Relationship and variation of qPCR and culturable Enterococci estimates in ambient surface waters are predictable

The quantitative polymerase chain reaction (qPCR) method provides rapid estimates of fecal indicator bacteria densities that have been indicated to be useful in the assessment of water quality. Primarily because this method provides faster results than standard culture-based methods, the U.S. Environmental Protection Agency is currently considering its use as a basis for revised ambient water quality criteria. In anticipation of this possibility, we sought to examine the relationship between qPCR-based and culture-based estimates of enterococci in surface waters. Using data from several research groups, we compared enterococci estimates by the two methods in water samples collected from 37 sites across the United States. A consistent linear pattern in the relationship between cell equivalents (CCE), based on the qPCR method, and colony-forming units (CFU), based on the traditional culturable method, was significant (P < 0.05) at most sites. A linearly decreasing variance of CCE with increasing CFU levels was significant (P < 0.05) or evident for all sites. Both marine and freshwater sites under continuous influence of point-source contamination tended to reveal a relatively constant proportion of CCE to CFU. The consistency in the mean and variance patterns of CCE versus CFU indicates that the relationship of results based on these two methods is more predictable at high CFU levels (e.g., log(10)CFU > 2.0/100 mL) while uncertainty increases at lower CFU values. It was further noted that the relative error in replicated qPCR estimates was generally higher than that in replicated culture counts even at relatively high target levels, suggesting a greater need for replicated analyses in the qPCR method to reduce relative error. Further studies evaluating the relationship between culture and qPCR should take into account analytical uncertainty as well as potential differences in results of these methods that may arise from sample variability, different sources of pollution, and environmental factors.