Dataset Information

Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942.

ABSTRACT: The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

SUBMITTER: Triana J

PROVIDER: S-EPMC4192687 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942.

Triana Julián J Montagud Arnau A Siurana Maria M Fuente David D Urchueguía Arantxa A Gamermann Daniel D Torres Javier J Tena Jose J de Córdoba Pedro Fernández PF Urchueguía Javier F JF

Metabolites 20140820 3

The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus ...[more]

PMID: 25141288

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Project description:Poor wound healing affects millions of people worldwide each year and needs better therapeutic strategies. Synechococcus elongatus PCC 7942 is a naturally occurring photoautotrophic cyanobacterium that can be easily obtained and large-scale expanded. Here, we investigated the therapeutic efficacy of this cyanobacterium in a mouse model of acute burn injury and whether the secretion of extracellular vesicles (EVs), important mediators of cell paracrine activity, is a key mechanism of the cyanobacterium-induced regulation of wound healing. Methods: The effects of Synechococcus elongatus PCC 7942 on burn wound healing in mice under light or dark conditions were evaluated by measuring wound closure rates, histological and immunofluorescence analyses. A series of assays in vivo and in vitro were conducted to assess the impact of the cyanobacterium on angiogenesis. GW4869 was used to interfere with the secretion of EVs by the cyanobacterium and the abilities of the GW4869-pretreated and untreated Synechococcus elongatus PCC 7942 to regulate endothelial angiogenesis were compared. The direct effects of the cyanobacterium-derived EVs (S. elongatus-EVs) on angiogenesis, wound healing and expressions of a class of pro-inflammatory factors that have regulatory roles in wound healing were also examined. Results: Synechococcus elongatus PCC 7942 treatment under light and dark conditions both significantly promoted angiogenesis and burn wound repair in mice. In vitro, the cyanobacterium enhanced angiogenic activities of endothelial cells, but the effects were markedly blocked by GW4869 pretreatment. S. elongatus-EVs were capable of augmenting endothelial angiogenesis in vitro, and stimulating new blood vessel formation and burn wound healing in mice. The expression of interleukin 6 (IL-6), which has an essential role in angiogenesis during skin wound repair, was induced in wound tissues and wound healing-related cells by S. elongatus-EVs and Synechococcus elongatus PCC 7942. Conclusion: Synechococcus elongatus PCC 7942 has the potential as a promising strategy for therapeutic angiogenesis and wound healing primarily by the delivery of functional EVs, not by its photosynthetic activity. The promotion of IL-6 expression may be a mechanism of the cyanobacterium and its EVs-induced pro-angiogenic and -wound healing effects.

Project description:Cyanobacteria are prokaryotic organisms that capture energy from sunlight using oxygenic photosynthesis and transform CO2 into products of interest such as fatty acids. Synechococcus elongatus PCC 7942 is a model cyanobacterium efficiently engineered to accumulate high levels of omega-3 fatty acids. However, its exploitation as a microbial cell factory requires a better knowledge of its metabolism, which can be approached by using systems biology tools. To fulfill this objective, we worked out an updated, more comprehensive, and functional genome-scale model of this freshwater cyanobacterium, which was termed iMS837. The model includes 837 genes, 887 reactions, and 801 metabolites. When compared with previous models of S. elongatus PCC 7942, iMS837 is more complete in key physiological and biotechnologically relevant metabolic hubs, such as fatty acid biosynthesis, oxidative phosphorylation, photosynthesis, and transport, among others. iMS837 shows high accuracy when predicting growth performance and gene essentiality. The validated model was further used as a test-bed for the assessment of suitable metabolic engineering strategies, yielding superior production of non-native omega-3 fatty acids such as α-linolenic acid (ALA). As previously reported, the computational analysis demonstrated that fabF overexpression is a feasible metabolic target to increase ALA production, whereas deletion and overexpression of fabH cannot be used for this purpose. Flux scanning based on enforced objective flux, a strain-design algorithm, allowed us to identify not only previously known gene overexpression targets that improve fatty acid synthesis, such as Acetyl-CoA carboxylase and β-ketoacyl-ACP synthase I, but also novel potential targets that might lead to higher ALA yields. Systematic sampling of the metabolic space contained in iMS837 identified a set of ten additional knockout metabolic targets that resulted in higher ALA productions. In silico simulations under photomixotrophic conditions with acetate or glucose as a carbon source boosted ALA production levels, indicating that photomixotrophic nutritional regimens could be potentially exploited in vivo to improve fatty acid production in cyanobacteria. Overall, we show that iMS837 is a powerful computational platform that proposes new metabolic engineering strategies to produce biotechnologically relevant compounds, using S. elongatus PCC 7942 as non-conventional microbial cell factory.

Dataset Information

Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942.

Publications

Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942.

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