Skip to main content
NCBI home page
Saudi Journal of Biological Sciences logoLink to Saudi Journal of Biological Sciences
. 2020 Dec 3;28(2):1494–1501. doi: 10.1016/j.sjbs.2020.11.079

Screening, selection and development of Bacillus subtilis apr-IBL04 for hyper production of macromolecule alkaline protease

Tahira Shafique a,⁎, Javeria Shafique b, Sheikh Zahid c, Mohsin Kazi d, Osamah Alnemer d, Ajaz Ahmad e,⁎
PMCID: PMC7878699  PMID: 33613077

Abstract

Bacillus subtilis microbe is commonly found in soil and produces proteases on nitrogen and carbon-containing sources and increases the fertility rate by degrading nitrogenous organic materials. The present study was aimed to develop hyper producing mutant strain of B. subtilis for the production of proteases, to improve the process variables by the response surface methodology (RSM) under central composite design (CCD) and the production of protease by the particular mutant strain in a liquid state fermentation media. The mutation of the strain was carried out using ethidium bromide. Pure B. subtilis strain was collected and screened for hyper-production of protease. The production of protease by mutant B. subtilis strain was optimized by varying temperature, inoculum size, pH and incubation time under liquid state fermentation. The CCD model were found to be reliable with r2 of 0.999. The maximum enzyme activity of B. subtilis IBL-04 mutant with 3 mL/100 mL inoculum size, 72 h fermentation time, pH 8, and 45 °C temperature was developed with enzyme activity 631.09 U/mL, indicates 1–7-fold increase in enzyme activity than the parent strain having 82.32 U/mL activity. These characteristics render its potential use in industries for pharmaceutical and dairy formulation.

Keywords: Alkaline protease, Bacillus subtilis, Ethidium bromide, RSM, Enzyme activity

1. Introduction

The proteases are biological macro-molecules known as simple destructive enzymes due to their broad range of scientific, catalytic, analytic, and industrial applications (Neurath and Walsh, 2011). These proteolytic enzymes are universal and commonly found in all types of microorganisms and are vital for the growth and development of a cell and are preferred over inorganic catalyst (Sharma et al., 2004). They are hydrolytic in their mode of action and are of most importance due to their significant demand in pharmaceuticals, food and other related industries for different formulations (Razzaq et al., 2019, Ikram-Ul-Haq and Umber, 2006). Catalysis of the peptide bond in protein is catalyzed by the protease enzyme (P. Singhal et al., 2012). It has been seen that these enzymes act as a bioactive catalyst in living biological processes such as blood clotting, regulation of apoptosis, as well as in transcriptional regulation moreover it is a compulsory reactant for dehairing process of leather, detergents, for removing silver over the x-ray surfaces, food, medicine, and textile industry and (Walsh and Remigio, 2011). Alkaline proteases are separable from the immense range of sources and many types of these enzymes are present in plants, animals, bacteria, fungi, viruses and archaea (Jeongn et al., 2004).

Proteases found in plants and animals are not sufficient to fulfill the industrial demand due to the increasing demand and it is compulsory to produce this enzyme at a low cost and in a shorter period (S. Kumar et al., 2005). B. subtilis among the Bacillus species is a best alkaline protease producer at commercial level (Oda, 2012), its molecular mass varies from 40 to 130 kDa (M.I. Gimenez et al., 2000; C.A. Studdert et al., 2001). Alkaline proteases produced by B. subtilis have physiochemical properties (Mitchell et al., 2007). B. subtilis found in different sources like wastewater and soil are diverse these microbes enhanced the soil fertility as well, isolated and used to produce the protease at a commercial level (H.S. Alnahdi, 2012). The mutagenicity is the induction of the genetic variation in the cell through the changes in the genetic makeup of the cell (usually deoxyribonucleic acid DNA) (Hubar et al., 2017). These variations or changes can subsequently be inherited from one cell to another (Deng et al., 2010). The mutagenesis is a significant procedure where DNA mutations are deliberately intended to yield mutant strains or genes of the organism. Numerous components of a gene, for example, its control components and its gene product can be changed so that the functioning of the genes or protein can be observed in detail (Uyar et al., 2011). The mutation yields mutant proteins with interesting, new or improved properties.

