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659501.0000Methodological aspects of investigating the resistome in pig farm environments. A typical One Health issue, antimicrobial resistance (AMR) development and its spread among people, animals, and the environment attracts significant research attention. The animal sector is one of the major contributors to the development and dissemination of AMR and accounts for more than 50 % of global antibiotics usage. The use of antibiotics exerts a selective pressure for resistant bacteria in the exposed microbiome, but many questions about the epidemiology of AMR in farm environments remain unanswered. This is connected to several methodological challenges and limitations, such as inconsistent sampling methods, complexity of farm environment samples and the lack of standardized protocols for sample collection, processing and bioinformatical analysis. In this project, we combined metagenomics and bioinformatics to optimise the methodology for reproducible research on the resistome in complex samples from the indoor farm environment. The work included optimizing sample collection, transportation, and storage, as well as DNA extraction, sequencing, and bioinformatic analysis, such as metagenome assembly and antibiotic resistance gene (ARG) detection. Our studies suggest that the current most optimal and cost-effective pipeline for ARG search should be based on Illumina sequencing of sock sample material at high depth (at least 25 M 250 bp PE for AMR gene families and 43 M for gene variants). We present a computational analysis utilizing MEGAHIT assembly to balance the identification of bacteria carrying ARGs with the potential loss of diversity and abundance of resistance genes. Our findings indicate that searching against multiple ARG databases is essential for detecting the highest diversity of ARGs.202539954816
659710.9999Exploiting a targeted resistome sequencing approach in assessing antimicrobial resistance in retail foods. BACKGROUND: With the escalating risk of antimicrobial resistance (AMR), there are limited analytical options available that can comprehensively assess the burden of AMR carried by clinical/environmental samples. Food can be a potential source of AMR bacteria for humans, but its significance in driving the clinical spread of AMR remains unclear, largely due to the lack of holistic-yet-sensitive tools for surveillance and evaluation. Metagenomics is a culture-independent approach well suited for uncovering genetic determinants of defined microbial traits, such as AMR, present within unknown bacterial communities. Despite its popularity, the conventional approach of non-selectively sequencing a sample's metagenome (namely, shotgun-metagenomics) has several technical drawbacks that lead to uncertainty about its effectiveness for AMR assessment; for instance, the low discovery rate of resistance-associated genes due to their naturally small genomic footprint within the vast metagenome. Here, we describe the development of a targeted resistome sequencing method and demonstrate its application in the characterization of the AMR gene profile of bacteria associated with several retail foods. RESULT: A targeted-metagenomic sequencing workflow using a customized bait-capture system targeting over 4,000 referenced AMR genes and 263 plasmid replicon sequences was validated against both mock and sample-derived bacterial community preparations. Compared to shotgun-metagenomics, the targeted method consistently provided for improved recovery of resistance gene targets with a much-improved target detection efficiency (> 300-fold). Targeted resistome analyses conducted on 36 retail-acquired food samples (fresh sprouts, n = 10; ground meat, n = 26) and their corresponding bacterial enrichment cultures (n = 36) reveals in-depth features regarding the identity and diversity of AMR genes, most of which were otherwise undetected by the whole-metagenome shotgun sequencing method. Furthermore, our findings suggest that foodborne Gammaproteobacteria could be the major reservoir of food-associated AMR genetic determinants, and that the resistome structure of the selected high-risk food commodities are, to a large extent, dictated by microbiome composition. CONCLUSIONS: For metagenomic sequencing-based surveillance of AMR, the target-capture method presented herein represents a more sensitive and efficient approach to evaluate the resistome profile of complex food or environmental samples. This study also further implicates retail foods as carriers of diverse resistance-conferring genes indicating a potential impact on the dissemination of AMR.202336991496
