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Correlation Between Diarrhea Severity and Oocyst Count via Quantitative PCR or Fluorescence Microscopy in Experimental Cryptosporidiosis in Calves

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  • Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, Virginia; Department of Population Medicine and Diagnostic Science, College of Veterinary Medicine, Cornell University, Ithaca, New York

Cryptosporidium is an important diarrhea-associated pathogen, however the correlation between parasite burden and diarrhea severity remains unclear. We studied this relationship in 10 experimentally infected calves using immunofluorescence microscopy and real-time polymerase chain reaction (qPCR) (N = 124 fecal samples). The qPCR data were corrected for extraction/amplification efficiency and gene copy number to generate parasite counts. The qPCR and microscopic oocyst quantities exhibited significant correlation (R2 = 0.33, P < 0.05), however qPCR had increased sensitivity. Upon comparison with diarrhea severity scores (from 0 to 3), a PCR-based count of ≥ 2.6 × 105 parasites or an immunofluorescence microscopy count of ≥ 4.5 × 104 oocysts were discriminatory predictors of moderate-to-severe diarrhea (versus no-to-mild diarrhea), with accuracies and predictive values of 72–82%. In summary, a quantitative approach for Cryptosporidium can refine predictive power for diarrhea and appears useful for distinguishing clinical cryptosporidiosis versus subclinical infection.

Author Notes

* Address correspondence to Darwin J. Operario, Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, P.O. Box 801340, 345 Crispell Drive, Charlottesville, VA 22908. E-mail: do2s@eservices.virginia.edu

Authors' addresses: Darwin J. Operario and Eric R. Houpt, Division of Infectious Diseases and International Health, Department of Medicine, University of Virginia, Charlottesville, VA, E-mails: do2s@virginia.edu and erh6k@virginia.edu. Lauren S. Bristol, Janice Liotta, and Daryl V. Nydam, Department of Population Medicine and Diagnostic Science, College of Veterinary Medicine, Cornell University, Ithaca, NY, E-mails: lls92@cornell.edu, jll55@cornell.edu, and dvn2@cornell.edu.

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