients Estimated By Multiple Linear Regressions (Significance of Regression Coefficients) Variables Beta Std. Error t-test p-value (Significant at <0.05) (Constant) E-11 x x x x x1x x1x x1x x1x x2x x2x x2x x3x x3x x4x * Statistically significant at 95% confidence limits of regression analysis The values of p lesser than 0.05 (95% significant) are statistically significant for alkaline protease production by submerged fermentation by the culture Exiguobacterium acetylicum MTCC Therefore equation 4 can be reduced by considering significant values of p to equation 5and it is statistically significant model of the optimization studies.

28 Y=40.593* x * x1x * x1x * x2x * x3x * x3x * x4x4.eq. (5) The statistical method of media optimization for maximal production of alkaline protease by the culture Exiguobacterium acetylicum MTCC 9115 by submerged fermentation conclusively indicates the effect of selected variables as follows. The three important variables viz. Dextrose (x1), NaCl (x3) and Induction (x4) at their doubled concentration levels have been found to profoundly increase the production of alkaline protease. Moreover NaCl in dual combination with other variables like Dextrose (x1), Peptone (x2) and casein induction (x4) has been found to enhance the production of alkaline protease by submerged fermentation. The 3-D surface plots enable the graphical representation of the regression equation for the optimization of alkaline protease production by submerged fermentation by the culture Exiguobacterium acetylicum MTCC The Figures 4.13 to 4.18 show the effect of two variables on protease production while the other three variables were held at a constant level.

29 Figure: 4.13 Effect of Dextrose (x1) and Peptone (x2) over alkaline protease production by submerged fermentation The above graph represents the affect of varying combinations of Dextrose and Peptone over alkaline protease production by submerged fermentation. The graph clearly indicates that Dextrose at -0.5 coded value with Peptone at a coded value of -2.0 has shown maximal production of protease whereas a combination of Dextrose and Peptone at coded values of -2.0 and +2.0 respectively has shown the least production of protease enzyme by submerged fermentation Figure: 4.14 Effect of Dextrose (x1) and NaCl (x3) over alkaline protease production by submerged fermentation The above graph clearly indicates that both Dextrose and NaCl at coded value of 0.0 yield maximum but both at coded value of -2.0 give the least production of alkaline protease by submerged fermentation.

30 Figure: 4.15 Effect of Dextrose (x1) and casein induction (x4) over alkaline protease production by submerged fermentation The above figure is a graphical representation of the effect of different combinations of Dextrose and Induction over alkaline protease production by submerged fermentation. It is clearly evident from the above graph that Dextrose within the range of the coded values of 0.0 to -2.0 with Induction at a coded value of -2.0 gives the maximum protease production. The least or zero production of protease has been noticed at -2.0 coded value of Dextrose and +2.0 coded value of induction. Figure: 4.16 Effect of Peptone (x2) and NaCl (x3) over alkaline protease production by submerged fermentation The graph indicates the effect of Peptone and NaCl over alkaline protease production. Peptone at a coded value of -2.0 with NaCl at coded values within the range of -1.0 to -1.5 has given the highest yield of enzyme. The least production has been observed in a combination of Peptone and NaCl at coded value of 2.0 and -2.0 respectively.

31 Figure 4.17 Effect of Peptone (x2) and casein Induction (x4) over alkaline protease production by submerged fermentation The above figure is a graphical representation of the combinatorial effect of peptone and induction over the production of alkaline protease by submerged fermentation. The graph indicates that Induction within the coded value range of -0.5 to 0.5 with Peptone at coded value of either 1.0 or -1.0 gives the maximum yield. A little lower yield was given by the combination of Induction at coded value of 0.0 with Peptone in the coded value range of Figure 4.18 Effect of NaCl (x3) and casein Induction (x4) over alkaline protease production by submerged fermentation It is evident from the above graph that a combination of NaCl and Induction at -1.5 and 0.0 coded values respectively gives the highest protease production. The combination that gives very lower yields is represented as NaCl at -2.0 coded value of -2.0 with Induction at a coded value of 0.5.