659620.9999Shotgun metagenomic sequencing of bulk tank milk filters reveals the role of Moraxellaceae and Enterobacteriaceae as carriers of antimicrobial resistance genes. In the present context of growing antimicrobial resistance (AMR) concern, understanding the distribution of AMR determinants in food matrices such as milk is crucial to protect consumers and maintain high food safety standards. Herein, the resistome of different dairy farms was investigated through a shotgun metagenomic sequencing approach, taking advantage of in-line milk filters as promising tools. The application of both the reads-based and the assembly-based approaches has allowed the identification of numerous AMR determinants, enabling a comprehensive resolution of the resistome. Notably most of the species harboring AMR genes were predicted to be Gram-negative genera, namely Enterobacter, Acinetobacter, Escherichia, and Pseudomonas, pointing out the role of these bacteria as reservoirs of AMR determinants. In this context, the use of de novo assembly has allowed a more holistic AMR detection strategy, while the reads-based approach has enabled the detection of AMR genes from low abundance bacteria, usually undetectable by assembly-based methods. The application of both reads-based and assembly-based approaches, despite being computationally demanding, has facilitated the comprehensive characterization of a food chain resistome, while also allowing the construction of complete metagenome assembled genomes and the investigation of mobile genetic elements. Our findings suggest that milk filters can successfully be used to investigate the resistome of bulk tank milk through the application of the shotgun metagenomic sequencing. In accordance with our results, raw milk can be considered a source of AMR bacteria and genes; this points out the importance of properly informing food business operators about the risk associated with poor hygiene practices in the dairy production environment and consumers of the potential microbial food safety risks derived from raw milk products consumption. Translating these findings as risk assessment outputs heralds the next generation of food safety controls.202235840264
389330.9999Diverse antibiotic resistance genes in dairy cow manure. Application of manure from antibiotic-treated animals to crops facilitates the dissemination of antibiotic resistance determinants into the environment. However, our knowledge of the identity, diversity, and patterns of distribution of these antibiotic resistance determinants remains limited. We used a new combination of methods to examine the resistome of dairy cow manure, a common soil amendment. Metagenomic libraries constructed with DNA extracted from manure were screened for resistance to beta-lactams, phenicols, aminoglycosides, and tetracyclines. Functional screening of fosmid and small-insert libraries identified 80 different antibiotic resistance genes whose deduced protein sequences were on average 50 to 60% identical to sequences deposited in GenBank. The resistance genes were frequently found in clusters and originated from a taxonomically diverse set of species, suggesting that some microorganisms in manure harbor multiple resistance genes. Furthermore, amid the great genetic diversity in manure, we discovered a novel clade of chloramphenicol acetyltransferases. Our study combined functional metagenomics with third-generation PacBio sequencing to significantly extend the roster of functional antibiotic resistance genes found in animal gut bacteria, providing a particularly broad resource for understanding the origins and dispersal of antibiotic resistance genes in agriculture and clinical settings. IMPORTANCE The increasing prevalence of antibiotic resistance among bacteria is one of the most intractable challenges in 21st-century public health. The origins of resistance are complex, and a better understanding of the impacts of antibiotics used on farms would produce a more robust platform for public policy. Microbiomes of farm animals are reservoirs of antibiotic resistance genes, which may affect distribution of antibiotic resistance genes in human pathogens. Previous studies have focused on antibiotic resistance genes in manures of animals subjected to intensive antibiotic use, such as pigs and chickens. Cow manure has received less attention, although it is commonly used in crop production. Here, we report the discovery of novel and diverse antibiotic resistance genes in the cow microbiome, demonstrating that it is a significant reservoir of antibiotic resistance genes. The genomic resource presented here lays the groundwork for understanding the dispersal of antibiotic resistance from the agroecosystem to other settings.201424757214
656940.9999Unveiling Rare Pathogens and Antibiotic Resistance in Tanzanian Cholera Outbreak Waters. The emergence of antibiotic resistance is a global health concern. Therefore, understanding the mechanisms of its spread is crucial for implementing evidence-based strategies to tackle resistance in the context of the One Health approach. In developing countries where sanitation systems and access to clean and safe water are still major challenges, contamination may introduce bacteria and bacteriophages harboring antibiotic resistance genes (ARGs) into the environment. This contamination can increase the risk of exposure and community transmission of ARGs and infectious pathogens. However, there is a paucity of information on the mechanisms of bacteriophage-mediated spread of ARGs and patterns through the environment. Here, we deploy Droplet Digital PCR (ddPCR) and metagenomics approaches to analyze the abundance of ARGs and bacterial pathogens disseminated through clean and wastewater systems. We detected a relatively less-studied and rare human zoonotic pathogen, Vibrio metschnikovii, known to spread through fecal--oral contamination, similarly to V. cholerae. Several antibiotic resistance genes were identified in both bacterial and bacteriophage fractions from water sources. Using metagenomics, we detected several resistance genes related to tetracyclines and beta-lactams in all the samples. Environmental samples from outlet wastewater had a high diversity of ARGs and contained high levels of blaOXA-48. Other identified resistance profiles included tetA, tetM, and blaCTX-M9. Specifically, we demonstrated that blaCTX-M1 is enriched in the bacteriophage fraction from wastewater. In general, however, the bacterial community has a significantly higher abundance of resistance genes compared to the bacteriophage population. In conclusion, the study highlights the need to implement environmental monitoring of clean and wastewater to inform the risk of infectious disease outbreaks and the spread of antibiotic resistance in the context of One Health.202337894148
