# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 5127 | 0 | 1.0000 | ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics. Metagenomics can be used to monitor the spread of antibiotic resistance genes (ARGs). ARGs found in databases such as ResFinder and CARD primarily originate from culturable and pathogenic bacteria, while ARGs from non-culturable and non-pathogenic bacteria remain understudied. Functional metagenomics is based on phenotypic gene selection and can identify ARGs from non-culturable bacteria with a potentially low identity shared with known ARGs. In 2016, the ResFinderFG v1.0 database was created to collect ARGs from functional metagenomics studies. Here, we present the second version of the database, ResFinderFG v2.0, which is available on the Center of Genomic Epidemiology web server (https://cge.food.dtu.dk/services/ResFinderFG/). It comprises 3913 ARGs identified by functional metagenomics from 50 carefully curated datasets. We assessed its potential to detect ARGs in comparison to other popular databases in gut, soil and water (marine + freshwater) Global Microbial Gene Catalogues (https://gmgc.embl.de). ResFinderFG v2.0 allowed for the detection of ARGs that were not detected using other databases. These included ARGs conferring resistance to beta-lactams, cycline, phenicol, glycopeptide/cycloserine and trimethoprim/sulfonamide. Thus, ResFinderFG v2.0 can be used to identify ARGs differing from those found in conventional databases and therefore improve the description of resistomes. | 2023 | 37207327 |
| 3246 | 1 | 0.9996 | Antibiotic Resistance Gene Detection in the Microbiome Context. Within the past decade, microbiologists have moved from detecting single antibiotic resistance genes (ARGs) to detecting all known resistance genes within a sample due to advances in next generation sequencing. This has provided a wealth of data on the variation and relative abundances of ARGs present in a total bacterial population. However, to use these data in terms of therapy or risk to patients, they must be analyzed in the context of the background microbiome. Using a quantitative PCR ARG chip and 16S rRNA amplicon sequencing, we have sought to identify the ARGs and bacteria present in a fecal sample of a healthy adult using genomic tools. Of the 42 ARGs detected, 12 fitted into the ResCon1 category of ARGs: cfxA, cphA, bacA, sul3, aadE, bla(TEM), aphA1, aphA3, aph(2')-Id, aacA/aphd, catA1, and vanC. Therefore, we describe these 12 genes as the core resistome of this person's fecal microbiome and the remaining 30 ARGs as descriptors of the microbial population within the fecal microbiome. The dominant phyla and genera agree with those previously detected in the greatest abundances in fecal samples of healthy humans. The majority of the ARGs detected were associated with the presence of specific bacterial taxa, which were confirmed using microbiome analysis. We acknowledge the limitations of the data in the context of the limited sample set. However, the principle of combining qPCR and microbiome analysis was shown to be helpful to identify the association of the ARGs with specific taxa. | 2018 | 29185915 |
| 5114 | 2 | 0.9995 | Datasets for benchmarking antimicrobial resistance genes in bacterial metagenomic and whole genome sequencing. Whole genome sequencing (WGS) is a key tool in identifying and characterising disease-associated bacteria across clinical, agricultural, and environmental contexts. One increasingly common use of genomic and metagenomic sequencing is in identifying the type and range of antimicrobial resistance (AMR) genes present in bacterial isolates in order to make predictions regarding their AMR phenotype. However, there are a large number of alternative bioinformatics software and pipelines available, which can lead to dissimilar results. It is, therefore, vital that researchers carefully evaluate their genomic and metagenomic AMR analysis methods using a common dataset. To this end, as part of the Microbial Bioinformatics Hackathon and Workshop 2021, a 'gold standard' reference genomic and simulated metagenomic dataset was generated containing raw sequence reads mapped against their corresponding reference genome from a range of 174 potentially pathogenic bacteria. These datasets and their accompanying metadata are freely available for use in benchmarking studies of bacteria and their antimicrobial resistance genes and will help improve tool development for the identification of AMR genes in complex samples. | 2022 | 35705638 |
| 3261 | 3 | 0.9995 | A global metagenomic map of urban microbiomes and antimicrobial resistance. We present a global atlas of 4,728 metagenomic samples from mass-transit systems in 60 cities over 3 years, representing the first systematic, worldwide catalog of the urban microbial ecosystem. This atlas provides an annotated, geospatial profile of microbial strains, functional characteristics, antimicrobial resistance (AMR) markers, and genetic elements, including 10,928 viruses, 1,302 bacteria, 2 archaea, and 838,532 CRISPR arrays not found in reference databases. We identified 4,246 known species of urban microorganisms and a consistent set of 31 species found in 97% of samples that were distinct from human commensal organisms. Profiles of AMR genes varied widely in type and density across cities. Cities showed distinct microbial taxonomic signatures that were driven by climate and geographic differences. These results constitute a high-resolution global metagenomic atlas that enables discovery of organisms and genes, highlights potential public health and forensic applications, and provides a culture-independent view of AMR burden in cities. | 2021 | 34043940 |
