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On the Origins and Control of Community Types in the Human Microbiome
- Source :
- PLoS Computational Biology, PLoS Computational Biology, Vol 12, Iss 2, p e1004688 (2016)
- Publication Year :
- 2015
-
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.<br />Author Summary We coexist with a vast number of microbes that live in and on our bodies, and play important roles in physiology and disease. Two interesting phenomena have been observed in the human microbiome. The first is the stratification of healthy individuals based on the relative abundances of their microbes, which holds promise for drastically improving personalized medicine. The second is the astounding success of fecal microbial transplantation in treating certain diseases related to disordered microbiomes. Surprisingly, both phenomena have not been analytically or quantitatively understood, despite a few early qualitative attempts. This work shows that through a dynamic systems and control theoretical approach the success of fecal microbial transplantation can be explained and that the microbiome-based stratification can be as simple as the existence of strongly interacting species.
- Subjects :
- 0301 basic medicine
Species Delimitation
Speciation
Pathogenesis
Pathology and Laboratory Medicine
Quantitative Biology - Quantitative Methods
Systems Science
Medicine and Health Sciences
Cluster Analysis
lcsh:QH301-705.5
Quantitative Methods (q-bio.QM)
Ecology
Directed Graphs
Microbiota
Human microbiome
Genomics
Dynamical Systems
3. Good health
Computational Theory and Mathematics
Community Ecology
Medical Microbiology
Modeling and Simulation
Host-Pathogen Interactions
Physical Sciences
Enterotype
Algorithms
Research Article
Computer and Information Sciences
Evolutionary Processes
Systems and Control (eess.SY)
Microbial Genomics
Biology
Models, Biological
Microbiology
Ecosystems
03 medical and health sciences
Cellular and Molecular Neuroscience
Microbial Ecosystems
Microbial ecology
FOS: Electrical engineering, electronic engineering, information engineering
Genetics
Humans
Ecosystem
Microbiome
Molecular Biology
Ecology, Evolution, Behavior and Systematics
Evolutionary Biology
Community
Ecology and Environmental Sciences
Computational Biology
Biology and Life Sciences
Ecological network
Species Interactions
030104 developmental biology
lcsh:Biology (General)
FOS: Biological sciences
Graph Theory
Computer Science - Systems and Control
Mathematics
Subjects
Details
- ISSN :
- 15537358
- Volume :
- 12
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- PLoS computational biology
- Accession number :
- edsair.doi.dedup.....f496c0362d459e47e1f45efded7195be