High resolution melting-curve (HRM) analysis for the diagnosis of cryptosporidiosis in humans.

Cryptosporidiosis of humans is an intestinal disease caused predominantly by infection with Cryptosporidium hominis or C. parvum. This disease is transmitted mainly via the faecal-oral route (water or food) and has major socioeconomic impact globally. The diagnosis and genetic characterization of the main species and population variants (also called "genotypes" and "subgenotypes") of Cryptosporidium infecting humans is central to the prevention, surveillance and control of cryptosporidiosis, particularly as there is presently no cost effective anti-cryptosporidial chemotherapeutic regimen or vaccine available. In the present study, we established a polymerase chain reaction (PCR)-coupled high resolution melting-curve (HRM) analysis method, utilizing the second internal transcribed spacer (ITS-2) of nuclear ribosomal DNA as the genetic marker, for the diagnosis of Cryptosporidium hominis, C. parvum or C. meleagridis infection. An evaluation of the method revealed intra- and inter-assay variabilities of <1.5 and 3.5%, respectively. Cryptosporidium hominis, C. parvum and C. meleagridis were detected in 97, 44 and 2, respectively, of the 143 Cryptosporidium oocyst DNA samples originating from Australians with clinical cryptosporidiosis. The melting profiles characterized by peaks of 72.47+/-0.33 degrees C and 74.19+/-0.45 degrees C (profile 1), 72.17+/-0.32 degrees C (profile 2) and 73.33+/-0.03 degrees C (profile 3) genetically identified as C. hominis, C. parvum and C. meleagridis, respectively. In conclusion, PCR-coupled melting analysis of ITS-2 achieved the diagnosis of Cryptosporidium hominis, C. parvum or C. meleagridis infection. This approach is well suited for the rapid screening of large numbers of Cryptosporidium oocyst DNA samples and, although qualitative, is significantly less time-consuming to carry out than electrophoretic analysis and has the added advantage of data storage and analysis capabilities in silico. This method provides a useful tool for investigating the epidemiology and outbreaks of cryptosporidiosis, and could be applicable to species of Cryptosporidium other than those investigated herein.