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Optimizing recombinant production of L-asparaginase 1 from Saccharomyces cerevisiae using response surface methodology. | LitMetric

Optimizing recombinant production of L-asparaginase 1 from Saccharomyces cerevisiae using response surface methodology.

Folia Microbiol (Praha)

Department of Pharmaceutical Biotechnology, School of Pharmacy, Shahid Beheshti University of Medical Sciences, No. 2660, Valiasr-Niayesh Junction, Vali-e-Asr Ave, Tehran 1991953381, Iran.

Published: December 2024

AI Article Synopsis

Article Abstract

L-asparaginase is an essential enzyme used in cancer treatment, but its production faces challenges like low yield, high cost, and immunogenicity. Recombinant production is a promising method to overcome these limitations. In this study, response surface methodology (RSM) was used to optimize the production of L-asparaginase 1 from Saccharomyces cerevisiae in Escherichia coli K-12 BW25113. The Box-Behnken design (BBD) was utilized for the RSM modeling, and a total of 29 experiments were conducted. These experiments aimed to examine the impact of different factors, including the concentration of isopropyl-b-LD-thiogalactopyranoside (IPTG), the cell density prior to induction, the duration of induction, and the temperature, on the expression level of L-asparaginase 1. The results revealed that while the post-induction temperature, cell density at induction time, and post-induction time all had a significant influence on the response, the post-induction time exhibited the greatest effect. The optimized conditions (induction at cell density 0.8 with 0.7 mM IPTG for 4 h at 30 °C) resulted in a significant amount of L-asparaginase with a titer of 93.52 μg/mL, which was consistent with the model-based prediction. The study concluded that RSM optimization effectively increased the production of L-asparaginase 1 in E. coli, which could have the potential for large-scale fermentation. Further research can explore using other host cells, optimizing the fermentation process, and examining the effect of other variables to increase production.

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Source
http://dx.doi.org/10.1007/s12223-024-01163-2DOI Listing

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