670750.9999Investigating the occurrence of antimicrobial resistance in the environment in Canada: a scoping review. Antimicrobial resistance is an environmental, agricultural, and public health problem that is impacting the health of humans and animals. The role of the environment as a source of and transmission pathway for antibiotic resistant bacteria and antibiotic resistance genes is a topic of increasing interest that, to date, has received limited attention. This study aimed to describe the sources and possible pathways contributing to antimicrobial resistance dissemination through bioaerosols, water, and soil in Canada using a scoping review methodology and systems thinking approach. A systems map was created to describe the occurrence and relationships between sources and pathways for antimicrobial resistance dissemination through water, soil, and bioaerosols. The map guided the development of the scoping review protocol, specifically the keywords searched and what data were extracted from the included studies. In total, 103 studies of antimicrobial resistance in water, 67 in soil, and 12 in air were identified. Studies to detect the presence of antimicrobial resistance genes have mainly been conducted at wastewater treatment plants and commercial animal livestock facilities. We also identified elements in the systems map with little or no data available (e.g., retail) that need to be investigated further to have a better understanding of antimicrobial resistance dissemination through different Canadian environments.202540279669
325460.9999Temporal trends of antibiotic resistance in culturable bacteria reveal the role of potential pathogens as pioneering carriers and resistance accumulators. Understanding the occurrence and temporal trends of antibiotic resistance genes (ARGs) within bacteria is crucial for controlling and predicting the proliferation of antibiotic-resistant bacteria. However, gaps remain in understanding the long-term trends across different bacterial species and in assessing related health risks. We collected 22,360 bacterial complete genome sequences with collection time and compiled a temporal dataset of ARGs in culturable bacteria. Our results revealed the widespread presence of ARGs among culturable bacterial species, with potential pathogens carrying significantly more ARGs than non-pathogenic species. Temporal trend analysis revealed that only 11.0 % of bacterial species experienced an increase of more than one unit in ARG quantity and diversity over one century, with 83.3 % of them being potential pathogenic species. The temporal accumulation of ARGs in many potential pathogenic species is influenced by the abundance of mobile genetic elements, with several species also exhibiting temporal accumulation of plasmid-borne ARGs. Notably, Shigella flexneri and Klebsiella pneumoniae exhibited an accumulation of high-risk ARGs associated with at least five antibiotic types over at least 40 years. Furthermore, the distribution of ARG-carrying strains before the use of antibiotics revealed a wide range of bacterial species and antibiotic types for intrinsic resistance, including some synthetic antibiotics. This work reveals the significant role of potential pathogens in the expansion of antibiotic resistance and highlights the importance of strengthening vigilance against the emergence of novel multidrug-resistant pathogens.202540712179
325370.9999Metagenome-assembled genomes indicate that antimicrobial resistance genes are highly prevalent among urban bacteria and multidrug and glycopeptide resistances are ubiquitous in most taxa. INTRODUCTION: Every year, millions of deaths are associated with the increased spread of antimicrobial resistance genes (ARGs) in bacteria. With the increasing urbanization of the global population, the spread of ARGs in urban bacteria has become a more severe threat to human health. METHODS: In this study, we used metagenome-assembled genomes (MAGs) recovered from 1,153 urban metagenomes in multiple urban locations to investigate the fate and occurrence of ARGs in urban bacteria. Additionally, we analyzed the occurrence of these ARGs on plasmids and estimated the virulence of the bacterial species. RESULTS: Our results showed that multidrug and glycopeptide ARGs are ubiquitous among urban bacteria. Additionally, we analyzed the deterministic effects of phylogeny on the spread of these ARGs and found ARG classes that have a non-random distribution within the phylogeny of our recovered MAGs. However, few ARGs were found on plasmids and most of the recovered MAGs contained few virulence factors. DISCUSSION: Our results suggest that the observed non-random spreads of ARGs are not due to the transfer of plasmids and that most of the bacteria observed in the study are unlikely to be virulent. Additional research is needed to evaluate whether the ubiquitous and widespread ARG classes will become entirely prevalent among urban bacteria and how they spread among phylogenetically distinct species.202336760505
