dc.contributor.author
Lührmann, Anja
dc.contributor.author
Palmini, Andrea
dc.contributor.author
Hellmich, Justinus
dc.contributor.author
Belik, Vitaly
dc.contributor.author
Zentek, Jürgen
dc.contributor.author
Vahjen, Wilfried
dc.date.accessioned
2023-11-06T06:44:09Z
dc.date.available
2023-11-06T06:44:09Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/41425
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-41147
dc.description.abstract
Reducing antibiotic use is one of the biggest challenges in pig farming, as antibiotics have been used for years to control typical problems such as newborn or post-weaning diarrhea. The pressure a one health approach has created on animal production regarding antimicrobial resistance is an opportunity to find other strategies against enterobacterial pathogens in suckling and weaned piglets. A farm-specific approach could have a good success due to the individual farm structures in Germany and other countries. In this study, non-metric multidimensional scaling, hierarchical clustering, and latent class analysis were used to determine the impact of antibiotic use on antibiotic resistance patterns and pathogen prevalence in 20 German pig farms. This may help to develop individualized health strategies. 802 fresh fecal samples were collected from sows and piglets from 20 piglet production and rearing farms at different production times (sows antepartum and postpartum, suckling piglets, weaned piglets). In addition, the use of antibiotics was recorded. DNA extracts were subjected to quantitative real-time qPCR with primers specific for antibiotic resistance genes (int1, sul1-3, dfrA1, mcr-1, blaCTX-M), and virulence factors of relevant bacteria (C. difficile, C. perfringens, Salmonella, Escherichia/Shigella/Hafnia, E. coli). Linear and logistic regression models were used to analyze the relationship between different antibiotics and the major genes contributing to the clustering of observations for the different animal groups. Clustering revealed different farm clusters for sows, suckling piglets, and weaned piglets, with the most remarkable diversity in antibiotic use among weaned piglets. Amoxicillin, lincomycin, and enrofloxacin were identified as the most probable cause of increased odds of the presence of relevant antibiotic resistance genes (mcr1, dfrA1, blaCTX-M). Still, direct effects of a specific antibiotic on its associated resistance gene were rare. Enrofloxacin and florfenicol favored the occurrence of C. difficile in sows. The E. coli fimbriae genes were less affected by antibiotic use in sows and piglets, but the F4 fimbriae gene could be associated with the integrase 1 gene in piglets. The results confirm that multidrug-resistant enterobacteria are widespread in German pig farms and give awareness of the impact of current antibiotic use while searching for alternative health strategies.
en
dc.format.extent
16 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Antibiotic resistance
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::630 Landwirtschaft::630 Landwirtschaft und verwandte Bereiche
dc.title
Antimicrobial resistance- and pathogen patterns in the fecal microbiota of sows and their offspring in German commercial pig farms
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e0290554
dcterms.bibliographicCitation.doi
10.1371/journal.pone.0290554
dcterms.bibliographicCitation.journaltitle
PLoS ONE
dcterms.bibliographicCitation.number
8
dcterms.bibliographicCitation.volume
18
dcterms.bibliographicCitation.url
https://doi.org/10.1371/journal.pone.0290554
refubium.affiliation
Veterinärmedizin
refubium.affiliation.other
Institut für Tierernährung
refubium.affiliation.other
Institut für Veterinär-Epidemiologie und Biometrie
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin finanziert
de
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1932-6203
refubium.resourceType.provider
WoS-Alert