Antimicrobial resistance monitoring in the Danish swine production by phenotypic methods and metagenomics from 1999 to 2018

• Published in: Euro surveillance : bulletin européen sur les maladies transmissibles 2023-05, Vol.28 (20), p.2
• Main Authors: Duarte, Ana Sofia R, Marques, Ana Rita, Andersen, Vibe D, Korsgaard, Helle B, Mordhorst, Hanne, Møller, Frederik D, Petersen, Thomas N, Vigre, Håkan, Hald, Tine, Aarestrup, Frank M
• Format: Article
• Language: English
• Subjects: Animals; Anti-Bacterial Agents - pharmacology; Anti-Bacterial Agents - therapeutic use; Anti-Infective Agents; Antimicrobial agents; Bacteria; Bacteria - genetics; Denmark; Drug resistance; Drug Resistance, Bacterial - genetics; E coli; Escherichia coli - genetics; Female; Genomics; Macrolides; Metagenomics; Protein Synthesis Inhibitors; Surveillance; Swine
• ISSN: 1560-7917; 1025-496X; 1560-7917
• DOI: 10.2807/1560-7917.ES.2023.28.20.2200678

BackgroundIn Denmark, antimicrobial resistance (AMR) in pigs has been monitored since 1995 by phenotypic approaches using the same indicator bacteria. Emerging methodologies, such as metagenomics, may allow novel surveillance ways.AimThis study aimed to assess the relevance of indicator bacteria ( and ) for AMR surveillance in pigs, and the utility of metagenomics.MethodsWe collated existing data on AMR and antimicrobial use (AMU) from the Danish surveillance programme and performed metagenomics sequencing on caecal samples that had been collected/stored through the programme during 1999-2004 and 2015-2018. We compared phenotypic and metagenomics results regarding AMR, and the correlation of both with AMU.ResultsVia the relative abundance of AMR genes, metagenomics allowed to rank these genes as well as the AMRs they contributed to, by their level of occurrence. Across the two study periods, resistance to aminoglycosides, macrolides, tetracycline, and beta-lactams appeared prominent, while resistance to fosfomycin and quinolones appeared low. In 2015-2018 sulfonamide resistance shifted from a low occurrence category to an intermediate one. Resistance to glycopeptides consistently decreased during the entire study period. Outcomes of both phenotypic and metagenomics approaches appeared to positively correlate with AMU. Metagenomics further allowed to identify multiple time-lagged correlations between AMU and AMR, the most evident being that increased macrolide use in sow/piglets or fatteners led to increased macrolide resistance with a lag of 3-6 months.ConclusionWe validated the long-term usefulness of indicator bacteria and showed that metagenomics is a promising approach for AMR surveillance.