2018
DOI: 10.1038/s41564-018-0192-9
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Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries

Abstract: Antimicrobial resistance (AMR) in bacteria and associated human morbidity and mortality is increasing. The use of antimicrobials in livestock selects for AMR that can subsequently be transferred to humans. This flow of AMR between reservoirs demands surveillance in livestock and in humans. We quantified and characterized the acquired resistance gene pools (resistomes) of 181 pig and 178 poultry farms from nine European countries, sequencing more than 5,000 Gb of DNA using shotgun metagenomics. We quantified ac… Show more

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Cited by 257 publications
(264 citation statements)
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“…ResFinder -Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on farm antimicrobial consumption Weinroth et al (2018) Bovine faecal samples during a clinical trial using ceftiofur and chlortetracycline MEGARes -Treatment with ceftiofur was not associated with changes in b-lactam resistance genes -Treatment with chlortetracycline had a significant increase in relative abundance of tetracycline resistance genes -There was an increase in resistance to an antimicrobial class not administered during the study, which is a possible indication of co-selection of resistance genes Munk et al (2018) Samples from pig and poultry farms ResFinder -Higher AMR gene loads were observed in pig farms, whereas poultry resistomes were more diverse -Several critical AMR genes, including mcr-1 and optrA, were detected, the abundance of which differed both between host species and between countries -The total acquired AMR genes level was associated with the overall country-specific antimicrobial usage in livestock The main advantages of shotgun metagenomics over classical methods for analysing the resistome is that this methodology is faster, allows for the simultaneous detection of a vast number of resistance genes of different microbial origins within a given sample and the estimation of their relative abundance, and in some cases it is possible to get important information on the genetic background of the detected AMR determinants (microbial species or strain of origin and/or association with mobile genetic elements, such as plasmids, integrons, transposons, prophages, etc.). In fact, shotgun metagenomics can be also used to characterise the so-called mobilome (pool of mobile genetic elements) in a given sample (Ravi et al, 2017).…”
Section: Metagenomics In Food-borne Outbreak Detection/investigationmentioning
confidence: 99%
“…ResFinder -Metagenomic read-mapping outperformed cultivation-based techniques in terms of predicting expected tetracycline resistance based on farm antimicrobial consumption Weinroth et al (2018) Bovine faecal samples during a clinical trial using ceftiofur and chlortetracycline MEGARes -Treatment with ceftiofur was not associated with changes in b-lactam resistance genes -Treatment with chlortetracycline had a significant increase in relative abundance of tetracycline resistance genes -There was an increase in resistance to an antimicrobial class not administered during the study, which is a possible indication of co-selection of resistance genes Munk et al (2018) Samples from pig and poultry farms ResFinder -Higher AMR gene loads were observed in pig farms, whereas poultry resistomes were more diverse -Several critical AMR genes, including mcr-1 and optrA, were detected, the abundance of which differed both between host species and between countries -The total acquired AMR genes level was associated with the overall country-specific antimicrobial usage in livestock The main advantages of shotgun metagenomics over classical methods for analysing the resistome is that this methodology is faster, allows for the simultaneous detection of a vast number of resistance genes of different microbial origins within a given sample and the estimation of their relative abundance, and in some cases it is possible to get important information on the genetic background of the detected AMR determinants (microbial species or strain of origin and/or association with mobile genetic elements, such as plasmids, integrons, transposons, prophages, etc.). In fact, shotgun metagenomics can be also used to characterise the so-called mobilome (pool of mobile genetic elements) in a given sample (Ravi et al, 2017).…”
Section: Metagenomics In Food-borne Outbreak Detection/investigationmentioning
confidence: 99%
“…To construct COALA, we used 15 available antibiotic resistance gene databases mentioned in [6]. These databases are CARD [8], ResFinder [26], ResfinderFG [27], ARDB [28],…”
Section: Datasetmentioning
confidence: 99%
“…to species/strain level) and the relative abundance of organisms present in the microbiome. Apart from characterizing the microbiome, metagenomics has potential application in AMR surveillance [120]. For example, it could facilitate the tracking of AMR genes and mobiles genetic elements in difficult-to-culture or non-culturable microorganisms, which might also play a role in transmission of AMR across the food chain, as well as the abundance and diversity of AMR genes in animals, food, environment and humans.…”
Section: Metagenomics For Foodborne Pathogens and Antimicrobial Resismentioning
confidence: 99%
“…As compared to the use of WGS for foodborne outbreak investigation and epidemiological surveillance, and AMR surveillance, the use of metagenomics for the same purposes are still in its early days (some examples have been discussed by a recent review from [76]). In a recent extensive study that examined the single largest metagenomic AMR monitoring effort of livestock (9 EU countries, 181 pig and 178 poultry farms, 359 herds, >9000 animal samples and >5000 GB sequencing data), the pig and poultry resistomes showed great difference in abundance and composition [120]. There was a pronounced country-specific effect on the resistomes, more so in pigs than in poultry [120].…”
Section: Metagenomics For Foodborne Pathogens and Antimicrobial Resismentioning
confidence: 99%
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