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Modelling a Gas-fermenting Bacterium for Sustainable Chemical Production

出版	University of Auckland, 2016
URL	http://books.google.com.hk/books?id=pa6ptAEACAAJ&hl=&source=gbs_api

註釋We urgently need more sustainable fuel and chemical production. Gas fermentation is an emerging technology that could recycle significant amounts of waste carbon in the form of CO and CO2 into sustainable fuels and commodity chemicals. The aim of this thesis is to computationally model the metabolism of promising gas fermentation bacterium Clostridium autoethanogenum LZ1561 and use this model to design novel chemical production strains. I reconstructed the metabolism of C. autoethanogenum, building a metabolic knowledgebase of 1032 reactions, 1035 metabolites and 822 genes. I converted this knowledgebase into biologically plausible genome-scale models (GEMs) and selected a GEM and a novel lexicographic flux balance analysis objective function that predicted the metabolic state of experimental gas fermentation training data. I demonstrated that this model could accurately predict cell growth rates and the secretion of fermentation products by validating it against data from 123 distinct gas fermentations. I used this GEM to assess the ability of LZ1561 to produce twenty industrially relevant chemicals, demonstrating that LZ1561 is an appropriate microbial host for the production of a range of chemicals. I recommend seven chemicals that researchers should investigate. I then designed a new microbial strain predicted to make high yields of isopropanol, one of these recommended chemical targets. I assessed the feasibility of fifty heterologous pathways for isopropanol production and we tested the most promising pathways in the lab by transforming LZ1561 with expression plasmids containing isopropanol pathway genes. These strains produced low yields of isopropanol during continuous fermentation. I used an evolutionary algorithm to identify strain design strategies predicted to increase this yield from 5.9% to 85% of the maximum possible yield by directing metabolic flux towards isopropanol production. This thesis confirms that the autotrophic metabolism of C. autoethanogenum can be predicted using a GEM and that this organism is a suitable host for the sustainable production of a range of chemicals. Use of the knowledge from this thesis coupled with improvements to molecular biology tools for C. autoethanogenum promises to allow gas fermentation to become an effective sustainable chemical production technology.