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    Risk factors for the abundance of antimicrobial resistance genes aph(3′)-III, erm(B), sul2 and tet(W) in pig and broiler faeces in nine European countries

    Journal od Antimicrobial Chemotherapy

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    Data
    2021
    Autor
    Yang, Dongsheng
    Heederik, Dick J. J.
    Mevius, Dik J.
    Scherpenisse, Peter
    Luiken, Roosmarijn E. C.
    Van Gompel, Liese
    Skarżyńska, Magdalena
    Wadepohl, Katharina
    Chauvin, Claire
    Heijnsbergen van, Eri
    Wouters, Inge M.
    Greve, Gerdit D.
    Jongerius-Gortemaker, Betty G. M.
    Tersteeg-Zijderveld, Monique
    Zając, Magdalena
    Wasyl, Dariusz
    Juraschek, Katharina
    Fischer, Jennie
    Wagenaar, Jaap A.
    Smit, Lidwien A. M.
    Schmitt, Heike
    on behalf of the EFFORT consortium
    Metadane
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    Streszczenie
    Objectives: The occurrence and zoonotic potential of antimicrobial resistance (AMR) in pigs and broilers has been studied intensively in past decades. Here, we describe AMR levels of European pig and broiler farms and determine the potential risk factors. Methods: We collected faeces from 181 pig farms and 181 broiler farms in nine European countries. Real-time quantitative PCR (qPCR) was used to quantify the relative abundance of four antimicrobial resistance genes (ARGs) [aph(3′)-III, erm(B), sul2 and tet(W)] in these faeces samples. Information on antimicrobial use (AMU) and other farm characteristics was collected through a questionnaire. A mixed model using country and farm as random effects was performed to evaluate the relationship of AMR with AMU and other farm charac- teristics. The correlation between individual qPCR data and previously published pooled metagenomic data was evaluated. Variance component analysis was conducted to assess the variance contribution of all factors. Results: The highest abundance of ARG was for tet(W) in pig faeces and erm(B) in broiler faeces. In addition to the significant positive association between corresponding ARG and AMU levels, we also found on-farm biose- curity measures were associated with relative ARG abundance in both pigs and broilers. Between-country and between-farm variation can partially be explained by AMU. Different ARG targets may have different sample size requirements to represent the overall farm level precisely. Conclusions: qPCR is an efficient tool for targeted assessment of AMR in livestock-related samples. The AMR variation between samples was mainly contributed to by between-country, between-farm and within-farm dif- ferences, and then by on-farm AMU.
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    https://academic.oup.com/jac/advance-article/doi/10.1093/jac/dkac002/6513516?login=true
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