ijib international journal of industrial...

EVALUATION OF WELL-ADJUSTED SOLID SUBSTRATEMEDIUM FOR ENHANCED PROTEASE PRODUCTION BYBACILLUS SUBTILIS DKMNR: MIXTURE DESIGN A CASESTUDY

Kezia Devarapalli1,2,*, Prasanthi Velaga3, Narasimha Rao Medicherla.1 andSureddy Visweswara Naidu1

1Centre for Biotechnology, Department of Chemical Engineering, Andhra University,Visakhapatnam, India.2Department of Biotechnology, St. Martins Engineering College, Dhulapally, Secundrabad, India.3Department of Quality Control, Startek Laboratories, Hyderabad, India.

Abstract: Alkaline protease production under solid state fermentation was investigated using the isolatedstrain of Bacillus subtilis DKMNR. Among all agro-industrial waste material evaluated, green gram husk,soya bean meal and bengal gram husk supported maximum protease production. The simplex lattice designwas used to improve the enzyme production and to observe the effect of the three substrates. Maximumenzyme production (1045 U/gds) was observed when the substrate mixture was of 0.8 g of green gram husk,3.4 g of soybean meal and 0.8 g of bengal gram husk. The yield was improved with the supplementation ofcarbon and nitrogen sources to the solid medium. Optimum enzyme production was achieved with 1.25 g ofglucose and 0.5 g of casein. Glucose did not repress the enzyme production but the inorganic nitrogensources except urea, all showed little negative impact. The physiological fermentation factors such as pH ofthe medium (pH 9.0), moisture content (120 %), inoculum concentration (2 ml), incubation temperature(32 °C) and incubation time (48 hr) played a vital role in alkaline protease production.

Keywords: Alkaline protease, Bacillus subtilis DKMNR, Solid state fermentation, Mixed design, Optimization.

INTERNATIONAL JOURNAL OF INDUSTRIAL BIOTECHNOLOGYVolume 1 • Number 1 • January-June 2011, pp. 41-53, International Science Press (India)I J I B

* Corresponding Author: [email protected], Telephone:+91 9703507043, 040 27230536.

1. INTRODUCTION

Among the industrial enzymes, proteases make up thegreatest portion of worldwide sales with a steadilyincreasing demand for applications in the leather,cosmetic, pharmaceutical, detergent, brewing and foodindustries[1-2]. However, the largest share of the enzymemarket has been held by detergent alkaline proteasesactive and stable in the alkaline pH range as they play aspecific catalytic role in the hydrolysis of proteins [3].This has created increasing attention in exploitation ofexotic microbial strains for production of alkalineproteases.

Most of the microbial products at industrial scale aregenerally produced using submerged fermentation due toits apparent advantages in consistent enzyme productioncharacteristics with defined medium and process

conditions. Further, it has advantages in downstreamprocessing in spite of the cost-intensiveness for mediumcomponents [1, 4-5]. However, solid-state fermentationhas gained renewed interest and fresh attention fromresearchers because of its edge in biomass energyconservation, solid waste treatment and its application toproduce secondary metabolites over submergedfermentation [6-9]. Production of biocatalysts using agro-biotech substrates under solid-state fermentationconditions provide several advantages in productivity, cost-effectiveness in labour, time and medium componentsfurther the effluent production is less and thus it is eco-friendly [6-10]. However, these production characteristicshave to offer a competitive advantage over existingproducts.

There are a large number of techniques available todesign culture media. They can vary from the traditionalone-variable at- a-time method to more complex statisticaland mathematical techniques [2] involving experimental

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42 International Journal of Industrial Biotechnology (IJIB)

designs such as full and partial factorials, Plackett-Burman design, followed by optimization techniques suchas response surface methodology (RSM) [9], artificialneural networks (ANNs) [3,4], fuzzy logic and geneticalgorithms (GA)[3,4] among others. Regrettably, nomultipurpose technique is known to be applicable to allsituations. Mixture designs were found to be effectivetool for screening and evaluation of the various solidsubstrates [8]. In a mixture experiment, the independentfactors are proportions of different components of a blend.The interpretation of data in mixture experiments wherethe components represent proportionate amounts of thefactors differs from classical factorial experiments wherethe response varies depending on the amounts of eachinput variable. The key to mixture experiments is that themixture components are subject to a constraint requiringthat the proportions sum to one. In mixture experiments,the measured response is assumed to depend only on therelative proportions of the ingredients or components inthe mixture, and not on the amount of the mixture.However, one can overcome this limitation by adding theamount of mixture as an additional factor in the experiment,thereby allowing mixture and process variables to beingtreated together. The advantage of mixture experimentsover factorial design is that one can more efficiently studythe interaction influence amongst factors on the production,and subsequently eliminate both neutral- and negative-factors. Mixture experiments have been the subject ofmany studies and have enjoyed extensive application inpharmaceuticals, geology, petroleum, food, and tobaccoindustries.