B. subtilis gene apr-IBL-04 (1149 bp) is responsible for the production of alkaline protease (Xu et al., 2019). Different mutagens are commonly used to cause mutation in the DNA likewise: chemical mutagens (ethyl methyl sulfonate, ethidium bromide, nitrous oxide (NO2), hydroxylamine (HA), etc.) and radioactive X-ray and UV radiations (Justin et al., 2001). These mutagens are highly carcinogenic and can cause mutation at different concentrations. RSM is a statistical and mathematical techniques useful in to determining the effect of a variety of independent variables on the yield. RSM is also helpful to estimate the interaction between variables and also helpful to indicate the optimum conditions according to set variables with a minimal number of observations and experiments (S. Puri et al., 2002; V.V.R. Bandaru et al., 2006). To check the gene expression optimized conditions with different variables are required to select the maximum activity producing strain. In this research, Ethidium bromide was used to cause mutation in the B. subtilis strain to develop a hyper producing microbial strain for alkaline protease production in liquid state fermentation followed by the optimized conditions by applying the screening, selection, and optimization by applying RSM under CCD. The present study was constructed with the following objectives; (1) To develop hyper producing mutant strain of B. subtilis for the production of proteases. (2) To improve the process variables by the RSM under CCD. (3) To improve the production of protease by the particular mutant strain in a liquid state fermentation media.

2. Material and methods

2.1. Microbial strain collection and materials

Pure line B. subtilis strain was collected from the Industrial Biotechnology Lab 04, department of biochemistry. The culture was grown on agar-agar medium slants for 72 h at pH ranges from 7 to 7.5 at 37 °C. The cultured slants were preserved at 4 °C for further use in inoculum preparation.

Ethidium bromide, Luria Bertania, peptone, 2-Deoxy-D glucose, triton X-100, agar, skim milk, calcium chloride, sodium chloride, glucose, dibasic-potassium phosphate, phosphate buffer, hydrochloric acid, follin-ciocalteau reagent, magnesium sulfate, sephadex G-75, sodium hydroxide, potassium dihydrogen phosphate, trichloroacetic acid, methylated spirit, distilled water. The chemicals were purchased from sigma-USA.

2.2. Screening and selection of bacterial strain for protease activity

B. subtilis suspensions were pre-cultured in agar-agar medium plates at pH 7 and 30 °C temperature. Pre-cultures were agitated on shaker bath at 150 rpm for 24 h. This homogenized culture was inoculated in fermentation media; (g/L) glucose, 10; peptone 5; KH2PO4, 2; CaCl2, 0.4; MgSO4.7H2 0.02; in double distilled water. The medium was autoclaved for 15 min at 121 °C and inoculated with B. subtilis. The inoculated media was incubated for 24 h at 37 °C temperature. After that the fermented broth was centrifuged to harvest the enzyme at 4 °C for 20 min at rotating speed of 10,000 rpm and supernatant was collected and used for estimation of enzyme activity (Essam et al., 2012). After enzyme assay absorbance was checked by using UV/Visible Spectroscopy at 660 nm (A.K Sharma et al., 2015). The activity of pure lines are given in the Table 1, and best strain optimized was used for further experiments and mutagenic treatment.

Table 1.

Activity of pure line Bacillus subtilis.

S. No. Incubation time (h) Temperature (°C) Inoculum size (mL) pH Activity
1 24 37 1 7 82.32
2 24 37 1 7 80.73
3 24 37 1 7 82.23
Open in a new tab

2.3. Protease assay

Activity of protease was analyzed by the standard procedure of enzyme assay (Gopiriya et al., 2014). 1 mL of 0.5% casein phosphate buffer solution of pH 8 was taken in each 0.2 mL supernatant which was taken from the culture medium. The mixture solution was incubated at 37 °C for 30 min. Then 3 mL of 10% TCA (Trichloroacetic acid) was poured in that mixture and then incubated for 10 min at 40 °C for precipitation, and centrifuged for 15 min at 12,000 rpm. The supernatant was collected and 500 mM Na2CO3, 1 mL of FC reagent was added and was further incubated for 30 min in dark to produce blue color. Then characterization was done under UV/Visible spectroscopy at 660 nm to check the optical density.

