rep-PCR and Penalized Discriminant Analysis to Distinguish Sources of Non-Point Fecal Contamination
Authors: Albert, John; Munakata-Marr, Junko; Siegrist, Robert; Tenorio, Luis
Source: Proceedings of the Water Environment Federation, WEFTEC 2002: Session 51 through Session 60 , pp. 653-668(16)
Publisher: Water Environment Federation
Abstract:Fecal contamination from non-point sources has become a widespread problem for many geographic areas across the US. This investigation focused on the characterizing potential sources of non-point fecal contamination in water within alpine watersheds. Summit County, an alpine region located in the Colorado Rocky Mountains, reported that 8.1% of all wells tested from July 1994 to July 2001were positive for coliform bacteria. After treatment, 25.4% of wells that initially tested positive again had positive tests results. This region of Colorado is subject to a number of fecal contaminant sources including wild and domesticated animals as well as human. In order to identify sources of fecal contamination, whole cell repetitive sequence PCR (rep-PCR) DNA fingerprinting of Escherichia coli was employed using the BOX A1R primer. The purpose of this study was to develop a genetic library of various strains of E.coli that could be used in conjunction with functional discriminant analysis to identify non-point fecal contamination with the help of. Fecal samples were collected from both domesticated and wild animals at four main locations within Summit County. Human samples were collected from volunteers and wastewater effluent at the Colorado School of Mines. Isolation of E.coli from raw samples relied on metabolism on the following media: mFC, MacConkey, Choragi, 1% tryptone, Simmons Citrate, Methyl Red, and EC-Mug. Only isolates that demonstrated positive results for E. coli on each medium were further processed. Whole cells from plate cultures were used in PCR reactions with the BOX A1R primer. Electrophoresis of PCR product on agarose gels produced specific fingerprinting patterns. Computer-aided gel analysis software generated a library of the fingerprint patterns produced by electrophoresis. Functional discriminant analysis was then used to assign fingerprint patterns to source groups.
Document Type: Research article
Publication date: 2002-01-01
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