1
|
Munk P, Yang D, Röder T, Maier L, Petersen TN, Duarte ASR, Clausen PTLC, Brinch C, Van Gompel L, Luiken R, Wagenaar JA, Schmitt H, Heederik DJJ, Mevius DJ, Smit LAM, Bossers A, Aarestrup FM. The European livestock resistome. mSystems 2024; 9:e0132823. [PMID: 38501800 PMCID: PMC11019871 DOI: 10.1128/msystems.01328-23] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Accepted: 02/21/2024] [Indexed: 03/20/2024] Open
Abstract
Metagenomic sequencing has proven to be a powerful tool in the monitoring of antimicrobial resistance (AMR). Here, we provide a comparative analysis of the resistome from pigs, poultry, veal calves, turkey, and rainbow trout, for a total of 538 herds across nine European countries. We calculated the effects of per-farm management practices and antimicrobial usage (AMU) on the resistome in pigs, broilers, and veal calves. We also provide an in-depth study of the associations between bacterial diversity, resistome diversity, and AMR abundances as well as co-occurrence analysis of bacterial taxa and antimicrobial resistance genes (ARGs) and the universality of the latter. The resistomes of veal calves and pigs clustered together, as did those of avian origin, while the rainbow trout resistome was different. Moreover, we identified clear core resistomes for each specific food-producing animal species. We identified positive associations between bacterial alpha diversity and both resistome alpha diversity and abundance. Network analyses revealed very few taxa-ARG associations in pigs but a large number for the avian species. Using updated reference databases and optimized bioinformatics, previously reported significant associations between AMU, biosecurity, and AMR in pig and poultry farms were validated. AMU is an important driver for AMR; however, our integrated analyses suggest that factors contributing to increased bacterial diversity might also be associated with higher AMR load. We also found that dispersal limitations of ARGs are shaping livestock resistomes, and future efforts to fight AMR should continue to emphasize biosecurity measures.IMPORTANCEUnderstanding the occurrence, diversity, and drivers for antimicrobial resistance (AMR) is important to focus future control efforts. So far, almost all attempts to limit AMR in livestock have addressed antimicrobial consumption. We here performed an integrated analysis of the resistomes of five important farmed animal populations across Europe finding that the resistome and AMR levels are also shaped by factors related to bacterial diversity, as well as dispersal limitations. Thus, future studies and interventions aimed at reducing AMR should not only address antimicrobial usage but also consider other epidemiological and ecological factors.
Collapse
Affiliation(s)
- Patrick Munk
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - Dongsheng Yang
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Timo Röder
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - Leonie Maier
- School of Biological Sciences, University of Edinburgh, Max Born Crescent, Edinburgh, United Kingdom
| | | | | | | | - Christian Brinch
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
| | - Liese Van Gompel
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Roosmarijn Luiken
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Jaap A. Wagenaar
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Heike Schmitt
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Dick J. J. Heederik
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - Dik J. Mevius
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
- Wageningen Bioveterinary Research, Wageningen University & Research, Lelystad, The Netherlands
| | - Lidwien A. M. Smit
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
| | - EFFORT ConsortiumGravelandHaitskeGonzalez-ZornBrunoMoyanoGabrielSandersPascalChauvinClaireBattistiAntonioDewulfJeroenWadepohlKatharinaWasylDariuszSkarzyńskaMagdalenaZajacMagdalenaPękala-SafińskaAgnieszkaDaskalovHristoStärkKatharina D. C.