Protease Activity = Liberated Tyrosine × Total assay volume/Used Protease volume × incubation Time

2.4. Tyrosine standard curve

A stock solution of an amino acid tyrosine (100 µg/mL) was prepared and aliquots in the range of 5–350 µM. A standard curve was plotted between the increasing concentrations of tyrosine against absorbance at 660 nm.

2.5. Mutagenic treatment

B. subtilis suspension was treated with different concentrations of ethidium bromide (EB) for different periods and was incubated at almost 37 °C for different time intervals. The sample solution at different time intervals were taken serially diluted and centrifuged immediately at 12,000 rpm for 15 min. Pellet obtained was re-suspended in 5 mL phosphate buffer (S.S. Mehmod et al., 2015) to stop the further reaction of EB. The cell suspension was washed in phosphate buffer solution by serial dilution procedure (Fig. 1).

Fig. 1.

Fig. 1

Open in a new tab

Serial dilution of Bacillus subtilis after mutagenic treatment.

2.6. Screening and selection of mutant strain

The mutant strain was grown on agar plates. The petri dishes were incubated at 37 °C for 24 h. The number of colonies formed in each skim milk, agar containing dish was expected to be formed by a single spore cell. A hyper producing mutant for the production of protease was detected by analyzing its growth pattern (Mukhtar and Haq, 2012). The screening of a mutant strain was performed in 25 mL of petri dish1% skim milk and 2% agar, peptone, triton x-100; a colony restrictor, and 2-deoxy D glucose; an antibiotic marker shown in (Fig. 2). After incubation of 24 h at 37 °C, all the dishes were over-flood with TCA 10% solution for 5 min which removed the mild protease layer over the colonies and the circular and transparent zones around the colonies in an opaque white background was picked up and analyzing the absorbance of protease.

Fig. 2.

Fig. 2

Open in a new tab

Selection of mutant strain on 2-deoxy D-glucose skim milk plates.

2.7. Purification and enzyme assay

Protease produced by mutagenic strains of various concentrations and time-periods at skim milk agar plates were collected by adding 10% TCA solution which stops the reaction of protein hydrolysis, after leaving for 15–20 min, centrifuged, 1 mL supernatant was taken and filtered through Whatman filter paper no.1. Enzyme filtrate (2 mL) was taken in a test tube and 4 mL of 0.1 M NaOH and 0.5 mL of diluted Folin Ciocalteau reagent was added. The residues of tyrosine released by enzymatic break down of protein were determined under spectrophotometry under 660 nm wavelength (A.K Sharma et al., 2015). The strain showed greater activity was selected for further optimization for fermentation media.

2.8. Optimization parameters of liquid state fermentation media and RSM

The fermentation media for protease production was prepared by 1% carbon source, 0.5% organic or inorganic nitrogen sources, 2% K2HPO4, 0.02% MgSO4, and 0.04% CaCl2. The different ranges of pH 6–10 shown in (Fig. 3) of the media were adjusted with NaOH/1N HCl and then autoclaved for 15–20 min at 121 °C. After the selection of a best mutated bacterial strain various parameters for the fermentation process were optimized in triplicate flasks for hyper protease production with selected B. subtilis mutated and parent strains and in liquid state fermentation (LSF) medium at varying temperatures, fermentation time, pH, and inoculum size by applying RSM.

Fig. 3.

Fig. 3

Open in a new tab

Fermentation media at different pH for protease production.