32 Protease activity (U/ml) 4.5 Solid state fermentation Screening of Solid substrates Agro-industrial wastes have been used as solid substrate by researchers for a long time from now. These waste products not only function as an adhering material to the microbial cells, but they also provide nutrients (Prakasham et al, 2006). In the present study agro industrial products such as Rice husk, Wheat husk, Wheat bran, Barley husk, Peanut husk, Bengal gram husk and Green gram husk have been screened for alkaline protease production by SSF (Figure 4.19). All the solid substrates have supported enzyme production. However, the study has clearly indicated Barley husk as the best solid substrate followed by green gram husk and peanut husk. Figure 4.19 Effect of solid substrates on protease activity Rice husk Wheat husk Wheat bran Barley husk Solid substrate Peanut husk Bengal gram husk Green gram husk Different agro-industrial waste products have been screened for protease production by SSF and Barley husk has shown maximum enzyme production.

33 Relative activity (%) Effect of inoculum size (%v/w) over alkaline protease production by SSF The effct of inoculum size over protease production by SSF was studied by using 24h old culture of E.acetylicum MTCC The optimum inoculum size was estimated as 20% (v/w) for protease production by SSF (Figure 4.20). Similar results were reported for alkaline protease production by Themoactinomycetes thalophilus PEE 14 by Diwakar et al, Figure 4.20 Effect of inoculum size over protease production by SSF Inoculum (%v/w) The optimum inoculum size was determined by culturing the test organism with different inoculum sizes (5%-30% v/w) and 20% inoculum was recorded as optimal for protease production by SSF Media optimization studies for solid state fermentation Screening studies In order to enhance the production of alkaline protease by SSF, the solid substrate, Bengal gram husk has been supplemented with different

34 Relative activity (%) carbon sources, nitrogen sources and mineral salts. The screening study was conducted at a two level i.e. either the nutrient is present or absent. Among the carbon sources screened Dextrose 0.2 (g/10g solid substrate) has shown maximal enzyme production (Figure 4.21) and among the nitrogen sources peptone 0.2 (g/10g solid substrate) has recorded high yields (Figure 4.22). However in case of mineral salts, MgSO (g/10g solid substrate) has shown maximal production of alkaline protease by Exiguobacterium acetylicum MTCC 9115 by SSF (Figure 4.23). Figure 4.21 Effect of carbon sources on protease production by SSF Carbon source 0.2 (%w/v) The solid substrate barley husk was supplemented with different carbon sources to assess their effect on protease production and Dextrose (0.2g/10g solid substrate) has shown maximal enzyme production

35 Relative activity (%) Relative activity (%) Figure 4.22 Effect of Nitrogen sources on protease production by SSF Nitrogen source (0.2%w/v) Different nitrogen sources were screened for protease production by supplementing them in SSF media and Peptone (0.2g/10g solid substrate) has given the maximum yield. Figure 4.23 Effect of mineral salts on protease production by SSF Mineral salts (0.11%) Effect of mineral salts on protease production by SSF was studied by including different mineral salts in SSF medium and MgSO4 (0.011g/10g solid substrate) has shown maximum enzyme production

36 Hence from screening studies Dextrose, Peptone, and MgSO4 have been selected as critical medium components for further optimization studies. Apart from the above three factors, initial moisture content % [v/w] has also been identified as one very critical factor that affects the production of enzyme and hence has been chosen for optimization studies. In total four factors viz. Dextrose (0.2g/10g solid substrate), Peptone (0.2g/10g solid substrate), MgSO4 (0011g/10g solid substrate) and moisture content 100% [v/w] have been chosen for further optimization by statistical methods Multiple responses optimization and model building A multiple response optimization (MRO) of the selected medium constituents was carried out by applying Central composite design (CCD) and response surface methodology (RSM) to enhance alkaline protease production by Exiguobacterium acetylicum MTCC 9115 by solid state fermentation. The four independent variables chosen for optimizing the maximal production of alkaline protease (Y) by solid state fermentation are Dextrose, 0.2g/10g solid substrate (x1);, Peptone 0.2g/10g solid substrate (x2) and MgSO g/10g solid substrate (x3) and moisture content 100% [w/v] (x4). To search for the optimum combination of selected components, experiments were carried out according to the given CCD experimental design and the response (Alkaline protease produced in U/ml) was recorded (Table 4.8). The model summary is given in the Table 4.9

