AWWA WQTC63992

For library-dependent bacterial source tracking (BST) methods, bacteria (e.g. E. coli) isolated fromwater samples are compared to reference libraries of genetic and phenotypic fingerprints of bacterial isolatesfrom known human and animal sources to identify the sources of fecal pollution. BST technology continues tobe developed and applied to new studies despite controversy over the usefulness of BST, especially the library-dependentmethods. This paper presents a recently completed E. coli BST project that included comparison of one phenotypicand three genetic library-dependent BST methods. E. coli isolates were characterized by automated ribotypingusing the Qualicon RiboPrinter, repetitive sequence polymerase chain reaction (ERIC-PCR), pulsed field gelelectrophoresis (PFGE) and Kirby-Bauer antibiotic resistance analysis (KB-ARA). These methods span thespectrum in their ability to resolve differences in related bacterial strains, training and labor required, and cost.Source samples were collected from municipal wastewater treatment plant influent/effluent and septage samples(collectively referred to as "domestic sewage"), livestock, wildlife, and pet fecal samples. In total, 2,275 E. coliisolated from 813 known source samples were screened using ERIC-PCR to exclude clonal (identical) isolatesand maximize diversity of the library. A total of 883 E. coli isolates from 745 different source samples wereselected for the library and analyzed by all four BST methods. Fingerprints of isolates were compared based onthe Pearson-product similarity coefficient with a "best match" approach to a single isolate at greater than or equal to 85% similarity forERIC-PCR, RiboPrinting and KB-ARA, and greater than or equal to 70% for PFGE. Data from the different BST methods were alsocombined in composite data sets, and a 70% similarity cutoff was used to allow for variation of the individualmethods. PFGE had the highest rate of correct classification (RCC) of any individual method in jackknifeanalysis of the library isolates, but could only identify 20% of the 555 E. coli isolated from 412 water samples.A four-method (ERIC-RP-PFGE-ARA) composite data set was found to have the next highest RCC valuesranging from 22% to 83% based on a seven-way split into domestic sewage, pet, cattle, other livestock, avian,non-avian, and wildlife sources. These RCCs were 3- to 7-foldhigher than random probability. Congruence measurements of individual methods and composite data setsrevealed that the ERIC-PCR and RiboPrinting (ERIC-RP) and ERIC-PCR and KB-ARA (ERIC-ARA)composite data sets were 90.7% and 87.2% similar, respectively, to the four-method composite data set.Further, these two-method composite data sets identified the same leading source of fecal pollution as the four-methodcomposite data set. In future studies, a "toolbox" approach using ERIC-RP or ERIC-ARA compositedata, along with library-dependent methods to aid with sampling design, may help provide cost, labor, and timesavings while not compromising the integrity of the BST results. Includes tables, figure.

Product Details

Edition:

Vol. - No.

Published:

11/01/2006

Number of Pages:

5

File Size:

1 file , 390 KB