429680.9999Twenty-first century molecular methods for analyzing antimicrobial resistance in surface waters to support One Health assessments. Antimicrobial resistance (AMR) in the environment is a growing global health concern, especially the dissemination of AMR into surface waters due to human and agricultural inputs. Within recent years, research has focused on trying to understand the impact of AMR in surface waters on human, agricultural and ecological health (One Health). While surface water quality assessments and surveillance of AMR have historically utilized culture-based methods, culturing bacteria has limitations due to difficulty in isolating environmental bacteria and the need for a priori information about the bacteria for selective isolation. The use of molecular techniques to analyze AMR at the genetic level has helped to overcome the difficulties with culture-based techniques since they do not require advance knowledge of the bacterial population and can analyze uncultivable environmental bacteria. The aim of this review is to provide an overview of common contemporary molecular methods available for analyzing AMR in surface waters, which include high throughput real-time polymerase chain reaction (HT-qPCR), metagenomics, and whole genome sequencing. This review will also feature how these methods may provide information on human and animal health risks. HT-qPCR works at the nanoliter scale, requires only a small amount of DNA, and can analyze numerous gene targets simultaneously, but may lack in analytical sensitivity and the ability to optimize individual assays compared to conventional qPCR. Metagenomics offers more detailed genomic information and taxonomic resolution than PCR by sequencing all the microbial genomes within a sample. Its open format allows for the discovery of new antibiotic resistance genes; however, the quantity of DNA necessary for this technique can be a limiting factor for surface water samples that typically have low numbers of bacteria per sample volume. Whole genome sequencing provides the complete genomic profile of a single environmental isolate and can identify all genetic elements that may confer AMR. However, a main disadvantage of this technique is that it only provides information about one bacterial isolate and is challenging to utilize for community analysis. While these contemporary techniques can quickly provide a vast array of information about AMR in surface waters, one technique does not fully characterize AMR nor its potential risks to human, animal, or ecological health. Rather, a combination of techniques (including both molecular- and culture-based) are necessary to fully understand AMR in surface waters from a One Health perspective.202133774111
660090.9999Metagenomic approaches for the quantification of antibiotic resistance genes in swine wastewater treatment system: a systematic review. This systematic review aims to identify the metagenomic methodological approaches employed for the detection of antimicrobial resistance genes (ARGs) in swine wastewater treatment systems. The search terms used were metagenome AND bacteria AND ("antimicrobial resistance gene" OR resistome OR ARG) AND wastewater AND (swine OR pig), and the search was conducted across the following electronic databases: PubMed, Scopus, ScienceDirect, Web of Science, Embase, and Cochrane Library. The search was limited to studies published between 2020 and 2024. Of the 220 studies retrieved, eight met the eligibility criteria for full-text analysis. The number of publications in this research area has increased in recent years, with China contributing the highest number of studies. ARGs are typically identified using bioinformatics pipelines that include steps such as quality trimming, assembly, metagenome-assembled genome (MAG) reconstruction, open reading frame (ORF) prediction, and ARG annotation. However, comparing ARGs quantification across studies remains challenging due to methodological differences and variability in quantification approaches. Therefore, this systematic review highlights the need for methodological standardization to facilitate comparison and enhance our understanding of antimicrobial resistance in swine wastewater treatment systems through metagenomic approaches.202540788461
