ArticlePloS one2019
A genome-scale metabolic network reconstruction of extremely halophilic bacterium Salinibacter ruber.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Metagenomic insights into the taxonomic and metabolic diversity of the microbiome of Lake Karum in the Danakil Depression, Ethiopia.Environmental microbiome · 2026Article
- Exploring Microbiological Dynamics in a Salt Cavern for Potential Hydrogen Storage Use.Environmental microbiology reports · 2025Article
- Unraveling the metabolic landscape of Exophiala spinifera strain FM: Model reconstruction, insights into biodesulfurization and beyond.PloS one · 2025Article
- Elucidating metabolic pathways through genomic analysis in highly heavy metal-resistantHeliyon · 2024Article
- Genome-scale metabolic modelling of extremophiles and its applications in astrobiological environments.Environmental microbiology reports · 2024Review
- Metabolic Potential of Microbial Communities in the Hypersaline Sediments of the Bonneville Salt Flats.mSystems · 2022Article
- A systems level approach to study metabolic networks in prokaryotes with the aromatic amino acid biosynthesis pathway.Frontiers in genetics · 2022Article
- Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways.Frontiers in molecular biosciences · 2021Review
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3 authors.
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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.
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