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
- School of Biological Sciences, University of Edinburgh, Max Born Crescent, Edinburgh, United Kingdom
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
- Wageningen Bioveterinary Research, Wageningen University & Research, Lelystad, The Netherlands
| | - Alex Bossers
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, The Netherlands, Utrecht
- Wageningen Bioveterinary Research, Wageningen University & Research, Lelystad, The Netherlands
| | - Frank M. Aarestrup
- National Food Institute, Technical University of Denmark, Lyngby, Denmark
| |
Collapse
|
2
|
Shao Y, Qi Z, Sang J, Yu Z, Li M, Wang Z, Tu J, Song X, Qi K. Metagenome-Based Analysis of the Microbial Community Structure and Drug-Resistance Characteristics of Livestock Feces in Anhui Province, China. Vet Sci 2024; 11:87. [PMID: 38393105 PMCID: PMC10892912 DOI: 10.3390/vetsci11020087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 01/25/2024] [Accepted: 01/30/2024] [Indexed: 02/25/2024] Open
Abstract
We analyzed metagenome data of feces from sows at different physiological periods reared on large-scale farms in Anhui Province, China, to provide a better understanding of the microbial diversity of the sow intestinal microbiome and the structure of antibiotic-resistance genes (ARGs) and virulence genes it carries. Species annotation of the metagenome showed that in the porcine intestinal microbiome, bacteria were dominant, representing >97% of the microorganisms at each physiological period. Firmicutes and Proteobacteria dominated the bacterial community. In the porcine gut microbiome, the viral component accounted for an average of 0.65%, and the species annotation results indicated that most viruses were phages. In addition, we analyzed the microbiome for ARGs and virulence genes. Multidrug-like, MLS-like, and tetracycline-like ARGs were most abundant in all samples. Evaluation of the resistance mechanisms indicated that antibiotic inactivation was the main mechanism of action in the samples. It is noteworthy that there was a significant positive correlation between ARGs and the total microbiome. Moreover, comparative analysis with the Virulence Factor Database showed that adhesion virulence factors were most abundant.
Collapse
Affiliation(s)
- Ying Shao
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhao Qi
- School of Information and Artificial Intelligence, Anhui Agricultural University, Hefei 230036, China;
| | - Jinhui Sang
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhaorong Yu
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Min Li
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhenyu Wang
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Jian Tu
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Xiangjun Song
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Kezong Qi
- Anhui Province Engineering Laboratory for Animal Food Quality and Bio-Safety, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China; (Y.S.); (J.S.); (Z.Y.); (M.L.); (Z.W.); (J.T.)
- Anhui Province Key Laboratory of Veterinary Pathobiology and Disease Control, College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| |
Collapse
|
3
|
Qiu J, Shi Y, Zhao F, Xu Y, Xu H, Dai Y, Cao Y. The Pan-Genomic Analysis of Corynebacterium striatum Revealed its Genetic Characteristics as an Emerging Multidrug-Resistant Pathogen. Evol Bioinform Online 2023; 19:11769343231191481. [PMID: 37576785 PMCID: PMC10422898 DOI: 10.1177/11769343231191481] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Accepted: 07/03/2023] [Indexed: 08/15/2023] Open
Abstract
Corynebacterium striatum is a Gram-positive bacterium that is straight or slightly curved and non-spore-forming. Although it was originally believed to be a part of the normal microbiome of human skin, a growing number of studies have identified it as a cause of various chronic diseases, bacteremia, and respiratory infections. However, despite its increasing importance as a pathogen, the genetic characteristics of the pathogen population, such as genomic characteristics and differences, the types of resistance genes and virulence factors carried by the pathogen and their distribution in the population are poorly understood. To address these knowledge gaps, we conducted a pan-genomic analysis of 314 strains of C. striatum isolated from various tissues and geographic locations. Our analysis revealed that C. striatum has an open pan-genome, comprising 5692 gene families, including 1845 core gene families, 2362 accessory gene families, and 1485 unique gene families. We also found that C. striatum exhibits a high degree of diversity across different sources, but strains isolated from skin tissue are more conserved. Furthermore, we identified 53 drug resistance genes and 42 virulence factors by comparing the strains to the drug resistance gene database (CARD) and the pathogen virulence factor database (VFDB), respectively. We found that these genes and factors are widely distributed among C. striatum, with 77.7% of strains carrying 2 or more resistance genes and displaying primary resistance to aminoglycosides, tetracyclines, lincomycin, macrolides, and streptomycin. The virulence factors are primarily associated with pathogen survival within the host, iron uptake, pili, and early biofilm formation. In summary, our study provides insights into the population diversity, resistance genes, and virulence factors ofC. striatum from different sources. Our findings could inform future research and clinical practices in the diagnosis, prevention, and treatment of C. striatum-associated diseases.
