# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9070 | 0 | 1.0000 | Automated annotation of mobile antibiotic resistance in Gram-negative bacteria: the Multiple Antibiotic Resistance Annotator (MARA) and database. BACKGROUND: Multiresistance in Gram-negative bacteria is often due to acquisition of several different antibiotic resistance genes, each associated with a different mobile genetic element, that tend to cluster together in complex conglomerations. Accurate, consistent annotation of resistance genes, the boundaries and fragments of mobile elements, and signatures of insertion, such as DR, facilitates comparative analysis of complex multiresistance regions and plasmids to better understand their evolution and how resistance genes spread. OBJECTIVES: To extend the Repository of Antibiotic resistance Cassettes (RAC) web site, which includes a database of 'features', and the Attacca automatic DNA annotation system, to encompass additional resistance genes and all types of associated mobile elements. METHODS: Antibiotic resistance genes and mobile elements were added to RAC, from existing registries where possible. Attacca grammars were extended to accommodate the expanded database, to allow overlapping features to be annotated and to identify and annotate features such as composite transposons and DR. RESULTS: The Multiple Antibiotic Resistance Annotator (MARA) database includes antibiotic resistance genes and selected mobile elements from Gram-negative bacteria, distinguishing important variants. Sequences can be submitted to the MARA web site for annotation. A list of positions and orientations of annotated features, indicating those that are truncated, DR and potential composite transposons is provided for each sequence, as well as a diagram showing annotated features approximately to scale. CONCLUSIONS: The MARA web site (http://mara.spokade.com) provides a comprehensive database for mobile antibiotic resistance in Gram-negative bacteria and accurately annotates resistance genes and associated mobile elements in submitted sequences to facilitate comparative analysis. | 2018 | 29373760 |
| 9071 | 1 | 0.9997 | RAC: Repository of Antibiotic resistance Cassettes. Antibiotic resistance in bacteria is often due to acquisition of resistance genes associated with different mobile genetic elements. In Gram-negative bacteria, many resistance genes are found as part of small mobile genetic elements called gene cassettes, generally found integrated into larger elements called integrons. Integrons carrying antibiotic resistance gene cassettes are often associated with mobile elements and here are designated 'mobile resistance integrons' (MRIs). More than one cassette can be inserted in the same integron to create arrays that contribute to the spread of multi-resistance. In many sequences in databases such as GenBank, only the genes within cassettes, rather than whole cassettes, are annotated and the same gene/cassette may be given different names in different entries, hampering analysis. We have developed the Repository of Antibiotic resistance Cassettes (RAC) website to provide an archive of gene cassettes that includes alternative gene names from multiple nomenclature systems and allows the community to contribute new cassettes. RAC also offers an additional function that allows users to submit sequences containing cassettes or arrays for annotation using the automatic annotation system Attacca. Attacca recognizes features (gene cassettes, integron regions) and identifies cassette arrays as patterns of features and can also distinguish minor cassette variants that may encode different resistance phenotypes (aacA4 cassettes and bla cassettes-encoding β-lactamases). Gaps in annotations are manually reviewed and those found to correspond to novel cassettes are assigned unique names. While there are other websites dedicated to integrons or antibiotic resistance genes, none includes a complete list of antibiotic resistance gene cassettes in MRI or offers consistent annotation and appropriate naming of all of these cassettes in submitted sequences. RAC thus provides a unique resource for researchers, which should reduce confusion and improve the quality of annotations of gene cassettes in integrons associated with antibiotic resistance. DATABASE URL: http://www2.chi.unsw.edu.au/rac. | 2011 | 22140215 |
| 9849 | 2 | 0.9996 | Analysis of antibiotic resistance regions in Gram-negative bacteria. Antibiotic resistance in Gram-negative bacteria is often due to the acquisition of resistance genes from a shared pool. In multiresistant isolates these genes, together with associated mobile elements, may be found in complex conglomerations on plasmids or on the chromosome. Analysis of available sequences reveals that these multiresistance regions (MRR) are modular, mosaic structures composed of different combinations of components from a limited set arranged in a limited number of ways. Components common to different MRR provide targets for homologous recombination, allowing these regions to evolve by combinatorial evolution, but our understanding of this process is far from complete. Advances in technology are leading to increasing amounts of sequence data, but currently available automated annotation methods usually focus on identifying ORFs and predicting protein function by homology. In MRR, where the genes are often well characterized, the challenge is to identify precisely which genes are present and to define the boundaries of complete and fragmented mobile elements. This review aims to summarize the types of mobile elements involved in multiresistance in Gram-negative bacteria and their associations with particular resistance genes, to describe common components of MRR and to illustrate methods for detailed analysis of these regions. | 2011 | 21564142 |