37 Table: 4.8 Experimental design matrix and results of CCD of media optimization for solid state fermentation Run Number Factors x1 x2 x3 x4 Protease measured U/ml Protease Predicted U/ml

38 Table 4.9 Model summary Model R R 2 Adjusted R 2 Standard Error of the Estimate The coefficient of determination (R 2 ) was calculated as for alkaline protease production by solid state fermentation indicating that the statistical model can explain 92.6% of variability in the response. The R 2 value always lies between 0 and 1 and closer is the value of R 2 to 1.0, stronger is the model and better is the prediction of the response (Khuri and Cornell, 1987). In the present case only 7.4% of the total variations in alkaline protease production by SSF are not explained by the model since the value of the determination coefficient, R 2 is The adjusted R 2 value corrects the R 2 value for the sample size and for the number of terms in the model. If there are many terms in the model and if the sample size is not very large, the adjusted R 2 may be noticeably smaller than the R 2 (Box and Hunter, 1978; Cochran and Cox 1957). In the present case, value of the adjusted determination coefficient (Adj R 2 ) is is also very high, indicating a higher significance of the model. Further the adjusted R 2 value (0.846) is lesser than the R 2 value which is The experimental results of the CCD design were fitted with a second order full polynomial equation by applying multiple regression analysis to the response. The empirical relationship between alkaline protease

39 production by solid state fermentation by Exiguobacterium acetylicum MTCC 9115 (Y) and the four test variables in coded units obtained by the application of RSM is given by equation 4. Y = * x * x * x * x * x1x * x1x * x1x * x1x * x2x * x2x * x2x * x3x * x3x * x4x4 The F-values of model (Table 4.10) and values of prob > F (<0.05) indicated that the model terms are significant. ANOVA has been conducted for the second order response surface model and the results are given in Table Table: 4.10 Analysis of Variance (ANOVA) for the Quadratic Models Model Sum of Degree Mean F Significant Squares of freedom Square Probability (p) Regression E-5 Residual Total The significance of each coefficient was determined by Student s t-test and p-values (Table 4.5). The larger the magnitude of the t-value and smaller the p-value, the more significant is the corresponding coefficient (Myers and Montgomery, 1995; Khuri and Cornell, 1987; Box and Hunter, 1978). This implies that the values of factors having p values lesser than 0.05 are statistically more significant.

40 Table: 4.11 Model Coefficients Estimated By Multiple Linear Regressions (Significance of Regression Coefficients) Variables Beta Std. Error t-test p-value (Significant at <0.05) (Constant) E-6 x x x x x1x x1x x1x x1x x2x x2x x2x x3x x3x x4x * Statistically significant at 95% confidence limits of regression analysis The values of p lesser than 0.05 (95% significant) are statistically significant for alkaline protease production by submerged fermentation by the culture Exiguobacterium acetylicum MTCC Therefore equation 4 can be reduced by considering significant values of p to equation 5and it is statistically significant model of the optimization studies. Y = * x * x * x3x * x4x4.eq. (5)

41 The statistical analysis of the results obtained on the media optimization studies conducted elucidates the impact of variables that positively effect the production of alkaline protease by Solid state fermentation. The studies emphasize the effect of MgSO4 (x3) and Moisture content (x4) both individually and in combination in enhancing the production of protease enzyme. Further moisture content at its doubled concentration level is found to increase the production of enzyme. The 3-D surface plots enable the graphical representation of the regression equation for the optimization of alkaline protease production by solid state fermentation by the culture Exiguobacterium acetylicum MTCC The Figures 4.24 to 4.29 show the effect of two variables on protease production while the other three variables were held at a constant level.

