ISSN: 0973-7510

E-ISSN: 2581-690X

M. Rameshpathy1, G. Jayaraman1, A.S. Vickram1, S. Venkatkumar1, Raja Das2 and T.B. Sridharan1
1School of Bio Sciences and Technology, 2School of Advanced Sciences,
VIT University, Vellore – 632 014, India.
J Pure Appl Microbiol. 2014;8(4):3185-3193
© The Author(s). 2014
Received: 06/01/2014 | Accepted: 20/03/2014 | Published: 31/08/2014
Abstract

The effect of various parameters like carbon sources, nitrogen sources, pH, temperature, NaCl and ampicillin on b-lactamase production by Bacillus cereus was investigated by one-factor-at-a-time method. Subsequently, Plackett– Burman method was employed to identify the significant variables. Of the different variables used, glucose, yeast extract and (NH4)2HPO4 had significant influence on b-lactamase production. Further optimisation using response surface methodology (RSM) and artificial neural network (ANN) revealed that the medium containing 10 g/l glucose, 10 g/l yeast extract, and 2 g/l (NH4)2HPO4 yielded 3,100 U/mg of b-lactamase. The higher values of coefficient of determination (0.9864RSM, 0.9786ANN) and lower average absolute deviation (0.049%RSM, 1.83%ANN) indicated the applicability both RSM and ANN in predicting and validating the production parameters for b-lactamase by B. cereus VITMUT. The study, for the first time describes higher production of b-lactamase by non- pathogenic halotolerant organism.

Keywords

Artificial Neural Network, b-lactamase, Bacillus cereus, Halotolerant, Response Surface Method

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