| 9880 | 3 | 0.9996 | 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 |
| 3771 | 4 | 0.9995 | RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning. Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface. | 2021 | 34846288 |
| 4453 | 5 | 0.9995 | dfrA trimethoprim resistance genes found in Gram-negative bacteria: compilation and unambiguous numbering. To track the spread of antibiotic resistance genes, accurate identification of individual genes is essential. Acquired trimethoprim resistance genes encoding trimethoprim-insensitive homologues of the sensitive dihydrofolate reductases encoded by the folA genes of bacteria are increasingly found in genome sequences. However, naming and numbering in publicly available records (journal publications or entries in the GenBank non-redundant DNA database) has not always been unambiguous. In addition, the nomenclature has evolved over time. Here, the changes in nomenclature and the most commonly encountered problems and pitfalls affecting dfrA gene identification arising from historically incorrect or inaccurate numbering are explained. The complete set of dfrA genes/DfrA proteins found in Gram-negative bacteria for which readily searchable sequence information is currently available has been compiled using less than 98% identity for both the gene and the derived protein sequence as the criteria for assignment of a new number. In most cases, trimethoprim resistance has been demonstrated. The gene context, predominantly in a gene cassette or near the ori end of CR1 or CR2, is also covered. The RefSeq database that underpins the programs used to automatically identify resistance genes in genome data sets has been curated to assign all sequences listed to the correct number. This led to the assignment of corrected or new gene numbers to several mis-assigned sequences. The unique numbers assigned for the dfrA/DfrA set are now listed in the RefSeq database, which we propose provides a way forward that should end future duplication of numbers and the confusion that causes. | 2021 | 34180526 |
| 9879 | 6 | 0.9995 | IntegronFinder 2.0: Identification and Analysis of Integrons across Bacteria, with a Focus on Antibiotic Resistance in Klebsiella. Integrons are flexible gene-exchanging platforms that contain multiple cassettes encoding accessory genes whose order is shuffled by a specific integrase. Integrons embedded within mobile genetic elements often contain multiple antibiotic resistance genes that they spread among nosocomial pathogens and contribute to the current antibiotic resistance crisis. However, most integrons are presumably sedentary and encode a much broader diversity of functions. IntegronFinder is a widely used software to identify novel integrons in bacterial genomes, but has aged and lacks some useful functionalities to handle very large datasets of draft genomes or metagenomes. Here, we present IntegronFinder version 2. We have updated the code, improved its efficiency and usability, adapted the output to incomplete genome data, and added a few novel functions. We describe these changes and illustrate the relevance of the program by analyzing the distribution of integrons across more than 20,000 fully sequenced genomes. We also take full advantage of its novel capabilities to analyze close to 4000 Klebsiella pneumoniae genomes for the presence of integrons and antibiotic resistance genes within them. Our data show that K. pneumoniae has a large diversity of integrons and the largest mobile integron in our database of plasmids. The pangenome of these integrons contains a total of 165 different gene families with most of the largest families being related with resistance to numerous types of antibiotics. IntegronFinder is a free and open-source software available on multiple public platforms. | 2022 | 35456751 |
| 9848 | 7 | 0.9995 | Cargo Genes of Tn7-Like Transposons Comprise an Enormous Diversity of Defense Systems, Mobile Genetic Elements, and Antibiotic Resistance Genes. Transposition is a major mechanism of horizontal gene mobility in prokaryotes. However, exploration of the genes mobilized by transposons (cargo) is hampered by the difficulty in delineating integrated transposons from their surrounding genetic context. Here, we present a computational approach that allowed us to identify the boundaries of 6,549 Tn7-like transposons. We found that 96% of these transposons carry at least one cargo gene. Delineation of distinct communities in a gene-sharing network demonstrates how transposons function as a conduit of genes between phylogenetically distant hosts. Comparative analysis of the cargo genes reveals significant enrichment of mobile genetic elements (MGEs) nested within Tn7-like transposons, such as insertion sequences and toxin-antitoxin modules, and of genes involved in recombination, anti-MGE defense, and antibiotic resistance. More unexpectedly, cargo also includes genes encoding central carbon metabolism enzymes. Twenty-two Tn7-like transposons carry both an anti-MGE defense system and antibiotic resistance genes, illustrating how bacteria can overcome these combined pressures upon acquisition of a single transposon. This work substantially expands the distribution of Tn7-like transposons, defines their evolutionary relationships, and provides a large-scale functional classification of prokaryotic genes mobilized by transposition. IMPORTANCE Transposons are major vehicles of horizontal gene transfer that, in addition to genes directly involved in transposition, carry cargo genes. However, characterization of these genes is hampered by the difficulty of identification of transposon boundaries. We developed a computational approach for detecting transposon ends and applied it to perform a comprehensive census of the cargo genes of Tn7-like transposons, a large class of bacterial mobile genetic elements (MGE), many of which employ a unique, CRISPR-mediated mechanism of site-specific transposition. The cargo genes encompass a striking diversity of MGE, defense, and antibiotic resistance systems. Unexpectedly, we also identified cargo genes encoding metabolic enzymes. Thus, Tn7-like transposons mobilize a vast repertoire of genes that can have multiple effects on the host bacteria. | 2021 | 34872347 |
