The bacterial composition of chlorinated drinking water was analyzed using 16S rRNA gene clone libraries derived from DNA extracts of 12 samples and compared to clone libraries previously generated using RNA extracts from the same samples. Phylogenetic analysis of 761 DNA-based clone sequences showed that unclassified bacteria were the most abundant group, representing nearly 62% of all DNA sequences analyzed. Other phylogenetic groups identified included Proteobacteria (20%), Actinobacteria (9%), Cyanobacteria (4%), and Bacteroidetes (2%). The composition of RNA-based libraries (1122 sequences) was similar to the DNA-based libraries with a few notable exceptions: Proteobacteria were more dominant in the RNA clone libraries (i.e., 35% RNA; 20% DNA). Differences in the Proteobacteria composition were also observed; alpha-Proteobacteria was 22 times more abundant in the RNA-based clones while beta-Proteobacteria was eight times more abundant in the DNA libraries. Nearly twice as many DNA operational taxonomic units (OTUs) than RNA OTUs were observed at distance 0.03 (101 DNA; 53 RNA). Twenty-four OTUs were shared between all RNA- and DNA-based libraries (OTU0.03) representing only 18% of the total OTUs, but 81% (1527/1883) of all sequences. Such differences between clone libraries demonstrate the necessity of generating both RNA- and DNA-derived clone libraries to compare these two different molecular approaches for community analyses.
Clone Library Water Distribution System Drinking Water System Dechloromonas Unclassified Bacterium
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The U.S. Environmental Protection Agency, through its Office of Research and Development, funded and managed the research described herein. It has been subjected to the Agency’s administrative review and has been approved for external publication. Any opinions expressed in this paper are those of the author(s) and do not necessarily reflect the views of the Agency, therefore, no official endorsement should be inferred. Any mention of trade names or commercial products does not constitute endorsement or recommendation for use. We acknowledge the assistance of Brandon Iker in developing clone libraries and for preliminary data analysis.
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