Identification of the sources of Escherichia coli in a watershed using carbon-utilization patterns and composite data sets

摘要: The field of bacterial source tracking (BST) has been rapidly evolving to meet the demands water pollution analysis, specifically contamination waterways and drinking reservoirs by point nonpoint pollution. goal current study was create a BST library based on carbon-utilization patterns (CUP) for predicting sources E. coli in watershed, compare this an antibiotic-resistance analysis (ARA) previously published same isolates, determine efficacy using composite dataset which combines data from both datasets into single unknown isolates. This accomplished generating CUP ARA-CUP isolates known fecal within watershed. These libraries were then used predict collected 13 sites watershed compared regard predictive accuracy. dominant South Bosque cattle as identified all three methods. 6-source had higher average rates correct classification (96.7%), specificity (99.2%), positive-predictive value (99.1%), negative-predictive (96.8%) than either ARA or 6 (ARCC 80.1% 86.7% respectively). is first two phenotypic methods, Antibiotic Resistance Analysis Carbon Utilization Profiling (CUP). also combine these methods "toolbox" type approach.