In silico analyses for elucidation of Escherichia coli physiology and its metabolic engineering applications

Abstract

Escherichia coli is the most widely considered prokaryotic model organism, and frequently used as the most important production host in the field of biotechnology. For better understanding of bacterial physiology and enhanced production of bio-chemicals that are of industrial values, plenty of omics data have been generated in recent years. In particular, genomic information of various E. coli strains has enabled reconstruction of their genome-scale metabolic models, which have constantly been updated. These metabolic models are used to better understand physiological features of E. coli and provide novel insights for metabolic engineering. Accordingly, in this thesis, genome-scale metabolic models for E. coli B REL606 and W strains were newly reconstructed based on comparative genome analyses, and these models were utilized for various in silico analyses. First, biomass formation rate and production capacities of industrially important organic acids were predicted using the constructed models of E. coli K-12, B REL606, and W strains. Also, iron ion ($Fe^{2+}$) effects observed as the specific physiological features of W strain were identified through comparative genome analyses and experimental validation. Next, because metabolic cofactors, including NADH and NADPH, contribute to significant roles in metabolic flux distributions, E. coli K-12 model was used to elucidate the redox cofactor states under various environmental and genetic perturbed conditions. Also, strategy of cofactor manipulations was developed for the enhanced production of desired products in this study. Finally, using large transcriptomic data and information of protein-DNA regulatory interactions, a comprehensive transcriptional regulatory network was constructed and integrated with the metabolic network of E. coli K-12. Subsequently, transcriptional factors (TFs) were systematically targeted for various applications of metabolic engineering because TFs can (in)directly control gene expressions throughout the microbial system. In conclusions, these studies provide important insights to physiological features of E. coli strains, and are expected to contribute to the advances of microbiology and metabolic engineering.