Author's School

School of Engineering & Applied Science

Author's Department/Program

Energy, Environmental and Chemical Engineering

Language

English (en)

Date of Award

1-1-2012

Degree Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Chair and Committee

Yinjie Tang

Abstract

Decoding microbial metabolism is of great importance in revealing the mechanisms governing the physiology of microbes and rewiring the cellular functions in metabolic engineering. Complementing the genomics, transcriptomics, proteinomics and metabolomics analysis of microbial metabolism, fluxomics tools can measure and simulate the in vivo enzymatic reactions as direct readouts of microbial metabolism. This dissertation develops and applies broad-scope tools in metabolic flux analysis to investigate metabolic insights of non-model environmental microorganisms. 13C-based pathway analysis has been applied to analyze specific carbon metabolic routes by tracing and analyzing isotopomer labeling patterns of different metabolites after growing cells with 13C-labeled substrates. Novel pathways, including Re-type citrate synthase in tricarboxylic acid cycle and citramalate pathways as an alternate route for isoleucine biosynthesis, have been identified in Thermoanaerobacter X514 and other environmental microorganisms. Via the same approach, the utilizations of diverse carbon/nitrogen substrates and productions of hydrogen during mixotrophic metabolism in Cyanothece 51142 have been characterized, and the medium for a slow-growing bacterium, Dehalococcoides ethenogenes 195, has been optimized. In addition, 13C-based metabolic flux analysis has been developed to quantitatively profile flux distributions in central metabolisms in a green sulfur bacterium, Chlorobaculum tepidum, and thermophilic ethanol-producing Thermoanaerobacter X514. The impact of isotope discrimination on 13C-based metabolic flux analysis has also been estimated. A constraint-based flux analysis approach was newly developed to integrate the bioprocess model into genome-scale flux balance analysis to decipher the dynamic metabolisms of Shewanella oneidensis MR-1. The sub-optimal metabolism and the time-dependent metabolic fluxes were profiled in a genome-scale metabolic network. A web-based platform was constructed for high-throughput metabolic model drafting to bridge the gap between fast-paced genome-sequencing and slow-paced metabolic model reconstruction. The platform provides over 1,000 sequenced genomes for model drafting and diverse customized tools for model reconstruction. The in silico simulation of flux distributions in both metabolic steady state and dynamic state can be achieved via flux balance analysis and dynamic flux balance analysis embedded in this platform. Cutting-edge fluxomics tools for functional characterization and metabolic prediction continue to be developed in the future. Broad-scope systems biology tools with integration of transcriptomics, proteinomics and fluxomics can reveal cell-wide regulations and speed up the metabolic engineering of non-model microorganisms for diverse bioenergy and environmental applications.

Comments

Permanent URL: http://dx.doi.org/10.7936/K7P55KKQ

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