In silico metabolic modeling of Halomonas sp. HG01 to produce PHAs and biofuels

Descrição

The development of predictive metabolic models is a key strategy for understanding and optimizing microbial bioprocesses. In this study, we propose reconstructing a genome-scale metabolic model for Halomonas sp. HG01 (wild-type strain) to enable computational simulations of its metabolic capabilities. Using constraint-based approaches within the COBRA Toolbox framework, we will perform in silico growth simulations under different carbon sources, including glucose, xylose, and glycerol, to evaluate substrate utilization and metabolic flexibility. Furthermore, a heterologous pathway for xylose assimilation will be introduced into the reconstructed model to assess its impact on metabolic flux distribution and cellular growth. Key physiological parameters, such as specific growth rate (µ) and intracellular fluxes, will be estimated through flux balance analysis and related methods. To validate the model's predictive capability, simulation results will be systematically compared with experimental data from bioreactor cultivations of the wild-type strain (HG01) and the evolved strains (HG02 and HG03). This comparison will identify discrepancies between model predictions and experimental observations, highlighting potential gaps in metabolic reconstruction. Ultimately, this work aims to evaluate the robustness and predictive accuracy of the metabolic model, providing insights into its limitations and guiding future optimization strategies for metabolic engineering and biotechnological applications involving Halomonas species.