title: Microbial Communities as Experimental Units.
abstract: Artificial ecosystem selection is an experimental technique that treats microbial communities as though they were discrete units by applying selection on community-level properties. Highly diverse microbial communities associated with humans and other organisms can have significant impacts on the health of the host. It is difficult to find correlations between microbial community composition and community-associated diseases, in part because it may be impossible to define a universal and robust species concept for microbes. Microbial communities are composed of potentially thousands of unique populations that evolved in intimate contact, so it is appropriate in many situations to view the community as the unit of analysis. This perspective is supported by recent discoveries using metagenomics and pangenomics. Artificial ecosystem selection experiments can be costly, but they bring the logical rigor of biological model systems to the emerging field of microbial community analysis.
authors: Mitch D. Day ( mday@uidaho.edu ) is a postdoctoral fellow, Daniel Beck is a doctoral student, and James A. Foster is a professor, all in the Department of Biological Sciences at the University of Idaho, in Moscow, Idaho. All are affiliated with the Initiative for Bioinformatics and Evolutionary Studies (IBEST), an interdisciplinary center devoted to developing a greater understanding of the patterns and processes of evolution and their relevance to biomedicine. All are also members of the National Science Foundation Science and Technology Center, BEACON, for the study of evolution in action.
authors: Mitch D
authors: MD
authors: Day
authors: Daniel
authors: D
authors: Beck
authors: James A
authors: JA
authors: Foster