1. Antimicrobial resistance genes aph(3')-III, erm(B), sul2 and tet(W) abundance in animal faeces, meat, production environments and human faeces in Europe
- Author
-
Yang, Dongsheng, Heederik, Dick J.J., Scherpenisse, Peter, Van Gompel, Liese, Luiken, Roosmarijn E.C., Wadepohl, Katharina, Skarżyńska, Magdalena, Van Heijnsbergen, Eri, Wouters, Inge M., Greve, Gerdit D., Jongerius-Gortemaker, Betty G.M., Tersteeg-Zijderveld, Monique, Portengen, Lützen, Juraschek, Katharina, Fischer, Jennie, Zajac, Magdalena, Wasyl, Dariusz, Wagenaar, Jaap A., Mevius, Dik J., Smit, Lidwien A.M., Schmitt, Heike, Graveland, Haitske, Joosten, Philip, Sarrazin, Steven, Dewulf, Jeroen, Van Essen, Alieda, Gonzalez-Zorn, Bruno, Moyano, Gabriel, Sanders, Pascal, David, Julie, Soumet, Christophe, Battisti, Antonio, Caprioli, Andrea, Blaha, Thomas, Brandt, Maximiliane, Aarestrup, Frank, Hald, Tine, Duarte, Ana Sofia Ribeiro, Hoszowski, Andrzej, Pekala-Safinnska, Agnieszka, Pazdzior, Ewa, Daskalov, Hristo, Saatkamp, Helmut W., Stark, Katharina D.C., IRAS OH Epidemiology Microbial Agents, Faculteit Diergeneeskunde, dIRAS RA-I&I RA, dIRAS RA-I&I I&I, Klinische infectiologie en microb. lab., LS IRAS EEPI GRA (Gezh.risico-analyse), One Health Microbieel, IRAS OH Epidemiology Chemical Agents, dIRAS RA-2, and dI&I I&I-4
- Subjects
Microbiology (medical) ,Livestock ,Meat ,Drivers ,Swine ,Epidemiology ,Bioinformatica & Diermodellen ,GTB Gewasgez. Bodem en Water ,Bedrijfseconomie ,WASS ,Escherichia-coli ,Feces ,Crop health ,Anti-Infective Agents ,Business Economics ,RNA, Ribosomal, 16S ,Drug Resistance, Bacterial ,Bio-informatics & Animal models ,Mechanisms ,Animals ,Humans ,Life Science ,Epidemiology, Bio-informatics & Animal models ,Pharmacology (medical) ,Host Pathogen Interaction & Diagnostics ,Epidemiologie ,Pharmacology ,Carriage ,Ecology ,Bacteriologie ,Bacteriology ,Bacteriology, Host Pathogen Interaction & Diagnostics ,Chicken ,Host Pathogen Interactie & Diagnostiek ,Anti-Bacterial Agents ,Risk-factors ,Cross-Sectional Studies ,Infectious Diseases ,Genes, Bacterial ,Epidemiologie, Bioinformatica & Diermodellen ,Gewasgezondheid ,Bacteriologie, Host Pathogen Interactie & Diagnostiek ,Cattle ,Pigs ,Chickens - Abstract
Background Real-time quantitative PCR (qPCR) is an affordable method to quantify antimicrobial resistance gene (ARG) targets, allowing comparisons of ARG abundance along animal production chains. Objectives We present a comparison of ARG abundance across various animal species, production environments and humans in Europe. AMR variation sources were quantified. The correlation of ARG abundance between qPCR data and previously published metagenomic data was assessed. Methods A cross-sectional study was conducted in nine European countries, comprising 9572 samples. qPCR was used to quantify abundance of ARGs [aph(3′)-III, erm(B), sul2, tet(W)] and 16S rRNA. Variance component analysis was conducted to explore AMR variation sources. Spearman’s rank correlation of ARG abundance values was evaluated between pooled qPCR data and earlier published pooled metagenomic data. Results ARG abundance varied strongly among animal species, environments and humans. This variation was dominated by between-farm variation (pigs) or within-farm variation (broilers, veal calves and turkeys). A decrease in ARG abundance along pig and broiler production chains (‘farm to fork’) was observed. ARG abundance was higher in farmers than in slaughterhouse workers, and lowest in control subjects. ARG abundance showed a high correlation (Spearman’s ρ > 0.7) between qPCR data and metagenomic data of pooled samples. Conclusions qPCR analysis is a valuable tool to assess ARG abundance in a large collection of livestock-associated samples. The between-country and between-farm variation of ARG abundance could partially be explained by antimicrobial use and farm biosecurity levels. ARG abundance in human faeces was related to livestock antimicrobial resistance exposure.
- Published
- 2022