6594100.9999An omics-based framework for assessing the health risk of antimicrobial resistance genes. Antibiotic resistance genes (ARGs) are widespread among bacteria. However, not all ARGs pose serious threats to public health, highlighting the importance of identifying those that are high-risk. Here, we developed an 'omics-based' framework to evaluate ARG risk considering human-associated-enrichment, gene mobility, and host pathogenicity. Our framework classifies human-associated, mobile ARGs (3.6% of all ARGs) as the highest risk, which we further differentiate as 'current threats' (Rank I; 3%) - already present among pathogens - and 'future threats' (Rank II; 0.6%) - novel resistance emerging from non-pathogens. Our framework identified 73 'current threat' ARG families. Of these, 35 were among the 37 high-risk ARGs proposed by the World Health Organization and other literature; the remaining 38 were significantly enriched in hospital plasmids. By evaluating all pathogen genomes released since framework construction, we confirmed that ARGs that recently transferred into pathogens were significantly enriched in Rank II ('future threats'). Lastly, we applied the framework to gut microbiome genomes from fecal microbiota transplantation donors. We found that although ARGs were widespread (73% of genomes), only 8.9% of genomes contained high-risk ARGs. Our framework provides an easy-to-implement approach to identify current and future antimicrobial resistance threats, with potential clinical applications including reducing risk of microbiome-based interventions.202134362925
6570110.9999Impact of point sources on antibiotic resistance genes in the natural environment: a systematic review of the evidence. There is a growing concern about the role of the environment in the dissemination of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARG). In this systematic review, we summarize evidence for increases of ARG in the natural environment associated with potential sources of ARB and ARG such as agricultural facilities and wastewater treatment plants. A total of 5247 citations were identified, including studies that ascertained both ARG and ARB outcomes. All studies were screened for relevance to the question and methodology. This paper summarizes the evidence only for those studies with ARG outcomes (n = 24). Sixteen studies were at high (n = 3) or at unclear (n = 13) risk of bias in the estimation of source effects due to lack of information or failure to control for confounders. Statistical methods were used in nine studies; three studies assessed the effect of multiple sources using modeling approaches, and none reported effect measures. Most studies reported higher ARG concentration downstream/near the source, but heterogeneous findings hindered making any sound conclusions. To quantify increases of ARG in the environment due to specific point sources, there is a need for studies that emphasize analytic or design control of confounding, and that provide effect measure estimates.201729231804
3458120.9999MinION Nanopore Sequencing Enables Correlation between Resistome Phenotype and Genotype of Coliform Bacteria in Municipal Sewage. Wastewater treatment plants (WWTPs) functioned as the intersection between the human society and nature environment, are receiving increasingly more attention on risk assessment of the acquisition of environmental antibiotic resistance genes (ARGs) by pathogenetic populations during treatment. However, because of the general lack of robust resistome profiling methods, genotype, and resistance phenotype is still poorly correlated in human pathogens of sewage samples. Here we applied MinION sequencing to quantify the resistance genes of multiple antibiotic resistant (MAR) coliform bacteria, a common indicator for human enteric pathogens in sewage samples. Our pipeline could deliver the results within 30 h from sample collection and the resistome quantification was consistent to that based on the Illumina platform. Additionally, the long nanopore reads not only enabled a simultaneous identification of the carrier populations of ARGs detected, but also facilitated the genome reconstruction of a representative MAR strain, from which we identified an instance of chromosomal integration of environmental resistance gene obtained by plasmid exchange with a porcine pathogen. This study demonstrated the utilization of MinION sequencing in quick monitoring and simultaneous phylogenetic tracking of environmental ARGs to address potential health risk associated with them.201729163399
3460130.9998Bioprospecting for β-lactam resistance genes using a metagenomics-guided strategy. Emergence of new antibiotic resistance bacteria poses a serious threat to human health, which is largely attributed to the evolution and spread of antibiotic resistance genes (ARGs). In this work, a metagenomics-guided strategy consisting of metagenomic analysis and function validation was proposed for rapidly identifying novel ARGs from hot spots of ARG dissemination, such as wastewater treatment plants (WWTPs) and animal feces. We used an antibiotic resistance gene database to annotate 76 putative β-lactam resistance genes from the metagenomes of sludge and chicken feces. Among these 76 candidate genes, 25 target genes that shared 40~70% amino acid identity to known β-lactamases were cloned by PCR from the metagenomes. Their resistances to four β-lactam antibiotics were further demonstrated. Furthermore, the validated ARGs were used as the reference sequences to identify novel ARGs in eight environmental samples, suggesting the necessity of re-examining the profiles of ARGs in environmental samples using the validated novel ARG sequences. This metagenomics-guided pipeline does not rely on the activity of ARGs during the initial screening process and may specifically select novel ARG sequences for function validation, which make it suitable for the high-throughput screening of novel ARGs from environmental metagenomes.201728584911