RSM is a modest design to evaluate the effect of several parameters affecting the response by varying them. The CCD model were used to study the interaction effects of protease using Design expert statistical software (version 7.1.1). The tests consists of measured responses of groups from experimental and controlled factors, according to 1 or more chosen criteria were used. For the current analysis, designs of four factors were applied to make fit the model of 2nd order polynomials which shows that the 30 experimental runs were compulsory for the optimization process. By solving the regression equation, the optimized standards of the variables were selected. The fermentation runs of 30 test runs were carried out in triplicates (Mukhtar, 2013). The media having varying pH was added in flasks of 250 mL, cotton plugged and aluminum foiled. The specifically selected substrate was inoculated with mutated B. subtilis strain with different inoculum sizes in each run and were incubated with continuous shaking for different fermentation periods at different temperatures (Table 2).

Table 2.

Values of experimental independent variables.

Independent variables Coded levels Coded levels
Ranges −1 +1
pH 6 10
Temperature (°C) 35 55
Inoculum size (mL) 1 5
Incubation period (h) 24 120
Open in a new tab

3. Results and discussion

3.1. Wild type strain growth

The wild type of strain was grown on skim milk agar plates to optimize the parent and mutant strain activity. The physiological growth of wild type strain B. subtilis is shown in Fig. 4A.

Fig. 4.

Fig. 4

Open in a new tab

Wild type strain growth (A). The growth pattern of chemically mutated Bacillus subtilis by EB 60 min on a Petri plate (B).

3.2. Mutagenesis of B. subtilis

Procedures of mutagenesis were optimized in terms of dose and type of mutagen. Mutagen specificity can be taken into account and mutagenesis itself can be enhanced to screen out the best mutants. Chemical mutagenesis was carried out by using Ethidium bromide (EB), independently

3.3. Chemical mutagenesis of B. subtilis by EB

EB is known as a mutagenic and carcinogenic organic and aromatic intercalating compound. EB causes a shift of frame type mutation in the genetically makes up. EB is a widely used chemical that is used as a fluorescent dye in biotech experiments. It is a mutagenic compound that interacts with RNA and double-stranded DNA. EB is water-soluble and shows great stability under normal pressure and temperature (Kumar et al., 2012).

3.4. Optimization of mutant strain

The best selected mutant strain for further optimization of physical and nutritional parameters were found at 60 min (Fig. 4B) among 4 different time intervals expressed in Table 3 incubation period of mutagenic treatment which produces 484 (IU/mL) of protease at 24 h fermentation time.

Table 3.

Effect of mutagen on protease production by Bacillus subtilis at different time intervals.

S. No. Incubation time (min) Enzyme activity IU/mL
1 30 437
2 60 484
3 90 435
4 120 426
Open in a new tab

3.5. Response-surface methodology

RSM is a mathematical and statistical technique which is used to analyze various parameters in which effective and valuable response is affected by different kind of parameters and the basic aim is to optimize that response (Beg Q.k. and R. Gupta, 2009) and to develop the best growth medium for B. subtilis. The activity of protease enzyme was taken as dependent and response variables were selected for further study (Table 4). The P-value and F- value in the ANOVA were studied which shows lesser the P-value, and grater the importance of the corresponding coefficient (Mhamdi et al., 2017). The F-value of 97.57 indicates the model is significant (Table 5) and minimum chances of errors in the model. The p-value of 0.05 demonstrates the model is significant. The model terms will not be significant if the values are greater than 0.1000. The present model were significant corresponding to its p-values.

Table 4.

CCD (Central Composite Design) for optimization of protease production by EB.

Run Temperature pH Inoculum Size (mL) Fermentation time (h) Protease activity (IU/mL)
1 55 6 5 120 70.49
2 40 8 3 72 566.64
3 35 6 5 120 274.73
4 45 8 3 72 630.86
5 45 8 2 72 585.15
6 45 7 3 72 563.15
7 35 10 5 24 287.89
8 45 9 3 72 542.11
9 45 8 3 72 631.09
10 35 6 1 120 274.06
11 55 6 1 24 269.60
12 35 10 1 24 283.43
13 45 8 4 72 582.92
14 55 10 5 120 276.74
15 45 8 3 96 517.13
16 35 10 1 120 282.14
17 45 8 3 48 583.14
18 45 8 3 72 630.84
19 45 8 3 72 630.89
20 35 10 5 120 283.43
21 55 10 5 24 283.40
22 45 8 3 72 630.86
23 50 8 3 72 493.49
24 45 8 3 72 630.89
25 35 6 1 24 274.51
26 35 6 5 24 278.97
27 55 6 1 120 269.60
28 55 6 1 120 270.05
29 55 6 1 120 281.64
30 55 6 1 120 275.62
Open in a new tab

Table 5.