42 Figure 4.24 Effect of Dextrose (x1) and Peptone (x2) over alkaline protease production by Solid state fermentation Figure 4.24 is the graphical representation of the combinatorial effect of Dextrose and Peptone over alkaline protease production by Exiguobacterium acetylicum MTCC 9115 by solid state fermentation. Maximal production of alkaline protease is obtained with Dextrose in the coded value range of -1.0 to -2.0 with Peptone at a coded value of However lower levels of alkaline protease production resulted from a combination of Dextrose and Peptone at coded values of -2.0 and 2.0 respectively. Figure 4.25 Effect of Dextrose (x1) and MgSO4 (x3) over alkaline protease production by Solid state fermentation The above graph shows the affect of Dextrose and MgSO4 over alkaline protease production by SSF. Dextrose within the range of 0.0 to -1.0 coded value with MgSO4 at a coded value of -2.0 yielded maximum production of alkaline protease. Lower levels of enzyme production resulted from a combination of Dextrose at -2.0 and MgSO4 at 2.0.

43 Figure 4.26 Effect of Dextrose (x1) and Moisture (x4) over alkaline protease production by Solid state fermentation The above graph represents the effect of Dextrose and moisture on alkaline protease production by SSF. Both Dextrose and Moisture at a coded value of -2.0 led to maximal production of alkaline protease. The lower yields of enzyme have resulted from a combination of Dextrose at with moisture at a coded value of 1.5. Figure 4.27 Effect of Peptone (x2) and MgSO4 (x3) over alkaline protease production by Solid state fermentation This figure is a graphical representation of the effect of Peptone and MgSO4 on alkaline protease production by SSF. The figure clearly indicates that maximum yield is obtained at Peptone in the coded value range of 0.5 to -2.0 with MgSO4 at However both Peptone and MgSO4 at a coded value of 2.0 gave the lower yield of protease enzyme by SSF.

44 Figure 4.28 Effect of Peptone (x2) and Moisture (x4) over alkaline protease production by Solid state fermentation From the above figure it is evident that highest yield of alkaline protease is obtained at a point where both Peptone and Moisture are at a coded value of But the least yield of protease enzyme resulted from a combination of Peptone and Moisture at coded values of 2.0 and 1.5 respectively. Figure 4.29 Effect of MgSO4 (x3) and Moisture (x4) over alkaline protease production by Solid state fermentation The above graph shows the combinatorial effect of MgSO4 and Moisture on alkaline protease production. The highest yields were obtained when both MgSO4 and Moisture were at a coded value of This combination in particular has prominently shown lower yield levels. Both MgSO4 and Moisture in the coded value range of 1.0 to 2.0 gave lower yields. Further MgSO4 within the range of -1.5 to -2.0 with Moisture in the range of the coded values of 1.0 to 2.0 also resulted in lower yields.

45 4.6 Purification The extra cellular protease enzyme produced by Exiguobacterium acetylicum MTCC 9115 was purified by different methods such as ammonium sulphate precipitation, Ion exchange chromatography and gel-filtration chromatography. The results obtained from purification studies are presented in the Table The 24h old culture of E. acetylicum MTCC 9115 was harvested by centrifugation and the supernatant was collected. The supernatant or the crude enzyme is subjected to fractionation by precipitation with 0-50% and 50-90% ammonium sulfate saturations. The fraction of proteins obtained on precipitation with 0-50% saturation of ammonium sulfate has shown proteolytic activity with a specific activity of (mg/ml). The protein fraction was further purified by Ion exchange chromatography. The protein sample was applied on pre-equlibrated Q- sepharose column. The bound proteins were eluted with 0.1M, 0.3M and 0.5M NaCl. Both and unbound proteins were assayed for protease activity (Figure 4.30). The 0.3M sodium chloride eluate has shown protease activity with a specific activity of 1500 mg/ml. The active fraction obtained from ion-exchange chromatography was purified by gel-filtration chromatography on Sephacryl-S-100 HR column. Proteins were eluted with 50mM Tris-HCl (ph 8.5) with a flow rate of 12ml/h. The fraction size of 1 ml was collected throughout the run (Figure 4.31). The protein concentration of each fraction was

