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J Clin Microbiol. 2017 Mar;55(3):844-858. doi: 10.1128/JCM.01798-16. Epub 2016 Dec 21.

Genomic Variation in IbA10G2 and Other Patient-Derived Cryptosporidium hominis Subtypes.

Author information

1
Laboratory Medicine Core Facility, Sahlgrenska University Hospital, Gothenburg, Sweden.
2
Department of Microbiology, Public Health Agency of Sweden, Solna, Sweden.
3
Department of Microbiology, National Veterinary Institute, Uppsala, Sweden.
4
Division of Pharmacognosy, Department of Medicinal Chemistry, Uppsala University, Sweden.
5
Department of Microbiology, Public Health Agency of Sweden, Solna, Sweden romanico.arrighi@folkhalsomyndigheten.se.

Abstract

In order to improve genotyping and epidemiological analysis of Cryptosporidium spp., genomic data need to be generated directly from a broad range of clinical specimens. Utilizing a robust method that we developed for the purification and generation of amplified target DNA, we present its application for the successful isolation and whole-genome sequencing of 14 different Cryptosporidium hominis patient specimens. Six isolates of subtype IbA10G2 were analyzed together with a single representative each of 8 other subtypes: IaA20R3, IaA23R3, IbA9G3, IbA13G3, IdA14, IeA11G3T3, IfA12G1, and IkA18G1. Parasite burden was measured over a range of more than 2 orders of magnitude for all samples, while the genomes were sequenced to mean depths of between 17× and 490× coverage. Sequence homology-based functional annotation identified several genes of interest, including the gene encoding Cryptosporidium oocyst wall protein 9 (COWP9), which presented a predicted loss-of-function mutation in all the sequence subtypes, except for that seen with IbA10G2, which has a sequence identical to the Cryptosporidium parvum reference Iowa II sequence. Furthermore, phylogenetic analysis showed that all the IbA10G2 genomes form a monophyletic clade in the C. hominis tree as expected and yet display some heterogeneity within the IbA10G2 subtype. The current report validates the aforementioned method for isolating and sequencing Cryptosporidium directly from clinical stool samples. In addition, the analysis demonstrates the potential in mining data generated from sequencing multiple whole genomes of Cryptosporidium from human fecal samples, while alluding to the potential for a higher degree of genotyping within Cryptosporidium epidemiology.

KEYWORDS:

clinical parasitology; cryptosporidiosis; genome sequencing; immunomagnetic separation

PMID:
28003424
PMCID:
PMC5328452
DOI:
10.1128/JCM.01798-16
[Indexed for MEDLINE]
Free PMC Article

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