The present study was aimed to exploit the locallyavailable, inexpensive agro-substrate for alkaline proteaseproduction using Bacillus subtilis DKMNR under solid-state fermentation and optimization of the variousparameters for improvement of the yield.

2. MATERIALS AND METHODS

2.1 Microorganism and Culture Conditions

The Bacillus subtilis DKMNR (MTCC No: 10551Genebank no: FR717670) culture used in this study wasisolated from garden soil samples around the departmentof Chemical Engineering, Andhra University,Visakhapatnam, A.P., India. The culture was periodicallysub cultured on the nutrient agar slants. The inoculationmedia was composed of (g/L) of Glucose, 18.8; peptone,11.24; K2HPO4, 0.50, MgSO4, 0.05 and CaCl2, 0.02 andpH 9 after inoculation of the media, incubated at 31°C onrotary shaker at 225 rpm for 24 hrs.

2.2 Collection and Processing of the Substrates

Various agro industrial materials such as rice bran, wheatbran, coconut oil cake, zuzubi oil cake, peanut press cake,rice husk, green gram husk, red gram husk, bengal gramhusk, black gram husk, soya bean meal, corn cobs, cornstover, corn leaves, sweet sorghum pulp, sugarcanebaggase and sugarcane leaves are obtained from the localagricultural market. Whereas applepomac, pine applewaste, orange waste, banana peels and orange peels wereobtained from the local fruit market and juice shops. Thepotato peels, mashed potatoes, processed tea powder andprocessed coffee waste was collected from the home. Allthe materials were dried at 80°C for 2 hours and the leafmaterials and fruit pulp were powdered. All the materialswere sieved to avoid the fine powder which causes theclumps formation upon addition of water and decrease thesubstrate availability to the microorganism [6].

2.3 Solid State Fermentation

Selected substrates materials were used as a solid mediumfor protease production. Five grams each of the substratewas taken separately in 250 ml Erlenmeyer flasks andmoisturized with 5ml of distilled water. These flasks weresterilized and inoculated with 2 ml of inoculum solution.The flasks were mixed thoroughly and incubated at 30°Cin an incubator for 48 hours.

2.4 Mixture Design

Mixture design was chosen to study the effect of mixedsubstrates on protease production. The best threesubstrates which could yield highest protease at individuallevel were chosen. A simplex lattice design was employedto optimize the substrate mixture. All the experimentswere conducted according to the Sathish et al [8].

In a mixture design, two models have to be taken intoaccount, one for each mixture being considered. In thiscase, a product model can be used with the two groupsof components x and z. This model is represented byEq. (1):

( ) ( )y f x g z e= ∗ + (1)

In Eq. (1) y is the response, the functions f (x) andg (z) are separated polynomial models that represent thetwo mixtures, and e is a zero-mean random variable withvariance independent of x and z.

The polynomial models used in Eq. (1) was modifiedsome terms from the complete polynomial expression inorder to eliminate the constraint originated in the correlatedvariables. Eq.(2) shows the canonical form of thequadratic model:

Evaluation of Well-Adjusted Solid Substrate Medium for Enhanced Protease Production by Bacillus Subtilis… 43

1

q q

i i ij i ji i j

y x x x= <

= β + β∑ ∑ ∑ (2)

Geometrically, in Eq. (2) the parameter βi representsthe expected response to the pure mixture xi = 1, xj = 0,j ≠ i. The first term in the Eq. (2) represents the responsewhen blending is strictly additive and there are nointeractions between the components of the mixture. Thequadratic term β ij xixj represents the excess responseover the linear model due to the interaction between twocomponents, and this effect is often called synergism orantagonism.

2.5 Enzyme Extraction

The enzyme was extracted according to the methoddescribed by Prakasham et al [6]. Fermented mediumwas mixed thoroughly with 50 mM glycine–NaOH buffer,pH 11 for 30 min and the extract was separated bysqueezing through a cloth. This process was repeatedthree times and extracts were pooled together and thencentrifuged. The supernatant was used as enzyme sourcefor protease assay.

2.6 Estimation of Protease Activity

The protease was assayed according to the method ofmodified Auson-Hagihara method [12]. One unit ofalkaline protease activity was defined as 1 µg of tyrosineliberated per ml under the assay conditions.

2.7 Optimization of the Various ProcessParameters

In order to increase the protease production in the solidstate fermentation various process parameters such aspH (5 to 12), moisture content (20 to 200 % w/w), inoculumsize (0.5 to 3.5) and temperature (26 to 40 °C) wereoptimized.

2.8 Effect of Carbon and Nitrogen Additives onProtease Production

The optimum SSF medium was supplemented withdifferent carbon and nitrogen sources initially at 0.5g.Further the best suitable additional carbon and nitrogensource was studied at various concentrations in order toimprove the protease production.

