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PLoS One. 2010 Sep 23;5(9):e12919. doi: 10.1371/journal.pone.0012919.

Functional biogeography as evidence of gene transfer in hypersaline microbial communities.

Author information

1
Center for Integrated BioSystems, Utah State University, Logan, Utah, United States of America. jacob.parnell@usu.edu

Abstract

BACKGROUND:

Horizontal gene transfer (HGT) plays a major role in speciation and evolution of bacteria and archaea by controlling gene distribution within an environment. However, information that links HGT to a natural community using relevant population-genetics parameters and spatial considerations is scarce. The Great Salt Lake (Utah, USA) provides an excellent model for studying HGT in the context of biogeography because it is a contiguous system with dispersal limitations due to a strong selective salinity gradient. We hypothesize that in spite of the barrier to phylogenetic dispersal, functional characteristics--in the form of HGT--expand beyond phylogenetic limitations due to selective pressure.

METHODOLOGY AND RESULTS:

To assay the functional genes and microorganisms throughout the GSL, we used a 16S rRNA oligonucleotide microarray (Phylochip) and a functional gene array (GeoChip) to measure biogeographic patterns of nine microbial communities. We found a significant difference in biogeography based on microarray analyses when comparing Sørensen similarity values for presence/absence of function and phylogeny (Student's t-test; p = 0.005).

CONCLUSION AND SIGNIFICANCE:

Biogeographic patterns exhibit behavior associated with horizontal gene transfer in that informational genes (16S rRNA) have a lower similarity than functional genes, and functional similarity is positively correlated with lake-wide selective pressure. Specifically, high concentrations of chromium throughout GSL correspond to an average similarity of chromium resistance genes that is 22% higher than taxonomic similarity. This suggests active HGT may be measured at the population level in microbial communities and these biogeographic patterns may serve as a model to study bacteria adaptation and speciation.

PMID:
20957119
PMCID:
PMC2950788
DOI:
10.1371/journal.pone.0012919
[Indexed for MEDLINE]
Free PMC Article

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