Media optimization for extracellular amylase production by Pseudomonas balearica vitps19 using response surface methodology
Moni Philip Jacob Kizhakedathil, Subathra Devi Chandrasekaran
Media optimization for extracellular amylase production by Pseudomonas balearica vitps19 using response surface methodology
BACKGROUND: In this study, we optimized the process for enhancing amylase production from Pseudomonas balearica VITPS19 isolated from agricultural lands in Kolathur, India.
METHODS: Process optimization for enhancing amylase production from the isolate was carried out by Response Surface Methodology (RSM) with optimized chemical and physical sources using Design expert v.7.0. A central composite design was used to evaluate the interaction between parameters. Interaction between four factors – maltose (C-source), malt extract (N-source), pH, and CaCl2 was studied.
RESULTS: The factors pH and CaCl2 concentration were found to affect amylase production. Validation of the experiment showed a nearly twofold increase in alpha amylase production.
CONCLUSION: Amylase production was thus optimized and increased yield was achieved.
Pseudomonas balearica VITPS19 / alpha amylase / optimization / response surface methodology / central composite design / pH
[1] |
Bradford M M (1976). A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem, 72(1-2): 248–254
CrossRef
Pubmed
Google scholar
|
[2] |
Dey G, Mitra A, Banerjee R,Maiti B R (2001). Enhanced production of amylase by optimization of nutritional constituents using response surface methodology. Biochem Eng J, 7(3): 227–231
CrossRef
Google scholar
|
[3] |
Elibol M, Tanyildizi M S, Dursun O (2005). Optimization of α-amylase production by Bacillus sp. using response surface methodology. Process Biochem, 40(7): 2291–2296
CrossRef
Google scholar
|
[4] |
Gangadharan D,Sivaramakrishnan S, Nampoothiri K M, Sukumaran R K, Pandey A (2008). Response surface methodology for the optimization of alpha amylase production by Bacillus amyloliquefaciens. Bioresour Technol, 99(11): 4597–4602
CrossRef
Pubmed
Google scholar
|
[5] |
Kizhakedathil M P J, Chandrasekaran S D (2017). Screening for extracellular enzymes from actinomycetes isolated from agricultural soils of Kolathur, Tamil Nadu, India. Curr Bioact Compd, 13 (In press)
CrossRef
Google scholar
|
[6] |
Kumar R, Mehta A (2013). Isolation, optimization and characterization of α-amylase from Bacillus alcalophilus. Int J Sci Res, 2(7): 171–174
|
[7] |
Liu J, Weng L, Zhang Q, Xu H, Ji L (2003). Optimization of glucose oxidase production by Aspergillus niger in a benchtop bioreactor using response surface methodology. World J Microbiol Biotechnol, 3(3): 317–323
CrossRef
Google scholar
|
[8] |
Meena B, Rajan L A, Vinithkumar N V, Kirubagaran R (2013). Novel marine actinobacteria from emerald Andaman & Nicobar Islands: a prospective source for industrial and pharmaceutical byproducts. BMC Microbiol, 13(1): 145
CrossRef
Pubmed
Google scholar
|
[9] |
Miller G L (1959). Use of dinitrosalycilic acid reagent for determination of reducing sugars. Anal Chem, 31(3): 426–428
CrossRef
Google scholar
|
[10] |
Myers R, Montgomery R C (2002). Response surface methodology: Process and product optimization using designed experiments. New York, Wiley
|
[11] |
Nigam P, Singh D (1995). Enzyme and microbial systems involved in starch processing. Enzyme Microb Technol, 17(9): 770–778
CrossRef
Google scholar
|
[12] |
Osorio N M (2001). Response Surface Modelling of the Production of v-3 Polyunsaturated Fatty Acids-Enriched Fats by a Commercial Immobilized Lipase. J Mol Catal B Enzym,11: 677–686
|
[13] |
Pujari V, Chandra T S (2000). Statistical optimization of medium components for enhanced riboflavin production by a UV-mutant of Eremothecium ashbyii. Process Biochem, 36: 31–37
|
[14] |
Rameshkumar A, Sivasudha T (2011). Optimization of nutritional constitute for enhanced α-amylase production by solid state fermentation technology. Int J Microbiol Res, 2(2): 148
|
[15] |
Rao K J, Kim C, Rhee S (2000). Statistical optimization of medium for the production of recombinant hirudin from Saccharomyces cereveasiae using response surface methodology. Process Biochem, 35(7): 639–647
CrossRef
Google scholar
|
[16] |
Saha K, Maity S, Roy S, Pahan K, Pathak R, Majumdar S, Gupta S (2014). Optimization of amylase production from B. amyloliquefaciens (MTCC 1270) using solid state fermentation. Int J Microbiol, 2014: 764046
CrossRef
Pubmed
Google scholar
|
[17] |
Stergiou P, Papamichael E (2014). Optimization of the production of extracellular α-amylase by Kluyveromyces marxianus IF0 0288 by response surface methodology. Braz Arch Biol Technol, 57(6): 421–426
CrossRef
Google scholar
|
[18] |
Suganthi V, Mohanasrinivasan V (2014). Optimization studies for enhanced bacteriocin production by Pediococcus pentosaceus KC692718 using response surface methodology. J Food Sci Technol,
CrossRef
Pubmed
Google scholar
|
[19] |
Sunitha K, Lee J, Oh T(1999). Optimization of medium components for phytase production by E. coli using response surface methodology. Bioprocess Eng, 21: 477–481
|
[20] |
Viswanathan S, Rohini S, Rajesh R, Poomari K (2014). Production and medium optimization of amylase by Bacillus Spp. using submerged fermentation method. W J Chem, 9(1): 1–6
|
[21] |
Vohra A, Satyanarayana T (2002). Statistical optimization of the medium components by response surface methodology to enhance phytase production by Pichia anomala. Proc Biogeosciences, 37: 999–1004
|
/
〈 | 〉 |