3. RESULTS AND DISCUSSION

3.1 Evaluation of Different Agro-IndustrialMaterial for Alkaline Protease Production

The selection of an ideal agro-biotech waste for economic

enzyme production in solid-state fermentation processdepends upon several factors, mainly related with costand availability of the substrate material. Thus it involvesscreening of several agro-industrial residues.Agro industrialmaterials such as rice bran (RB), wheat bran (WB),coconut oil cake (COC), zuzubi oil cake (ZOC), peanutpress cake (PPC), rice husk (RH), green gram husk (GH),red gram husk (RH), bengal gram husk (BGH), blackgram husk (BLH), soya bean meal (SM), corn cobs (CC),corn stover (CS), corn leaves (CL), sweet sorghum pulp(SSP), sugarcane baggase (SB) and sugarcane leaves(SL) (Fig.1) and household waste materials like applepomac (AP), pine apple waste (PW), orange waste (OW),banana peels (BP), orange peels(OP), potato peels(PP),mashed potatoes (MP), processed tea powder (PTP) andprocessed coffee waste (PCW) (Fig.1) were used assolid support/substrate matrices for production of enzymeby B. subtilis DKMNR. The data indicated that proteaseproduction pattern varied with the type of agro-waste.This phenomenon might be attributed to the dual role ofsolid materials on supply of nutrients to the growingmicrobial culture and providing anchorage for the growingcells.

Figure 1: Protease Production by Isolated Bacillus SubtilisDKMNR Using Market and Household Waste

Maximum protease production (914U/gds) wasobserved with green gram husk while minimum proteaseproduction (145 U/gds) was noticed with rice husk assubstrate/support material. Soya bean meal and bengalgram husk were found to be best substrates for proteaseproduction next to the green gram husk. This data furthersupported that, the composition of the substrate was oneof the important parameters for evaluation of extracellularmicrobial enzymes production. The results were inaccordance with the observations made with alkalophilicand thermophilic Bacillus species JB-99[13] and others


reported about bacterial strains [6, 14]. However, theresults varied in the production values suggesting that thepresent investigated bacterial strain was different in itsmetabolic and biochemical aspects to that of Bacillusspecies JB-99[13]. Evaluation of protease productionvalues of the strain with different organisms reported inthe literature did not indicate that, this strain could be apotential organism after optimization and scale up studies(Table 1). To obtain the maximum protease productionthe fermentation media is modified by mixing the differentagro-industrial wastes. Three different wastes such assoybean meal, bengal gram husk and green gram huskwere selected as they exhibited the maximum proteaseactivity when used as individual substrates.

Table 1Protease Production by Different Microorganisms

Microorganism Solid substrate Proteaseused production

(U/gdsmaterial)

Bacillus sp [6] Green gram husk 35,000

Bacillus species JB99 [13] Pigeon pea 12,430

Bacillus species [15] Wheat bran 429

Bacillus species [15] Lentil husk 168

Penicillium species [17] Soyabean 1950

Aspergillus oryzae[18] Wheat bran 1500

Rhizopus oryzae [19] Wheat bran 358

Rhizopu soryzae [20] Wheat bran 58.7

3.2 Mixture Designs for Substrate Optimization

An augmented simplex lattice design was employed forthe present investigation. In order to observe the mixedsubstrate effect on protease production, three solidsubstrates soybean meal (SM), green gram husk (GH)and bengal gram husk (BGH) were used in these designs,the total proportions of the different substrates made to100% i.e., 5g material. The design consists of total 10 runswhere three with pure mixtures (one for each component),other three with binary blends for each possible two-component blend, another three with complete blends (allthree components are included but not in equal proportions)and last one as centroid (where equal proportions of allthree components are included in this blend). Table 2shows all the experimental runs with the composition ofsubstrate as per mixture design model and the proteaseoutput values. Assuming that, the measured response ofprotease production was dependent on the relativeproportions of the components in the mixture, linearthrough to cubic models (STATISTICA 6.0) were used

for analysis of the mixture design using followingequations.

1

v

i iiY x

== β∑ Linear model (3)

1

v p

i i ij i ji i jY x x x

= <= β + β∑ ∑ ∑ Quadratic model (4)

1

v p p

i i ij i j ijk i j ki i j i j kY x x x x x x

= < < <= β + β + β∑ ∑∑ ∑∑∑

Special cubic (5)

1( – )v p p

i i ij i j ij i j i ji i j i j

p

ijk i j ki j k

Y x x x x x x x

x x x

= < <

< <

= β + β + δ

+ β

∑ ∑∑ ∑∑∑∑∑

Full cubic (6)

Where Y is a response, βi is a linear, βij is a quadraticand βijk cubic coefficients, βij is a parameter of the model.The β ixi represents linear blending portion and theparameters βij represents either synergic or antagonisticblending.

