Systems Tools for Metabolic Engineering of Parageobacillus thermoglucosidasius NCIMB 11955

: (Alternative Format Thesis)

Abstract

As global society transitions away from fossil fuels there is a need to produce chemical products from renewable precursors. Microbial fermentation is one method to achieve this aim which can be developed through metabolic engineering. Progressively, computational systems modelling and functional multi-omics analysis, are being applied to guide these metabolic engineering strategies. The research aimed to develop computational tools and acquire metabolic data to support this integrated system metabolic engineering approach for the thermophilic, facultative anaerobe P. thermoglucosidasius NCIMB 11955, a microbial chassis which offers the potential of being developed for sustainable bioconversion of renewable lignocellulosic waste to numerous products through its thermophilicity and catabolic versatility. This research built upon the foundation of an existing genome-scale metabolic model (GSMM) of P. thermoglucosidasius NCIMB 11955 such that it could perform genome-wide analysis of P. thermoglucosidasius metabolism. This predicted experimentally-supported results demonstrating that a combination of thiamine, biotin and iron(III) could support anaerobic growth of P. thermoglucosidasius and identified potentially oxygen-dependent biochemical pathways to critical metabolites for anaerobic growth. This research also generated fluxomic data of P. thermoglucosidasius metabolism through a dynamic feeding in vivo isotopic tracer approach, known as isotopically instationary 13C-Metabolic Flux Analysis (INST-13C-MFA). This research presents the first INST-13C-MFA data sets for a Parageobacillus species grown on glucose and xylose under aerobic and anaerobic conditions at a range of growth rates. A workflow for this analysis was established involving the evaluation of custom micro-bioreactors run as chemostats and a combined HPLC and GC-MS approach. However, statistically acceptable flux distributions models to represent this data remain a work in progress. Ultimately, with a more accurate, and ideally fluxomics-constrained, GSMM to act as a reference, existing strain design techniques could be used to develop P. thermoglucosidasius as microbial chassis for sustainable bioprocesses that could use waste lignocellulosic material as feedstocks.

Date of Award	22 Jun 2022
Original language	English
Awarding Institution	University of Bath
Supervisor	David Leak (Supervisor) & Tom Arnot (Supervisor)