ANOVA for response surface quadratic model.

Source Sum of squares df Mean square F-Value P-value
Prob > F
Model 4010.75 14 17922.66 97.57 <0.0001 Significant
A-Temperature 829.64 1 829.64 4.52 0.0506
B-Inoculum size 336.38 1 336.38 1.83 0.196
C-Fermn Temp. 330.49 1 330.49 1.8 0.1998
D-pH 489.6 1 489.6 2.67 0.1234
AB 44.72 1 44.72 0.24 0.6289
AC 455.5 1 455.5 2.48 0.1362
AD 101.15 1 101.15 0.55 0.4695
BC 168.29 1 168.29 0.92 0.3537
BD 78.9 1 78.9 0.43 0.5222
CD 201.43 1 201.43 1.1 0.3116
A2 9135.67 1 9135.67 49.73 <0.0001
B2 66.17 1 66.17 0.36 0.5573
C2 0.56 1 0.56 3.06E-03 0.9566
D2 146.8 1 146.8 0.8 0.3855
Residual 2755.4 15 183.7 0.68
Lack of Fit 955.1 10 95.51 0.916 Non-significant
Pure Error 802.23 5 173.22
Cor Total 5764.59 29
Open in a new tab

The comparison of observed response variability values with the variables under experiment and their particular interaction was calculated by the coefficient of determination R2. The best analysis of fitting of the model was calculated by R2, its values range from 0 to 1 and the model is found to be good if predicted value is near or equivalent to 1 (Olajuyigbe and Ajele, 2005). In the present study the coefficient of determination value was found to 0.9891 for the production of alkaline protease. This can be interpreting as up to 98.91% variability response. The adjusted R2 was 0.9790 which has a close relationship with R2. The predicted R2 was 0.9491 which shows close resemblance with R2 and adjusted R2. This shows the goodness of the model and the parameters optimized. The value 0.9491 of Pred R-Square is in agreement with the value of 0.979 of Adj R-Square with precision (CV%: 2.59). The Adeq-Precision calculates the ratio of signal to noise and this should be greater than 4 (Ahmad et al., 2020, Bagewadi et al., 2011). In the present investigation Adeq-precision was found to be 22.64 which shows a satisfactory signal. Hence the model can be used to direct the space of this design (Pant et al., 2015, Ahmad et al., 2015).

The BBD model resulted in six response plots for the optimization of alkaline protease and these were studied. The relationship of dependent and independent variables of protease were studied graphically by 3D response surface (RS) plots which were used to explain the optimum circumstances significantly. The optimum pH for protease enzyme synthesis by B. subtilis was 8–9 and temperature of 45 °C (Fig. 5A). In the case of protease enzyme produced by B. subtilis inoculum size and temperature have opposed effect. There is an increase in the production of an enzyme with an initial increase in inoculum size and temperature. RS plot showed that at 5 mL inoculum size at 45 °C temperature yields maximum protease production (Fig. 5B). Initially increase in fermentation time (72 h) and temperature (45 °C) increases the production of protease (Fig. 5C). 3D graphs indicates the pH range of 7–9 (alkaline) and inoculum size of 5 mL were optimum for protease production (Fig. 5D). Protease production was affected by fermentation time and pH at their most mid-level. The response surface graphs shows that at pH 8 and fermentation time 72 h protease enzyme production was found to be maximum (Fig. 5E). Conversely, the protease enzyme production also showed an optimum yield at 3 mL of inoculum size and 72 h fermentation time (Fig. 5E).

Fig. 5.