Table 2 presents the varying concentrations of solidsubstrate used during fermentation process and theprotease production data for each experiment. Theprotease production values varied from 685 to 1045 U/gds. This variation of protease yield under similarfermentation conditions but with different substratessuggested the importance of substrate composition onfermentative protease production. Analysis of individualsubstrate impact on protease production pattern indicatedthat green gram husk is the best substrate with 53% higheryield compared to other two selected materials. Furtheranalysis of the data (Table 2) revealed that mixed substrateimproved protease yield. This can be evidenced based onhigher protease yield from experiment 5 compared to 1and 2 (Table 2). However, presence of GH in mixedsubstrate fermentations, supported better productioncompared to SM and BGH which can be evidenced fromexperiments 4,6, 7 and 9 where a higher proteaseproduction was observed than individual or in othercombination substrates as sole substratum. These resultssuggest that green gram husk is playing the vital role inthe mixed substrate fermentation.

In view of the variation in protease yield withdifferent substrates and its production by fermentation isassociated with availability of nitrogen source, the nutrientrelease pattern during sterilization of substrate materialwas investigated by extracting with known amount ofdistilled water and their concentration was analyzed. Itwas noticed that more nutrients were release tofermentation medium by the GH was observed compared


to BGH and SM denoting that the higher protease yieldby GH may be correlated with availability of nutrients inthe composition of substrate.

Data from the experimental design was furtheranalyzed by employing a multiple linear regression usingprotease yield as the response. Sequential F-tests, on thelinear to full cubic solutions were performed forappropriate model selection (based on highest F-statisticssignificance) suitable for protease production. ANOVAresults of the all four models are presented in Table 3.The quadratic model showed a high F value (22.24) andlow p value (0.00588). The analysis of R2 value revealedthat the special cubic and cubic model have higher fit(R2 special cubic = 0.9593 & R2 Cubic = 0.984) than thequadratic model (R2quadratic = 0.9588). Inspite of thegreater R2 values than the quadratic model they havesmaller F-value (F special cubic = 0.0366 & F cubic =0.7702) and higher p-values (P special cubic = 0.8605 &P cubic = 0.6274). Such data suggest that the quadraticmodel is the most significant. Therefore further dataanalysis was performed using only quadratic model. Thenoticed R2 value of the quadratic model is 0.9588 indicatingthat 3 substrate components altogether would explainabout 95.88% of the variability in the response leaving

only 4.12% of the variability remaining unexplained. Inthe present study, a good co-relation was identifiedbetween predicted and experimental protease productionwith a variation of 5.8 %. The empirical relationshipbetween protease production (Y) and substrate variablesin coded units is obtained by the application of secondorder model as per Eq.7.

Y = 685.75 × SM + 910.38 × GH + 808.84 × BGH+ 684.41 × SM × GH + 809.32 × SM × BGH+ 506.6 × GH × BGH

(7)

Table 4Quadratic Model Terms

Coefficients t-Value p-Value

SM 685.7483 22.10519 0.000025

GH 910.3847 29.34638 0.000008

BGH 808.8392 26.07304 0.000013

SM*GH 684.4141 4.78690 0.008731

SM*BGH 809.3232 5.66054 0.004801

GH*BGH 506.5960 3.54321 0.023944

Table 2Mixed Design Experimental Layout and Protease Production

S. No Soybean Meal Green Gram Husk Bengal Gram Husk Protease Activity

(g)(SM) (g)(GH) (g)(BGH) (U/gds)

Coded Real Coded Real Coded Real Observed Predicted Error

1 1 5 0 0 0 0 685.00 685.74 -0.74

2 0 0 1 5 0 0 904.00 910.38 -6.38

3 0 0 0 0 1 5 823.00 808.83 14.16

4 0.5 2.5 0.5 2.5 0 0 966.00 969.17 -3.17

5 0.5 2.5 0 0 0.5 2.5 998.00 986.26 11.73

6 0 0 0.5 2.5 0.5 2.5 967.00 949.62 17.37

7 0.666667 3.4 0.166667 0.8 0.166667 0.8 1045.00 1023.91 21.08

8 0.166667 0.8 0.666667 3.4 0.166667 0.8 915.00 923.74 -8.74

9 0.166667 0.8 0.166667 0.8 0.666667 3.4 1019.00 1010.83 8.16

10 0.333333 1.6 0.333333 1.7 0.333333 1.7 917.00 970.47 -53.47

Table 3ANOVA

S. No Model SS MS F-Value p-Value R2 Adjusted R2

1 Linear 73184.79 13711.06 1.3114 0.328304 0.2725 0.0647

2 Quadratic 4138.62 23015.39 22.2445 0.005882 0.9588 0.9074

3 Special Cubic 4088.73 49.89 0.0366 0.860492 0.9593 0.8780

4 Cubic 1609.46 1239.64 0.7702 0.627401 0.9840 0.8560


Table 5Optimum Temperature Values for

Maximum Protease Production

Optimum OrganismTemperature (°C)

