Microbiology and Biotechnology Letters (한국미생물·생명공학회지)

The Korean Society for Microbiology and Biotechnology (한국미생물·생명공학회)
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Application of Response Surface Methodology and Plackett Burman Design assisted with Support Vector Machine for the Optimization of Nitrilase Production by Bacillus subtilis AGAB-2

  • Received : 2022.12.26
  • Accepted : 2023.02.14
  • Published : 2023.03.28
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Abstract

Nitrilases are a hydrolase group of enzymes that catalyzes nitrile compounds and produce industrially important organic acids. The current objective is to optimize nitrilase production using statistical methods assisted with artificial intelligence (AI) tool from novel nitrile degrading isolate. A nitrile hydrolyzing bacteria Bacillus subtilis AGAB-2 (GenBank Ascension number- MW857547) was isolated from industrial effluent waste through an enrichment culture technique. The culture conditions were optimized by creating an orthogonal design with 7 variables to investigate the effect of the significant factors on nitrilase activity. On the basis of obtained data, an AI-driven support vector machine was used for the fitted regression, which yielded new sets of predicted responses with zero mean error and reduced root mean square error. The results of the above global optimization were regarded as the theoretical optimal function conditions. Nitrilase activity of 9832 ± 15.3 U/ml was obtained under optimized conditions, which is a 5.3-fold increase in compared to unoptimized (1822 ± 18.42 U/ml). The statistical optimization method involving Plackett Burman Design and Response surface methodology in combination with an AI tool created a better response prediction model with a significant improvement in enzyme production.

Keywords

Acknowledgement

The author gratefully acknowledges Knowledge Consortium of Gujarat (KCG), Govt. of Gujarat for providing financial support through SHODH fellowship scheme (Ref No: 202001640002).

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