Systems-level characterization and reconstitution of genetic regulatory networks in Escherichia coli for rational strain optimization : towards improved bioprocesses

Abstract

Biological processes have demonstrated the potential to offer cost-effective and environment-friendly strategies for a wide range of applications such as food and chemical production, material synthesis, wastewater treatment, and environmental remediation. Despite this potential, biological processes frequently suffer from low productivity and stability stemming from the inadequate phenotypic characteristics of the cells involved. This limitation in biological processes has so far been tackled through various strain optimization strategies, which mostly require time-consuming, labor-intensive selection and screening methods. In this light, with recent advances in systems biology, which offers a holistic approach to understanding cells, the work presented in this thesis aimed to develop systems-level, rational strain engineering framework that could complement current optimization techniques. Towards this aim, cellular responses were elucidated at the systems level, and essential cellular functions and regulatory factors were characterized during the response of Escherichia coli to three important conditions in bioprocesses: (i) genetic disruption in quorum sensing, (ii) oxidative stress under anaerobic condition, and (iii) hydrocarbon solvent stress. Genetic regulatory networks underlying the respective responses were identified based on bioinformatics analysis of gene-transcription factor relationships, and these genetic networks were reconstituted to obtain desirable phenotypic characteristics of E. coli. In particular, it was shown that this strain-engineering framework, driven by re-wiring of regulatory components, significantly improved E. coli tolerance against oxidative stress and hydrocarbon stress. Taken together, this thesis demonstrates the potential of the systems-level cellular engineering framework developed in this work to design rational strain optimization strategies for improved bioprocesses, and to construct synthetic microbes that exhibit other desired phenotypic characteristics.