30 Bacillus species B21-2 [28]

35 Bacillus species Y [29]

Bacillus species.MH5-6 [30]

36 Bacillus licheniformis [31]

Bacillus species strain GX6638 [32]

Bacillus species no. AH-101 [33]

37 Bacillus firmus [34]

39.5 Bacillus licheniformis [35]

Where Y is the response of protease production inU/gds and GH, SM and BGH were the substrates withthe respective coded experimental values testing theexperiments as per the Table 2. The significance of eachcoefficient in Eq. 7 was determined by Student’s t-testand p-values and listed in Table 4. The larger magnitudeof the t-value and smaller p-value denote the correspondingcoefficient significance. The observed lower p-value(<0.05) in the present experiment suggested that all linearand interactive terms were significant. For the substrates,GH has one the highest – test value with a magnitude of910.38 and the p-value (8×10–6) was one of the leastwhich indicates that the largest influence in the mixturefor protease production. Even BGH has highest magnitudeof 808.84 and p-value of 13×10–6. The interaction of GHwith BGH indicated the lowest magnitude (3.54) andhigher p-value (23.9×10–3). Similarly, the interaction ofSM with the BGH has the highest magnitude (809.32)and lowest p-value (4.8×10–3) suggesting a large influenceon protease production which can be seen from the 5th

experiment in Table 2.

Figure 2: Triaxial Diagrams of Protease Production as aFunction of Substrate Concentration

The task of optimizing mixtures of different substratesfor protease production can be predicted using a triangularsurface response methodology as triaxial diagrams are

graphical representation of a combination of raw materials,rather than a predictive illustration of the product yield.Figure 2 depicts the triangular graphs showing the levelcurves of protease yield (obtained from Eq .7) as afunction of the substrate type. From the graph it isobserved that the highest yield was nearer to the GHhaving equal distance to the GH – SM and GH-BGHaxis. The SM- BGH axis demonstrated the least proteaseproduction.

Further, a numerical method given by Myers andMontgomery [21] was used to solve the regression Eq. 7to optimize the substrate mixture ratio. The resultsindicated that the optimum mixture for higher proteaseproduction is 44.4% of GH, 25% SM and 30.6% BGH bydry weight. For this substrate combination the predictedprotease yield was 1029.864 U/gds. Our results validatedthese fermentation conditions with a protease productionrate of 1054 U/gds. A similar optimization approach wasperformed by Sathish et al [8] for L-glutaminaseproduction in solid state fermentation. Rispoli and Shah[22], in cutinase production in submerged fermentation.The role of each substrate material was optimized for theproduction of protease in mixture design fermentation usingnatural agro-wastes such as SM, BGH and GH. Amongall materials, GH presence is essential and SM is the leastimportant component for maximizing protease productionamong selected substrates. An optimum proteaseproduction of 1054 U/gds could be obtained with a 44: 31:25 ratio of GH: BGH: SM respectively without anypretreatment of the material. Further work was precededwith respect to optimization of the fermentation parametersto increase the protease production. The parameters suchas pH, moisture content, inoculum concentration, incubationtime, and incubation temperature, concentration of theoptimized carbon and nitrogen sources from the selectedsources were investigated. Keeping the potentiality of thismicrobial strain in protease production further evaluationwas continued using the mixture of soybean meal, bengalgram husk and green gram husk as solid support/substratefor solid state fermentation.

3.3 Role of pH on Protease Production

Enzyme production by microbial strains strongly dependson the extracellular pH because culture pH stronglyinfluences many enzymatic processes and transport ofvarious components across the cell membranes which inturn support the cell growth and product production [3]pH dependent alkaline protease production studies by B.subtilis DKMNR in solid state fermentation using themixture of SM, BGH and GH suggested that, the enzymeproduction was influenced by the pH of the medium.


Maximum protease production (1246 U/gds) wasobserved at pH 9.0 (Fig. 3). The synthesis of the enzymeincreased with increase of the pH of the medium towardsalkaline range from neutrality up to 9.0 and was lessconstant in the pH range 9.0–12.0 by B. subtilis DKMNR.The enzyme production pattern suggested that, the isolatedbacterial strain was alkalophilic in nature and producesmaximum quantity of enzyme at alkaline pH conditions.

