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Potential Human Pathogenic Bacteria in a Mixed Urban Watershed as Revealed by Pyrosequencing

Author:
Ibekwe, A. Mark, Leddy, Menu, Murinda, Shelton E., Aziz, Ramy K.
ISSN:
1932-6203
Subject:
DNA, Firmicutes, Proteobacteria, agricultural runoff, animal pathogenic bacteria, concentrated animal feeding operations, databases, genetic markers, high-throughput nucleotide sequencing, humans, nucleotide sequences, pathogen identification, plate count, recreation, ribosomal RNA, risk assessment process, sediments, surface water, urban runoff, wastewater treatment, watersheds
Abstract:
Current microbial source tracking (MST) methods for water depend on testing for fecal indicator bacterial counts or specific marker gene sequences to identify fecal contamination where potential human pathogenic bacteria could be present. In this study, we applied 454 high-throughput pyrosequencing to identify bacterial pathogen DNA sequences, including those not traditionally monitored by MST and correlated their abundances to specific sources of contamination such as urban runoff and agricultural runoff from concentrated animal feeding operations (CAFOs), recreation park area, waste-water treatment plants, and natural sites with little or no human activities. Samples for pyrosequencing were surface water, and sediment collected from 19 sites. A total of 12,959 16S rRNA gene sequences with average length of ≤400 bp were obtained, and were assigned to corresponding taxonomic ranks using ribosomal database project (RDP), Classifier and Greengenes databases. The percent of total potential pathogens were highest in urban runoff water (7.94%), agricultural runoff sediment (6.52%), and Prado Park sediment (6.00%), respectively. Although the numbers of DNA sequence tags from pyrosequencing were very high for the natural site, corresponding percent potential pathogens were very low (3.78–4.08%). Most of the potential pathogenic bacterial sequences identified were from three major phyla, namely, Proteobacteria , Bacteroidetes , and Firmicutes . The use of deep sequencing may provide improved and faster methods for the identification of pathogen sources in most watersheds so that better risk assessment methods may be developed to enhance public health.
Agid:
1216311