The response surface method enables efficient optimization of induction parameters for the production of bioactive peptides in fed-batch bioreactors using Escherichia coli

Abstract

The production of recombinant peptides is critical in biotechnology and medicine for treating a variety of diseases. Thus, there is an urgent need for the development of quick, scalable, and cost-effective recombinant protein expression strategies. This study optimizes induction conditions for an insulin precursor, an analog GLP-1 precursor, and a peptide for COVID-19 therapy expression in E. coli using the response surface method. Factors such as pH, temperature, induction time, isopropyl-β-D-thiogalactopyranoside concentration, and optical density significantly influence peptide productivity. Experimental validation supports the effectiveness of these models in predicting peptide yields under optimal conditions. The optimal induction conditions were determined as follows: temperature at 37 °C, pH of the medium 7.0-8.0, induction at the early logarithmic phase of growth, isopropyl-β-D-thiogalactopyranoside concentration of 0.05 mM, and induction time of 6 h. After model validation, the productivity of each peptide producer exceeded 3 g/L. The optimal conditions achieved peptide titers significantly higher than those previously reported, suggesting that this technique is a versatile cultivation technology for the efficient production of different recombinant peptides. In conclusion, our research enhances the understanding of how tailored cultivation conditions can optimize recombinant peptide production efficiency.

Keywords: GLP- 1; Inclusion body; Insulin; Recombinant peptide; Response surface method; Soluble protein expression.