A well characterized alkaline metalloprotease enzyme called serralysin with fibrinolytic activity has been reported in the newly isolated Serratia marcescens RSPB11. In view of its potential application in thrombolytic therapy this study has been made for understanding the nutritional parameters requirement needed for production. Therefore, medium components required for the production of serralysin were optimized using a two step statistical approach. Fermentation variables were selected in accordance with the Plackett-Burman design and were further optimized via response surface methodological approach. A total of seven parameters viz., casein, dextrose, KH2PO4, MgSO4, NaCl, CaCl2 and inoculum have been considered for the optimization studies. The statistical model was constructed via central composite design (CCD) using five screened variables (casein, dextrose, KH2PO4, CaCl2 and inoculum size). An overall 51.8% increase in protease production was achieved in the optimized medium as compared with the unoptimized casein medium. With the application of statistical design methodology serralysin production increased significantly with optimized casein medium (23910 U/ml) when compared to yeast extract-peptone medium (5363 U/ml).
Bhargavi PL, Prakasham RS. Enhanced fibrinolytic protease production by Serratia marcescens RSPB11 through Plackett-Burman and response surface methodological approaches. J App Biol Biotech. 2016; 4 (03): 006-014. DOI: 10.7324/JABB.2016.40302
1. Molla A. Activation of hageman factor and prekallikrein and generation of kinin by various microbial proteinases. The journal of Biological Chemistry. 1989; 264:10589-10594.
2. Klein G, Kullich W. Short-term treatment of painful osteoarthritis of the knee with oral enzymes, a randomized, double-blind study versus diclofenac. Clinical Drug Investigation. 2000; 19:15-23.
3. Matsumoto K, Maeda H, Takata K, Kamata R, Okamura R. Purification and characterization of four proteases from a clinical isolate of Serratia marcescens kums 3958. Journal of Bacteriology .1984; 157:225-232.
4. Maeda H. Role of microbial proteases in pathogenesis. Microbiology and Immunology.1996; 40: 685-699.
5. Kumeta H, Hoshino T, Goda T, Okayama T, Shimada T, Ohgiya S, Matsuyama H, Ishizaki K. Identification of a member of the serralysin family isolated from a psychrotrophic bacterium Pseudomonas fluorescens 114. Bioscience Biotechnology and Biochemistry. 1999; 63:1165-1170.
6. Ulhas P, Ambalal C. Purification and characterization of solvent-tolerant, thermostable, alkaline metalloprotease from alkalophilic Pseudomonas aeruginosa MTCC 7926. Journal of Chemical Technology and Biotechnology. 2009; 84:1255-1262.
7. Romero F, Garcia LA, Salas J, Diaz M, Quiros L. Production, purification and partial characterization of two extracellular proteases from Serratia marcescens grown in whey. Process Biochemistry. 2001; 36: 501-515.
8. Bhargavi PL, Kumar BS, Prakasham RS. Impact of nutritional factors verses biomass and serralysin production in isolated Serratia marcescens. Current Trends in Biotechnology and Pharmacy. 2012; 6: 441-448
9. Bhargavi PL, Prakasham RS. A fibrinolytic, alkaline and thermostable metalloprotease from the newly isolated Serratia sp RSPB11. International Journal of Biological Macromolecules. 2013; 66: 479-486.
10. Adinarayana K, Ellaiah P. Response surface optimisation of the critical medium components for the production of alkaline protease by a newly isolated Bacillus sp. Journal of Pharmacy and Pharmaceutical Science. 2002; 5:272-278.
11. Khuri AI, Cornell JA. Response surfaces: design and analysis. Marcel Dekker: New York. 1987.
12. Ledesma, J, Bortolato AS, Boschetti CE, Martino DM. Optimization of environmentally benign polymers based on thymine and polyvinyl sulfonate using plackett-burman design and surface response. Journal of Chemistry. 2013; Article ID 947137:1-9.
13. Saxena R, Singh R. Statistical optimization of conditions for protease production from Bacillus sp. Acta Biol Szegediensis. 2010; 54: 135-141
14. Hymavathi M, Sathish T, Rao CS, Prakasham RS. Enhancement of L-asparaginase production by isolated Bacillus circulans (MTCC 8574) using response surface methodology. Applied Biochemistry and Biotechnology. 2009; 159:191-198.
