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Korean Journal of Chemical Engineering

, Volume 34, Issue 11, pp 2901–2915 | Cite as

Enhanced production of glutaminase free L-asparaginase II by Bacillus subtilis WB800N through media optimization

  • Chityala Sushma
  • Ashish Prabhu Anand
  • Venkata Dasu Veeranki
Biotechnology

Abstract

We studied the crucial components which elevate the expression of recombinant novel glutaminase free L-asparaginase II (rL-asp II) from Bacillus subtilis WB800N. The Plackett-Burman tool identified sucrose, NH4Cl, NaH2-PO4 and MgSO4 as the significant influencing factors (p<0.05). Further investigations showed that artificial neural network-genetic algorithm (ANN-GA) was more effective than central composite design (CCD) in optimizing the influencing factors. The maximum rL-asp II expression was found to be 389.56 IU/ml and 525.98 IU/ml using CCD (R2=90.4%) and ANN-GA (R2=96.2%), respectively. The validation experiments were carried out in a 3 L batch bioreactor where kinetic modelling of the obtained data was done. The rL-asp II expressed effectively inhibiting the polyacrylamide formation in vitro where no solidification was observed, when 2ml of purified rL-asp II used even after 60 min of incubation. This is the first study to report highest production of rL-asp II in B. subtilis WB800N (525.98 IU/ml) till date by combining statistical designs with consecutive intermittent addition of IPTG in batch reactor.

Keywords

Bacillus subtilis WB800N L-asparaginase II Artificial Neural Network-genetic Algorithm Batch Reactor Unstructured Bio-kinetic Models 

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Copyright information

© Korean Institute of Chemical Engineers, Seoul, Korea 2017

Authors and Affiliations

  • Chityala Sushma
    • 1
  • Ashish Prabhu Anand
    • 1
  • Venkata Dasu Veeranki
    • 1
  1. 1.Biochemical Engineering Laboratory, Department of Biosciences and BioengineeringIndian Institute of Technology (IIT) GuwahatiGuwahatiIndia

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