In vivo models of Escherichia coli infection in poultry.


Journal

Acta veterinaria Scandinavica
ISSN: 1751-0147
Titre abrégé: Acta Vet Scand
Pays: England
ID NLM: 0370400

Informations de publication

Date de publication:
02 Dec 2022
Historique:
received: 30 04 2022
accepted: 14 11 2022
entrez: 2 12 2022
pubmed: 3 12 2022
medline: 7 12 2022
Statut: epublish

Résumé

Escherichia coli represents a significant challenge to the poultry industry due to compromised animal welfare, vast productivity losses, elevated mortality, and increased use of antimicrobial compounds. Therefore, effective preventive strategies and insight into the pathogenesis and disease mechanisms of colibacillosis are essential to secure a healthy poultry production. Consequently, discriminative in vivo models of colibacillosis are prerequisite tools for evaluating e.g., preventive measures, exploring novel treatments and understanding disease development. Numerous models of colibacillosis are applied for experimental studies in poultry. Yet, few studies provide a proper characterisation of the model enabling other authors to reproduce experiments or use the model in general. The present paper provides a literature review on avian in vivo models of primary colibacillosis.

Identifiants

pubmed: 36461003
doi: 10.1186/s13028-022-00652-z
pii: 10.1186/s13028-022-00652-z
pmc: PMC9717535
doi:

Substances chimiques

Anti-Bacterial Agents 0

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

33

Informations de copyright

© 2022. The Author(s).

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Auteurs

Sofie Kromann (S)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Ridebanevej 3, 1870, Frederiksberg C, Denmark. sok@sund.ku.dk.
DanHatch Denmark A/S, Rugerivej 26, 9760, Vrå, Denmark. sok@sund.ku.dk.

Henrik Elvang Jensen (HE)

Department of Veterinary and Animal Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Ridebanevej 3, 1870, Frederiksberg C, Denmark.

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Classifications MeSH