TIDE Analysis of Cryptosporidium Infections by gp60 Typing Reveals Obscured Mixed Infections.


Journal

The Journal of infectious diseases
ISSN: 1537-6613
Titre abrégé: J Infect Dis
Pays: United States
ID NLM: 0413675

Informations de publication

Date de publication:
15 02 2022
Historique:
received: 22 05 2021
accepted: 18 08 2021
pubmed: 22 8 2021
medline: 10 5 2022
entrez: 21 8 2021
Statut: ppublish

Résumé

Cryptosporidiosis is a parasitic disease associated with potentially fatal diarrhea. The most used method in Cryptosporidium subtyping is based on the glycoprotein gene gp60. Each infection can represent a parasite population, and it is important to investigate the influence on transmission and virulence, as well as any impact on public health investigations. However, an easy-to-use method for detection is lacking. Here we report on the use of the bioinformatic program TIDE for deconvolution of gp60 chromatograms. A combination of single oocyst analysis and cloning successfully confirmed the within-sample parasite population diversity. Retrospective sample analysis was conducted on archived chromatograms. For Cryptosporidium parvum, 8.6% multistrain infections (13 of 152) obscured by currently used consensus base calling were detected. Importantly, we show that single oocysts can harbor a mixed population of sporozoites. We also identified a striking dominance of unappreciated polymerase stutter artefacts in all 218 chromatograms analyzed, challenging the uncritical use of gp60 typing. We demonstrate the value of a new, easy-to-use analytical procedure for critical characterization of C. parvum and Cryptosporidium hominis in epidemiological investigations, also applicable retrospectively. Our findings illuminate the hidden parasite diversity with important implications for tracing zoonotic and person-to-person transmissions.

Sections du résumé

BACKGROUND
Cryptosporidiosis is a parasitic disease associated with potentially fatal diarrhea. The most used method in Cryptosporidium subtyping is based on the glycoprotein gene gp60. Each infection can represent a parasite population, and it is important to investigate the influence on transmission and virulence, as well as any impact on public health investigations. However, an easy-to-use method for detection is lacking.
METHODS
Here we report on the use of the bioinformatic program TIDE for deconvolution of gp60 chromatograms. A combination of single oocyst analysis and cloning successfully confirmed the within-sample parasite population diversity. Retrospective sample analysis was conducted on archived chromatograms.
RESULTS
For Cryptosporidium parvum, 8.6% multistrain infections (13 of 152) obscured by currently used consensus base calling were detected. Importantly, we show that single oocysts can harbor a mixed population of sporozoites. We also identified a striking dominance of unappreciated polymerase stutter artefacts in all 218 chromatograms analyzed, challenging the uncritical use of gp60 typing.
CONCLUSIONS
We demonstrate the value of a new, easy-to-use analytical procedure for critical characterization of C. parvum and Cryptosporidium hominis in epidemiological investigations, also applicable retrospectively. Our findings illuminate the hidden parasite diversity with important implications for tracing zoonotic and person-to-person transmissions.

Identifiants

pubmed: 34417806
pii: 6356051
doi: 10.1093/infdis/jiab417
doi:

Substances chimiques

DNA, Protozoan 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

686-695

Informations de copyright

© The Author(s) 2021. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Auteurs

Ines Dettwiler (I)

Institute of Animal Pathology, University of Bern, Bern, Switzerland.

Karin Troell (K)

Department of Microbiology, National Veterinary Institute, Uppsala, Sweden.
Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden.

Guy Robinson (G)

Cryptosporidium Reference Unit, Public Health Wales Microbiology, Singleton Hospital, Swansea, United Kingdom.
Swansea University Medical School, Swansea, United Kingdom.

Rachel M Chalmers (RM)

Cryptosporidium Reference Unit, Public Health Wales Microbiology, Singleton Hospital, Swansea, United Kingdom.
Swansea University Medical School, Swansea, United Kingdom.

Walter Basso (W)

Institute of Parasitology, University of Bern, Bern, Switzerland.

Zaida Melina Rentería-Solís (ZM)

Institute for Parasitology, University of Leipzig, Leipzig, Germany.

Arwid Daugschies (A)

Institute for Parasitology, University of Leipzig, Leipzig, Germany.

Konrad Mühlethaler (K)

Institute for Infectious Diseases, University of Bern, Bern, Switzerland.

Mariko I Dale (MI)

Institute of Animal Pathology, University of Bern, Bern, Switzerland.

Jyothi Basapathi Raghavendra (J)

Institute of Animal Pathology, University of Bern, Bern, Switzerland.

Marie-Thérèse Ruf (MT)

Swiss Tropical and Public Health Institute, Basel, Switzerland.
University of Basel, Basel, Switzerland.

Sven Poppert (S)

Swiss Tropical and Public Health Institute, Basel, Switzerland.
University of Basel, Basel, Switzerland.

Mireille Meylan (M)

Clinic for Ruminants, University of Bern, Bern, Switzerland.

Philipp Olias (P)

Institute of Animal Pathology, University of Bern, Bern, Switzerland.

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Classifications MeSH