| Fecal contamination of surface water and antimicrobial resistance both present public health and environmental concerns. The purpose of this project was to determine the prevalence of resistant E. coli in feces from a variety of species in the Red Cedar watershed and to use discriminant analysis of antibiotic resistance profiles of E. coli to identify sources of fecal contamination in the Red Cedar River (Michigan). We hypothesized that there would be differences in antimicrobial resistance of fecal E. coli from different species, and that discriminant analysis would be able to separate and classify known-source isolates with greater accuracy than would be expected by chance. E. coli was cultured from septic tank and sewage samples, livestock, pets, free ranging wildlife, and river water samples, and one isolate per sample was subjected to microdilution susceptibility testing for 16 antimicrobial agents. The overall percentage of resistant isolates was greatest in livestock, followed by human (septic and sewage), companion animal, river, and wildlife samples. Significant differences among species groups were found for 10 out of 16 antimicrobials for resistant versus susceptible categories and 14 out of 16 antimicrobials for minimum inhibitory concentrations (MIC). The best four-group discriminant analysis model had an average rate of correct classification (ARCC) of 46%. Using this model, 52.3% of river isolates were classified as wildlife, 17.9% as pets, 16.4% as humans, and 13.5% as livestock, and positive predictive values were 41% for classification as human, 71% for livestock, 37% for pet, and 43% for wildlife. This study indicates that discriminant analysis of MIC values may be a cost effective aid to identifying major sources of fecal contamination. |
