Different Swine Production Systems Can Shape Slurry Resistome at Mechanism and Class Levels Based on Swine Manure Evaluation.
MinION nanopore device®
NGS—next-generation sequencing
One Health (OH)
Pigs (Sus domesticus)
animal husbandry
antimicrobial resistance (AMR)
metagenomics
swine manure (SM)
Journal
Frontiers in cellular and infection microbiology
ISSN: 2235-2988
Titre abrégé: Front Cell Infect Microbiol
Pays: Switzerland
ID NLM: 101585359
Informations de publication
Date de publication:
2022
2022
Historique:
received:
20
02
2022
accepted:
30
05
2022
entrez:
21
7
2022
pubmed:
22
7
2022
medline:
23
7
2022
Statut:
epublish
Résumé
Antimicrobial resistance is a major threat to public health. Antimicrobial use in animal husbandry is a major concern since it can favor an increase in antimicrobial resistance among farms. Herein, we aim to better understand and characterize the main resistome profiles in microbial communities found in pig farms. Sampling of swine manure was performed in two different timepoints (October 2019 and January 2020) in each of the 14 different swine farms, located in the mesoregion of Western Santa Catarina state in Brazil, a pole of swine product production of worldwide importance. Samples were divided into three groups: farms with the opened regimen and no usage of antimicrobials (F1; n = 10), farms with the closed regimen and usage of antimicrobials (F2; n = 16), and farms with the closed regimen and no usage of antimicrobials (F3; n = 2). The metagenomic evaluation was performed to obtain and identify genetic elements related to antimicrobial resistance using nanopore sequencing. We used ResistoXplorer software to perform composition, alpha and beta diversity, and clustering analysis. In addition, PCR reactions were performed to confirm the presence or absence of seven different beta-lactamase family genes and five phosphoethanolamine transferase gene variants clinically relevant. Our findings based on the identification of resistance genes at the mechanism level showed a prevalence of alteration of the drug target (72.3%) profile, followed by drug inactivation (17.5%) and drug efflux (10.1%). We identified predominantly aminoglycosides (45.3%), tetracyclines (15.9%), and multiclass (11,2%) resistance genes. PCoA analysis indicates differences between F1 and F2 profiles. F2 samples showed increased diversity when compared to the F1 group. In addition, herein we first report the identification of
Identifiants
pubmed: 35860383
doi: 10.3389/fcimb.2022.879656
pmc: PMC9289446
doi:
Substances chimiques
Anti-Bacterial Agents
0
Anti-Infective Agents
0
Manure
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
879656Informations de copyright
Copyright © 2022 Beltrame, Zamparette, Feltrin, da Cunha, Coltro, Athayde, Filho, Tápparo, Monteiro, Kich, Palmeiro, Wagner, Fongaro, Zárate-Bladés and Sincero.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest
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