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Review
. 2012 Jun 8;336(6086):1255-62.
doi: 10.1126/science.1224203. Epub 2012 Jun 6.

The application of ecological theory toward an understanding of the human microbiome

Elizabeth K Costello  1 , Keaton Stagaman, Les Dethlefsen, Brendan J M Bohannan, David A Relman
Affiliations
Review

The application of ecological theory toward an understanding of the human microbiome

Elizabeth K Costello et al. Science. .

Abstract

The human-microbial ecosystem plays a variety of important roles in human health and disease. Each person can be viewed as an island-like "patch" of habitat occupied by microbial assemblages formed by the fundamental processes of community ecology: dispersal, local diversification, environmental selection, and ecological drift. Community assembly theory, and metacommunity theory in particular, provides a framework for understanding the ecological dynamics of the human microbiome, such as compositional variability within and between hosts. We explore three core scenarios of human microbiome assembly: development in infants, representing assembly in previously unoccupied habitats; recovery from antibiotics, representing assembly after disturbance; and invasion by pathogens, representing assembly in the context of invasive species. Judicious application of ecological theory may lead to improved strategies for restoring and maintaining the microbiota and the crucial health-associated ecosystem services that it provides.

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Conflict of interest statement

There are no conflicts of interest.

Figures

Figure 1
Figure 1. Alternative community assembly scenarios could give rise to the compositional variations observed in the human microbiota
Each panel shows the assembly of local communities in different habitat types from a pool of available species. In A–C, each local community has access to all available colonists, but the order of invasion varies. In A, local species composition is determined primarily by environmental selection: regardless of invasion order, habitats with initially similar conditions select for similar assemblages. In B, the opposite is true: regardless of initial habitat conditions, historical contingencies (i.e., differences in the timing and order of species invasions) determine assemblage composition. In C, neither habitat nor history matter: local communities assemble via random draws from the species pool. In D, dispersal barriers result in local communities that assemble from different species pools. For each of the pools, local communities may assemble as in A, B, or C. The meaning of three different diversity measures is shown in Panel A: gamma diversity refers to the “regional” species pool, i.e., the total diversity of the local communities connected via dispersal; beta diversity refers to the differences between local communities (species turnover); and alpha diversity refers to the diversity within a local community. Although multiple scenarios are likely to apply to any real-world setting, one may dominate. For example, differences between body habitats may be best explained by environmental selection (A), differences between siblings for the same habitat may be best explained by historical contingency (B), differences between monozygotic twins prior to weaning highlight the role of stochasticity (C), and differences between infants born by Cesarean section versus vaginal delivery are likely to be explained by dispersal limitation. Adapted from Chase (14) and Fukami (15). NOTE TO ART EDITORS: In this figure, circles representing local communities could be changed to human forms (outlines).
Figure 2
Figure 2. Disturbance can be illustrated using a stability landscape schematic
The ball represents the community and the changing horizontal position of the ball represents the changing community state. The depth of a basin indicates the likelihood of a community remaining in that basin despite frequent “buffeting” by minor disturbance (50), and hence, the relative stability of the community state. Disturbance can alter (A) the community directly by changing its composition or activity, or (B) indirectly by changing the environmental parameters. In either case, the community can shift to an alternative state. In reality, continuous feedback between the community and its environment means that they change together. See Lemon et al. (accompanying STM manuscript) for applications to therapy. NOTE TO ART EDITORS: In this figure, the landscape line could be solid and the curves smoothed. The arrows in A could be curved to match landscape.
See this image and copyright information in PMC

References

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