Predicting the Metabolic Capabilities of Synechococcus Elongatus PCC 7942 Adapted to Different Light Regimes
Research Article Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes Jared T. Broddricka,b, David G. Welkiea, Denis Jalletc,1, Susan S. Goldena, Graham Peersc, and Bernhard O. Palssonb,† aDivision of Biological Sciences, University of California, San Diego, La Jolla, CA, USA, bDepartment of Bioengineering, University of California, San Diego, La Jolla, CA, USA, cDepartment of Biology, Colorado State University, Fort Collins, CO, USA ABSTRACT KEYWORDS There is great interest in engineering photoautotrophic metabolism to generate bioproducts of societal cyanobacteria, importance. Despite the success in employing genome-scale modeling coupled with flux balance analysis photosynthesis, to engineer heterotrophic metabolism, the lack of proper constraints necessary to generate biologically Synechococcus realistic predictions has hindered broad application of this methodology to phototrophic metabolism. Here elongatus, flux we describe a methodology for constraining genome-scale models of photoautotrophy in the cyanobacteria balance analy- Synechococcus elongatus PCC 7942. Experimental photophysiology parameters coupled to genome-scale sis, constraint flux balance analysis resulted in accurate predictions of growth rates and metabolic reaction fluxes at low and based modeling, high light conditions. Additionally, by constraining photon uptake fluxes, we characterize the metabolic cost of genome scale excess excitation energy. The predicted energy fluxes are consistent with known light-adapted phenotypes in modeling cyanobacteria. Finally, we leverage 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.
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