Discriminant analysis of fecal bacterial species composition for use as a phenotypic microbial source tracking method.

摘要

A rapidly growing method to identify origins of nonpoint source (NPS) pollution is microbial source tracking (MST). Current MST research utilizes either an organism's genetic or physiological traits to establish source identification. To determine if an MST method based on fecal bacterial species composition can be used to determine sources of NPS pollution, samples from known NPS contributors (human, cattle, poultry, and swine) were collected and analyzed for fecal coliform (FC) and fecal streptococci (FS). Five colonies from each bacterial type were randomly selected, isolated and identified using phenotypic profiles. The species composition was calculated from these data and analyzed statistically via discriminant analysis. The rates of correct classification (RCC) for FC species composition patterns were 64, 71, 47 and 70% for cattle, human, poultry and swine, respectively. The RCC for FS species composition patterns were 87, 86, 74, and 83% for cattle, human, poultry, and swine, respectively. The average rate of correct classification for samples from all known sources was significantly higher (P=0.05) for FS species composition data (82%) than for FC (63%). The average rate of correct classification was increased when the FC and FS species composition data was combined (93%). The results from this study indicate that a phenotypic MST methodology based on species composition of dominant fecal bacteria may be useful in determining major contributors to NPS pollution. Based on the average rates of correct classification, the use of FS species composition patterns appears to be more useful in identifying source than the use of FC patterns.