Linking non-culturable (qPCR) and culturable enterococci densities with hydrometeorological conditions.
Quantitative polymerase chain reaction (qPCR) measurement of enterococci has been proposed as a rapid technique for assessment of beach water quality, but the response of qPCR results to environmental conditions has not been fully explored. Culture-based E. coli and enterococci have been used in empirical predictive models to characterize their responses to environmental conditions and to increase monitoring frequency and efficiency. This approach has been attempted with qPCR results only in few studies. During the summer of 2006, water samples were collected from two southern Lake Michigan beaches and the nearby river outfall (Burns Ditch) and were analyzed for enterococci by culture-based and non-culture-based (i.e., qPCR) methods, as well as culture-based E. coli. Culturable enterococci densities (log CFU/100ml) for the beaches were significantly correlated with enterococci qPCR cell equivalents (CE) (R=0.650, P<0.0001, N=32). Enterococci CE and CFU densities were highest in Burns Ditch relative to the beach sites; however, only CFUs were significantly higher (P<0.0001). Culturable enterococci densities at Burns Ditch and the beaches were significantly correlated (R=0.565, P<0.0001, N=32). Culturable E. coli and enterococci densities were significantly correlated (R=0.682, P<0.0001, N=32). Regression analyses suggested that enterococci CFU could be predicted by lake turbidity, Burns Ditch discharge, and wind direction (adjusted R(2)=0.608); enterococci CE was best predicted by Burns Ditch discharge and log-transformed lake turbidity x wave height (adjusted R(2)=0.40). In summary, our results show that analytically, the qPCR method compares well to the non-culture-based method for measuring enterococci densities in beach water and that both these approaches can be predicted by hydrometeorological conditions. Selected predictors and model results highlight the differences between the environmental responses of the two method endpoints and the potentially high variance in qPCR results.
Byappanahalli
Muruleedhara N
MN
United States Geological Survey, Great Lakes Science Center, Lake Michigan Ecological Research Station, 1100 N. Mineral Springs Road, Porter, IN 46304, USA. byappan@usgs.gov
Whitman
Richard L
RL
Shively
Dawn A
DA
Nevers
Meredith B
MB
D015169:Colony Count, Microbial; D016983:Enterococcus / Q000302:isolation & purification*; D055904:Meteorology; D016133:Polymerase Chain Reaction / Q000379:methods*