title: The large-scale organization of the bacterial network of ecological co-occurrence interactions.
abstract: 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.
authors.affiliation: Blavatnik School of Computer Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel. shiri.freilich@gmail.com
authors.forename: Shiri
authors.initials: S
authors.lastname: Freilich
authors.forename: Anat
authors.initials: A
authors.lastname: Kreimer
authors.forename: Isacc
authors.initials: I
authors.lastname: Meilijson
authors.forename: Uri
authors.initials: U
authors.lastname: Gophna
authors.forename: Roded
authors.initials: R
authors.lastname: Sharan
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D001419:Bacteria / Q000254:growth & development / Q000378:metabolism; D018407:Bacterial Physiological Phenomena; D057225:Data Mining; D017753:Ecosystem; D004783:Environmental Microbiology; D056265:Microbial Interactions; D039781:PubMed