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Developing SSU rDNA metagenomic profiles of aquatic microbial communities for environmental assessments.

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Vincent C. Henrich, Professor (Creator)
Parke A. Rublee, Professor (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/

Abstract: Five water samples from three sources, two municipal reservoirs in central North Carolina and Toolik Lake in Alaska, were processed to conduct a comparative survey of microbial small subunit rDNA sequences. Genomic DNA was extracted and amplified by PCR using universal SSU rDNA primers to generate 16S and 18S rDNA clone libraries and 50 clones from each library were sequenced and placed in operational taxonomic units (OTUs). Through this recovery and analysis of SSU rRNA genes, a metagenomic profile of the microbial community emerged for each environmental sample. Analyses of these profiles, including species diversity estimates and rank-abundance curves, revealed that approximately 64% of prokaryotic OTUs and 80% of eukaryotic OTUs were novel. Diversity estimates were consistent with predicted ecosystem characteristics: they were greater for the mesotrophic to eutrophic temperate lakes, than for the oligotrophic arctic lake. Sample comparisons showed that community similarity declined as geographic distance between sites increased. Real-time quantitative PCR results showed that OTUs which had been recovered from only one library were actually present in other samples, but at much lower frequencies, suggesting that many, if not most, microorganisms are cosmopolitan. Together, these results support the potential value of using the microbial community as an indicator of local environmental conditions. In other words, it may be realistic to monitor water quality using a single, comprehensive suite of microorganisms by analyzing patterns of relative abundance.

Additional Information

Publication
Ecological Indicators 8:442-453.
Language: English
Date: 2008
Keywords
Metagenomics, Water quality assessment, Microbial community