46 determined. Further protease activity of the fractions was assayed by standard protease assay with casein as substrate. One unit of protease activity was defined as 1µg of tyrosine released per min under standard assay conditions. The purification process has resulted in 33% recovery with 20.1 fold purification factor. A recovery of 32% with a purification factor of 34.4 was reported by Kalpana devi et al in 2008 for alkaline protease produced by Aspergillus niger with a molecular weight of 38KDa. Further Charles et al in 2008 reported an alkaline protease of 42KDa with a recovery of 39% purified 42.4 fold from Aspergillus nidulans HA-10. Table 4.12 Summarized results of Purification of alkaline protease from Exiguobacterium acetylicum MTCC 9115 Purification step Total protein (mg) Specific activity (U/mg) Total Units (U) Recovery (%) Purification factor Crude % Ammonium sulfate precipitation Ion exchange (0.3 M NaCl eluate) Sephacryl S-100 HR

47 Absorbance (280nm) Figure: 4.30 Elution profile of proteins in Ion-exchange chromatography Fraction Number Proteins obtained on precipitation with 0-50% ammonium sulfate saturation were loaded on to Q-Sepharose column and eluted with 0.1 to 1.0M NaCl. Active fraction was found to elute with 0.3M NaCl.

48 Absorbance (280nm) Figure: 4.31 Elution profile of proteins in gel-filtration chromatography Fraction number Fraction of proteins eluted with 0.3M NaCl from ion-exchange chromatography was loaded on Sephacryl S-100 HR column. 1 ml fractions were collected at a flow rate of 12 ml/hr. Absorbance of all the fractions were read at 280nm and 53 rd feaction has shown protease activity. 4.7 Characterization of enzyme Molecular weight determination The purified protease enzyme obtained from gel filtration chromatography was subjected to 10% SDS-PAGE gel electrophoresis for molecular weight determination. Molecular weight was calculated on the basis of Rf values. SDS PAGE analysis of the purified enzyme revealed a

49 single band with a molecular weight of 41.2 kda (Figure 4.32). Alkaline protease has been isolated from a psychrotrophic species of Exiguobacterium sp. SKPB5 (MTCC 7803) with a molecular weight of 36 Kda (Kasana and Yadav, 2007). However alkaline metalloproteases are reported with high molecular masess (Miyoshi and Shinoda, 2000). An alkaline metalloprotease (MprI) from Alteromonas sp strain O-7 has an estimated molecular weight of 56Kda (Miyomoto et al 2002). An alkaline metalloprotease produced by Pseudomonas fluorescens was reported with a molecular mass of ~50Kda (Jankiewicz et al 2010).

50 Figure 4.32 SDS-PAGE analysis of purified protein L1 L2 M 66Kda 41.2KDa 43Kda 29Kda 14Kda SDS-PAGE analysis was performed on 10% SDS-PAGE. Lane M shows a medium range protein molecular weight marker (Bangalore Genei, Bangalore, India). Lane 1 and 2 loaded with the protein purified from gelfiltration chromatography show a band of size 41.2 kda each Zymography: The purified protease enzyme was subjected to zymographic analysis by SDS-PAGE containing 0.1% gelatin (Thangam and Rajkumar, 2002). Proteolytic activity of the protein is indicated by the clear band (Figure 4.33). Charles et al (2008) have conducted zymography with 0.1%gelatin

51 for extra cellular alkaline protease of Aspergillus nidulans HA-10. Ramakrishna et al have (2010) also conducted zymography for alkaline protease produced by Bacillus subtilis (MTTC N ) on 7% SDS- PAGE gels containing casein as the substrate at 4 o C. Figure 4.33 Zymographic analysis of purified protein Determination of thermostability and optimal temperature for enzyme activity Optimum temperature for maximal activity and thermal stability of the purified protease of Exiguobacterium acetylicum MTCC 9115 were determined with in the temperature range of 10 o C to 60 o C. The enzyme has shown thermal stability over temperature range of 10 o C to 50 o C but however maximum activity was recorded at 40 o C (Figure 4.34 &4.35). Alkaline protease of Bacillus sp. also demonstrated similar thermal stability pattern (Gupta et al, 2005). Optimum activity of the enzyme was recorded at 37 o C with thermal stability in the range of 10 o C to 50 o C.