15. Doddapaneni K, Tatineni KR, Potumarthi R, Mangamoori LN. Optimization of media constituents through response surface methodology for improved production of alkaline proteases by Serratia rubidaea. Journal of Chemical Technology and Biotechnology. 2007; 82:721-729.
16. Mishra A, Kumar S, Kumar S. Application of Box-Benhken experimental design for optimization of laccase production by Coriolus versicolor MTCC138 in solid-state fermentation. Journal of Scientific and Industrial Research. 2008; 67:1098-1107.
17. Mukherjee AK, Rai SK. A statistical approach for the enhanced production of alkaline protease showing fibrinolytic activity from a newly isolated Gram-negative Bacillus sp. strain AS-S20-I. New Biotechnology. 2011; 28:182-189
18. Chennupati S, Potumarthi R, Rao MG, Manga PL, Sridevi M, Jetty A. Multiple responses optimization and modeling of lipase production by Rhodotorula mucilaginosa MTCC-8737 using response surface methodology. Applied Biochemistry and Biotechnology. 2009; 159:317-329.
19. Rodriguez-Duran, Luis V, Contreras-Esquivel JC, Rodriguez R, Prado-Barragan LA, Aguilar CN. Optimization of tannase production by Aspergillus niger in solid-state packed-bed bioreactor. Journal of Microbiology Biotechnology. 2011; 21:960-967.
20. Srinivasulu Y, Subramanyam M. Expression and optimization of capsular polysaccharide production by Neisseria meningitidis serogroup- A using statistical designs and surface plots. International Journal of Pharmacy and Pharmaceutical Science. 2011; 3:148-151.
21. Cao W, Gong G, Liu X, Hu W, Li Z, Liu H, Li Y. Optimization of epothilone B production by Sorangium cellulosum using multiple steps of the response surface methodology. African Journal of Biotechnology. 2011; 10:11058-11070.
22. Rao, C. S, Sathish T, Mahalaxmi M, Laxmi G. S, Rao RS, Prakasham RS. Modeling and optimization of fermentation factors for enhancement of alkaline protease production by isolated Bacillus circulans using feed-forward neural network and genetic algorithm. Journal of Applied Microbiology. 2008; 104:889-898.
23. Pansuriya RC, Rekha SS. Effects of dissolved oxygen and agitation on production of serratiopeptidase by Serratia marcescens NRRL b-23112 in stirred tank bioreactor and its kinetic modeling. Journal of Microbiology and Biotechnology. 2011; 21:430-437.
24. Bhargavi PL, Prakasham RS. Proteolytic enzyme production by isolated Serratia sp RSPB11: role of environmental parameters. Current Trends in Biotechnology and Pharmacy. 2012; 6:55-65.
25. Anson ML. Estimation of pepsin, papain and cathepsin with haemogloblin. Journal of General Physiology.1938; 22:79-89.
26. Plackett RL, Burman JP. The design of optimum multifactorial experiments. Biometrika. 1946; 33:305-325.
27. Dey G, Mitra A, Banerjee R, Maiti BR. Enhanced production of amylase by optimization of nutritional constituents using response surface methodology. Biochemical Engineering Journal. 2001; 7:227-231.
28. Ustariz FJ, Laca A, Garcia LA, Diaz M. Fermentation conditions increasing protease production by Serratia marcescens in fresh whey. Revista Tecnica de la Facultad de Ingenieria Universidad del Zulia. 2008; 1:79-89.
29. Venil CK, Perumalsamy PL. Application of response surface methodology in medium optimization for protease production by the new strain of Serratia marcescens SB08. Polish Journal of Microbiology. 2009; 58:117-124.
30. Pansuriya RC, Rekha SS. Evolutionary operation (EVOP) to optimize whey-independent serratiopeptidase production from Serratia marcescens NRRL B-23112. Journal of Microbiology and Biotechnology. 2010; 20:950-957.
Year
Month