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A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.

ABSTRACT: A genome-scale metabolic network reconstruction of Salinibacter ruber DSM13855 is presented here. To our knowledge, this is the first metabolic model of an organism in the phylum Rhodothermaeota. This model, which will be called iMB631, was reconstructed based on genomic and biochemical data available on the strain Salinibacter ruber DSM13855. This network consists of 1459 reactions, 1363 metabolites and 631 genes. Model evaluation was performed based on existing biochemical data in the literature and also by performing laboratory experiments. For growth on different carbon sources, we show that iMB631 is able to correctly predict the growth in 91% of cases where growth has been observed experimentally and 83% of conditions in which S. ruber did not grow. The F-score was 93%, demonstrating a generally acceptable performance of the model. Based on the predicted flux distributions, we found that under certain autotrophic condition, a reductive tricarboxylic acid cycle (rTCA) has fluxes in all necessary reactions to support autotrophic growth. To include special metabolites of the bacterium, salinixanthin biosynthesis pathway was modeled based on the pathway proposed recently. For years, main glucose consumption pathway has been under debates in S. ruber. Using flux balance analysis, iMB631 predicts pentose phosphate pathway, rather than glycolysis, as the active glucose consumption method in the S. ruber.

SUBMITTER: Bagheri M

PROVIDER: S-EPMC6508672 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.

Bagheri Maryam M Marashi Sayed-Amir SA Amoozegar Mohammad Ali MA

PloS one 20190509 5

A genome-scale metabolic network reconstruction of Salinibacter ruber DSM13855 is presented here. To our knowledge, this is the first metabolic model of an organism in the phylum Rhodothermaeota. This model, which will be called iMB631, was reconstructed based on genomic and biochemical data available on the strain Salinibacter ruber DSM13855. This network consists of 1459 reactions, 1363 metabolites and 631 genes. Model evaluation was performed based on existing biochemical data in the literatu ...[more]

PMID: 31071110

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Project description:BackgroundThermus thermophilus, an extremely thermophilic bacterium, has been widely recognized as a model organism for studying how microbes can survive and adapt under high temperature environment. However, the thermotolerant mechanisms and cellular metabolism still remains mostly unravelled. Thus, it is highly required to consider systems biological approaches where T. thermophilus metabolic network model can be employed together with high throughput experimental data for elucidating its physiological characteristics under such harsh conditions.ResultsWe reconstructed a genome-scale metabolic model of T. thermophilus, iTT548, the first ever large-scale network of a thermophilic bacterium, accounting for 548 unique genes, 796 reactions and 635 unique metabolites. Our initial comparative analysis of the model with Escherichia coli has revealed several distinctive metabolic reactions, mainly in amino acid metabolism and carotenoid biosynthesis, producing relevant compounds to retain the cellular membrane for withstanding high temperature. Constraints-based flux analysis was, then, applied to simulate the metabolic state in glucose minimal and amino acid rich media. Remarkably, resulting growth predictions were highly consistent with the experimental observations. The subsequent comparative flux analysis under different environmental conditions highlighted that the cells consumed branched chain amino acids preferably and utilized them directly in the relevant anabolic pathways for the fatty acid synthesis. Finally, gene essentiality study was also conducted via single gene deletion analysis, to identify the conditional essential genes in glucose minimal and complex media.ConclusionsThe reconstructed genome-scale metabolic model elucidates the phenotypes of T. thermophilus, thus allowing us to gain valuable insights into its cellular metabolism through in silico simulations. The information obtained from such analysis would not only shed light on the understanding of physiology of thermophiles but also helps us to devise metabolic engineering strategies to develop T. thermophilus as a thermostable microbial cell factory.

Dataset Information

A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.

Publications

A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.

Similar Datasets

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