Dataset Information

Longitudinal metagenomic study reveals the dynamics of fecal antibiotic resistome in pigs throughout the lifetime.

ABSTRACT:

Background

The dissemination of antibiotic resistance genes (ARGs) poses a substantial threat to environmental safety and human health. Herein, we present a longitudinal paired study across the swine lifetime from birth to market, coupled with metagenomic sequencing to explore the dynamics of ARGs and their health risk in the swine fecal microbiome.

Results

We systematically characterized the composition and distribution of ARGs among the different growth stages. In total, 829 ARG subtypes belonging to 21 different ARG types were detected, in which tetracycline, aminoglycoside, and MLS were the most abundant types. Indeed, 134 core ARG subtypes were shared in all stages and displayed a growth stage-associated pattern. Furthermore, the correlation between ARGs, gut microbiota and mobile genetic elements (MGEs) revealed Escherichia coli represented the main carrier of ARGs. We also found that in most cases, the dominant ARGs could be transmitted to progeny piglets, suggesting the potential ARGs generation transmission. Finally, the evaluation of the antibiotic resistance threats provides us some early warning of those high health risk ARGs.

Conclusions

Collectively, this relatively more comprehensive study provides a primary overview of ARG profile in swine microbiome across the lifetime and highlights the health risk and the intergenerational spread of ARGs in pig farm.

SUBMITTER: Ma L

PROVIDER: S-EPMC10634126 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature

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Publications

Longitudinal metagenomic study reveals the dynamics of fecal antibiotic resistome in pigs throughout the lifetime.

Ma Lingyan L Song Yuanyuan Y Lyu Wentao W Chen Qu Q Xiao Xingning X Jin Yuanxiang Y Yang Hua H Wang Wen W Xiao Yingping Y

Animal microbiome 20231108 1

<h4>Background</h4>The dissemination of antibiotic resistance genes (ARGs) poses a substantial threat to environmental safety and human health. Herein, we present a longitudinal paired study across the swine lifetime from birth to market, coupled with metagenomic sequencing to explore the dynamics of ARGs and their health risk in the swine fecal microbiome.<h4>Results</h4>We systematically characterized the composition and distribution of ARGs among the different growth stages. In total, 829 ARG ...[more]

PMID: 37941060

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Project description:Antibiotics are widely used in pig farming across the world which has led to concerns about the potential impact on human health through the selection of antibiotic resistant pathogenic bacteria. This worry has resulted in the development of a production scheme known as pigs Raised Without Antibiotics (RWA), in which pigs are produced in commercial farms, but are ear-tagged as RWA until slaughter unless they receive treatment, thus allowing the farmer to sell the pigs either as premium priced RWA or as conventional meat. Development of antibiotic resistance in pig farming has been studied in national surveys of antibiotic usage and resistance, as well as in experimental studies of groups of pigs, but not in individual pigs followed longitudinally in a commercial pig farm. In this study, a cohort of RWA designated pigs were sampled at 10 time points from birth until slaughter along with pen-mates treated with antibiotics at the same farm. From these samples, the microbiome, determined using 16S sequencing, and the resistome, as determined using qPCR for 82 resistance genes, was investigated, allowing us to examine the difference between RWA pigs and antibiotic treated pigs. We furthermore included 176 additional pigs from six different RWA farms which were sampled at the slaughterhouse as an endpoint to substantiate the cohort as well as for evaluation of intra-farm variability. The results showed a clear effect of age in both the microbiome and resistome composition from early life up until slaughter. As a function of antibiotic treatment, however, we observed a small but significant divergence between treated and untreated animals in their microbiome composition immediately following treatment, which disappeared before 8 weeks of age. The effect on the resistome was evident and an effect of treatment could still be detected at week 8. In animals sampled at the slaughterhouse, we observed no difference in the microbiome or the resistome as a result of treatment status but did see a strong effect of farm origin. Network analysis of co-occurrence of microbiome and resistome data suggested that some resistance genes may be transferred through mobile genetic elements, so we used Hi-C metagenomics on a subset of samples to investigate this. We conclude that antibiotic treatment has a differential effect on the microbiome vs. the resistome and that although resistance gene load is increased by antibiotic treatment load, this effect disappears before slaughter. More studies are needed to elucidate the optimal way to rear pigs without antibiotics.