52 Activity (%) Relative activity (%) Soroor et al (2009) have also reported an alkaline protease from Photorhabdus Sp. Strain EK1 with a temperature optimum of 40 o C. Figure 4.34 Effect of temperature for alkaline protease activity Temperature ( o C) The purified protease was incubated with casein at different temperatures ion the range of o C to determine the optimum temperature. Purified protease has shown maximum protease activity at 40 o C Figure 4.35 Thermal stability of protease enzyme Time (min) Thermal stability of the purified enzyme was studied by incubating the protease enzyme at varying temperatures for 2 h. The enzyme has shown thermal stability over a temperature range of o C however the activity drastically decreased at 50 and 60 o C within 20 min.

53 4.7.4 Determination of ph optimum and ph stability of the purified protease from Exiguobacterium acetylicum MTCC 9115 The purified enzyme was investigated for determination of ph stability and optimum ph for maximal enzyme production. The enzyme was assayed for ph stability and optimal activity in different ph values in the range of The enzyme retained its activity at ph values in the range of 6-11 (Figure 4.36). The optimum ph for alkaline protease activity was found to be 9.0. The enzyme has depicted the residual activity of 96% at ph 10.0.The enzyme activity reduced to 54% at ph These results are in accordance with the observations of Jaswal and Kocher (2007) who reported an optimal ph of 9.0 for the alkaline protease produced by Bacillus circulans. Dhandapani and Vijayaraghavan, 1994 also isolated an alkaline protease with Bacillus stearothermophilus with optimal ph of 9.0. Alkaline protease produced by Aureobasidium pullulans was also reported with an optimal ph of 9.0(Chi et al, 2007).

54 Activity (%) Figure 4.36 Effect of ph on purified alkaline protease isolated from Exiguobacterium acetylicum MTCC ph The enzyme was pre-incubated at varying ph values in the range of 4-12 in different buffer systems at 35 o C for 2 h to determine its ph stability. Optimum ph of the purified enzyme is 9.0 with stability in the range of ph Effect of incubation period on alkaline protease activity Optimum incubation period for protease activity was determined by incubating the reaction mixture containing 1% [w/v] casein and enzyme in 50mM Glycine-NaOH buffer for varying time intervals at 35 o C. The maximal enzyme activity was recorded at 30 min of incubation (Figure 4.37).

55 Relative activity (%) Figure 4.37 Effect of incubation period over enzyme activity Time (min) The purified protease enzyme has shown an optimal incubation time of 30 min for maximal protease activity Effect of Metal ions The effect of metal ions over the activity of purified enzyme was studied (Table 4.13). The study has shown that the activity of enzyme was positively influenced by divalent metal ions. Cu +2, Mg +2 have increased the activity of the enzyme to 127% 114% respectively followed by Na, Mn +2 Ca +2 and Zn +2. However Co +2 ions has marginally reduced the enzyme activity. These results are in accordance with those shown by the alkaline protease of Exiguobacterium SKPB5 (MTCC 7803) (Kasana and Yadav 2007). An alkaline metalloprotease of and Pseudomonas fluorescens also has shown similar activity where Ca 2+ had increased the activity, while Zn 2+, Co 2+, Cd 2+ had strongly inhibited the enzyme at higher concentrations (Jankiewicz et al, 2010).

56 Table 4.13 Effect of metal ions on enzyme activity Metal ions (5mM) Relative activity (%) Control 100 Ca Co Cu Na 110 Mn Mg Zn Effect of NaCl concentration on the protease activity: The effect of NaCl on enzyme activity has been studied in the range of 0.1M to 1.0M NaCl (Figure 4.38). The enzyme has retained activity in all the concentrations indicating it to be a halotolerant enzyme. In fact moderate increase in the activity of the enzyme was observed between 0.1and 0.5M NaCl. Similar results have been shown by Joshi et al in The alkaline protease they isolated from Bacillus cereus MTCC 6840 isolated from lake Nainital, Uttaranchal state, India was unaffected at 5% NaCl concentration.

