Competitive and cooperative metabolic interactions in bacterial communities

• Published in: Nature communications Vol. 2; no. 1; p. 589
• Main Authors: Freilich, Shiri, Zarecki, Raphy, Eilam, Omer, Segal, Ella Shtifman, Henry, Christopher S., Kupiec, Martin, Gophna, Uri, Sharan, Roded, Ruppin, Eytan
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 13-12-2011; Nature Publishing Group
• Subjects: 631/326/252/58; 631/326/2565/855; 631/326/41; Antibiosis - physiology; Bacteria - growth & development; Bacteria - metabolism; Biodegradation, Environmental; Computer Simulation; Ecology; Ecosystem; Humanities and Social Sciences; Microbial Consortia - physiology; Models, Biological; multidisciplinary; Science; Science (multidisciplinary); Symbiosis - physiology
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/ncomms1597

Revealing the ecological principles that shape communities is a major challenge of the post-genomic era. To date, a systematic approach for describing inter-species interactions has been lacking. Here we independently predict the competitive and cooperative potential between 6,903 bacterial pairs derived from a collection of 118 species' metabolic models. We chart an intricate association between competition and cooperation indicating that the cooperative potential is maximized at moderate levels of resource overlap. Utilizing ecological data from 2,801 samples, we explore the associations between bacterial interactions and coexistence patterns. The high level of competition observed between species with mutual-exclusive distribution patterns supports the role of competition in community assembly. Cooperative interactions are typically unidirectional with no obvious benefit to the giver. However, within their natural communities, bacteria typically form close cooperative loops resulting in indirect benefit to all species involved. These findings are important for the future design of consortia optimized towards bioremediation and bio-production applications.
Genome-scale metabolic models for bacterial species allow a systematic study of inter-species interactions. Here, competitive and cooperative potential is predicted between 6,903 pairs of species, to explore the role of these interactions in shaping coexistence patterns in natural communities.