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
Oglądaj/ Open
Data
2021Autor
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
Pokaż pełny rekordStreszczenie
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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