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The large-scale organization of the bacterial network of ecological co-occurrence interactions

In their natural environments, microorganisms form complex systems of interactions. Understating the structure and organization of bacterial communities is likely to have broad medical and ecological consequences, yet a comprehensive description of the network of environmental interactions is curren...

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Detalles Bibliográficos
Autores principales: Freilich, Shiri, Kreimer, Anat, Meilijson, Isacc, Gophna, Uri, Sharan, Roded, Ruppin, Eytan
Formato: Texto
Lenguaje:English
Publicado: Oxford University Press 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2896517/
https://www.ncbi.nlm.nih.gov/pubmed/20194113
http://dx.doi.org/10.1093/nar/gkq118
Descripción
Sumario:In their natural environments, microorganisms form complex systems of interactions. Understating the structure and organization of bacterial communities is likely to have broad medical and ecological consequences, yet a comprehensive description of the network of environmental interactions is currently lacking. Here, we mine co-occurrences in the scientific literature to construct such a network and demonstrate an expected pattern of association between the species’ lifestyle and the recorded number of co-occurring partners. We further focus on the well-annotated gut community and show that most co-occurrence interactions of typical gut bacteria occur within this community. The network is then clustered into species-groups that significantly correspond with natural occurring communities. The relationships between resource competition, metabolic yield and growth rate within the clusters correspond with the r/K selection theory. Overall, these results support the constructed clusters as a first approximation of a bacterial ecosystem model. This comprehensive collection of predicted communities forms a new data resource for further systematic characterization of the ecological design principals shaping communities. Here, we demonstrate its utility for predicting cooperation and inhibition within communities.