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Microbial Communities as Experimental Units
Author(s) -
Mitch D. Day,
Daniel Beck,
James A. Foster
Publication year - 2011
Publication title -
bioscience
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 2.761
H-Index - 209
eISSN - 1525-3244
pISSN - 0006-3568
DOI - 10.1525/bio.2011.61.5.9
Subject(s) - metagenomics , selection (genetic algorithm) , microbial population biology , ecology , microbial ecology , ecosystem , biology , field (mathematics) , perspective (graphical) , computer science , artificial intelligence , mathematics , biochemistry , genetics , gene , bacteria , pure mathematics
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.

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