Collapse
Affiliation(s)
- Junhui Qiu
- Microbiology and Metabolic Engineering Key Laboratory of Sichuan Provence, College of Life Science, Sichuan University, Chengdu, Sichuan, China
| | - Yulan Shi
- Wound Treatment Center of West China Hospital of Sichuan University, West China College of Nursing, Sichuan University, Chengdu, Sichuan, China
| | - Fei Zhao
- Microbiology and Metabolic Engineering Key Laboratory of Sichuan Provence, College of Life Science, Sichuan University, Chengdu, Sichuan, China
| | - Yi Xu
- Microbiology and Metabolic Engineering Key Laboratory of Sichuan Provence, College of Life Science, Sichuan University, Chengdu, Sichuan, China
| | - Hui Xu
- Microbiology and Metabolic Engineering Key Laboratory of Sichuan Provence, College of Life Science, Sichuan University, Chengdu, Sichuan, China
| | - Yan Dai
- Wound Treatment Center of West China Hospital of Sichuan University, West China College of Nursing, Sichuan University, Chengdu, Sichuan, China
| | - Yi Cao
- Microbiology and Metabolic Engineering Key Laboratory of Sichuan Provence, College of Life Science, Sichuan University, Chengdu, Sichuan, China
| |
Collapse
|
4
|
Becker J, Perreten V, Schüpbach-Regula G, Stucki D, Steiner A, Meylan M. Associations of antimicrobial use with antimicrobial susceptibility at the calf level in bacteria isolated from the respiratory and digestive tracts of veal calves before slaughter. J Antimicrob Chemother 2022; 77:2859-2866. [PMID: 35962594 PMCID: PMC9525080 DOI: 10.1093/jac/dkac246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 06/24/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives Antimicrobial drugs are frequently administered in veal calves, but investigations on associations with antimicrobial susceptibility of bacteria are scarce and convey partly contradictory findings. The aim of this study was to investigate associations of antimicrobial use (AMU) during the fattening period with antimicrobial susceptibility shortly before slaughter. Methods Detailed treatment data of 1905 veal calves from 38 farms were collected prospectively during monthly farm visits for 1 year (n = 1864 treatments, n = 535 visits); 1582 Escherichia coli, 1059 Pasteurella multocida and 315 Mannheimia haemolytica were isolated from rectal and nasopharyngeal swabs collected before slaughter and subjected to antimicrobial susceptibility testing by microdilution. Associations of antimicrobial treatments with resistant isolates were investigated at the calf level. Results Associations of AMU with antimicrobial resistance were observed using generalized linear models. For E. coli, the odds of being resistant were increased with increased AMU (OR 1.36 when number of treatments >1, P = 0.066). Use of tetracyclines was associated with resistance to tetracycline (OR 1.86, P < 0.001) and use of penicillins was associated with resistance to ampicillin (OR 1.66, P = 0.014). No significant associations were observed for P. multocida (use of aminoglycosides: OR 3.66 for resistance to spectinomycin, P = 0.074). For M. haemolytica, the odds of being resistant were increased with increased AMU (OR 4.63, P < 0.001), and use of tetracyclines was associated with resistance to tetracycline (OR 6.49, P < 0.001). Conclusions Occurrence of resistant bacteria shortly before slaughter was associated with AMU in veal calves. Prudent and appropriate use may contribute to limit the selection of resistant bacteria on veal farms.
Collapse
Affiliation(s)
- Jens Becker
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - Vincent Perreten
- Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Länggassstrasse 122, 3012 Bern, Switzerland
| | - Gertraud Schüpbach-Regula
- Veterinary Public Health Institute, Vetsuisse Faculty, University of Bern, Schwarzenburgstrasse 161, 3097 Liebefeld, Switzerland
| | - Dimitri Stucki
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - Adrian Steiner
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| | - Mireille Meylan
- Clinic for Ruminants, Vetsuisse Faculty, University of Bern, Bremgartenstrasse 109a, 3012 Bern, Switzerland
| |
Collapse
|
5
|
Luiken RE, Heederik DJ, Scherpenisse P, Van Gompel L, van Heijnsbergen E, Greve GD, Jongerius-Gortemaker BG, Tersteeg-Zijderveld MH, Fischer J, Juraschek K, Skarżyńska M, Zając M, Wasyl D, Wagenaar JA, Smit LA, Wouters IM, Mevius DJ, Schmitt H. Determinants for antimicrobial resistance genes in farm dust on 333 poultry and pig farms in nine European countries. ENVIRONMENTAL RESEARCH 2022; 208:112715. [PMID: 35033551 DOI: 10.1016/j.envres.2022.112715] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 01/05/2022] [Accepted: 01/07/2022] [Indexed: 06/14/2023]
