title: On the Origins and Control of Community Types in the Human Microbiome.
abstract: Microbiome-based stratification of healthy individuals into compositional categories, referred to as "enterotypes" or "community types", holds promise for drastically improving personalized medicine. Despite this potential, the existence of community types and the degree of their distinctness have been highly debated. Here we adopted a dynamic systems approach and found that heterogeneity in the interspecific interactions or the presence of strongly interacting species is sufficient to explain community types, independent of the topology of the underlying ecological network. By controlling the presence or absence of these strongly interacting species we can steer the microbial ecosystem to any desired community type. This open-loop control strategy still holds even when the community types are not distinct but appear as dense regions within a continuous gradient. This finding can be used to develop viable therapeutic strategies for shifting the microbial composition to a healthy configuration.
authors: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors: Travis E
authors: TE
authors: Gibson
authors: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors: Amir
authors: A
authors: Bashan
authors: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Department of Electrical Engineering, University of Southern California, Los Angeles, California, United States of America.|Chu Kochen Honors College, College of Electrical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
authors: Hong-Tai
authors: HT
authors: Cao
authors: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.
authors: Scott T
authors: ST
authors: Weiss
authors: Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, United States of America.|Center for Cancer Systems Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America.
authors: Yang-Yu
authors: YY
authors: Liu
mesh_terms: D000465:Algorithms; D016000:Cluster Analysis; D019295:Computational Biology; D006801:Humans; D064307:Microbiota; D008954:Models, Biological