Cyanobacteria are important microbial cell factories that are widely used in the biotechnology filed nowadays. They can use light as the sole energy source to fix CO2, accumulate biomass, and produce various valuable bio-products. Engineered cyanobacterial species can uptake nutrients from wastes to further reduce the cost. Recently, it is reported that cyanobacteria will provide much higher carbon yield than heterotrophs by co-utilizing organic carbons and CO2. However, the quantitative information of such `photo-fermentation' process is still limited. Decoding the carbon metabolism of cyanobacteria during the photo-fermentation process can reveal the functional pathways, carbon distribution, and the energy requirement, all of which will provide guidelines for rational design of metabolic engineering strategies.
The emerging of multiple omics tools, e.g. genomics, transcriptomics, proteinomics, and metabolomics analysis, allowed the comprehensive determination of microbial metabolisms. This dissertation describes the development of 13C fingerprint-based method to characterize the carbon metabolic network in cyanobacteria model species Synechocystis sp. PCC 6803 and the integration of this method with metabolic flux analysis and transcriptomics analysis to quantify the diverse carbon and energy metabolism regulation under different internal or external stimuli. The project mainly consists of four aspects: (1) developing the GC-MS based low-cost 13C fingerprint method; (2) exploring the carbon metabolic network structure and quantifying the central carbon metabolism under different environmental conditions; (3) determining the energy requirement for cell maintenance in cyanobacteria; (4) investigating the effects of light conditions on cyanobacterial carbon metabolism. These new findings not only improve our understandings of the flexible carbon metabolism employed by cyanobacteria, but also offer evolutionary insight into photosynthesis and potential applications of photo-fermentation.
","abstract_html":"<p>Cyanobacteria are important microbial cell factories that are widely used in the biotechnology filed nowadays. They can use light as the sole energy source to fix CO2, accumulate biomass, and produce various valuable bio-products. Engineered cyanobacterial species can uptake nutrients from wastes to further reduce the cost. Recently, it is reported that cyanobacteria will provide much higher carbon yield than heterotrophs by co-utilizing organic carbons and CO2. However, the quantitative information of such `photo-fermentation' process is still limited. Decoding the carbon metabolism of cyanobacteria during the photo-fermentation process can reveal the functional pathways, carbon distribution, and the energy requirement, all of which will provide guidelines for rational design of metabolic engineering strategies.</p><p>The emerging of multiple omics tools, e.g. genomics, transcriptomics, proteinomics, and metabolomics analysis, allowed the comprehensive determination of microbial metabolisms. This dissertation describes the development of 13C fingerprint-based method to characterize the carbon metabolic network in cyanobacteria model species Synechocystis sp. PCC 6803 and the integration of this method with metabolic flux analysis and transcriptomics analysis to quantify the diverse carbon and energy metabolism regulation under different internal or external stimuli. The project mainly consists of four aspects: (1) developing the GC-MS based low-cost 13C fingerprint method; (2) exploring the carbon metabolic network structure and quantifying the central carbon metabolism under different environmental conditions; (3) determining the energy requirement for cell maintenance in cyanobacteria; (4) investigating the effects of light conditions on cyanobacterial carbon metabolism. These new findings not only improve our understandings of the flexible carbon metabolism employed by cyanobacteria, but also offer evolutionary insight into photosynthesis and potential applications of photo-fermentation.</p>","abstract_has_math":false,"creators":["You, Le"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Energy, Environmental & Chemical Engineering","degree_department":null,"school":null,"contributors":["Yinjie Tang","Robert Blankenship, Marcus Foston, Tae Seok Moon, Himadri Pakrasi, Fuzhong Zhang"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015-05-15T07:00:00Z","date_published":"2015-05-15T07:00:00Z","updated_at":"2026-07-24T06:13:55Z","subjects":["13C metabolic flux analysis","carbon metabolism","coculture","energy metabolism","transcriptomics","Engineering"],"languages":["English (en)"],"rights":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["https://openscholarship.wustl.edu/eng_etds/100"],"render_values":[{"text":"https://openscholarship.wustl.edu/eng_etds/100","href":"https://openscholarship.wustl.edu/eng_etds/100","code":true}]}]},"links":{"outbound_url":"https://doi.org/10.7936/K78C9TD7","outbound_label":"DOI","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Yinjie Tang","Robert Blankenship, Marcus Foston, Tae Seok Moon, Himadri Pakrasi, Fuzhong Zhang"]},{"key":"dc:creator","label":"Author","values":["You, Le"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2015-06-18T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Energy, Environmental & Chemical Engineering","McKelvey School of Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["13C metabolic flux analysis","carbon metabolism","coculture","energy metabolism","transcriptomics","Engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English (en)"]},{"key":"dc:rights","label":"Dc Rights","values":["I have not registered my thesis with the U.S. Copyright Office, and do not intend to."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://doi.org/10.7936/K78C9TD7","https://openscholarship.wustl.edu/eng_etds/100"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Permanent URL: https://doi.org/10.7936/K78C9TD7"]},{"key":"dc:description.abstract","label":"Abstract","values":["Cyanobacteria are important microbial cell factories that are widely used in the biotechnology filed nowadays. They can use light as the sole energy source to fix CO2, accumulate biomass, and produce various valuable bio-products. Engineered cyanobacterial species can uptake nutrients from wastes to further reduce the cost. Recently, it is reported that cyanobacteria will provide much higher carbon yield than heterotrophs by co-utilizing organic carbons and CO2. However, the quantitative information of such `photo-fermentation' process is still limited. Decoding the carbon metabolism of cyanobacteria during the photo-fermentation process can reveal the functional pathways, carbon distribution, and the energy requirement, all of which will provide guidelines for rational design of metabolic engineering strategies.
