Volume 92, Issue 1
  • ISSN: 0002-9637
  • E-ISSN: 1476-1645



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) ( = 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 (R = 0.33, < 0.05), however qPCR had increased sensitivity. Upon comparison with diarrhea severity scores (from 0 to 3), a PCR-based count of ≥ 2.6 × 10 parasites or an immunofluorescence microscopy count of ≥ 4.5 × 10 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 can refine predictive power for diarrhea and appears useful for distinguishing clinical cryptosporidiosis versus subclinical infection.


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  1. Chalmers RM, Davies AP, , 2010. Minireview: clinical cryptosporidiosis. Exp Parasitol 124: 138146.[Crossref] [Google Scholar]
  2. Bern C, Martines J, de Zoysa I, Glass RI, , 1992. The magnitude of the global problem of diarrheal disease: a ten-year update. Bull World Health Organ 70: 705714. [Google Scholar]
  3. Kotloff KL, Nataro JP, Blackwelder WC, Nasrin D, Farag TH, Panchalingam S, Wu Y, Sow SO, Sur D, Breiman RF, Faruque AS, Zaidi AK, Saha D, Alonso PL, Tamboura B, Sanogo D, Onwuchekwa U, Manna B, Ramamurthy T, Kanungo S, Ochieng JB, Omore R, Oundo JO, Hossain A, Das SK, Ahmed S, Qureshi S, Quadri F, Adegbola RA, Antonio M, Hossain MJ, Akinsola A, Mandomando I, Nhampossa T, Acacio S, Biswas K, O'Reilly CE, Mintz ED, Berkeley LY, Muhsen K, Sommerfelt H, Robins-Browne RM, Levine MM, , 2013. Burden and aetiology of diarrheal disease in infants and young children in developing countries (the Global Enteric Multicenter Study, GEMS): a prospective, case-control study. Lancet 382: 209222.[Crossref] [Google Scholar]
  4. Chappell CL, Okhuysen PC, Langer-Curry R, Widmer G, Akiyoshi DE, Tanriverdi S, Tzipori S, , 2006. Cryptosporidium hominis: experimental challenge of healthy adults. Am J Trop Med Hyg 75: 851857. [Google Scholar]
  5. Zambriski JA, Nydam DV, Wilcox ZJ, Bowman DD, Mohammed HO, Liotta JL, , 2013. Cryptosporidium parvum: determination of ID(5)(0) and the dose-response relationship in experimentally challenged dairy calves. Vet Parasitol 197: 104112.[Crossref] [Google Scholar]
  6. Goodgame RW, Kimball K, Ou CN, White AC, Jr Genta RM, Lifschitz CH, Chappell CL, , 1995. Intestinal function and injury in acquired immunodeficiency syndrome-related cryptosporidiosis. Gastroenterology 108: 10751082.[Crossref] [Google Scholar]
  7. Haque R, Mondal D, Karim A, Molla IH, Rahim A, Faruque AS, Ahmad N, Kirkpatrick BD, Houpt E, Snider C, Petri WA, Jr, 2009. Prospective case-control study of the association between common enteric protozoal parasites and diarrhea in Bangladesh. Clin Infect Dis 48: 11911197.[Crossref] [Google Scholar]
  8. Chalmers RM, Katzer F, , 2013. Looking for Cryptosporidium: the application of advances in detection and diagnosis. Trends Parasitol 29: 237251.[Crossref] [Google Scholar]
  9. Liu J, Gratz J, Amour C, Kibiki G, Becker S, Janaki L, Verweij JJ, Taniuchi M, Sobuz SU, Haque R, Haverstick DM, Houpt ER, , 2013. A laboratory-developed TaqMan Array Card for simultaneous detection of 19 enteropathogens. J Clin Microbiol 51: 472480.[Crossref] [Google Scholar]
  10. Taniuchi M, Verweij JJ, Noor Z, Sobuz SU, Lieshout L, Petri WA, Jr Haque R, Houpt ER, , 2011. High throughput multiplex PCR and probe-based detection with Luminex beads for seven intestinal parasites. Am J Trop Med Hyg 84: 332337.[Crossref] [Google Scholar]