Abstract
Livestock feces with antimicrobial resistant bacteria reaches the farm floor, manure pit, farm land and wider environment by run off and aerosolization. Little research has been done on the role of dust in the spread of antimicrobial resistance (AMR) in farms. Concentrations and potential determinants of antimicrobial resistance genes (ARGs) in farm dust are at present not known. Therefore in this study absolute ARG levels, representing the levels people and animals might be exposed to, and relative abundances of ARGs, representing the levels in the bacterial population, were quantified in airborne farm dust using qPCR. Four ARGs were determined in 947 freshly settled farm dust samples, captured with electrostatic dustfall collectors (EDCs), from 174 poultry (broiler) and 159 pig farms across nine European countries. By using linear mixed modeling, associations with fecal ARG levels, antimicrobial use (AMU) and farm and animal related parameters were determined. Results show similar relative abundances in farm dust as in feces and a significant positive association (ranging between 0.21 and 0.82) between the two reservoirs. AMU in pigs was positively associated with ARG abundances in dust from the same stable. Higher biosecurity standards were associated with lower relative ARG abundances in poultry and higher relative ARG abundances in pigs. Lower absolute ARG levels in dust were driven by, among others, summer season and certain bedding materials for poultry, and lower animal density and summer season for pigs. This study indicates different pathways that contribute to shaping the dust resistome in livestock farms, related to dust generation, or affecting the bacterial microbiome. Farm dust is a large reservoir of ARGs from which transmission to bacteria in other reservoirs can possibly occur. The identified determinants of ARG abundances in farm dust can guide future research and potentially farm management policy.
Collapse
Affiliation(s)
- Roosmarijn Ec Luiken
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands.
| | - Dick Jj Heederik
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Peter Scherpenisse
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Liese Van Gompel
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Eri van Heijnsbergen
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Gerdit D Greve
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | | | | | - Jennie Fischer
- Department of Biological Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, 10589, Berlin, Germany
| | - Katharina Juraschek
- Department of Biological Safety, German Federal Institute for Risk Assessment (BfR), Max-Dohrn-Strasse 8-10, 10589, Berlin, Germany
| | - Magdalena Skarżyńska
- Department of Microbiology, National Veterinary Research Institute (PIWet), Partyzantów 57, 24-100, Puławy, Poland
| | - Magdalena Zając
- Department of Microbiology, National Veterinary Research Institute (PIWet), Partyzantów 57, 24-100, Puławy, Poland
| | - Dariusz Wasyl
- Department of Microbiology, National Veterinary Research Institute (PIWet), Partyzantów 57, 24-100, Puławy, Poland
| | - Jaap A Wagenaar
- Department Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 1, 3584CL, Utrecht, the Netherlands; Wageningen Bioveterinary Research, Houtribweg 39, 8221RA, Lelystad, the Netherlands
| | - Lidwien Am Smit
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Inge M Wouters
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands
| | - Dik J Mevius
- Department Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Yalelaan 1, 3584CL, Utrecht, the Netherlands; Wageningen Bioveterinary Research, Houtribweg 39, 8221RA, Lelystad, the Netherlands
| | - Heike Schmitt
- Institute for Risk Assessment Sciences, Utrecht University, Yalelaan 2, 3584CM, Utrecht, the Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA, Bilthoven, the Netherlands
| |
Collapse
|
6
|
Yang D, Heederik DJJ, Scherpenisse P, Van Gompel L, Luiken REC, Wadepohl K, Skarżyńska M, Van Heijnsbergen E, Wouters IM, Greve GD, Jongerius-Gortemaker BGM, Tersteeg-Zijderveld M, Portengen L, Juraschek K, Fischer J, Zając M, Wasyl D, Wagenaar JA, Mevius DJ, Smit LAM, Schmitt H. OUP accepted manuscript. J Antimicrob Chemother 2022; 77:1883-1893. [PMID: 35466367 PMCID: PMC9244224 DOI: 10.1093/jac/dkac133] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Accepted: 03/31/2022] [Indexed: 11/21/2022] Open
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.