Figure 3: Effect of pH on the Production of Protease byIsolated B.subtilis DKMNR

Further evaluation of enzyme data in the studied pHrange indicated a linear increase in the biocatalystproduction up to pH 9.0. The observed variation inprotease production under solid state fermentation withmixed substrate attributed to higher enzyme productionin the pH range of 9.0 to 10.0. In the literature the authorsreported that protease from solid state cultures ofAspergillus parasiticus showed optimum activity at pH8.0 and 80 % less activity at pH 5.0. Johnvesly et al[13]working on alkaline thermo stable protease found that,the enzyme produced by thermoalkalophilic Bacillusspecies JB-99 showed catalytic activity in a broad pHrange (6.0 to 12.0) with 11.0 as optimum pH. The datagenerated in the present investigation suggested that, theinfluence of pH on alkaline protease produced by isolatedB. subtilis DKMNR might be related with synthesis levelbecause, the extraction of the enzyme after solid statefermentation was performed using alkaline pH buffer.The adapted extraction procedure eliminated the inhibitionof protease at cellular transport and at activity level andthe observed growth associated nature of this enzymeproduction in this bacterial strain.

3.4 Role of Moisture Content onProtease Production

Among the several factors that are important for microbialgrowth and enzyme production under solid-state

fermentation using a particular substrate, moisture level(content)/water activity was one of the most criticalfactors [8, 23]. Solid-state fermentation processes aredifferent from submerged fermentation culturing, sincemicrobial growth and product formation occurs at or nearthe surface of the solid substrate particle having lowmoisture contents [10]. Thus, it is crucial to provideoptimized water level that controls the water activity (aw)of the fermenting substrate for achieving maximumproduct production. Reports on enzyme production bymicrobial species under solid-state fermentation indicatedthat the availability of water in lower or higherconcentrations affected microbial activity adversely [15].Moreover, water is known to have profound impact onthe physico -chemical properties of the solids and this, inturn, affects the overall process productivity [10].

Figure 4: Effect of Moisture Content on the Productionof Protease by B. Subtilis DKMNR

The data indicated that, characteristic nature ofenzyme production along with studied moisture level andmoisture content played a critical role in alkaline proteaseproduction in B.subtilis DKMNR. Maximum enzymeproduction was observed with 140 % moisture content,which was noticed as 9824 U/gds matrix biomass (Fig 4).Linearity between moisture content and enzymeproduction was observed up to 140 % and thereafterfurther increase in moisture level in the fermentationmedium resulted in reduction of protease production. Thepercent reduction in enzyme production from either sideof the optimum moisture level (120 %) varied (Fig.4).This was evidenced from the fact that, an increase in 40% moisture level reduced the production to the tune ofonly 17 % to that of optimum production while decreasein same quantity of moisture level caused 30 % reductionindicating the severity of damage to cell metabolism andsubsequent enzyme production will be more with lowwater activity in solid state medium than higher water


level to that of critical requirement. The decrease inproduction with increase in moisture level in the solidmedium might be attributed to decrease in mass transferof heat and gases caused by water logging among theinter-particulate area which in turn adversely affectscellular and biosynthetic activities associated withmicrobial growth [24]. The observed reduction of enzymeproduction at reduced moisture level might be associatedwith reduced availability of water content for microbialgrowth. The results further indicated that, moisturecontent during solid-state fermentation played a majorrole in regulating alkaline protease production in theisolated B. subtilis DKMNR. Though the pattern ofprotease production with the function of moisture level inthe bacterial strain and comparison of protease productionvalues of strains reported in the literature were observedto be similar. However, optimum requirement of moisturecontent during solid state fermentation process varied withthe type of organism and agro industrial material [6].

3.5 Role of Inoculum Concentration onProtease Production

Initial inoculum level influenced the cellular metabolicactivity, growth of the microorganism and metaboliteproduction [25]. The role of initial inoculum concentrationon alkaline protease production under solid-statefermentation environment with soybean meal, bengal gramhusk and green gram husk as medium was investigatedto determine the optimum inoculum requirement. Inoculumlevel selected for this study ranged from 0.5 % to 3.5 %from 24 hr grown bacterial cell suspension having anabsorbance of 0.8 at 600 nm.

Figure 5: Effect of Inoculum Concentration on theProduction of Protease by B. Subtilis DKMNR

Alkaline protease production by B. subtilis DKMNRstrain under solid-state fermentation conditions varied withinitial inoculum level and showed parabolic nature in the

studied inoculum range (Fig.5). Maximum proteasesynthesis (1391U/gds) was noticed in 2 % inoculumsupplemented fermentation conditions. The reductionpattern of enzyme production with increase or decreasein inoculum supplementation from the optimum level alsoshowed difference. Increase of inoculum level from 2 to3.5 % adversely caused 33 and 48 % reduction in theenzyme production. Decrease of the same from 2 % to1.5 and 1 % resulted in 36% and 69 % reduced proteaseproduction, respectively depicting the importance ofinoculum level optimization for efficient proteaseproduction under solid-state fermentation conditions.

