Abstract
Cyclospora cayetanensis is a protozoan parasite that causes foodborne and waterborne diarrheal illness outbreaks worldwide. Most of these outbreaks are associated with the consumption of fresh produce. Sensitive and specific methods to detect C. cayetanensis in agricultural water are needed to identify the parasite in agricultural water used to irrigate crops that have been implicated in outbreaks. In this study, a method to detect C. cayetanensis in water by combining dead-end ultrafiltration (DEUF) with sensitive and specific molecular detection was developed and evaluated. Triplicates of 10-liter agricultural water samples were seeded with 200, 100, 25, 12, and 6 C. cayetanensis oocysts. Surface water samples were also collected in the Mid-Atlantic region. All water samples were processed by DEUF and backflushed from the ultrafilters. DNA was extracted from concentrated samples and analyzed by quantitative PCR (qPCR) targeting the C. cayetanensis 18S rRNA gene. All water samples seeded with 12, 25, 100, and 200 oocysts were positive, and all unseeded samples were negative. Samples seeded with 6 oocysts had a detection rate of 66.6% (8/12). The method was also able to detect C. cayetanensis isolates in surface water samples from different locations of the Chesapeake and Ohio Canal (C&O Canal) in Maryland. This approach could consistently detect C. cayetanensis DNA in 10-liter agricultural water samples contaminated with low levels of oocysts, equivalent to the levels that may be found in naturally incurred environmental water sources. Our data demonstrate the robustness of the method as a useful tool to detect C. cayetanensis from environmental sources.IMPORTANCECyclospora cayetanensis is a protozoan parasite that causes foodborne and waterborne outbreaks of diarrheal illness worldwide. These foodborne outbreaks associated with the consumption of fresh produce and agricultural water could play a role in the contamination process. In this study, a method to detect C. cayetanensis in agricultural water by combining a robust filtration system with sensitive and specific molecular detection was developed and validated by the FDA. The results showed that this approach could consistently detect low levels of C. cayetanensis contamination in 10 liters of agricultural water, corresponding to the levels that may be found in naturally occurring environmental water sources. The method was also able to detect C. cayetanensis in surface water samples from a specific location in the Mid-Atlantic region. Our data demonstrate the robustness of the method to detect C. cayetanensis in agricultural water samples, which could be very useful to identify environmental sources of contamination.