Food and Waterborne Parasitology (Jun 2022)

Validation of a multilocus genotyping scheme for subtyping Cryptosporidium parvum for epidemiological purposes

  • Guy Robinson,
  • Gregorio Pérez-Cordón,
  • Clare Hamilton,
  • Frank Katzer,
  • Lisa Connelly,
  • Claire L. Alexander,
  • Rachel M. Chalmers

Journal volume & issue
Vol. 27
p. e00151

Abstract

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Subtyping Cryptosporidium parvum for outbreak investigations or epidemiological surveillance usually relies on DNA sequence analysis of a gene coding for a 60 KDa glycoprotein (gp60). Although gp60 can be useful for allelic discrimination and to help investigate sources and routes of transmission, the presence of common subtypes and recombination during the parasite's sexual life-cycle demand a multilocus-based method for more discriminatory genotyping. While whole genome sequencing would provide the ultimate approach, it is a time consuming and expensive option for faecal parasites such as Cryptosporidium that occur at low density and are difficult to propagate routinely. In this study, we selected and evaluated a panel of previously identified variable-number tandem-repeat (VNTR) markers, to establish a multilocus genotyping scheme based on fragment sizing, appropriate for inter-laboratory surveillance and outbreak investigations. Seven VNTR markers were validated in vitro and demonstrated typeability of 0.85 and discriminatory power of 0.99. The discriminatory power was much greater than the currently used gp60 sequencing (0.74), which identified 26 subtypes, compared to 100 different MLVA profiles within the same sample set. The assay was robust, with repeatable results and reproducibility across three laboratories demonstrating the scheme was suitable for inter-laboratory comparison of C. parvum subtypes. As the majority of genotypes (79%) were unique among epidemiologically unrelated samples, there was efficiency to infer linkage, and epidemiological concordance was observed in historical outbreaks. We propose that the multilocus variable number of tandem repeats analysis scheme is suitable to assist outbreak investigations.

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