3.6 Role of Incubation Temperature onProtease Production

Temperature is another critical parameter that has to becontrolled and varied from organism to organism. Themechanism of temperature control of enzyme productionis not well understood [26]. However, studies by Frankenaet al [7] showed that a link existed between enzymesynthesis and energy metabolism in Bacilli, which wascontrolled by temperature and oxygen uptake. Theoptimum temperature values reported for maximumprotease production are given in the table 4.

Figure 6: Effect of Incubation Temperature on the Productionof Protease by Isolated B. Subtilis DKMNR

Alkaline protease production by B. subtilis DKMNRin solid state fermentation was increased by optimizingthe temperature of the environment. Maximum proteaseproduction was 1505 U/gds at 32 °C. The incubationtemperature showed parabolic nature in this study (Fig.6).The increase and decrease of temperature showed a lotof difference in the protease production. An incrementof 4 °C in the temperature reduced the enzyme productionto 39% and decrease of 4 °C in the incubation temperaturealso decreased the protease production to 30%. Therefore,


the shifting of temperature from 26 to 40 °C has enhancedthe protease production in the fermentation media to two-fold when compared to the control experiment.

3.7 Role of Different Carbon Sources onProtease Production

The selection of an ideal substrate for enzyme productionin solid-state fermentation process is one of the criticalfactors to be considered [1, 4]. This is because, some ofthe nutrients may be available in sub-optimal concentrations,or even absent in the substrate and therefore no substratemay be suitable. In such cases, it would be necessary tosupplement substrate externally with deficit nutrients tohave optimal yields. Several carbon sources such asgalactose, arabinose, fructose, maltose, soluble starch,glucose, xylose, mannose and ribose were selected andsupplemented to the solid medium at 1 % level in order toenhance the microbial growth.

Figure 7: Effect of Different Carbon Sources on theProduction of Protease by Isolated B. subtilis DKMNR

The data suggested that, supplementation of externalcarbon source influenced alkaline protease production inthis bacterial strain and all the selected carbon sourcesshowed positive impact on cellular metabolism leading tothe production of the enzyme (Fig.7). The results indicatedthat the selected media (mixture of soybean meal, bengalgram husk and green gram husk) was not the idealsubstrate for alkaline protease production by this isolatedBacillus subtilis DKMNR because of the deficiency incarbon source. Improvement of cell growth and subsequentmetabolite synthesis, in several microorganisms, wasnoticed upon supplementation of external carbon sources[36-37]. However, enhancement in enzyme productionlevels varied with the type of carbon source (Fig.7).Glucose supplemented conditions supported maximumproduction with an increase of 112 % over control (noexternal carbon source supplementation).

Protease production was observed to be 12 % increaseover control condition, with glucose as external carbonsource. This data suggested that, glucose was not arepressor of protease enzyme in the bacterial strain underinvestigation unlike the observed catabolic repression byglucose in Bacillus subtilis and Bacillus licheniformis[27, 38].

One interesting phenomenon in this investigation wasmaltose, which is a disaccharide with two monomers ofglucose units supported protease production better fromthis bacterial species when compared to carbon source(Fig.7). This might be attributed to the fact that, maltoseas such might enter inside the cell before conversion intoglucose units. In fact, maltose metabolism in bacterialcells begins at maltose-6 phosphate and subsequently getsconverted to glucose-6 phosphate and is metabolizedfurther. This apparently eliminates the glucose associatedphysiological changes in the medium such as lowering ofsolution pH especially the medium is alkaline in nature.Such glucose-mediated reduction in protease productionassociated with lowering of pH was noticed by Zamostet al [39] while working on production and characterizationof a thermostable protease by an asporogenous mutant ofBacillus stearothermophilus. This was further evidencedfrom the fact that reduced alkaline protease productionin lower pH medium environment.

Figure 8: Influence of Glucose Concentration on theProduction of Protease by Isolated B. subtilis DKMNR

In order to know optimum requirement of carbonsource for better alkaline protease production by thebacterial strain is under investigation in solid-statefermentation conditions, the enzyme production patternwas investigated by supplementation of differentconcentrations of glucose (0 to 2 %) (Fig.8). The datarevealed that alkaline protease production in this bacterialstrain was regulated by availability of glucose in themedium and maximum production (1971 U/gds) occurredwith 1.25 % glucose concentration under experimental


conditions. Approximately 15 % improvement of enzymeyield was noticed under 1.25% glucose supplementedconditions when compared to 0.5 %. Further increase inglucose concentration adversely affected proteaseproduction in B. subtilis DKMNR under solid-statefermentation condition. The results obtained were inaccordance with reported alkaline protease production inthe presence of different sugar [40].