Fig. 5

Open in a new tab

Response surface graphs showing (A) Interaction of pH 8–9 vs temperature 49 °C (B) Inoculum size (5 mL) vs temperature 49 °C; (C) Fermentation time 72 h vs temperature 45 °C (D) Inoculum size 5 mL vs pH 8–9 (E) Fermentation Time 72 h vs pH 8 (F) Fermentation time 72 h vs Inoculum size 3 mL.

Adequacy of the model is analyzed by residuals from the least square fit. To assume the probable normality a diagnostic check of the design were plotted for the production of protease by B. subtilis (Fig. 6A). For the production of protease by B. subtilis in liquid state fermentation, a very close relationship in predicted and actual values were observed and a strong correlation was used to demonstrate the accuracy and precision of CCD (Fig. 6B). Between residual and predicted values a strong correlation was used to demonstrate the accuracy and precision of CCD (central composite design) (Fig. 6C-D). For the production of protease by selected chemically mutated strain, optimized parameters were 3 mL/100 mL of inoculum size, 72 h fermentation time, pH 8, and 45 °C temperature. The activity of the protease enzyme were increased 1–7 folds than the parent strain or the enzyme showed 631 IU/mL activity produce by mutant strains while the wild type strain exhibit 82.32 IU/mL activity.

Fig. 6.

Fig. 6

Open in a new tab

Diagnostic plots (A) Normal % of Probability Plot (B) Correlation between Actual and Predicted value (C) Correlation between Residuals and Predicted values (D) Correlation between Residuals and Run represents adequacy of the model analyzed by residuals from the least square fit.

4. Conclusion

Alkaline bacterial proteases play an essential role in different pharmaceutical, food and industries and their future use is likely to be increased. The investigators are using advancing strategies such as computer biology, protein/genetic engineering, and molecular biology for the production of improved strains of protease. In the current investigation mutagenesis of B. subtilis apr-IBL-04 was done for hyper protease producing strain by using EB as a mutagen. A random chemical mutation was preceded for different periods and at different chemical concentrations. Selection and screening were done to select the strain that ability of hyper producing protease at minimum nutritional elements. Further on various physical parameters, inoculum size, fermentation time, temperature, and pH was optimized by applying RSM under CCD yielded maximum protease production. The maximum enzyme activity of B. subtilis IBL-04 mutant under optimized conditions were found to be 1–7-fold increase in enzyme activity than the parent strain. Overall the model was able to calculate the alkaline protease yield and provide valuable tools for optimization.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgment

The authors extend their appreciation to the Deanship of Scientific Research at King Saud University for funding this work through Research Group Number (RG-1438-069).

Footnotes

Peer review under responsibility of King Saud University.

Contributor Information

Tahira Shafique, Email: rao_tahira@yahoo.com.

Ajaz Ahmad, Email: aajaz@ksu.edu.sa.