The emerging of multiple omics tools, e.g. genomics, transcriptomics, proteinomics, and metabolomics analysis, allowed the comprehensive determination of microbial metabolisms. This dissertation describes the development of 13C fingerprint-based method to characterize the carbon metabolic network in cyanobacteria model species Synechocystis sp. PCC 6803 and the integration of this method with metabolic flux analysis and transcriptomics analysis to quantify the diverse carbon and energy metabolism regulation under different internal or external stimuli. The project mainly consists of four aspects: (1) developing the GC-MS based low-cost 13C fingerprint method; (2) exploring the carbon metabolic network structure and quantifying the central carbon metabolism under different environmental conditions; (3) determining the energy requirement for cell maintenance in cyanobacteria; (4) investigating the effects of light conditions on cyanobacterial carbon metabolism. These new findings not only improve our understandings of the flexible carbon metabolism employed by cyanobacteria, but also offer evolutionary insight into photosynthesis and potential applications of photo-fermentation.
"]},{"key":"dc:title","label":"Title","values":["Development of 13C Fingerprint Tool and Its Application for Exploring Carbon and Energy Metabolism in Cyanobacterium Synechocystis sp. PCC 6803"]}]}],"canonical_facts":{"dc:contributor":["Yinjie Tang","Robert Blankenship, Marcus Foston, Tae Seok Moon, Himadri Pakrasi, Fuzhong Zhang"],"dc:creator":["You, Le"],"dc:date.available":["2015-06-18T07:00:00Z"],"dc:description":["Permanent URL: https://doi.org/10.7936/K78C9TD7"],"dc:description.abstract":["Cyanobacteria are important microbial cell factories that are widely used in the biotechnology filed nowadays. They can use light as the sole energy source to fix CO2, accumulate biomass, and produce various valuable bio-products. Engineered cyanobacterial species can uptake nutrients from wastes to further reduce the cost. Recently, it is reported that cyanobacteria will provide much higher carbon yield than heterotrophs by co-utilizing organic carbons and CO2. However, the quantitative information of such `photo-fermentation' process is still limited. Decoding the carbon metabolism of cyanobacteria during the photo-fermentation process can reveal the functional pathways, carbon distribution, and the energy requirement, all of which will provide guidelines for rational design of metabolic engineering strategies.
The emerging of multiple omics tools, e.g. genomics, transcriptomics, proteinomics, and metabolomics analysis, allowed the comprehensive determination of microbial metabolisms. This dissertation describes the development of 13C fingerprint-based method to characterize the carbon metabolic network in cyanobacteria model species Synechocystis sp. PCC 6803 and the integration of this method with metabolic flux analysis and transcriptomics analysis to quantify the diverse carbon and energy metabolism regulation under different internal or external stimuli. The project mainly consists of four aspects: (1) developing the GC-MS based low-cost 13C fingerprint method; (2) exploring the carbon metabolic network structure and quantifying the central carbon metabolism under different environmental conditions; (3) determining the energy requirement for cell maintenance in cyanobacteria; (4) investigating the effects of light conditions on cyanobacterial carbon metabolism. These new findings not only improve our understandings of the flexible carbon metabolism employed by cyanobacteria, but also offer evolutionary insight into photosynthesis and potential applications of photo-fermentation.
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