| 9850 | 8 | 0.9995 | Annotation and Comparative Genomics of Prokaryotic Transposable Elements. The data generated in nearly 30 years of bacterial genome sequencing has revealed the abundance of transposable elements (TE) and their importance in genome and transcript remodeling through the mediation of DNA insertions and deletions, structural rearrangements, and regulation of gene expression. Furthermore, what we have learned from studying transposition mechanisms and their regulation in bacterial TE is fundamental to our current understanding of TE in other organisms because much of what has been observed in bacteria is conserved in all domains of life. However, unlike eukaryotic TE, prokaryotic TE sequester and transmit important classes of genes that impact host fitness, such as resistance to antibiotics and heavy metals and virulence factors affecting animals and plants, among other acquired traits. This provides dynamism and plasticity to bacteria, which would otherwise be propagated clonally. The insertion sequences (IS), the simplest form of prokaryotic TE, are autonomous and compact mobile genetic elements. These can be organized into compound transposons, in which two similar IS can flank any DNA segment and render it transposable. Other more complex structures, called unit transposons, can be grouped into four major families (Tn3, Tn7, Tn402, Tn554) with specific genetic characteristics. This chapter will revisit the prominent structural features of these elements, focusing on a genomic annotation framework and comparative analysis. Relevant aspects of TE will also be presented, stressing their key position in genome impact and evolution, especially in the emergence of antimicrobial resistance and other adaptive traits. | 2024 | 38819561 |
| 4455 | 9 | 0.9995 | A novel method to discover fluoroquinolone antibiotic resistance (qnr) genes in fragmented nucleotide sequences. BACKGROUND: Broad-spectrum fluoroquinolone antibiotics are central in modern health care and are used to treat and prevent a wide range of bacterial infections. The recently discovered qnr genes provide a mechanism of resistance with the potential to rapidly spread between bacteria using horizontal gene transfer. As for many antibiotic resistance genes present in pathogens today, qnr genes are hypothesized to originate from environmental bacteria. The vast amount of data generated by shotgun metagenomics can therefore be used to explore the diversity of qnr genes in more detail. RESULTS: In this paper we describe a new method to identify qnr genes in nucleotide sequence data. We show, using cross-validation, that the method has a high statistical power of correctly classifying sequences from novel classes of qnr genes, even for fragments as short as 100 nucleotides. Based on sequences from public repositories, the method was able to identify all previously reported plasmid-mediated qnr genes. In addition, several fragments from novel putative qnr genes were identified in metagenomes. The method was also able to annotate 39 chromosomal variants of which 11 have previously not been reported in literature. CONCLUSIONS: The method described in this paper significantly improves the sensitivity and specificity of identification and annotation of qnr genes in nucleotide sequence data. The predicted novel putative qnr genes in the metagenomic data support the hypothesis of a large and uncharacterized diversity within this family of resistance genes in environmental bacterial communities. An implementation of the method is freely available at http://bioinformatics.math.chalmers.se/qnr/. | 2012 | 23231464 |
| 4661 | 10 | 0.9995 | Methods for the targeted sequencing and analysis of integrons and their gene cassettes from complex microbial communities. Integrons are microbial genetic elements that can integrate mobile gene cassettes. They are mostly known for spreading antibiotic resistance cassettes among human pathogens. However, beyond clinical settings, gene cassettes encode an extraordinarily diverse range of functions important for bacterial adaptation. The recovery and sequencing of cassettes has promising applications, including: surveillance of clinically important genes, particularly antibiotic resistance determinants; investigating the functional diversity of integron-carrying bacteria; and novel enzyme discovery. Although gene cassettes can be directly recovered using PCR, there are no standardised methods for their amplification and, importantly, for validating sequences as genuine integron gene cassettes. Here, we present reproducible methods for the amplification, sequence processing, and validation of gene cassette amplicons from complex communities. We describe two different PCR assays that either amplify cassettes together with integron integrases, or gene cassettes together within cassette arrays. We compare the performance of Nanopore and Illumina sequencing, and present bioinformatic pipelines that filter sequences to ensure that they represent amplicons from genuine integrons. Using a diverse set of environmental DNAs, we show that our approach can consistently recover thousands of unique cassettes per sample and up to hundreds of different integron integrases. Recovered cassettes confer a wide range of functions, including antibiotic resistance, with as many as 300 resistance cassettes found in a single sample. In particular, we show that class one integrons are collecting and concentrating resistance genes out of the broader diversity of cassette functions. The methods described here can be applied to any environmental or clinical microbiome sample. | 2022 | 35298369 |
