Predicting the metabolic capabilities of Synechococcus elongatus PCC 7942 adapted to different light regimes.
Constraint based modeling
Cyanobacteria engineering
Flux balance analysis
Genome-scale modeling
Photosynthesis
Synechococcus elongatus
Journal
Metabolic engineering
ISSN: 1096-7184
Titre abrégé: Metab Eng
Pays: Belgium
ID NLM: 9815657
Informations de publication
Date de publication:
03 2019
03 2019
Historique:
received:
14
08
2018
revised:
02
11
2018
accepted:
06
11
2018
pubmed:
16
11
2018
medline:
19
6
2019
entrez:
16
11
2018
Statut:
ppublish
Résumé
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.
Identifiants
pubmed: 30439494
pii: S1096-7176(18)30328-8
doi: 10.1016/j.ymben.2018.11.001
pmc: PMC6407710
mid: NIHMS1010568
pii:
doi:
Substances chimiques
Butylene Glycols
0
Chlorophyll
1406-65-1
2,3-butylene glycol
45427ZB5IJ
Oxygen
S88TT14065
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
42-56Subventions
Organisme : NIGMS NIH HHS
ID : R35 GM118290
Pays : United States
Informations de copyright
Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
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