References

  1. Sharma A.K., Sharma V., Saxena J., Yadav B., Alam A., Prakash A. Optimization of pro- tease production from bacteria isolated from soil. Appl. Res. J. 2015;1:388–394. [Google Scholar]
  2. Ahmad A., Rehman M.U., Wali A.F., El-Serehy H.A., Al-Misned F.A., Maodaa S.N., Aljawdah H.M., Mir T.M., Ahmad P. Box-behnken response surface design of polysaccharide extraction from rhododendron arboreum and the evaluation of its antioxidant potential. Molecules. 2020;24 doi: 10.3390/molecules25173835. 25(17):3835. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Bagewadi Z.K., Garg S.D., Deshnur P.B., Shetti N.S., Banne A.A. Production dynamics of extracellular alkaline protease from Neisseria sps isolated from soil. Biotechnol. Bioinf. Bioeng. 2011;1:483–493. [Google Scholar]
  4. Beg Q.K., Gupta R. Purification and characterization of an oxidation stable, thiol dependant serine alkaline protease from Bacillus mojavensis. Enz. Microb. Technol. 2009;32:294–304. [Google Scholar]
  5. Studdert C.A., Herrera Seitz M.K., Plasencia Gil M.I., Sanchez J.J., de Castro R.E. Puri- fication and biochemical characterization of the haloalkaliphilic archaeon Natronococcus occultus extracellular serine protease. J. Basic Microbiol. 2001;41:375–383. doi: 10.1002/1521-4028(200112)41:6<375::AID-JOBM375>3.0.CO;2-0. [DOI] [PubMed] [Google Scholar]
  6. Deng A., Wu J., Zhang Y., Zhang G., Wen T. Purification and characterization of a surfactant-stable high-alkaline protease from Bacillus sp. B001. Biores. Tech. 2010;101:7100–7106. doi: 10.1016/j.biortech.2010.03.130. [DOI] [PubMed] [Google Scholar]
  7. Essam F., Juamily A.I., Bushra H., Zaidy A.I. Optimization conditions of production fibrinolytic enzyme from Bacillus lichineformis B4 local isolate. Br. J. Pharmacol. Toxic. 2012;3:289–295. [Google Scholar]
  8. Gopipriya, R., Santhosh, S., Dhandapani, R., 2014. Production, optimization and partial purification of protease by Bacillus megaterium MP8 Isolated from Marine Water. J. of Appl. Microbiol. ISSN., 2: 2278-1250.
  9. Ikram-Ul-Haq H.M., Umber H. Production of protease by Penicillium chrysogenum through optimization of environmental conditions. J. Agric. Soc. Sci. 2006;2:23–25. [Google Scholar]
  10. Razzaq A., Shamsi S., Ali A., Ali Q., Sajjad M., Malik A., Ashraf M. Microbial proteases applications. Front. Bioeng. Biotechnol. 2019;7:110. doi: 10.3389/fbioe.2019.00110. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Alnahdi H.S. Isolation and screening of extracellular proteases produced by new Iso- lated Bacillus sp. J. Appl. Pharm. Sci. 2012:2–71. [Google Scholar]
  12. Hubar C.H., Shen M.C., Lin J.S., Yang N.C. Nattokinase decreases plasma levels of fibrinogen, factor VII, and factor VIII in human subjects. Nut. Res. 2017;29:190–196. doi: 10.1016/j.nutres.2009.01.009. [DOI] [PubMed] [Google Scholar]
  13. Jeong Y.K., Yang W.S., Kim K.H., Chung K.T., Loo W.H., Park J.U. Purification of a fibrinolytic enzyme (myulchikinase) from pickled anchovy and its cytotoxicity to the tumor cell lines. Biotechnol. 2004;26:393–397. doi: 10.1023/b:bile.0000018257.18617.6d. [DOI] [PubMed] [Google Scholar]
  14. Justin C., Khodursky A., Peter B., Brown P.O., Hanawalt P.C. Comparative gene expression profiles following UV exposure in wild type and SOS-deficient Escherichia coli. Genetics. 2001;158:41–64. doi: 10.1093/genetics/158.1.41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Kumar D., Venkatachalam P., Govindarajan N., Balakumaran M., Kalaichelvan P. Production and purification of alkaline protease from Bacillus sp. MPTK 712 isolated from dairy sludge Global. Vet. 2012;8:433–439. [Google Scholar]
  16. Giménez M.I., Studdert C.A., Sánchez J.J., De Castro R.E. Extracellular protease of Natrialba magadii: purification and biochemical characterization, Extremophiles. Microbe. 2000;4:181–188. doi: 10.1007/s007920070033. [DOI] [PubMed] [Google Scholar]