4297140.9998Predicting clinical resistance prevalence using sewage metagenomic data. Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across the world. The sewage resistome correlated to clinical surveillance data of invasive Escherichia coli isolates, but none of several tested approaches provided a sufficient resolution for clear discrimination between resistance towards different classes of antibiotics. However, in combination with socioeconomic data, the overall clinical resistance situation could be predicted with good precision. We conclude that analyses of bacterial genes in sewage could contribute to informing management of antibiotic resistance.202033244050
3884150.9998Distribution and quantification of antibiotic resistant genes and bacteria across agricultural and non-agricultural metagenomes. There is concern that antibiotic resistance can potentially be transferred from animals to humans through the food chain. The relationship between specific antibiotic resistant bacteria and the genes they carry remains to be described. Few details are known about the ecology of antibiotic resistant genes and bacteria in food production systems, or how antibiotic resistance genes in food animals compare to antibiotic resistance genes in other ecosystems. Here we report the distribution of antibiotic resistant genes in publicly available agricultural and non-agricultural metagenomic samples and identify which bacteria are likely to be carrying those genes. Antibiotic resistance, as coded for in the genes used in this study, is a process that was associated with all natural, agricultural, and human-impacted ecosystems examined, with between 0.7 to 4.4% of all classified genes in each habitat coding for resistance to antibiotic and toxic compounds (RATC). Agricultural, human, and coastal-marine metagenomes have characteristic distributions of antibiotic resistance genes, and different bacteria that carry the genes. There is a larger percentage of the total genome associated with antibiotic resistance in gastrointestinal-associated and agricultural metagenomes compared to marine and Antarctic samples. Since antibiotic resistance genes are a natural part of both human-impacted and pristine habitats, presence of these resistance genes in any specific habitat is therefore not sufficient to indicate or determine impact of anthropogenic antibiotic use. We recommend that baseline studies and control samples be taken in order to determine natural background levels of antibiotic resistant bacteria and/or antibiotic resistance genes when investigating the impacts of veterinary use of antibiotics on human health. We raise questions regarding whether the underlying biology of each type of bacteria contributes to the likelihood of transfer via the food chain.201223133629
4550160.9998Whole-genome sequencing and gene sharing network analysis powered by machine learning identifies antibiotic resistance sharing between animals, humans and environment in livestock farming. Anthropogenic environments such as those created by intensive farming of livestock, have been proposed to provide ideal selection pressure for the emergence of antimicrobial-resistant Escherichia coli bacteria and antimicrobial resistance genes (ARGs) and spread to humans. Here, we performed a longitudinal study in a large-scale commercial poultry farm in China, collecting E. coli isolates from both farm and slaughterhouse; targeting animals, carcasses, workers and their households and environment. By using whole-genome phylogenetic analysis and network analysis based on single nucleotide polymorphisms (SNPs), we found highly interrelated non-pathogenic and pathogenic E. coli strains with phylogenetic intermixing, and a high prevalence of shared multidrug resistance profiles amongst livestock, human and environment. Through an original data processing pipeline which combines omics, machine learning, gene sharing network and mobile genetic elements analysis, we investigated the resistance to 26 different antimicrobials and identified 361 genes associated to antimicrobial resistance (AMR) phenotypes; 58 of these were known AMR-associated genes and 35 were associated to multidrug resistance. We uncovered an extensive network of genes, correlated to AMR phenotypes, shared among livestock, humans, farm and slaughterhouse environments. We also found several human, livestock and environmental isolates sharing closely related mobile genetic elements carrying ARGs across host species and environments. In a scenario where no consensus exists on how antibiotic use in the livestock may affect antibiotic resistance in the human population, our findings provide novel insights into the broader epidemiology of antimicrobial resistance in livestock farming. Moreover, our original data analysis method has the potential to uncover AMR transmission pathways when applied to the study of other pathogens active in other anthropogenic environments characterised by complex interconnections between host species.202235333870