| 2544 | 4 | 0.9994 | Antibiotic resistance potential of the healthy preterm infant gut microbiome. BACKGROUND: Few studies have investigated the gut microbiome of infants, fewer still preterm infants. In this study we sought to quantify and interrogate the resistome within a cohort of premature infants using shotgun metagenomic sequencing. We describe the gut microbiomes from preterm but healthy infants, characterising the taxonomic diversity identified and frequency of antibiotic resistance genes detected. RESULTS: Dominant clinically important species identified within the microbiomes included C. perfringens, K. pneumoniae and members of the Staphylococci and Enterobacter genera. Screening at the gene level we identified an average of 13 antimicrobial resistance genes per preterm infant, ranging across eight different antibiotic classes, including aminoglycosides and fluoroquinolones. Some antibiotic resistance genes were associated with clinically relevant bacteria, including the identification of mecA and high levels of Staphylococci within some infants. We were able to demonstrate that in a third of the infants the S. aureus identified was unrelated using MLST or metagenome assembly, but low abundance prevented such analysis within the remaining samples. CONCLUSIONS: We found that the healthy preterm infant gut microbiomes in this study harboured a significant diversity of antibiotic resistance genes. This broad picture of resistances and the wider taxonomic diversity identified raises further caution to the use of antibiotics without consideration of the resident microbial communities. | 2017 | 28149696 |
| 5128 | 5 | 0.9994 | Whole genomes from bacteria collected at diagnostic units around the world 2020. The Two Weeks in the World research project has resulted in a dataset of 3087 clinically relevant bacterial genomes with pertaining metadata, collected from 59 diagnostic units in 35 countries around the world during 2020. A relational database is available with metadata and summary data from selected bioinformatic analysis, such as species prediction and identification of acquired resistance genes. | 2023 | 37717051 |
| 2593 | 6 | 0.9994 | Meta-genomic analysis of toilet waste from long distance flights; a step towards global surveillance of infectious diseases and antimicrobial resistance. Human populations worldwide are increasingly confronted with infectious diseases and antimicrobial resistance spreading faster and appearing more frequently. Knowledge regarding their occurrence and worldwide transmission is important to control outbreaks and prevent epidemics. Here, we performed shotgun sequencing of toilet waste from 18 international airplanes arriving in Copenhagen, Denmark, from nine cities in three world regions. An average of 18.6 Gb (14.8 to 25.7 Gb) of raw Illumina paired end sequence data was generated, cleaned, trimmed and mapped against reference sequence databases for bacteria and antimicrobial resistance genes. An average of 106,839 (0.06%) reads were assigned to resistance genes with genes encoding resistance to tetracycline, macrolide and beta-lactam resistance genes as the most abundant in all samples. We found significantly higher abundance and diversity of genes encoding antimicrobial resistance, including critical important resistance (e.g. blaCTX-M) carried on airplanes from South Asia compared to North America. Presence of Salmonella enterica and norovirus were also detected in higher amounts from South Asia, whereas Clostridium difficile was most abundant in samples from North America. Our study provides a first step towards a potential novel strategy for global surveillance enabling simultaneous detection of multiple human health threatening genetic elements, infectious agents and resistance genes. | 2015 | 26161690 |
| 3245 | 7 | 0.9994 | From Metagenomes to Functional Expression of Resistance: floR Gene Diversity in Bacteria from Salmon Farms. Background. The increase in antibiotic resistance in human-impacted environments, such as coastal waters with aquaculture activity, is related to the widespread use of antibiotics, even at sub-lethal concentrations. In Chile, the world's second largest producer of salmon, aquaculture is considered the main source of antibiotics in coastal waters. In this work, we aimed to characterize the genetic and phenotypic profiles of antibiotic resistance in bacterial communities from salmon farms. Methods. Bacterial metagenomes from an intensive aquaculture zone in southern Chile were sequenced, and the composition, abundance and sequence of antibiotic resistance genes (ARGs) were analyzed using assembled and raw read data. Total DNA from bacterial communities was used