Project description:BackgroundAntibiotics and antibiotic resistance genes (ARGs) used in intensive animal farming threaten human health worldwide; however, the common resistome, ARG mobility, and ARG host composition in different animal manures and mixed manure composts remain unclear. In the present study, metagenomic assembly and cross-sample mapping were used to comprehensively decipher the common resistome and its potential mobility and hosts in animal manure and composts.ResultsIn total, 201 ARGs were shared among different animal (layer, broiler, swine, beef cow, and dairy cow) manures and accounted for 86-99% of total relative abundance of ARGs. Except for multidrug, sulfonamide, and trimethoprim resistance genes, the relative abundance of most ARGs in composts was significantly lower than that in animal manure. Procrustes analysis indicated that antibiotic residues positively correlated with ARG composition in manure but not in composts. More than 75% ARG subtypes were shared between plasmids and chromosomes in our samples. Transposases could play a pivotal role in mediating the transfer of ARGs between different phyla in animal manure and composting. Cross-sample mapping to contigs carrying ARGs showed that the hosts of common resistome in manure had preference on animal species, and the dominant genus of ARG host shifted from Enterococcus in manure to Pseudomonas in composts. The broad host range and linking with diverse mobile genetic elements (MGEs) were two key factors for ARGs, such as sul1 and aadA, which could survive during composting. The multidrug resistance genes represented the dominant ARGs in pathogenic antibiotic-resistant bacteria in manure but could be effectively controlled by composting.ConclusionsOur experiments revealed the common resistome in animal manure, classified and relative quantified the ARG hosts, and assessed the mobility of ARGs. Composting can mitigate ARGs in animal manure by altering the bacterial hosts; however, persistent ARGs can escape from the removal because of diverse host range and MGEs. Our findings provide an overall background for source tracking, risk assessment, and control of livestock ARGs.

Project description:Better interrogation of antimicrobial resistance requires new approaches to detect the associated genes in metagenomic samples. Targeted enrichment is an ideal method for their sequencing and characterization. However, no open-source, up-to-date hybridization probe set targeting antimicrobial resistance genes exists. Here, we describe the Comprehensive Antibiotic Resistance Probe Design Machine (CARPDM), a probe design software package made to run alongside all future Comprehensive Antibiotic Resistance Database releases. To test its efficacy, we have created and tested two separate probe sets: allCARD, which enriches all genes encoded in the Comprehensive Antibiotic Resistance Database's protein homolog models (n = 4,661), and clinicalCARD, which focuses on a clinically relevant subset of resistance genes (n = 323). We demonstrate that allCARD increases the number of reads mapping to resistance genes by up to 594-fold. clinicalCARD performs similarly when clinically relevant genes are present, increasing the number of resistance-gene mapping reads by up to 598-fold. In parallel with this development, we have established a protocol to synthesize any probe set in-house, saving up to 350 dollars per reaction. Together, these probe sets, their associated design program CARPDM, and the protocol for in-house synthesis will democratize metagenomic resistome analyses, allowing researchers access to a cost-effective and efficient means to explore the antibiotic resistome.IMPORTANCEAntimicrobial resistance threatens to undermine all modern medicine and is driven by the spread of antimicrobial resistance genes among pathogens, environments, patients, and animals. DNA sequencing of complex samples, such as wastewater, shows considerable promise for tracking these genes and making risk assessments. However, these methods suffer from high costs and low detection limits, plus a requirement for frequent redesign due to the constantly evolving diversity of resistance genes. Building upon our Comprehensive Antibiotic Resistance Database, our research provides software for on-demand renewal, based on the latest knowledge of resistance gene diversity, of our novel bait-capture hybridization platform that simultaneously reduces cost and increases detection levels for DNA sequencing of complex samples. The significance of our research is in the development of new software tools, reagent synthesis protocols, and hybridization enrichment protocols to provide affordable, high-resolution metagenomics DNA sequencing, which we test using environmental and wastewater samples.

Project description:BackgroundAntibiotic-resistant pathogens pose high risks to human and animal health worldwide. In recent years, the role of gut microbiota as a reservoir of antibiotic resistance genes (ARGs) in humans and animals has been increasingly investigated. However, the structure and function of the gut bacterial community, as well as the ARGs they carry in migratory birds remain unknown.ResultsHere, we collected samples from migratory bird species and their associated environments and characterized their gut microbiomes and resistomes using shotgun metagenomic sequencing. We found that migratory birds vary greatly in gut bacterial composition but are similar in their microbiome metabolism and function. Birds from the same environment tend to harbor similar bacterial communities. In total, 1030 different ARGs (202 resistance types) conferring resistance to tetracycline, aminoglycoside, β-lactam, sulphonamide, chloramphenicol, macrolide-lincosamide-streptogramin (MLS), and quinolone are identified. Procrustes analysis indicated that microbial community structure is not correlated with the resistome in migratory birds. Moreover, metagenomic assembly-based host tracking revealed that most of the ARG-carrying contigs originate from Proteobacteria. Co-occurrence patterns revealed by network analysis showed that emrD, emrY, ANT(6)-Ia, and tetO, the hubs of ARG type network, are indicators of other co-occurring ARG types. Compared with the microbiomes and resistomes in the environment, migratory birds harbor a lower phylogenetic diversity but have more antibiotic resistance proteins. Interestingly, we found that the mcr-1 resistance gene is widespread among different birds, accounting for 50% of the total samples. Meanwhile, a large number of novel β-lactamase genes are also reconstructed from bird metagenomic assemblies based on fARGene software.ConclusionsOur study provides a comprehensive overview of the diversity and abundance of ARGs in migratory birds and highlights the possible role of migratory birds as ARG disseminators into the environment. Video abstract.

Dataset Information

Longitudinal metagenomic study reveals the dynamics of fecal antibiotic resistome in pigs throughout the lifetime.

Background

Results

Conclusions

Publications

Longitudinal metagenomic study reveals the dynamics of fecal antibiotic resistome in pigs throughout the lifetime.

Similar Datasets

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