alexa Use Of Statistical And Computational Intelligence Based Optimization Technique To Increase Streptokinase Production | 4673
ISSN: 2155-952X

Journal of Biotechnology & Biomaterials
Open Access

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3rd World Congress on Biotechnology

Pavan Kumar and Sanjoy Ghosh
Posters: Agrotechnol
DOI: 10.4172/2155-952X.S1.020
Abstract
Streptokinase is obtained from strain of beta-haemolytic streptococci. It is a well known fibrinolytic activator used particularly in treatment of acute myocardial infarction. In our work recombinant cells of E.coli-BL21 strain containing vector pRSET-B with amp marker is utilized. Various classical mathematical models have already been developed that often depicts the dynamics of the bioreactor operational procedure. One of the computational intelligence based tool, neural network has been devised to supervise the bioprocess of the production dynamics. Matlab-7.2 toolbox is utilized in our work for computational purpose to efficiently carry out neural approach with multilayer perceptron. Parameters including cell biomass, plasmid copy number are taken as input and product streptokinase as output. Comparing the observed and predicted data a relevant statistical inference can be drawn in terms of r2 value which shows the significant correlation. Statistical optimization methodology for media and culture conditions is devised to maximize the production of recombinant enzyme. In Plackett Burman method, seven media components were taken; using Design Expert-8.0 software. The response was taken in terms of streptokinase production. Finally employing chi-square test and criteria of p-value four media components (glucose, yeast extract, phosphates MgSO4) were screened out. Furthermore the interaction of factors associated to culture condition has been resolved with their significance in bioreactor dynamics using central composite design (CCD). The result depicts that using the optimized culture conditions (pH, agitation, temperature and inoculum concentration) the production of streptokinase is about 20% higher in magnitude in comparison to the case applying usual basal conditions.
Biography
Pavan Kumar did MSc (spl. Bioinformatics) from University of Allahabad and subsequently obtained MTech (IT) degree from Indian Institute of Information Technology Allahabad (U.P.) INDIA, in 2007. Presently he is pursuing his PhD from Indian Institute of Technology Roorkee (Uttarakhand) INDIA, in the field of computational bioprocess engineering. He has presented several papers in National and International conferences, recently got Young Scientist Award in National Conference on Biotechnology and Biodiversity 2012, Rewa (M.P.). His prime research interest is associated to modeling and simulation of streptokinase production and analysis of various parameters related to bioreactor system.
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