57 Relative activity (%) Figure 4.38 Effect of NaCl over protease activity NaCl (M) The effect of NaCl over purified protease enzyme was studied and the enzyme has shown protease activity over 0.1M to 1.0M NaCl Effect of organic solvents on the alkaline protease activity The protease enzyme produced by E.acetylicum MTCC 9115 has shown good amount of stability against the organic solvents under study. The stability of purified protease towards the organic solvents under study in descending order is as follows: DMSO, Isopropanaol, acetone, xylene and hexane (Figure 4.39). Moradian et al 2009 isolated an alkaline protease with stability against organic solvents from Bacillus sp. HR-08. They have reported on enhanced activity of protease in presence of 20%DMSO, isopropanol and dimethyl formamide (DMF). Raja Abd Rahman in 2006 reported an alkaline protease from Pseudomonas aeruginosa strain K with stability in the presence of organic solvents with log Pa/w values equal or more than 4.0. Further their study has shown that the activity of enzyme enhanced by 1.11, 1.82, 1.50, 1.75 and 1.80

58 Residual activity (%) times with 14 days of incubation in 1-decanol, isooctane, decane, dodecane and hexadecane, respectively. The study conducted by Li et al in 2009 on an alkaline protease from Bacillus licheniformis YP1A has shown that the enzyme retained 95% of activity in presence of 50% (v/v) of organic solvents such as DMSO, DMF, and cyclohexane. Organic solvent stability of an enzyme indicates its applications in peptide synthesis (Ghorbel et al 2003). Figure 4.39 Effect of organic solvents on protease activity organic solvent (%v/v) DMSO Isopropanol Acetone Hexane Xylene Stability of the protease enzyme was studied by pre-incubating the enzyme with different organic solvents. The enzyme has shown stability against organic solvents in the order of DMSO, Isopropanaol, acetone, xylene and hexane.

59 Effect of protease inhibitors on protease activity Effect of protease inhibitors over the purified protease enzyme was investigated. Inhibition studies enable understanding of the nature of the enzyme. Purified protease was pre-incubated with protease inhibitors and was then assayed for residual activity according to the standard protocol with casein as substrate. The relative activities recorded by protease enzyme from E. acetylicum are represented in the Table The purified enzyme was denatured to a great extent by EDTA at 1mM and 5mM concentrations with recoded activity of 18% and 7% respectively. This result confirms the metalloprotease nature of the enzyme. PMSF at 1mM and 5mM concentrations has reduced relative activity of the enzyme to 46% and 23% respectively. However pepstatin and pcmb had no effect over the enzyme. An alkaline metalloprotease produced by Pseudomonas aeruginosa was reportedly 100% inhibited by 5mM EDTA (Gupta et al, 2005). Soroor et al 2009 have reported an alkaline metalloprotease from Photorhabdus Sp. Strain EK1 which is inhibited by 80% by 20mM EDTA. Simkhada et al, 2010 have reported an alkaline metalloprotease whose activity was inhibited by EDTA from Streptomyces olivochromogenes (SOMP).

60 Table 4.14 Effect of protease inhibitors Protease Residual activity (%) Inhibitor 1mM 5mM EDTA 18% 7% PMSF 46% 23% pcmb 98% 93% Pepstatin 99% 97% Effect of Detergents on purified alkaline protease The enzyme remained stable in Tween 80 and Triton X-100 but SDS has reduced the activity by 31% (Table 4.15). These results are in well accordance with the findings of Monod et al (1993). Their studies have revealed that activity of alkaline metalloprotease produced by Aspergillus fumigates has reduced by 25%-50% with 1% SDS. However the enzyme activity remained unaffected by Tween 80 and Triton X-100. Further Venugopal and Saramma (2006) have shown that alkaline protease produced by Vibrio fulvis has retained 60% and 65% protease activity in presence of 0.1% and 0.5% SDS.

