Liese Van Gompel1, Roosmarijn E C Luiken1, Steven Sarrazin2, Patrick Munk3, Berith E Knudsen3, Rasmus B Hansen4, Alex Bossers1,5, Frank M Aarestrup3, Jeroen Dewulf2, Jaap A Wagenaar5,6, Dik J Mevius5,6, Heike Schmitt1,7, Dick J J Heederik1, Alejandro Dorado-García1, Lidwien A M Smit1. 1. Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 2, CM Utrecht, The Netherlands. 2. Veterinary Epidemiology Unit, Department of Reproduction, Obstetrics and Herd Health, Faculty of Veterinary Medicine, Ghent University, Salisburylaan 133, Merelbeke, Belgium. 3. Research Group for Genomic Epidemiology, National Food Institute, Technical University of Denmark, Kemitorvet 204, Kongens Lyngby, Denmark. 4. Intomics A/S, Lottenborgvej 26, Kongens Lyngby, Denmark. 5. Wageningen Bioveterinary Research, Houtribweg 39, RA, Lelystad, The Netherlands. 6. Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 1, CL, Utrecht, The Netherlands. 7. Centre of Infectious Disease Control, National Institute for Public Health and the Environment, Antonie van Leeuwenhoeklaan 9, MA, Bilthoven, The Netherlands.
Abstract
OBJECTIVES: Previous studies in food-producing animals have shown associations between antimicrobial use (AMU) and resistance (AMR) in specifically isolated bacterial species. Multi-country data are scarce and only describe between-country differences. Here we investigate associations between the pig faecal mobile resistome and characteristics at the farm-level across Europe. METHODS: A cross-sectional study was conducted among 176 conventional pig farms from nine European countries. Twenty-five faecal samples from fattening pigs were pooled per farm and acquired resistomes were determined using shotgun metagenomics and the Resfinder reference database, i.e. the full collection of horizontally acquired AMR genes (ARGs). Normalized fragments resistance genes per kilobase reference per million bacterial fragments (FPKM) were calculated. Specific farm-level data (AMU, biosecurity) were collected. Random-effects meta-analyses were performed by country, relating farm-level data to relative ARG abundances (FPKM). RESULTS: Total AMU during fattening was positively associated with total ARG (total FPKM). Positive associations were particularly observed between widely used macrolides and tetracyclines, and ARGs corresponding to the respective antimicrobial classes. Significant AMU-ARG associations were not found for β-lactams and only few colistin ARGs were found, despite high use of these antimicrobial classes in younger pigs. Increased internal biosecurity was directly related to higher abundances of ARGs mainly encoding macrolide resistance. These effects of biosecurity were independent of AMU in mutually adjusted models. CONCLUSIONS: Using resistome data in association studies is unprecedented and adds accuracy and new insights to previously observed AMU-AMR associations. Major components of the pig resistome are positively and independently associated with on-farm AMU and biosecurity conditions.
OBJECTIVES: Previous studies in food-producing animals have shown associations between antimicrobial use (AMU) and resistance (AMR) in specifically isolated bacterial species. Multi-country data are scarce and only describe between-country differences. Here we investigate associations between the pig faecal mobile resistome and characteristics at the farm-level across Europe. METHODS: A cross-sectional study was conducted among 176 conventional pig farms from nine European countries. Twenty-five faecal samples from fattening pigs were pooled per farm and acquired resistomes were determined using shotgun metagenomics and the Resfinder reference database, i.e. the full collection of horizontally acquired AMR genes (ARGs). Normalized fragments resistance genes per kilobase reference per million bacterial fragments (FPKM) were calculated. Specific farm-level data (AMU, biosecurity) were collected. Random-effects meta-analyses were performed by country, relating farm-level data to relative ARG abundances (FPKM). RESULTS: Total AMU during fattening was positively associated with total ARG (total FPKM). Positive associations were particularly observed between widely used macrolides and tetracyclines, and ARGs corresponding to the respective antimicrobial classes. Significant AMU-ARG associations were not found for β-lactams and only few colistin ARGs were found, despite high use of these antimicrobial classes in younger pigs. Increased internal biosecurity was directly related to higher abundances of ARGs mainly encoding macrolide resistance. These effects of biosecurity were independent of AMU in mutually adjusted models. CONCLUSIONS: Using resistome data in association studies is unprecedented and adds accuracy and new insights to previously observed AMU-AMR associations. Major components of the pig resistome are positively and independently associated with on-farm AMU and biosecurity conditions.
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