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

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.


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

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© The Author(s) 2014. Open Access. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License which permits unrestricted use, sharing, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.