3972170.9998Characterization of the resistome and antibiotic-resistant bacteria in top soil improvers and irrigation waters devoted to food production: a case study from Italy. Biosolids and reclaimed waters are valuable resources for reintroducing organic matter into agricultural soils and reducing the water footprint of intensive agricultural food system. While the circular economy is a sustainable practice, it may introduce vulnerabilities in the food chain, by exposing crops to zoonotic agents and antimicrobial resistance determinants. This option is far from being a speculation and evidence start to accumulate indicating that the risk is tangible. This study provides further evidence that the circular economy practices of reusing biomass and reclaimed waters in agricultural setting may be vectors for the spreading of antibiotic resistance genes (ARGs) targeting molecules used to treat human bacterial infections. We screened biosolid and water samples for ARGs presence using shotgun metagenomic sequencing. We demonstrated that the identified ARGs are present in live bacterial organisms, harbouring multidrug-resistant gene clusters, confirmed through phenotypic testing and whole-genome sequencing of isolated bacteria. Additionally, we observed that most of the antibiotic-resistant bacteria identified belonged to environmentally widespread species, which were not expected to be exposed to the antimicrobials, suggesting that inter-species transfer of resistance genes.202540439791
3461180.9998Metagenomics insights into bacterial diversity and antibiotic resistome of the sewage in the city of Belém, Pará, Brazil. INTRODUCTION: The advancement of antimicrobial resistance is a significant public health issue today. With the spread of resistant bacterial strains in water resources, especially in urban sewage, metagenomic studies enable the investigation of the microbial composition and resistance genes present in these locations. This study characterized the bacterial community and antibiotic resistance genes in a sewage system that receives effluents from various sources through metagenomics. METHODS: One liter of surface water was collected at four points of a sewage channel, and after filtration, the total DNA was extracted and then sequenced on an NGS platform (Illumina® NextSeq). The sequenced data were trimmed, and the microbiome was predicted using the Kraken software, while the resistome was analyzed on the CARD webserver. All ecological and statistical analyses were performed using the. RStudio tool. RESULTS AND DISCUSSION: The complete metagenome results showed a community with high diversity at the beginning and more restricted diversity at the end of the sampling, with a predominance of the phyla Bacteroidetes, Actinobacteria, Firmicutes, and Proteobacteria. Most species were considered pathogenic, with an emphasis on those belonging to the Enterobacteriaceae family. It was possible to identify bacterial groups of different threat levels to human health according to a report by the U.S. Centers for Disease Control and Prevention. The resistome analysis predominantly revealed genes that confer resistance to multiple drugs, followed by aminoglycosides and macrolides, with efflux pumps and drug inactivation being the most prevalent resistance mechanisms. This work was pioneering in characterizing resistance in a sanitary environment in the Amazon region and reinforces that sanitation measures for urban sewage are necessary to prevent the advancement of antibiotic resistance and the contamination of water resources, as evidenced by the process of eutrophication.202439629213
6593190.9998Metagenomic analysis of human, animal, and environmental samples identifies potential emerging pathogens, profiles antibiotic resistance genes, and reveals horizontal gene transfer dynamics. Antimicrobial resistance (AMR) poses a significant threat to global health. The indiscriminate use of antibiotics has accelerated the emergence and spread of drug-resistant bacteria, compromising our ability to treat infectious diseases. A One Health approach is essential to address this urgent issue, recognizing the interconnectedness of human, animal, and environmental health. This study investigated the prevalence and transmission of AMR in a temporary settlement in Kathmandu, Nepal. By employing shotgun metagenomics, we analyzed a diverse range of samples, including human fecal samples, avian fecal samples, and environmental samples. Our analysis revealed a complex interplay of pathogenic bacteria, virulence factors (VF), and antimicrobial resistance genes (ARGs) across these different domains. We identified a diverse range of bacterial species, including potential pathogens, in both human and animal samples. Notably, Prevotella spp. was the dominant gut bacterium in human samples. Additionally, we detected a wide range of phages and viruses, including Stx-2 converting phages, which can contribute to the virulence of Shiga toxin-producing E. coli (STEC) strains. Our analysis revealed the presence of 72 virulence factor genes and 53 ARG subtypes across the studied samples. Poultry samples exhibited the highest number of ARG subtypes, suggesting that the intensive use of antibiotics in poultry production may contribute to the dissemination of AMR. Furthermore, we observed frequent horizontal gene transfer (HGT) events, with gut microbiomes serving as key reservoirs for ARGs. This study underscores the critical role of a One Health approach in addressing AMR. By integrating human, animal, and environmental health perspectives, we can better understand the complex dynamics of AMR and develop effective strategies for prevention and control. Our findings highlight the urgent need for robust surveillance systems, judicious antibiotic use, and improved hygiene practices to mitigate the impact of AMR on public health.202540204742