3.8 Role of Different Nitrogen Sources onProtease Production

Nitrogen source is one of the essential requirements forhealthy microbial growth and is required to produceseveral cellular organic compounds such as amino acids,nucleic acids, proteins and cell wall components. Thoughmost of microorganisms metabolize inorganic and organicnitrogen sources, the preference varies with the geneticnature of microbe and type of product produced [13]. Itwas reported that alkaline protease comprised 15.6 percent nitrogen and its production was regulated by theavailability of nitrogen in the medium [10, 38,40].Therefore, influence of different nitrogen sources onalkaline protease yield by isolated B. subtilis DKMNRwas investigated by supplementing 0.5 % selected nitrogencompound to solid medium under optimal fermentationenvironment and measuring enzyme production.

Figure 9: Effect of Different Nitrogen Sources on theProduction of Protease by Isolated B. subtilis DKMNR

Experimental data revealed that complex nitrogensources yield maximum alkaline protease production inthe bacterial strain. The data indicated the importance ofnitrogen requirement for production of the protease byFigure. 9. A media with the mixture of SM, BGH and GHwas insufficient nutrient medium for protease production.So, different nitrogen sources on protease production byB .subtilis DKMNR under solid state fermentationconditions with the above media was investigated. Casein

as nitrogen source showed maximum influence byenhancing the enzyme production to that of other organicand inorganic nitrogen sources. The increase in proteaseyield was observed to be approximately 2-fold over control.Similar observations were noticed in the case of proteaseproduction by different microbial species [13,41].

Alkaline protease production data in different inorganicnitrogen sources supplemented condition indicated thatenzyme production was having negative influence in thepresence of ammonium-based and nitrate-based nitrogensources. However, very little impact was observed whencompared to control (Fig.9). Sinha and Satyanarayana[42] noticed ammonium nitrogen associated regulation inprotease production in thermophilic Bacillus licheniformis.These observations clearly suggested that complex nitrogencompounds had an edge over inorganic nitrogen sourcesin alkaline protease production. This might be due to thelowering of pH, by ammonium ion caused reduction inthe enzyme yields.

However, genetic nature of microbial species especiallywith respect to ammonium ion concentration in the mediumand enzyme production could not be ruled out because,protease synthesis was known to be repressed by rapidlymetabolizable nitrogen sources [23]. These observationswere in accordance with the noticed protease productionin the presence of complex nitrogen sources in Bacilluslicheniformis [41] and alkalophilic Bacillus species [28].

Experiments were conducted to optimize the caseinconcentration as nitrogen source for production of alkalineprotease production, by varying the concentration of yeastextract in the medium. The results indicated that theprotease production decreased with increase in caseinconcentration in the medium. This data suggested that aneconomic production of alkaline protease by this bacteriumcan be obtained with 0.5 % casein supplementation to

Figure 10: Effect of Casein Concentration on the Productionof Protease by Isolated B.subtilis DKMNR


the mixture of SM, BGH and GH based solid-statefermentation medium though enzyme yield was 3267U/gds. The results are depicted in (Fig.10).

3.9 Role of Incubation Time on Protease Production

Incubation time is one of the essential physiologicalfermentation parameters to be evaluated for optimalproduction of any microbial product/metabolite. Todetermine the optimum incubation time required foralkaline protease production by isolated B. subtilisDKMNR, the enzyme production pattern was investigatedduring solid-state fermentation process using soybeanmeal, bengal gram husk and green gram husk as solidmatrix. It was observed that protease production increasedwith incubation time from the beginning of thefermentation (Fig.11). Several reports also indicated that,extracellular enzyme production of those enzymes, thatwere having biochemical importance to the producingmicrobial strains, was related with growth characteristicsof the producing microorganism.

Figure 11: Effect of Incubation Time on the Production ofAlkaline Protease by Isolated B. subtilis DKMNR

Maximum protease production by this bacterialstrain under solid-state fermentation environment withthe mixture of media was found to be 3264 U/gds.Influence of incubation time on alkaline proteaseproduction under solid-state fermentation with soya beanmeal suggesting that the enzyme production was growingtill 48 hrs. The results obtained were considered withthe observations made in thermo alkalophilic Bacillusspecies JB-99 using Pigeon pea waste as substratematerial supplemented with mineral salt solution [13],alkaline protease producing Bacillus species strainGX6638 [32], Bacillus species AR-009; [14] and withStreptomyces thermovulgaris[43].

4. CONCLUSION

Alkaline protease production by isolated Bacillus subtilisDKMNR under solid state fermentation was influencedby the chemical nature of the mixture of the substrates(soybean meal, green gram husk and bengal gram husk).Overall, the enzyme production was 117 % highercompared to initial level (i.e., without any nutrientsaddition). The results obtained further supported that;nitrogen and carbon sources were the major limitingfactors in extracellular protease production by themicrobial strain. Enhanced protease production wasyielded by the supplementation of glucose and casein tothe solid medium.

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