  11. Jenkins MB, Anguish LJ, Bowman DD, Walker MJ, Ghiorse WC, , 1997. Assessment of a dye permeability assay for determination of inactivation rates of Cryptosporidium parvum oocysts. Appl Environ Microbiol 63: 38443850. [Google Scholar]
  12. Jiang J, Alderisio KA, Xiao L, , 2005. Distribution of Cryptosporidium genotypes in storm event water samples from three watersheds in New York. Appl Environ Microbiol 71: 44464454.[Crossref] [Google Scholar]
  13. Anguish LJ, Ghiorse WC, , 1997. Computer-assisted laser scanning and video microscopy for analysis of Cryptosporidium parvum oocysts in soil, sediment, and feces. Appl Environ Microbiol 63: 724733. [Google Scholar]
  14. Campbell AT, Robertson LJ, Smith HV, , 1992. Viability of Cryptosporidium parvum oocysts: correlation of in vitro excystation with inclusion or exclusion of fluorogenic vital dyes. Appl Environ Microbiol 58: 34883493. [Google Scholar]
  15. Ollivett TL, Nydam DV, Linden TC, Bowman DD, Van Amburgh ME, , 2012. Effect of nutritional plane on health and performance in dairy calves after experimental infection with Cryptosporidium parvum . J Am Vet Med Assoc 241: 15141520.[Crossref] [Google Scholar]
  16. Bellosa ML, Nydam DV, Liotta JL, Zambriski JA, Linden TC, Bowman DD, , 2011. A comparison of fecal percent dry matter and number of Cryptosporidium parvum oocysts shed to observational fecal consistency scoring in dairy calves. J Parasitol 97: 349351.[Crossref] [Google Scholar]
  17. Xiao L, Herd RP, , 1993. Quantitation of Giardia cysts and Cryptosporidium oocysts in fecal samples by direct immunofluorescence assay. J Clin Microbiol 31: 29442946. [Google Scholar]
  18. Burton AJ, Nydam DV, Jones G, Zambriski JA, Linden TC, Cox G, Davis R, Brown A, Bowman DD, , 2011. Antibody responses following administration of a Cryptosporidium parvum rCP15/60 vaccine to pregnant cattle. Vet Parasitol 175: 178181.[Crossref] [Google Scholar]
  19. Stroup SE, Roy S, McHele J, Maro V, Ntabaguzi S, Siddique A, Kang G, Guerrant RL, Kirkpatrick BD, Fayer R, Herbein J, Ward H, Haque R, Houpt ER, , 2006. Real-time PCR detection and speciation of Cryptosporidium infection using Scorpion probes. J Med Microbiol 55: 12171222.[Crossref] [Google Scholar]
  20. De Waele V, Berzano M, Berkvens D, Speybroeck N, Lowery C, Mulcahy GM, Murphy TM, , 2011. Age-stratified Bayesian analysis to estimate sensitivity and specificity of four diagnostic tests for detection of Cryptosporidium oocysts in neonatal calves. J Clin Microbiol 49: 7684.[Crossref] [Google Scholar]
  21. Geurden T, Berkvens D, Geldhof P, Vercruysse J, Claerebout E, , 2006. A Bayesian approach for the evaluation of six diagnostic assays and the estimation of Cryptosporidium prevalence in dairy calves. Vet Res 37: 671682.[Crossref] [Google Scholar]
  22. Amar CF, East CL, Gray J, Iturriza-Gomara M, Maclure EA, McLauchlin J, , 2007. Detection by PCR of eight groups of enteric pathogens in 4,627 fecal samples: re-examination of the English case-control Infectious Intestinal Disease Study (1993–1996). Eur J Clin Microbiol Infect Dis 26: 311323.[Crossref] [Google Scholar]
  23. Taniuchi M, Sobuz SU, Begum S, Platts-Mills JA, Liu J, Yang Z, Wang XQ, Petri WA, Jr Haque R, Houpt ER, , 2013. Etiology of diarrhea in Bangladeshi infants in the first year of life analyzed using molecular methods. J Infect Dis 208: 17941802.[Crossref] [Google Scholar]

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  • Received : 05 Aug 2014
  • Accepted : 17 Sep 2014
  • Published online : 07 Jan 2015

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