ArticleMicrobiologyOpen2016
Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.
Article in MicrobiologyOpen, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Modeling the emergent metabolic potential of soil microbiomes in Atacama landscapes.Environmental microbiome · 2025Article
- A comparative whole-genome approach identifies bacterial traits for marine microbial interactions.Communications biology · 2022Article
- Article
- Co-occurrence Interaction Networks of Extremophile Species Living in a Copper Mining Tailing.Frontiers in microbiology · 2021Article
- Probabilistic Modeling of Microbial Metabolic Networks for Integrating Partial Quantitative Knowledge Within the Nitrogen Cycle.Frontiers in microbiology · 2018Article
- Gene Expression Analysis ofFrontiers in microbiology · 2017Article
- Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation.Frontiers in microbiology · 2017Article
- A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.PloS one · 2017Article
- Putative bacterial interactions from metagenomic knowledge with an integrative systems ecology approach.MicrobiologyOpen · 2016Article
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Authors and funding
8 authors.
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Abstract
Following the trend of studies that investigate microbial ecosystems using different metagenomic techniques, we propose a new integrative systems ecology approach that aims to decipher functional roles within a consortium through the integration of genomic and metabolic knowledge at genome scale. For the sake of application, using public genomes of five bacterial strains involved in copper bioleaching: Acidiphilium cryptum, Acidithiobacillus ferrooxidans, Acidithiobacillus thiooxidans, Leptospirillum ferriphilum, and Sulfobacillus thermosulfidooxidans, we first reconstructed a global metabolic network. Next, using a parsimony assumption, we deciphered sets of genes, called Sets from Genome Segments (SGS), that (1) are close on their respective genomes, (2) take an active part in metabolic pathways and (3) whose associated metabolic reactions are also closely connected within metabolic networks. Overall, this SGS paradigm depicts genomic functional units that emphasize respective roles of bacterial strains to catalyze metabolic pathways and environmental processes. Our analysis suggested that only few functional metabolic genes are horizontally transferred within the consortium and that no single bacterial strain can accomplish by itself the whole copper bioleaching. The use of SGS pinpoints a functional compartmentalization among the investigated species and exhibits putative bacterial interactions necessary for promoting these pathways.
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