as a template to recover floR gene variants, which were tested by heterologous expression and functional characterization of phenicol resistance. Results. Prediction of ARGs in salmon farm metagenomes using more permissive parameters yielded significantly more results than the default Resistance Gene Identifier (RGI) software. ARGs grouped into drug classes showed similar abundance profiles to global ocean bacteria. The floR gene was the most abundant phenicol-resistance gene with the lowest gene counts, showing a conserved sequence although with variations from the reference floR. These differences were recovered by RGI prediction and, in greater depth, by mapping reads to the floR sequence using SNP base-calling. These variants were analyzed by heterologous expression, revealing the co-existence of high- and low-resistance sequences in the environmental bacteria. Conclusions. This study highlights the importance of combining metagenomic and phenotypic approaches to study the genetic variability in and evolution of antibiotic-resistant bacteria associated with salmon farms. | 2025 | 40001366 |
| 5106 | 8 | 0.9994 | Metagenomic diagnostics for the simultaneous detection of multiple pathogens in human stool specimens from Côte d'Ivoire: a proof-of-concept study. BACKGROUND: The intestinal microbiome is a complex community and its role in influencing human health is poorly understood. While conventional microbiology commonly attributes digestive disorders to a single microorganism, a metagenomic approach can detect multiple pathogens simultaneously and might elucidate the role of microbial communities in the pathogenesis of intestinal diseases. We present a proof-of-concept that a shotgun metagenomic approach provides useful information on the diverse composition of intestinal pathogens and antimicrobial resistance profiles in human stool samples. METHODS: In October 2012, we obtained stool specimens from patients with persistent diarrhea in south Côte d'Ivoire. Four stool samples were purposefully selected and subjected to microscopy, multiplex polymerase chain reaction (PCR), and a metagenomic approach. For the latter, we employed the National Center for Biotechnology Information nucleotide database and screened for 36 pathogenic organisms (bacteria, helminths, intestinal protozoa, and viruses) that may cause digestive disorders. We further characterized the bacterial population and the prevailing resistance patterns by comparing our metagenomic datasets with a genome-specific marker database and with a comprehensive antibiotic resistance database. RESULTS: In the four patients, the metagenomic approach identified between eight and 11 pathogen classes that potentially cause digestive disorders. For bacterial pathogens, the diagnostic agreement between multiplex PCR and metagenomics was high; yet, metagenomics diagnosed several bacteria not detected by multiplex PCR. In contrast, some of the helminth and intestinal protozoa infections detected by microscopy were missed by metagenomics. The antimicrobial resistance analysis revealed the presence of genes conferring resistance to several commonly used antibiotics. CONCLUSIONS: A metagenomic approach provides detailed information on the presence and diversity of pathogenic organisms in human stool samples. Metagenomic studies allow for in-depth molecular characterization such as the antimicrobial resistance status, which may be useful to develop setting-specific treatment algorithms. While metagenomic approaches remain challenging, the benefits of gaining new insights into intestinal microbial communities call for a broader application in epidemiologic studies. TRIAL REGISTRATION: ISRCTN86951400. | 2016 | 26391184 |
| 6591 | 9 | 0.9994 | Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries. 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 acquired AMR using the ResFinder database and a second database constructed for this study, consisting of AMR genes identified through screening environmental DNA. The pig and poultry resistomes were very different in abundance and composition. There was a significant country effect on the resistomes, more so in pigs than in poultry. We found higher AMR loads in pigs, whereas poultry resistomes were more diverse. We detected several recently described, critical AMR genes, including mcr-1 and optrA, the abundance of which differed both between host species and between countries. We found that the total acquired AMR level was associated with the overall country-specific antimicrobial usage in livestock and that countries with comparable usage patterns had similar resistomes. However, functionally determined AMR genes were not associated with total drug use. | 2018 | 30038308 |
| 4623 | 10 | 0.9994 | Capturing the Resistome: a Targeted Capture Method To Reveal Antibiotic Resistance Determinants in Metagenomes. Identification of the nucleotide sequences encoding antibiotic resistance elements and determination of their association with antibiotic resistance are critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, both of which are heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the sequences in the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2,000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probe set on DNA libraries generated from multidrug-resistant bacteria to selectively capture resistance genes reproducibly produced higher numbers of reads on target at a greater length of coverage than shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables a sensitive means of gene detection in diverse environments where genes encoding antibiotic resistance represent less than 0.1% of the metagenome. | 2019 | 31611361 |
| 6597 | 11 | 0.9994 | Exploiting 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. | 2023 | 36991496 |
| 3243 | 12 | 0.9994 | Virulence-associated and antibiotic resistance genes of microbial populations in cattle feces analyzed using a metagenomic approach. The bovine fecal microbiota impacts human food safety as well as animal health. Although the bacteria of cattle feces have been well characterized using culture-based and culture-independent methods, techniques have been lacking to correlate total community composition with community function. We used high throughput sequencing of total DNA extracted from fecal material to characterize general community composition and examine the repertoire of microbial genes present in beef cattle feces, including genes associated with antibiotic resistance and bacterial virulence. Results suggest that traditional 16S sequencing using "universal" primers to generate full-length sequence may under represent Acitinobacteria and Proteobacteria. Over eight percent (8.4%) of the sequences from our beef cattle fecal pool sample could be categorized as virulence genes, including a suite of genes associated with resistance to antibiotic and toxic compounds (RATC). This is a higher proportion of virulence genes found in Sargasso sea, chicken cecum, and cow rumen samples, but comparable to the proportion found in Antarctic marine derived lake, human fecal, and farm soil samples. The quantitative nature of metagenomic data, combined with the large number of RATC classes represented in samples from widely different habitats indicates that metagenomic data can be used to track relative amounts of antibiotic resistance genes in individual animals over time. Consequently, these data can be used to generate sample-specific and temporal antibiotic resistance gene profiles to facilitate an understanding of the ecology of the microbial communities in each habitat as well as the epidemiology of antibiotic resistant gene transport between and among habitats. | 2011 | 21167876 |
| 3460 | 13 | 0.9994 | Bioprospecting 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. | 2017 | 28584911 |
| 3770 | 14 | 0.9994 | Detection of mobile genetic elements associated with antibiotic resistance in Salmonella enterica using a newly developed web tool: MobileElementFinder. OBJECTIVES: Antimicrobial resistance (AMR) in clinically relevant bacteria is a growing threat to public health globally. In these bacteria, antimicrobial resistance genes are often associated with mobile genetic elements (MGEs), which promote their mobility, enabling them to rapidly spread throughout a bacterial community. METHODS: The tool MobileElementFinder was developed to enable rapid detection of MGEs and their genetic context in assembled sequence data. MGEs are detected based on sequence similarity to a database of 4452 known elements augmented with annotation of resistance genes, virulence factors and detection of plasmids. RESULTS: MobileElementFinder was applied to analyse the mobilome of 1725 sequenced Salmonella enterica isolates of animal origin from Denmark, Germany and the USA. We found that the MGEs were seemingly conserved according to multilocus ST and not restricted to either the host or the country of origin. Moreover, we identified putative translocatable units for specific aminoglycoside, sulphonamide and tetracycline genes. Several putative composite transposons were predicted that could mobilize, among others, AMR, metal resistance and phosphodiesterase genes associated with macrophage survivability. This is, to our knowledge, the first time the phosphodiesterase-like pdeL has been found to be potentially mobilized into S. enterica. CONCLUSIONS: MobileElementFinder is a powerful tool to study the epidemiology of MGEs in a large number of genome sequences and to determine the potential for genomic plasticity of bacteria. This web service provides a convenient method of detecting MGEs in assembled sequence data. MobileElementFinder can be accessed at https://cge.cbs.dtu.dk/services/MobileElementFinder/. | 2021 | 33009809 |
| 6595 | 15 | 0.9993 | Methodological 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. | 2025 | 39954816 |
| 3124 | 16 | 0.9993 | A novel microbial source tracking microarray for pathogen detection and fecal source identification in environmental systems. Pathogen detection and the identification of fecal contamination sources are challenging in environmental waters. Factors including pathogen diversity and ubiquity of fecal indicator bacteria hamper risk assessment and remediation of contamination sources. A custom microarray targeting pathogens (viruses, bacteria, protozoa), microbial source tracking (MST) markers, and antibiotic resistance genes was tested against DNA obtained from whole genome amplification (WGA) of RNA and DNA from sewage and animal (avian, cattle, poultry, and swine) feces. Perfect and mismatch probes established the specificity of the microarray in sewage, and fluorescence decrease of positive probes over a 1:10 dilution series demonstrated semiquantitative measurement. Pathogens, including norovirus, Campylobacter fetus, Helicobacter pylori, Salmonella enterica, and Giardia lamblia were detected in sewage, as well as MST markers and resistance genes to aminoglycosides, beta-lactams, and tetracycline. Sensitivity (percentage true positives) of MST results in sewage and animal waste samples (21-33%) was lower than specificity (83-90%, percentage of true negatives). Next generation DNA sequencing revealed two dominant bacterial families that were common to all sample types: Ruminococcaceae and Lachnospiraceae. Five dominant phyla and 15 dominant families comprised 97% and 74%, respectively, of sequences from all fecal sources. Phyla and families not represented on the microarray are possible candidates for inclusion in subsequent array designs. | 2015 | 25970344 |
| 4977 | 17 | 0.9993 | In silico analyses of diversity and dissemination of antimicrobial resistance genes and mobile genetics elements, for plasmids of enteric pathogens. INTRODUCTION: The antimicrobial resistance (AMR) mobilome plays a key role in the dissemination of resistance genes encoded by mobile genetics elements (MGEs) including plasmids, transposons (Tns), and insertion sequences (ISs). These MGEs contribute to the dissemination of multidrug resistance (MDR) in enteric bacterial pathogens which have been considered as a global public health risk. METHODS: To further understand the diversity and distribution of AMR genes and MGEs across different plasmid types, we utilized multiple sequence-based computational approaches to evaluate AMR-associated plasmid genetics. A collection of 1,309 complete plasmid sequences from Gammaproteobacterial species, including 100 plasmids from each of the following 14 incompatibility (Inc) types: A/C, BO, FIA, FIB, FIC, FIIA, HI1, HI2, I1, K, M, N, P except W, where only 9 sequences were available, was extracted from the National Center for Biotechnology Information (NCBI) GenBank database using BLAST tools. The extracted FASTA files were analyzed using the AMRFinderPlus web-based tools to detect antimicrobial, disinfectant, biocide, and heavy metal resistance genes and ISFinder to identify IS/Tn MGEs within the plasmid sequences. RESULTS AND DISCUSSION: In silico prediction based on plasmid replicon types showed that the resistance genes were diverse among plasmids, yet multiple genes were widely distributed across the plasmids from enteric bacterial species. These findings provide insights into the diversity of resistance genes and that MGEs mediate potential transmission of these genes across multiple plasmid replicon types. This notion was supported by the observation that many IS/Tn MGEs and resistance genes known to be associated with them were common across multiple different plasmid types. Our results provide critical insights about how the diverse population of resistance genes that are carried by the different plasmid types can allow for the dissemination of AMR across enteric bacteria. The results also highlight the value of computational-based approaches and in silico analyses for the assessment of AMR and MGEs, which are important elements of molecular epidemiology and public health outcomes. | 2022 | 36777021 |
| 4563 | 18 | 0.9993 | Prophages as a source of antimicrobial resistance genes in the human microbiome. Prophages-viruses that integrate into bacterial genomes-are ubiquitous in the microbial realm. Prophages contribute significantly to horizontal gene transfer, including the potential spread of antimicrobial resistance (AMR) genes, because they can collect host genes. Understanding their role in the human microbiome is essential for fully understanding AMR dynamics and possible clinical implications. We analysed almost 15,000 bacterial genomes for prophages and AMR genes. The bacteria were isolated from diverse human body sites and geographical regions, and their genomes were retrieved from GenBank. AMR genes were detected in 6.6% of bacterial genomes, with a higher prevalence in people with symptomatic diseases. We found a wide variety of AMR genes combating multiple drug classes. We discovered AMR genes previously associated with plasmids, such as blaOXA-23 in Acinetobacter baumannii prophages or genes found in prophages in species they had not been previously described in, such as mefA-msrD in Gardnerella prophages, suggesting prophage-mediated gene transfer of AMR genes. Prophages encoding AMR genes were found at varying frequencies across body sites and geographical regions, with Asia showing the highest diversity of AMR genes. | 2025 | 40166311 |
| 3232 | 19 | 0.9993 | Metagenome-Based Analysis of the Microbial Community Structure and Drug-Resistance Characteristics of Livestock Feces in Anhui Province, China. 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. | 2024 | 38393105 |