Collapse
Affiliation(s)
| | - Dick J J Heederik
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Peter Scherpenisse
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Liese Van Gompel
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Roosmarijn E C Luiken
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Katharina Wadepohl
- Außenstelle für Epidemiologie, Tierärztliche Hochschule Hannover, Hannover, Germany
| | - Magdalena Skarżyńska
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Eri Van Heijnsbergen
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Inge M Wouters
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Gerdit D Greve
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | | | - Monique Tersteeg-Zijderveld
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Lützen Portengen
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Katharina Juraschek
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | - Jennie Fischer
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | - Magdalena Zając
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Dariusz Wasyl
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Jaap A Wagenaar
- Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands
| | - Dik J Mevius
- Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands
- Department of Bacteriology and Epidemiology, Wageningen Bioveterinary Research, Lelystad, The Netherlands
| | - Lidwien A M Smit
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | | |
Collapse
|
7
|
Yang D, Heederik DJJ, Mevius DJ, Scherpenisse P, Luiken REC, Van Gompel L, Skarżyńska M, Wadepohl K, Chauvin C, Van Heijnsbergen E, Wouters IM, Greve GD, Jongerius-Gortemaker BGM, Tersteeg-Zijderveld M, Zając M, Wasyl D, Juraschek K, Fischer J, Wagenaar JA, Smit LAM, Schmitt H. OUP accepted manuscript. J Antimicrob Chemother 2022; 77:969-978. [PMID: 35061866 PMCID: PMC8969523 DOI: 10.1093/jac/dkac002] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 12/26/2021] [Indexed: 11/29/2022] Open
Abstract
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 characteristics. 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 biosecurity 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 differences, and then by on-farm AMU.
Collapse
Affiliation(s)
- Dongsheng Yang
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
- Corresponding author. E-mail:
| | - Dick J. J. Heederik
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Dik J. Mevius
- Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands
- Department of Bacteriology and Epidemiology, Wageningen Bioveterinary Research, Lelystad, The Netherlands
| | - Peter Scherpenisse
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Roosmarijn E. C. Luiken
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Liese Van Gompel
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Magdalena Skarżyńska
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Katharina Wadepohl
- Außenstelle für Epidemiologie, Tierärztliche Hochschule Hannover, Hannover, Germany
| | - Claire Chauvin
- ANSES, Epidemiology, Health and Welfare Unit, Paris, France
| | - Eri Van Heijnsbergen
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Inge M. Wouters
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Gerdit D. Greve
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | | | - Monique Tersteeg-Zijderveld
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Magdalena Zając
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Dariusz Wasyl
- Department of Microbiology, National Veterinary Research Institute, Pulawy, Poland
| | - Katharina Juraschek
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | - Jennie Fischer
- Department of Biological Safety, German Federal Institute for Risk Assessment, Berlin, Germany
| | - Jaap A. Wagenaar
- Department of Infectious Diseases and Immunology, Utrecht University, Utrecht, The Netherlands
| | - Lidwien A. M. Smit
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Heike Schmitt
- Institute for Risk Assessment Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
- National Institute for Public Health and the Environment, Bilthoven, The Netherlands
| | | |
Collapse
|
8
|
Risk Factors for Antimicrobial Resistance in Turkey Farms: A Cross-Sectional Study in Three European Countries. Antibiotics (Basel) 2021; 10:antibiotics10070820. [PMID: 34356741 PMCID: PMC8300668 DOI: 10.3390/antibiotics10070820] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 06/30/2021] [Accepted: 06/30/2021] [Indexed: 11/17/2022] Open
Abstract
Food-producing animals are an important reservoir and potential source of transmission of antimicrobial resistance (AMR) to humans. However, research on AMR in turkey farms is limited. This study aimed to identify risk factors for AMR in turkey farms in three European countries (Germany, France, and Spain). Between 2014 and 2016, faecal samples, antimicrobial usage (AMU), and biosecurity information were collected from 60 farms. The level of AMR in faecal samples was quantified in three ways: By measuring the abundance of AMR genes through (i) shotgun metagenomics sequencing (n = 60), (ii) quantitative real-time polymerase chain reaction (qPCR) targeting ermB, tetW, sul2, and aph3′-III; (n = 304), and (iii) by identifying the phenotypic prevalence of AMR in Escherichia coli isolates by minimum inhibitory concentrations (MIC) (n = 600). The association between AMU or biosecurity and AMR was explored. Significant positive associations were detected between AMU and both genotypic and phenotypic AMR for specific antimicrobial classes. Beta-lactam and colistin resistance (metagenomics sequencing); ampicillin and ciprofloxacin resistance (MIC) were associated with AMU. However, no robust AMU-AMR association was detected by analyzing qPCR targets. In addition, no evidence was found that lower biosecurity increases AMR abundance. Using multiple complementary AMR detection methods added insights into AMU-AMR associations at turkey farms.
Collapse
|