Day and night for cyanobacteria: systems and synthetic biology approaches to understanding and engineering Synechocystis sp. PCC 6803 under day/night light cycles
| dc.contributor.author | Werner, Allison Jean Zimont, author | |
| dc.contributor.author | Peebles, Christie A. M., advisor | |
| dc.contributor.author | Reardon, Kenneth, committee member | |
| dc.contributor.author | Prasad, Ashok, committee member | |
| dc.contributor.author | Heuberger, Adam, committee member | |
| dc.date.accessioned | 2018-09-10T20:04:29Z | |
| dc.date.available | 2020-09-06T20:04:15Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Photosynthetic organisms—including plants, algae, and cyanobacteria—harness sunlight as an energy source to grow, utilizing atmospheric carbon dioxide in the process. This ability can be harnessed for the sustainable production of food, fuels, and chemicals, reducing demand for petrol-based products and overall greenhouse gas emissions. Photosynthetic success rests on the efficient and timely capture of sunlight. Natural day/night cycles subject these organisms to changing energy availability, presenting a fundamental question: How do phototrophs regulate metabolism to thrive under daily and dramatic changes in energy supply? This question has significant impact on the productivity of plants, algae, and cyanobacteria. Cyanobacteria have been extensively engineered for the production of biofuels, polymers, and valuable pigments under continuous-light (CL) laboratory conditions. However, industrial production requires outdoor cultivation under diurnal light/dark (LD) cycles, where yield improvements in engineered strains observed in CL are lost in LD cycles. The success of industrially-productive cyanobacteria biotechnology is limited by the lack of appropriate strain engineering tools and gap in knowledge of photosynthetic metabolism under daily day/night light cycles. The aim of this thesis is therefore to improve the feasibility of cyanobacteria biotechnology in industrially-relevant conditions by integrating aspects of diurnal LD cycles into genetic tools and by expanding the current knowledge of dynamic photosynthetic metabolism. The first part of this thesis presents novel genetic engineering tools which enable light-entrained gene expression under diurnal LD cycles. The tools developed here enable engineering of temporally controlled chemical production under diurnal LD cycles, which we hypothesize will improve yield in outdoor cultivation environments. The second part of this thesis presents time-course characterization of growth and metabolite abundance under realistic diurnal LD cycles. Previous work was limited to on/off patterns of low light and restricted to detecting few metabolites. To expand the realism of light profiles and metabolite scope, a photobioreactor was engineered to supply sinusoidal patterns and intensity of light (sinLD cycles), and a multi-platform mass spectrometry workflow was developed to enable semi-comprehensive metabolite detection. Cyanobacteria growth under realistic diurnal sinLD cycles is presented for the first time, to our knowledge. We observe a short lag phase at the onset of day, followed by cell mass increase during the early day, cell division during afternoon and evening, and slight mass loss overnight. Further, comprehensive metabolite abundance every 30-120 minutes across a 24-hour diurnal sinLD cycle is presented. Insoluble C6 carbohydrates displayed sharp oscillations at the day/night transition; insoluble C5 carbohydrates and glucosamine display these in addition to abundance 're-sets' at the night/day transition. Free amino acids and nucleic acids increase immediately upon transition to light during the lag phase, followed by gradual incorporation into protein during the mass accumulation phase. Metabolites involved in central metabolism did not oscillate to the same extent as other pathways. Accumulation of phosphoenolpyruvate but not pyruvate during the light phase suggests a potential bottleneck. Integration of the metabolomics data into genome-scale metabolic models to perform dynamic flux balance analysis could improve the method by which engineering targets are identified for production in outdoor conditions. Together, this thesis demonstrates the need for revision of the current approach to cyanobacteria strain engineering. More broadly, this work highlights the dynamic nature of photosynthetic metabolism and motivates future investigations into metabolic regulation and metabolic flux under realistic day/night cycles. | |
| dc.format.medium | born digital | |
| dc.format.medium | doctoral dissertations | |
| dc.identifier | Werner_colostate_0053A_14905.pdf | |
| dc.identifier.uri | https://hdl.handle.net/10217/191320 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | 2000-2019 | |
| dc.rights | Copyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright. | |
| dc.subject | diel cycles | |
| dc.subject | genetic engineering | |
| dc.subject | metabolism | |
| dc.subject | diurnal cycles | |
| dc.subject | cyanobacteria | |
| dc.subject | metabolic engineering | |
| dc.title | Day and night for cyanobacteria: systems and synthetic biology approaches to understanding and engineering Synechocystis sp. PCC 6803 under day/night light cycles | |
| dc.type | Text | |
| dcterms.embargo.expires | 2020-09-06 | |
| dcterms.embargo.terms | 2020-09-06 | |
| dcterms.rights.dpla | This Item is protected by copyright and/or related rights (https://rightsstatements.org/vocab/InC/1.0/). You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). | |
| thesis.degree.discipline | Cell and Molecular Biology | |
| thesis.degree.grantor | Colorado State University | |
| thesis.degree.level | Doctoral | |
| thesis.degree.name | Doctor of Philosophy (Ph.D.) |
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