Aims: Carbon source utilization profiles as a phenotypic fingerprinting methodology for determining sources of faecal pollution in water were evaluated. Methods and Results: Three hundred and sixty-five Enterococcus isolates were collected from known faecal sources in four different geographical regions and were identified to species with the commercial Biolog system. Discriminant analysis (DA) was used to identify the substrate-containing wells that best classified the 365 isolates by source. By using 30 of the 95 wells for the analysis, the average rate of correct classification (ARCC) by source was 92AE7% for a human vs non-human two-way classification when isolates from all regions were combined into one library. Corresponding ARCCs for other classification schemes were 81AE9% for a four-way classification of human vs livestock vs wildlife vs domestic pets, and 85AE7% for a three-way classification without human isolates. When three individual libraries were made based on classification of sources within Enterococcus species, the ARCC was 95AE3% for the Ent. faecalis library, 95AE8% for the Ent. gallinarum library and 94AE7% for the Ent. mundtii library. Thirty Enterococcus isolates (unknown sources) were obtained from each of three stream sites where a specific source of pollution was apparent; 90AE0% of the isolates from a human-suspected source were classified as human, 86AE6% were classified as livestock from a livestock-suspected site, and 93AE3% were classified as wildlife from a wildlife-suspected site. Conclusions: Phenotypic fingerprinting with carbon source utilization profiles provided levels of correct classification by sources from an Enterococcus library that were in the upper range of those reported in the literature. ARCCs for three Enterococcus species-specific libraries were very high and may be the best approach for further developing this concept and methodology. Significance and Impact of the Study: The results, based on a modest Enterococcus library and a preliminary field validation test, demonstrated the potential for carbon source utilization profiles to be employed as a phenotypic method for determining sources of faecal pollution in water.

A new library-based microbial source tracking (MST) approach intended for initial application in the coastal waters of Virginia was evaluated. Host-origin isolates of Enterococcus spp. were collected from beaches and the surrounding tidewater region of Virginia and used to construct a library based on the pattern of DNA band lengths produced by the amplification of the 16S-23S rDNA intergenic spacer (IGS) region, and subsequent digestion with MboI. Initial results from small host-origin libraries (64 and 200 total isolates) with discriminant analysis (DA) and logistic regression (LR) yielded high average rates of correct classification (ARCC) for a four-source classification split (birds, dogs, sewage, and wildlife), with ARCCs ranging from 83 to 100%. However, the poor results obtained when classification was attempted on a non-library validation set (VS, ARCCs of 47 and 48%, respectively, using DA and LR) demonstrated that a library of 200 isolates was insufficient to adequately represent the diversity of the enterococci in the sampled region. An increase in the library size to 1029 total isolates was accompanied by a reduction in the ARCC of the library to 42.7% with DA and 45.7% with LR, plus similarly poor results obtained from the VS. The low correct classification rates generated by the larger known-source library were unsuitable for field application. Many reported MST methods have been based on results obtained using small host-origin libraries without external validation. Our results indicate that such an approach can be very misleading, and that larger libraries and external validation is essential for the confirmation of preliminary results.

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