Dataset Information

Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

ABSTRACT: There is great interest in engineering photoautotrophic metabolism to generate bioproducts of societal importance. Despite the success in employing genome-scale modeling coupled with flux balance analysis to engineer heterotrophic metabolism, the lack of proper constraints necessary to generate biologically realistic predictions has hindered broad application of this methodology to phototrophic metabolism. Here we describe a methodology for constraining genome-scale models of photoautotrophy in the cyanobacteria Synechococcus elongatus PCC 7942. Experimental photophysiology parameters coupled to genome-scale flux balance analysis resulted in accurate predictions of growth rates and metabolic reaction fluxes at low and high light conditions. Additionally, by constraining photon uptake fluxes, we characterized the metabolic cost of excess excitation energy. The predicted energy fluxes were consistent with known light-adapted phenotypes in cyanobacteria. Finally, we leveraged the modeling framework to characterize existing photoautotrophic and photomixtotrophic engineering strategies for 2,3-butanediol production in S. elongatus. This methodology, applicable to genome-scale modeling of all phototrophic microorganisms, can facilitate the use of flux balance analysis in the engineering of light-driven metabolism.

SUBMITTER: Broddrick JT

PROVIDER: S-EPMC6407710 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

Broddrick Jared T JT Welkie David G DG Jallet Denis D Golden Susan S SS Peers Graham G Palsson Bernhard O BO

Metabolic engineering 20181113

There is great interest in engineering photoautotrophic metabolism to generate bioproducts of societal importance. Despite the success in employing genome-scale modeling coupled with flux balance analysis to engineer heterotrophic metabolism, the lack of proper constraints necessary to generate biologically realistic predictions has hindered broad application of this methodology to phototrophic metabolism. Here we describe a methodology for constraining genome-scale models of photoautotrophy in ...[more]

PMID: 30439494

Similar Datasets

Project description:The direct conversion of carbon dioxide into biofuels by photosynthetic microorganisms is a promising alternative energy solution. In this study, a model cyanobacterium, Synechococcus elongatus PCC 7942, is engineered to produce free fatty acids (FFA), potential biodiesel precursors, via gene knockout of the FFA-recycling acyl-ACP synthetase and expression of a thioesterase for release of the FFA. Similar to previous efforts, the engineered strains produce and excrete FFA, but the yields are too low for large-scale production. While other efforts have applied additional metabolic engineering strategies in an attempt to boost FFA production, we focus on characterizing the engineered strains to identify the physiological effects that limit cell growth and FFA synthesis. The strains engineered for FFA-production show reduced photosynthetic yields, chlorophyll-a degradation, and changes in the cellular localization of the light-harvesting pigments, phycocyanin and allophycocyanin. Possible causes of these physiological effects are also identified. The addition of exogenous linolenic acid, a polyunsaturated FFA, to cultures of S. elongatus 7942 yielded a physiological response similar to that observed in the FFA-producing strains with only one notable difference. In addition, the lipid constituents of the cell and thylakoid membranes in the FFA-producing strains show changes in both the relative amounts of lipid components and the degree of saturation of the fatty acid side chains. These changes in lipid composition may affect membrane integrity and structure, the binding and diffusion of phycobilisomes, and the activity of membrane-bound enzymes including those involved in photosynthesis. Thus, the toxicity of unsaturated FFA and changes in membrane composition may be responsible for the physiological effects observed in FFA-producing S. elongatus 7942. These issues must be addressed to enable the high yields of FFA synthesis necessary for large-scale biofuel production.

Dataset Information

Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

Publications

Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets