# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9068 | 0 | 0.9918 | TnCentral: a Prokaryotic Transposable Element Database and Web Portal for Transposon Analysis. We describe here the structure and organization of TnCentral (https://tncentral.proteininformationresource.org/ [or the mirror link at https://tncentral.ncc.unesp.br/]), a web resource for prokaryotic transposable elements (TE). TnCentral currently contains ∼400 carefully annotated TE, including transposons from the Tn3, Tn7, Tn402, and Tn554 families; compound transposons; integrons; and associated insertion sequences (IS). These TE carry passenger genes, including genes conferring resistance to over 25 classes of antibiotics and nine types of heavy metal, as well as genes responsible for pathogenesis in plants, toxin/antitoxin gene pairs, transcription factors, and genes involved in metabolism. Each TE has its own entry page, providing details about its transposition genes, passenger genes, and other sequence features required for transposition, as well as a graphical map of all features. TnCentral content can be browsed and queried through text- and sequence-based searches with a graphic output. We describe three use cases, which illustrate how the search interface, results tables, and entry pages can be used to explore and compare TE. TnCentral also includes downloadable software to facilitate user-driven identification, with manual annotation, of certain types of TE in genomic sequences. Through the TnCentral homepage, users can also access TnPedia, which provides comprehensive reviews of the major TE families, including an extensive general section and specialized sections with descriptions of insertion sequence and transposon families. TnCentral and TnPedia are intuitive resources that can be used by clinicians and scientists to assess TE diversity in clinical, veterinary, and environmental samples. IMPORTANCE The ability of bacteria to undergo rapid evolution and adapt to changing environmental circumstances drives the public health crisis of multiple antibiotic resistance, as well as outbreaks of disease in economically important agricultural crops and animal husbandry. Prokaryotic transposable elements (TE) play a critical role in this. Many carry "passenger genes" (not required for the transposition process) conferring resistance to antibiotics or heavy metals or causing disease in plants and animals. Passenger genes are spread by normal TE transposition activities and by insertion into plasmids, which then spread via conjugation within and across bacterial populations. Thus, an understanding of TE composition and transposition mechanisms is key to developing strategies to combat bacterial pathogenesis. Toward this end, we have developed TnCentral, a bioinformatics resource dedicated to describing and exploring the structural and functional features of prokaryotic TE whose use is intuitive and accessible to users with or without bioinformatics expertise. | 2021 | 34517763 |
| 9066 | 1 | 0.9915 | VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria. VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile. | 2018 | 28077405 |
| 9076 | 2 | 0.9911 | ResiDB: An automated database manager for sequence data. The amount of publicly available DNA sequence data is drastically increasing, making it a tedious task to create sequence databases necessary for the design of diagnostic assays. The selection of appropriate sequences is especially challenging in genes affected by frequent point mutations such as antibiotic resistance genes. To overcome this issue, we have designed the webtool resiDB, a rapid and user-friendly sequence database manager for bacteria, fungi, viruses, protozoa, invertebrates, plants, archaea, environmental and whole genome shotgun sequence data. It automatically identifies and curates sequence clusters to create custom sequence databases based on user-defined input sequences. A collection of helpful visualization tools gives the user the opportunity to easily access, evaluate, edit, and download the newly created database. Consequently, researchers do no longer have to manually manage sequence data retrieval, deal with hardware limitations, and run multiple independent software tools, each having its own requirements, input and output formats. Our tool was developed within the H2020 project FAPIC aiming to develop a single diagnostic assay targeting all sepsis-relevant pathogens and antibiotic resistance mechanisms. ResiDB is freely accessible to all users through https://residb.ait.ac.at/. | 2021 | 33495705 |
| 4556 | 3 | 0.9909 | Genomic analysis of diverse environmental Acinetobacter isolates identifies plasmids, antibiotic resistance genes, and capsular polysaccharides shared with clinical strains. Acinetobacter baumannii, an important pathogen known for its widespread antibiotic resistance, has been the focus of extensive research within its genus, primarily involving clinical isolates. Consequently, data on environmental A. baumannii and other Acinetobacter species remain limited. Here, we utilized Illumina and Nanopore sequencing to analyze the genomes of 10 Acinetobacter isolates representing 6 different species sourced from aquatic environments in South Australia. All 10 isolates were phylogenetically distinct compared to clinical and other non-clinical Acinetobacter strains, often tens of thousands of single-nucleotide polymorphisms from their nearest neighbors. Despite the genetic divergence, we identified pdif modules (sections of mobilized DNA) carrying clinically important antimicrobial resistance genes in species other than A. baumannii, including carbapenemase oxa58, tetracycline resistance gene tet(39), and macrolide resistance genes msr(E)-mph(E). These pdif modules were located on plasmids with high sequence identity to those circulating in globally distributed A. baumannii ST1 and ST2 clones. The environmental A. baumannii isolate characterized here (SAAb472; ST350) did not possess any native plasmids; however, it could capture two clinically important plasmids (pRAY and pACICU2) with high transfer frequencies. Furthermore, A. baumannii SAAb472 possessed virulence genes and a capsular polysaccharide type analogous to clinical strains. Our findings highlight the potential for environmental Acinetobacter species to acquire and disseminate clinically important antimicrobial resistance genes, underscoring the need for further research into the ecology and evolution of this important genus.IMPORTANCEAntimicrobial resistance (AMR) is a global threat to human, animal, and environmental health. Studying AMR in environmental bacteria is crucial to understand the emergence and dissemination of resistance genes and pathogens, and to identify potential reservoirs and transmission routes. This study provides novel insights into the genomic diversity and AMR potential of environmental Acinetobacter species. By comparing the genomes of aquatic Acinetobacter isolates with clinical and non-clinical strains, we revealed that they are highly divergent yet carry pdif modules that encode resistance to antibiotics commonly used in clinical settings. We also demonstrated that an environmental A. baumannii isolate can acquire clinically relevant plasmids and carries virulence factors similar to those of hospital-associated strains. These findings suggest that environmental Acinetobacter species may serve as reservoirs and vectors of clinically important genes. Consequently, further research is warranted to comprehensively understand the ecology and evolution of this genus. | 2024 | 38206028 |
| 5119 | 4 | 0.9909 | ROCker models for reliable detection and typing of short-read sequences carrying mcr, erm, mph, and lnu antibiotic resistance genes. Quantitative monitoring of emerging antimicrobial resistance genes (ARGs) using short-read sequences remains challenging due to the high frequency of amino acid functional domains and motifs shared with related but functionally distinct (non-target) proteins. To facilitate ARG monitoring efforts using unassembled short reads, we present novel ROCker models for mcr, mph, erm, and lnu ARG families, as well as models for variants of special public health concern within these families, including mcr-1, mphA, ermB, lnuF, lnuB, and lnuG genes. For this, we curated target gene sequence sets for model training and built these models using the recently updated ROCker V2 pipeline (Gerhardt et al., in review). To validate our models, we simulated reads from the whole genome of ARG-carrying isolates spanning a range of common read lengths and used them to challenge the filtering efficacy of ROCker versus common static filtering approaches, such as similarity searches using BLASTx with various e-value thresholds or hidden Markov models. ROCker models consistently showed F1 scores up to 10× higher (31% higher on average) and lower false-positive (by 30%, on average) and false-negative (by 16%, on average) rates based on 250 bp reads compared to alternative methods. The ROCker models and all related reference materials and data are freely available through http://enve-omics.ce.gatech.edu/rocker/models, further expanding the available model collection previously developed for other genes. Their application to short-read metagenomes, metatranscriptomes, and PCR amplicon data should facilitate more accurate classification and quantification of unassembled short-read sequences for these ARG families and specific genes.IMPORTANCEAntimicrobial resistance gene families encoding erm and mph genes confer resistance to the macrolide class of antimicrobials, which are used to treat a wide range of infections. Similarly, the mcr gene family confers resistance to polymyxin E (colistin), a drug of last resort for many serious drug-resistant bacterial infections, and the lnu gene family confers resistance to lincomycin, which is reserved for patients allergic to penicillin or where bacteria have developed resistance to other antimicrobials. Assessing the prevalence of these genes in clinical or environmental samples and monitoring their spread to new pathogens are thus important for quantifying the associated public health risk. However, detecting these and other resistance genes in short-read sequence data is technically challenging. Our ROCker bioinformatic pipeline achieves reliable detection and typing of broad-range target gene sequences in complex data sets, thus contributing toward solving an important problem in ongoing surveillance efforts of antimicrobial resistance. | 2025 | 41143534 |
| 1871 | 5 | 0.9908 | Phylogeographical Landscape of Citrobacter portucalensis Carrying Clinically Relevant Resistomes. During a surveillance study conducted to assess the occurrence and genomic landscape of critical priority pathogens circulating at the human-animal-environment interface in Brazil, as part of the Grand Challenges Explorations-New Approaches to Characterize the Global Burden of Antimicrobial Resistance program, two multidrug-resistant (MDR) Citrobacter portucalensis carrying bla(CTX-M-15) extended-spectrum β-lactamase (ESBL) genes, isolated from green sea turtles, were characterized. Genomic and phylogeographical analysis of C. portucalensis genomes available in public databases revealed the intercontinental dissemination of clades carrying different arrays of clinically relevant genes conferring resistance to carbapenems, broad-spectrum cephalosporins, cephamycins, aminoglycosides and fluoroquinolones, disinfectants, and heavy metals. Our observations suggest that C. portucalensis could be emerging as critical priority bacteria of both public and One Health importance worldwide. IMPORTANCE The global spread of antibiotic-resistant priority pathogens beyond the hospital setting is a critical issue within a One Health context that integrates the human-animal-environment interfaces. On the other hand, next-generation sequencing technologies along with user-friendly and high-quality bioinformatics tools have improved the identification of bacterial species, and bacterial resistance surveillance. The novel Citrobacter portucalensis species was proposed in 2017 after taxonomic reclassification and definition of the strain A60(T) isolated in 2008. Here, we presented genomic data showing the occurrence of multidrug-resistant C. portucalensis isolates carrying bla(CTX-M-15) ESBL genes in South America. Additionally, we observed the intercontinental dissemination of clades harboring a broad resistome to clinically relevant antibiotics. Therefore, these findings highlight that C. portucalensis is a global MDR bacteria that carries intrinsic bla(CMY)- and qnrB-type genes and has become a critical priority pathogen due to the acquisition of clinically relevant resistance determinants, such as ESBL and carbapenemase-encoding genes. | 2022 | 35357225 |
| 9880 | 6 | 0.9908 | Plasmid Classification in an Era of Whole-Genome Sequencing: Application in Studies of Antibiotic Resistance Epidemiology. Plasmids are extra-chromosomal genetic elements ubiquitous in bacteria, and commonly transmissible between host cells. Their genomes include variable repertoires of 'accessory genes,' such as antibiotic resistance genes, as well as 'backbone' loci which are largely conserved within plasmid families, and often involved in key plasmid-specific functions (e.g., replication, stable inheritance, mobility). Classifying plasmids into different types according to their phylogenetic relatedness provides insight into the epidemiology of plasmid-mediated antibiotic resistance. Current typing schemes exploit backbone loci associated with replication (replicon typing), or plasmid mobility (MOB typing). Conventional PCR-based methods for plasmid typing remain widely used. With the emergence of whole-genome sequencing (WGS), large datasets can be analyzed using in silico plasmid typing methods. However, short reads from popular high-throughput sequencers can be challenging to assemble, so complete plasmid sequences may not be accurately reconstructed. Therefore, localizing resistance genes to specific plasmids may be difficult, limiting epidemiological insight. Long-read sequencing will become increasingly popular as costs decline, especially when resolving accurate plasmid structures is the primary goal. This review discusses the application of plasmid classification in WGS-based studies of antibiotic resistance epidemiology; novel in silico plasmid analysis tools are highlighted. Due to the diverse and plastic nature of plasmid genomes, current typing schemes do not classify all plasmids, and identifying conserved, phylogenetically concordant genes for subtyping and phylogenetics is challenging. Analyzing plasmids as nodes in a network that represents gene-sharing relationships between plasmids provides a complementary way to assess plasmid diversity, and allows inferences about horizontal gene transfer to be made. | 2017 | 28232822 |
| 9067 | 7 | 0.9908 | PIPdb: a comprehensive plasmid sequence resource for tracking the horizontal transfer of pathogenic factors and antimicrobial resistance genes. Plasmids, as independent genetic elements, carrying resistance or virulence genes and transfer them among different pathogens, posing a significant threat to human health. Under the 'One Health' approach, it is crucial to control the spread of plasmids carrying such genes. To achieve this, a comprehensive characterization of plasmids in pathogens is essential. Here we present the Plasmids in Pathogens Database (PIPdb), a pioneering resource that includes 792 964 plasmid segment clusters (PSCs) derived from 1 009 571 assembled genomes across 450 pathogenic species from 110 genera. To our knowledge, PIPdb is the first database specifically dedicated to plasmids in pathogenic bacteria, offering detailed multi-dimensional metadata such as collection date, geographical origin, ecosystem, host taxonomy, and habitat. PIPdb also provides extensive functional annotations, including plasmid type, insertion sequences, integron, oriT, relaxase, T4CP, virulence factors genes, heavy metal resistance genes and antibiotic resistance genes. The database features a user-friendly interface that facilitates studies on plasmids across diverse host taxa, habitats, and ecosystems, with a focus on those carrying antimicrobial resistance genes (ARGs). We have integrated online tools for plasmid identification and annotation from assembled genomes. Additionally, PIPdb includes a risk-scoring system for identifying potentially high-risk plasmids. The PIPdb web interface is accessible at https://nmdc.cn/pipdb. | 2025 | 39460620 |
| 5115 | 8 | 0.9908 | Search Engine for Antimicrobial Resistance: A Cloud Compatible Pipeline and Web Interface for Rapidly Detecting Antimicrobial Resistance Genes Directly from Sequence Data. BACKGROUND: Antimicrobial resistance remains a growing and significant concern in human and veterinary medicine. Current laboratory methods for the detection and surveillance of antimicrobial resistant bacteria are limited in their effectiveness and scope. With the rapidly developing field of whole genome sequencing beginning to be utilised in clinical practice, the ability to interrogate sequencing data quickly and easily for the presence of antimicrobial resistance genes will become increasingly important and useful for informing clinical decisions. Additionally, use of such tools will provide insight into the dynamics of antimicrobial resistance genes in metagenomic samples such as those used in environmental monitoring. RESULTS: Here we present the Search Engine for Antimicrobial Resistance (SEAR), a pipeline and web interface for detection of horizontally acquired antimicrobial resistance genes in raw sequencing data. The pipeline provides gene information, abundance estimation and the reconstructed sequence of antimicrobial resistance genes; it also provides web links to additional information on each gene. The pipeline utilises clustering and read mapping to annotate full-length genes relative to a user-defined database. It also uses local alignment of annotated genes to a range of online databases to provide additional information. We demonstrate SEAR's application in the detection and abundance estimation of antimicrobial resistance genes in two novel environmental metagenomes, 32 human faecal microbiome datasets and 126 clinical isolates of Shigella sonnei. CONCLUSIONS: We have developed a pipeline that contributes to the improved capacity for antimicrobial resistance detection afforded by next generation sequencing technologies, allowing for rapid detection of antimicrobial resistance genes directly from sequencing data. SEAR uses raw sequencing data via an intuitive interface so can be run rapidly without requiring advanced bioinformatic skills or resources. Finally, we show that SEAR is effective in detecting antimicrobial resistance genes in metagenomic and isolate sequencing data from both environmental metagenomes and sequencing data from clinical isolates. | 2015 | 26197475 |
| 3785 | 9 | 0.9907 | A network approach to decipher the dynamics of Lysobacteraceae plasmid gene sharing. Plasmids provide an efficient vehicle for gene sharing among bacterial populations, playing a key role in bacterial evolution. Network approaches are particularly suitable to represent multipartite relationships and are useful tools to characterize plasmid-mediated gene sharing events. The bacterial family Lysobacteraceae includes plant commensal, plant pathogenic and opportunistic human pathogens for which plasmid-mediated adaptation has been reported. We searched for homologues of plasmid gene sequences from this family in the entire diversity of available bacterial genome sequences and built a network of plasmid gene sharing from the results. While plasmid genes are openly shared between the bacteria of the family Lysobacteraceae, taxonomy strongly defined the boundaries of these exchanges, which only barely reached other families. Most inferred plasmid gene sharing events involved a few genes only, and evidence of full plasmid transfers were restricted to taxonomically closely related taxa. We detected multiple plasmid-chromosome gene transfers, including the known sharing of a heavy metal resistance transposon. In the network, bacterial lifestyles shaped substructures of isolates colonizing specific ecological niches and harbouring specific types of resistance genes. Genes associated with pathogenicity or antibiotic and metal resistance were among those that most importantly structured the network, highlighting the imprints of human-mediated selective pressure on pathogenic populations. A massive sequencing effort on environmental Lysobacteraceae is therefore required to refine our understanding of how this reservoir fuels the emergence and the spread of genes among this family and its potential impact on plant, animal and human health. | 2023 | 35593155 |
| 5126 | 10 | 0.9907 | Blanket antimicrobial resistance gene database with structural information, BOARDS, provides insights on historical landscape of resistance prevalence and effects of mutations in enzyme structure. Antimicrobial resistance (AMR) in pathogenic bacteria poses a significant threat to public health, yet there is still a need for development in the tools to deeply understand AMR genes based on genetic or structural information. In this study, we present an interactive web database named Blanket Overarching Antimicrobial-Resistance gene Database with Structural information (BOARDS, sbml.unist.ac.kr), a database that comprehensively includes 3,943 reported AMR gene information for 1,997 extended spectrum beta-lactamase (ESBL) and 1,946 other genes as well as a total of 27,395 predicted protein structures. These structures, which include both wild-type AMR genes and their mutants, were derived from 80,094 publicly available whole-genome sequences. In addition, we developed the rapid analysis and detection tool of antimicrobial-resistance (RADAR), a one-stop analysis pipeline to detect AMR genes across whole-genome sequencing (WGSs). By integrating BOARDS and RADAR, the AMR prevalence landscape for eight multi-drug resistant pathogens was reconstructed, leading to unexpected findings such as the pre-existence of the MCR genes before their official reports. Enzymatic structure prediction-based analysis revealed that the occurrence of mutations found in some ESBL genes was found to be closely related to the binding affinities with their antibiotic substrates. Overall, BOARDS can play a significant role in performing in-depth analysis on AMR.IMPORTANCEWhile the increasing antibiotic resistance (AMR) in pathogen has been a burden on public health, effective tools for deep understanding of AMR based on genetic or structural information remain limited. In this study, a blanket overarching antimicrobial-resistance gene database with structure information (BOARDS)-a web-based database that comprehensively collected AMR gene data with predictive protein structural information was constructed. Additionally, we report the development of a RADAR pipeline that can analyze whole-genome sequences as well. BOARDS, which includes sequence and structural information, has shown the historical landscape and prevalence of the AMR genes and can provide insight into single-nucleotide polymorphism effects on antibiotic degrading enzymes within protein structures. | 2024 | 38085058 |
| 3776 | 11 | 0.9907 | FARME DB: a functional antibiotic resistance element database. Antibiotic resistance (AR) is a major global public health threat but few resources exist that catalog AR genes outside of a clinical context. Current AR sequence databases are assembled almost exclusively from genomic sequences derived from clinical bacterial isolates and thus do not include many microbial sequences derived from environmental samples that confer resistance in functional metagenomic studies. These environmental metagenomic sequences often show little or no similarity to AR sequences from clinical isolates using standard classification criteria. In addition, existing AR databases provide no information about flanking sequences containing regulatory or mobile genetic elements. To help address this issue, we created an annotated database of DNA and protein sequences derived exclusively from environmental metagenomic sequences showing AR in laboratory experiments. Our Functional Antibiotic Resistant Metagenomic Element (FARME) database is a compilation of publically available DNA sequences and predicted protein sequences conferring AR as well as regulatory elements, mobile genetic elements and predicted proteins flanking antibiotic resistant genes. FARME is the first database to focus on functional metagenomic AR gene elements and provides a resource to better understand AR in the 99% of bacteria which cannot be cultured and the relationship between environmental AR sequences and antibiotic resistant genes derived from cultured isolates.Database URL: http://staff.washington.edu/jwallace/farme. | 2017 | 28077567 |
| 6507 | 12 | 0.9907 | What Are the Drivers Triggering Antimicrobial Resistance Emergence and Spread? Outlook from a One Health Perspective. Antimicrobial resistance (AMR) has emerged as a critical global public health threat, exacerbating healthcare burdens and imposing substantial economic costs. Currently, AMR contributes to nearly five million deaths annually worldwide, surpassing mortality rates of any single infectious disease. The economic burden associated with AMR-related disease management is estimated at approximately $730 billion per year. This review synthesizes current research on the mechanisms and multifaceted drivers of AMR development and dissemination through the lens of the One Health framework, which integrates human, animal, and environmental health perspectives. Intrinsic factors, including antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs), enable bacteria to evolve adaptive resistance mechanisms such as enzymatic inactivation, efflux pumps, and biofilm formation. Extrinsic drivers span environmental stressors (e.g., antimicrobials, heavy metals, disinfectants), socioeconomic practices, healthcare policies, and climate change, collectively accelerating AMR proliferation. Horizontal gene transfer and ecological pressures further facilitate the spread of antimicrobial-resistant bacteria across ecosystems. The cascading impacts of AMR threaten human health and agricultural productivity, elevate foodborne infection risks, and impose substantial economic burdens, particularly in low- and middle-income countries. To address this complex issue, the review advocates for interdisciplinary collaboration, robust policy implementation (e.g., antimicrobial stewardship), and innovative technologies (e.g., genomic surveillance, predictive modeling) under the One Health paradigm. Such integrated strategies are essential to mitigate AMR transmission, safeguard global health, and ensure sustainable development. | 2025 | 40558133 |
| 6656 | 13 | 0.9907 | Understanding the Evolution and Transmission Dynamics of Antibiotic Resistance Genes: A Comprehensive Review. Antibiotic resistance poses a formidable challenge to global public health, necessitating comprehensive understanding and strategic interventions. This review explores the evolution and transmission dynamics of antibiotic resistance genes, with a focus on Bangladesh. The indiscriminate use of antibiotics, compounded by substandard formulations and clinical misdiagnosis, fuels the emergence and spread of resistance in the country. Studies reveal high resistance rates among common pathogens, emphasizing the urgent need for targeted interventions and rational antibiotic use. Molecular assessments uncover a diverse array of antibiotic resistance genes in environmental reservoirs, highlighting the complex interplay between human activities and resistance dissemination. Horizontal gene transfer mechanisms, particularly plasmid-mediated conjugation, facilitate the exchange of resistance determinants among bacterial populations, driving the evolution of multidrug-resistant strains. The review discusses clinical implications, emphasizing the interconnectedness of environmental and clinical settings in resistance dynamics. Furthermore, bioinformatic and experimental evidence elucidates novel mechanisms of resistance gene transfer, underscoring the dynamic nature of resistance evolution. In conclusion, combating antibiotic resistance requires a multifaceted approach, integrating surveillance, stewardship, and innovative research to preserve the efficacy of antimicrobial agents and safeguard public health. | 2024 | 39113256 |
| 4999 | 14 | 0.9907 | Dissemination Routes of Carbapenem and Pan-Aminoglycoside Resistance Mechanisms in Hospital and Urban Wastewater Canalizations of Ghana. Wastewater has a major role in antimicrobial resistance (AMR) dynamics and public health. The impact on AMR of wastewater flux at the community-hospital interface in low- and middle-income countries (LMICs) is poorly understood. Therefore, the present study analyzed the epidemiological scenario of resistance genes, mobile genetic elements (MGEs), and bacterial populations in wastewater around the Tamale metropolitan area (Ghana). Wastewater samples were collected from the drainage and canalizations before and after three hospitals and one urban waste treatment plant (UWTP). From all carbapenem/pan-aminoglycoside-resistant bacteria, 36 isolates were selected to determine bacterial species and phenotypical resistance profiles. Nanopore sequencing was used to screen resistance genes and plasmids, whereas, sequence types, resistome and plasmidome contents, pan-genome structures, and resistance gene variants were analyzed with Illumina sequencing. The combination of these sequencing data allowed for the resolution of the resistance gene-carrying platforms. Hospitals and the UWTP collected genetic and bacterial elements from community wastewater and amplified successful resistance gene-bacterium associations, which reached the community canalizations. Uncommon carbapenemase/β-lactamase gene variants, like bla(DIM-1), and novel variants, including bla(VIM-71), bla(CARB-53), and bla(CMY-172), were identified and seem to spread via clonal expansion of environmental Pseudomonas spp. However, bla(NDM-1), bla(CTX-M-15), and armA genes, among others, were associated with MGEs that allowed for their dissemination between environmental and clinical bacterial hosts. In conclusion, untreated hospital wastewater in Ghana is a hot spot for the emergence and spread of genes and gene-plasmid-bacterium associations that accelerate AMR, including to last-resort antibiotics. Urgent actions must be taken in wastewater management in LMICs in order to delay AMR expansion. IMPORTANCE Antimicrobial resistance (AMR) is one the major threats to public health today, especially resistance to last-resort compounds for the treatment of critical infections, such as carbapenems and aminoglycosides. Innumerable works have focused on the clinical ambit of AMR, but studies addressing the impact of wastewater cycles on the emergence and dissemination of resistant bacteria are still limited. The lack of knowledge is even greater when referring to low- and middle-income countries, where there is an absence of accurate sanitary systems. Furthermore, the combination of short- and long-read sequencing has surpassed former technical limitations, allowing the complete characterization of resistance genes, mobile genetic platforms, plasmids, and bacteria. The present study deciphered the multiple elements and routes involved in AMR dynamics in wastewater canalizations and, therefore, in the local population of Tamale, providing the basis to adopt accurate control measures to preserve and promote public health. | 2022 | 35103490 |
| 9077 | 15 | 0.9906 | The PLSDB 2025 update: enhanced annotations and improved functionality for comprehensive plasmid research. Plasmids are extrachromosomal DNA molecules in bacteria and archaea, playing critical roles in horizontal gene transfer, antibiotic resistance, and pathogenicity. Since its first release in 2018, our database on plasmids, PLSDB, has significantly grown and enhanced its content and scope. From 34 513 records contained in the 2021 version, PLSDB now hosts 72 360 entries. Designed to provide life scientists with convenient access to extensive plasmid data and to support computer scientists by offering curated datasets for artificial intelligence (AI) development, this latest update brings more comprehensive and accurate information for plasmid research, with interactive visualization options. We enriched PLSDB by refining the identification and classification of plasmid host ecosystems and host diseases. Additionally, we incorporated annotations for new functional structures, including protein-coding genes and biosynthetic gene clusters. Further, we enhanced existing annotations, such as antimicrobial resistance genes and mobility typing. To accommodate these improvements and to host the increase plasmid sets, the webserver architecture and underlying data structures of PLSDB have been re-reconstructed, resulting in decreased response times and enhanced visualization of features while ensuring that users have access to a more efficient and user-friendly interface. The latest release of PLSDB is freely accessible at https://www.ccb.uni-saarland.de/plsdb2025. | 2025 | 39565221 |
| 4551 | 16 | 0.9906 | Genomic insights into virulence, antimicrobial resistance, and adaptation acumen of Escherichia coli isolated from an urban environment. Populations of common commensal bacteria such as Escherichia coli undergo genetic changes by the acquisition of certain virulence and antimicrobial resistance (AMR) encoding genetic elements leading to the emergence of pathogenic strains capable of surviving in the previously uninhabited or protected niches. These bacteria are also reported to be prevalent in the environment where they survive by adopting various recombination strategies to counter microflora of the soil and water, under constant selection pressure(s). In this study, we performed molecular characterization, phenotypic AMR analysis, and whole genome sequencing (WGS) of E. coli (n = 37) isolated from soil and surface water representing the urban and peri-urban areas. The primary aim of this study was to understand the genetic architecture and pathogenic acumen exhibited by environmental E. coli. WGS-based analysis entailing resistome and virulome profiling indicated the presence of various virulence (adherence, iron uptake, and toxins) and AMR encoding genes, including bla(NDM-5) in the environmental isolates. A majority of our isolates belonged to phylogroup B1 (73%). A few isolates in our collection were of sequence type(s) (ST) 58 and 224 that could have emerged recently as clonal lineages and might pose risk of infection/transmission. Mobile genetic elements (MGEs) such as plasmids (predominantly) of the IncF family, prophages, pipolins, and insertion elements such as IS1 and IS5 were also observed to exist, which may presumably aid in the propagation of genes encoding resistance against antimicrobial drugs. The observed high prevalence of MGEs associated with multidrug resistance in pathogenic E. coli isolates belonging to the phylogroup B1 underscores the need for extended surveillance to keep track of and prevent the transmission of the bacterium to certain vulnerable human and animal populations. IMPORTANCE: Evolutionary patterns of E. coli bacteria convey that they evolve into highly pathogenic forms by acquiring fitness advantages, such as AMR, and various virulence factors through the horizontal gene transfer (HGT)-mediated acquisition of MGEs. However, limited research on the genetic profiles of environmental E. coli, particularly from India, hinders our understanding of their transition to pathogenic forms and impedes the adoption of a comprehensive approach to address the connection between environmentally dwelling E. coli populations and human and veterinary public health. This study focuses on high-resolution genomic analysis of the environmental E. coli isolates aiming to understand the genetic similarities and differences among isolates from different environmental niches and uncover the survival strategies employed by these bacteria to thrive in their surroundings. Our approach involved molecular characterization of environmental samples using PCR-based DNA fingerprinting and subsequent WGS analysis. This multidisciplinary approach is likely to provide valuable insights into the understanding of any potential spill-over to human and animal populations and locales. Investigating these environmental isolates has significant potential for developing epidemiological strategies against transmission and understanding niche-specific evolutionary patterns. | 2024 | 38376265 |
| 4559 | 17 | 0.9906 | Systematic detection of horizontal gene transfer across genera among multidrug-resistant bacteria in a single hospital. Multidrug-resistant bacteria pose a serious health threat, especially in hospitals. Horizontal gene transfer (HGT) of mobile genetic elements (MGEs) facilitates the spread of antibiotic resistance, virulence, and environmental persistence genes between nosocomial pathogens. We screened the genomes of 2173 bacterial isolates from healthcare-associated infections from a single hospital over 18 months, and identified identical nucleotide regions in bacteria belonging to distinct genera. To further resolve these shared sequences, we performed long-read sequencing on a subset of isolates and generated highly contiguous genomes. We then tracked the appearance of ten different plasmids in all 2173 genomes, and found evidence of plasmid transfer independent from bacterial transmission. Finally, we identified two instances of likely plasmid transfer within individual patients, including one plasmid that likely transferred to a second patient. This work expands our understanding of HGT in healthcare settings, and can inform efforts to limit the spread of drug-resistant pathogens in hospitals. | 2020 | 32285801 |
| 6610 | 18 | 0.9906 | The Gut Microbiome and Colistin Resistance: A Hidden Driver of Antimicrobial Failure. Colistin, a polymyxin antibiotic reintroduced as a last-resort therapy against multidrug-resistant Gram-negative bacteria, is increasingly being compromised by the emergence of plasmid-mediated colistin resistance genes (mcr-1 to mcr-10). The human gut microbiota serves as a major reservoir and transmission hub for these resistance determinants, even among individuals without prior colistin exposure. This review explores the mechanisms, dissemination, and clinical implications of mcr-mediated colistin resistance within the gut microbiota, highlighting its role in horizontal gene transfer, colonization, and environmental persistence. A comprehensive synthesis of the recent literature was conducted, focusing on epidemiological studies, molecular mechanisms, neonatal implications and decolonization strategies. The intestinal tract supports the enrichment and exchange of mcr genes among commensal and pathogenic bacteria, especially under antibiotic pressure. Colistin use in agriculture has amplified gut colonization with resistant strains in both animals and humans. Surveillance gaps remain, particularly in neonatal populations, where colonization may occur early and persist silently. Promising interventions, such as fecal microbiota transplantation and phage therapies, are under investigation but lack large-scale clinical validation. The gut microbiome plays a central role in the global spread of colistin resistance. Mitigating this threat requires integrated One Health responses, improved diagnostics for gut colonization, and investment in microbiome-based therapies. A proactive, multisectoral approach is essential to safeguard colistin efficacy and address the expanding threat of mcr-mediated resistance. | 2025 | 41009471 |
| 5114 | 19 | 0.9906 | 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 |