DOI: 10.6084/m9.figshare.31389634
title: High extracellular expression of glucose isomerase from <i>Streptomyces murinus</i> in <i>E. coli</i> via OsmY signal peptide System; an integrated experimental and molecular dynamics analysis

description: Glucose isomerase (GI) is a key enzyme for the industrial conversion of glucose to fructose. A recombinant Escherichia coli strain expressing the GI gene from <i>Streptomyces murinus</i> was engineered, integrating protein design, expression optimization, and structural validation. SDS-PAGE confirmed secretion of the ~43 kDa enzyme, maximized under lactose induction. The OsmY signal peptide enabled efficient extracellular targeting, while an Asp-rich N-terminal extension improved thermostability, increasing T50 from 70 °C to 72 °C. Molecular dynamics revealed reduced loop fluctuations and enhanced electrostatics, supporting stability without loss of activity. Response Surface Methodology produced a predictive cubic model (R² = 0.99), identifying temperature, induction time, carbon and nitrogen sources as key factors. Maximum activity (18.79 U/mL) was achieved at 37 °C, pH 8, glucose, and NH4Cl. Industrial recommendations yielded 5–7 U/mL with improved stability. This integrated approach provides a robust, scalable strategy for thermostable GI production suited to cost-sensitive fructose manufacturing.   Heterologous expression of the <i>Streptomyces murinus</i> GI gene in <i>E. coli</i> with OsmY signal peptide enabled efficient secretion and minimized intracellular retention.Targeted N-terminal engineering with an Asp-rich extension increased the enzyme’s thermal half-life (T<sub>5</sub><sub>0</sub>) from 70°C to 72°C.Molecular dynamics simulations revealed reduced loop flexibility (ΔRMSF ≈0.6 Å), a stable core, and enhanced surface electrostatic potential, collectively improving thermostability without loss of catalytic activity.Response Surface Methodology (RSM) optimization produced a highly predictive cubic model (R<sup>2</sup> = 0.9969), identifying temperature, induction time, carbon source, and nitrogen source as key determinants of activity.Maximum experimental activity (18.79 U/mL) was achieved under 37°C, pH 8, 0 h induction, glucose, and NH<sub>4</sub>Cl.Model-based industrial recommendations (30–32°C, pH 7.2–7.5, 4–8 h induction, glucose, and KNO<sub>3</sub>) yielded 5–7 U/mL with improved process stability.Storage stability tests confirmed sustained activity over one week.Regression analysis showed no significant correlation between OD<sub>6</sub><sub>00</sub> and activity (R<sup>2</sup> = 0.041), indicating biomass is not a reliable predictor of yield.The integrated strategy of protein design, expression optimization, and statistical modeling provides a robust, scalable approach for thermostable GI production in cost-sensitive fructose manufacturing. Heterologous expression of the <i>Streptomyces murinus</i> GI gene in <i>E. coli</i> with OsmY signal peptide enabled efficient secretion and minimized intracellular retention. Targeted N-terminal engineering with an Asp-rich extension increased the enzyme’s thermal half-life (T<sub>5</sub><sub>0</sub>) from 70°C to 72°C. Molecular dynamics simulations revealed reduced loop flexibility (ΔRMSF ≈0.6 Å), a stable core, and enhanced surface electrostatic potential, collectively improving thermostability without loss of catalytic activity. Response Surface Methodology (RSM) optimization produced a highly predictive cubic model (R<sup>2</sup> = 0.9969), identifying temperature, induction time, carbon source, and nitrogen source as key determinants of activity. Maximum experimental activity (18.79 U/mL) was achieved under 37°C, pH 8, 0 h induction, glucose, and NH<sub>4</sub>Cl. Model-based industrial recommendations (30–32°C, pH 7.2–7.5, 4–8 h induction, glucose, and KNO<sub>3</sub>) yielded 5–7 U/mL with improved process stability. Storage stability tests confirmed sustained activity over one week. Regression analysis showed no significant correlation between OD<sub>6</sub><sub>00</sub> and activity (R<sup>2</sup> = 0.041), indicating biomass is not a reliable predictor of yield. The integrated strategy of protein design, expression optimization, and statistical modeling provides a robust, scalable approach for thermostable GI production in cost-sensitive fructose manufacturing.