Hepatitis E Virus: Animal Models and Zoonosis.


Journal

Annual review of animal biosciences
ISSN: 2165-8110
Titre abrégé: Annu Rev Anim Biosci
Pays: United States
ID NLM: 101614024

Informations de publication

Date de publication:
15 02 2019
Historique:
pubmed: 5 10 2018
medline: 9 4 2020
entrez: 5 10 2018
Statut: ppublish

Résumé

Hepatitis E virus (HEV) is an important human pathogen that historically has been difficult to study. Limited levels of replication in vitro hindered our understanding of the viral life cycle. Sporadic and low-level virus shedding, lack of standardized detection methods, and subclinical infections made the development of animal models difficult. Better diagnostic techniques and understanding of the virus increased our ability to identify and characterize animal strains and animals that are amenable to model human-relevant infection. These advances are translating into the development of useful HEV animal models so that some of the greatest concerns associated with HEV infection, including host immunology, chronic infection, severe pregnancy mortality, and extrahepatic manifestations, can now be studied. Continued development of these animal models will be instrumental in understanding the many complex questions associated with HEV infection and for assessing therapeutics and prevention strategies to minimize HEV becoming a greater risk to the human population.

Identifiants

pubmed: 30285462
doi: 10.1146/annurev-animal-020518-115117
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

427-448

Subventions

Organisme : NIAID NIH HHS
ID : R01 AI074667
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI050611
Pays : United States

Auteurs

Scott P Kenney (SP)

Food Animal Health Research Program, College of Veterinary Medicine, Ohio State University, Wooster, Ohio 44691, USA; email: kenney.157@osu.edu.

Xiang-Jin Meng (XJ)

Virginia-Maryland College of Veterinary Medicine, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24060, USA; email: xjmeng@vt.edu.

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Classifications MeSH