  17. Mhamdi S., Ktari N., Hajji S., Nasri M., Kamoun A.S. Alkaline proteases from a newly isolated Micromonospora chaiyaphumensis S103 characterization and application as a detergent additive and for chitin extraction from shrimp shell waste. Int. J. Biolo. Macromol. 2017;94:415–422. doi: 10.1016/j.ijbiomac.2016.10.036. [DOI] [PubMed] [Google Scholar]
  18. Mitchell, R.S., Kumar, V., Abbas, A.K., Fausto, N., 2007. Robbins Basic Pathology. Philadelphia Saunders., 1: 4160-2973.
  19. Mukhtar H., Haq I.U. Purification and characterization of alkaline protease produced by a mutant strain of Bacillus subtilis. Pak. J. Bot. 2012;44:1697–1704. [Google Scholar]
  20. Mukhtar N.H. Partial purification of alkaline protease by mutant strain of Bacillus subtilis EMS-6. Biol. Soc. Pak. 2013;59:165–171. [Google Scholar]
  21. Neurath H., Walsh K.A. Proc. Natl. Acad. Sci. U. S. A. 2011;73:3825–3832. doi: 10.1073/pnas.73.11.3825. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Oda K. New families of carboxyl peptidases: serine carboxyl peptidases and glutamic peptidases. J. Bio. Chem. 2012;151:13–25. doi: 10.1093/jb/mvr129. [DOI] [PubMed] [Google Scholar]
  23. Singhal P., Nigam V.K., Vidyarthi A.S. Studies on production, characterization and applications of microbial alkaline proteases. Int. J. Adv. Biotechnol. Res. 2012;3:653–669. [Google Scholar]
  24. Olajuyigbe F.M., Ajele J.O. Production dynamics of extracellular protease from Bacillus species. Afr. J. Biotechnol. 2005;4(8):776–779. [Google Scholar]
  25. Pant G., Prakash A., Pavani J.V.P., Bera S., Deviram G.V.N.S., Kumar A., Prasuna R.G. Production, optimization and partial purification of protease from Bacillus subtilis. J. Taib Uni. Sci. 2015;9:50–55. [Google Scholar]
  26. Ahmad A., Alkharfy K.M., Wani T.A., Raish M. Application of Box-Behnken design for ultrasonic-assisted extraction of polysaccharides from Paeonia emodi. Int. J. Biol. Macromol. 2015;72:990–997. doi: 10.1016/j.ijbiomac.2014.10.011. [DOI] [PubMed] [Google Scholar]
  27. Kumar S., Sharma N.S., Saharan M.R., Singh R. Extracellular acid protease from Rhi- zopus oryzae: purification and characterization. Process Biochem. 2005;40:1701–1705. [Google Scholar]
  28. Puri S., Beg Q.K., Gupta R. Optimization of alkaline protease production from Bacillus sp. by response surface methodology. Curr. Microbiol. 2002;44:286–290. doi: 10.1007/s00284-001-0006-8. [DOI] [PubMed] [Google Scholar]
  29. Sharma S., Aneja M.K., Mayer J., Scholter M., Munch J.C. RNA fingerprinting of microbial community in the rhizosphere soil of grain legumes. Fems. Microbiol. Lett. 2004;240:181–186. doi: 10.1016/j.femsle.2004.09.026. [DOI] [PubMed] [Google Scholar]
  30. Uyar F., Porsuk I., Kizil G., Yilmaz E.I. Optimal conditions for production of extracellular protease from newly isolated Bacillus cereus strain CA15. EurAsian J. Bio Sci. 2011;5:19–50. [Google Scholar]
  31. Bandaru V.V.R., Somalanka S.R., Mendu D.R., Madicherla N.R., Chityala A. Optimization of fermentation conditions for the production of ethanol from sago starch by co-immobilized amyloglucosidase and cells of Zymomonas mobilis using response surface methodology. Enzym. Microb. Technol. 2006;38:209–214. [Google Scholar]
  32. Walsh, Remigio, Z., 2011. Production and characterisation of protease enzyme produced by a novel moderate thermophilic bacterium (EP1001) isolated from an alkaline hot spring, Zimbabwe. Afr. J. of Microb. Res., 6: 5542–5551.
  33. Xu Y., Xu F., Ding X., Qian K. Cloning, secretory expression, partial characterization, and structural modeling of an alkaline protease from Bacillus subtilis D-2. L Li - BioResources. 2019;14:5301–5353. [Google Scholar]

Articles from Saudi Journal of Biological Sciences are provided here courtesy of Elsevier

RESOURCES