61 Table 4.15 Effect of detergents on alkaline protease activity Detergents (1%) Residual activity (%) Control 100 SDS 31 Triton X Tween Immobilization Immobilized enzymes have many advantages over their free-state counterparts. Most important of those are reusability and operational stability. These factors have economic implications like cost-effectiveness for a process. Hence attempts have been made to immobilize the purified enzyme produced by Exiguobacterium acetylicum MTCC 9115 and its reusability was investigated. The purified enzyme was immobilized by calcium alginate method. The difference in initial protein concentration of the enzyme used and protein concentration of the supernatant after immobilization indicated that only 61% of the enzyme was immobilized. The enzyme beads were assayed for proteolytic activity by the standard assay procedure with casein as substrate. There has been a marginal decrease in the protease activity with immobilization. Reusability was checked by repeating protease assay for 5cycles. The immobilized enzyme has retained protease activity

62 for 3 cycles and later the enzyme activity decreased drastically. (Table 4.16) Table 4.16 Protease activity of Immobilized enzyme Enzyme Relative activity (%) Free enzyme 100 Immobilized enzyme cycle I 93% Immobilized enzyme cycle II 89% Immobilized enzyme cycle III 52% Immobilized enzyme cycle IV 12% The immobilization of alkaline protease from Bacillus subtilis KIBGE-HAS by calcium alginate method with 3reuses was reported by Anwar et al, 2009.Their study has indicated a relative activity of 85% and 35% residual activity for 2 nd and 3 rd reuses respectively. Sharma et al in 2006 have reported immobilization of a partially purified alkaline protease from a new strain of Aspergillus oryzae AWT Applications of alkaline protease from Exiguobacterium acetylicum Wash performance Evaluation of wash performance of the protease enzyme was performed by soaking a blood stained cloth in enzyme solution, followed by rinsing with water. The purified protease enzyme produced by E.acetylicum suspended in tap water has efficiently removed the blood stains from the test fabrics (Figure 4.40). Similar wash performance of alkaline protease

63 from Bacillus clausii I-52 was reported by Joo and Chang, (2006). Oberoi et al (2001) also reported the removal of blood stains by SDS stable alkaline protease produced by Bacillus sp. Figure 4.40 Evaluation of wash performance Detergent compatibility The alkaline protease produced by Exiguobacterium acetylicum MTCC 9115 was incubated with different commercial detergents to understand its detergent compatibility. The purified enzyme was incubated with detergent solutions of 7mg/ml for 2 h. The residual activity was measured by conducting standard protease assay with the preincubated enzyme samples. One unit of protease activity was defined as the enzyme required for releasing 1 µg of tyrosine per minute. The investigation has shown that the enzyme is stable with all the detergents tested (Table 4.17). However the enzyme has shown a little decreased residual activity of 87% with Mr.White. Similar results of detergent compatibility with 7mg/ml of detergent have been reported for crude alkaline protease by from B.licheniformis RP-1 by Sellami-Kamoun et al. (2008). Two detergent stable proteases of Bacillus mojavensis A21 with commercial detergent stability at 7mg/ml detergent concentration were reported by Haddar et al in 2009.

64 Table 4.17 Effect of commercial detergents on protease activity Detergent Relative activity (%) Ariel 96% Henko 98% Mr. White 87% Tide 94% Surf Excel 95% Wheel 92% Feather degradation Keratinase activity of Exiguobacterium acetylicum MTCC 9115 was evaluated activity by incubating the culture in feather medium containing 1% [w/v] white chicken feathers. The isolate Exiguobacterium acetylicum MTCC 9115 has shown complete degradation of white chicken feathers in 48 h time period (Figure 4.41).

65 Figure 4.41 Feather degradation activity of Exiguobacterium acetylicum MTCC 9115 Feather medium comprising of 1% (w/v) chicken feathers incubated with 10% inoculum of 24h old culture of Exiguobacterium acetylicum MTCC for 48 h