| 9888 | 11 | 0.9995 | Evolution and typing of IncC plasmids contributing to antibiotic resistance in Gram-negative bacteria. The large, broad host range IncC plasmids are important contributors to the spread of key antibiotic resistance genes and over 200 complete sequences of IncC plasmids have been reported. To track the spread of these plasmids accurate typing to identify the closest relatives is needed. However, typing can be complicated by the high variability in resistance gene content and various typing methods that rely on features of the conserved backbone have been developed. Plasmids can be broadly typed into two groups, type 1 and type 2, using four features that differentiate the otherwise closely related backbones. These types are found in many different countries in bacteria from humans and animals. However, hybrids of type 1 and type 2 are also occasionally seen, and two further types, each represented by a single plasmid, were distinguished. Generally, the antibiotic resistance genes are located within a small number of resistance islands, only one of which, ARI-B, is found in both type 1 and type 2. The introduction of each resistance island generates a new lineage and, though they are continuously evolving via the loss of resistance genes or introduction of new ones, the island positions serve as valuable lineage-specific markers. A current type 2 lineage of plasmids is derived from an early type 2 plasmid but the sequences of early type 1 plasmids include features not seen in more recent type 1 plasmids, indicating a shared ancestor rather than a direct lineal relationship. Some features, including ones essential for maintenance or for conjugation, have been examined experimentally. | 2018 | 30081066 |
| 9889 | 12 | 0.9995 | Evolution and dissemination of L and M plasmid lineages carrying antibiotic resistance genes in diverse Gram-negative bacteria. Conjugative, broad host-range plasmids of the L/M complex have been associated with antibiotic resistance since the 1970s. They are found in Gram-negative bacterial genera that cause human infections and persist in hospital environments. It is crucial that these plasmids are typed accurately so that their clinical and global dissemination can be traced in epidemiological studies. The L/M complex has previously been divided into L, M1 and M2 subtypes. However, those types do not encompass all diversity seen in the group. Here, we have examined 148 complete L/M plasmid sequences in order to understand the diversity of the complex and trace the evolution of distinct lineages. The backbone sequence of each plasmid was determined by removing translocatable genetic elements and reversing their effects in silico. The sequence identities of replication regions and complete backbones were then considered for typing. This supported the distinction of L and M plasmids and revealed that there are five L and eight M types, where each type is comprised of further sub-lineages that are distinguished by variation in their backbone and translocatable element content. Regions containing antibiotic resistance genes in L and M sub-lineages have often formed by initial rare insertion events, followed by insertion of other translocatable elements within the inceptive element. As such, islands evolve in situ to contain genes conferring resistance to multiple antibiotics. In some cases, different plasmid sub-lineages have acquired the same or related resistance genes independently. This highlights the importance of these plasmids in acting as vehicles for the dissemination of emerging resistance genes. Materials are provided here for typing plasmids of the L/M complex from complete sequences or draft genomes. This should enable rapid identification of novel types and facilitate tracking the evolution of existing lineages. | 2021 | 32781088 |
| 9867 | 13 | 0.9995 | Mosaic plasmids are abundant and unevenly distributed across prokaryotic taxa. Mosaic plasmids, plasmids composed of genetic elements from distinct sources, are associated with the spread of antibiotic resistance genes. Transposons are considered the primary mechanism for mosaic plasmid formation, though other mechanisms have been observed in specific instances. The frequency with which mosaic plasmids have been described suggests they may play an important role in plasmid population dynamics. Our survey of the confirmed plasmid sequences available from complete and draft genomes in the RefSeq database shows that 46% of them fit a strict definition of mosaic. Mosaic plasmids are also not evenly distributed over the taxa represented in the database. Plasmids from some genera, including Piscirickettsia and Yersinia, are almost all mosaic, while plasmids from other genera, including Borrelia, are rarely mosaic. While some mosaic plasmids share identical regions with hundreds of others, the median mosaic plasmid only shares with 8 other plasmids. When considering only plasmids from finished genomes (51.6% of the total), mosaic plasmids have significantly higher proportions of transposase and antibiotic resistance genes. Conversely, only 56.6% of mosaic fragments (DNA fragments shared between mosaic plasmids) contain a recognizable transposase gene, and only 1.2% of mosaic fragments are flanked by inverted repeats. Mosaic fragments associated with the IS26 transposase gene are 3.8-fold more abundant than any other sequence shared between mosaic plasmids in the database, though this is at least partly due to overrepresentation of Enterobacteriaceae plasmids. Mosaic plasmids are a complicated trait of some plasmid populations, only partly explained by transposition. Though antibiotic resistance genes led to the identification of many mosaic plasmids, mosaic plasmids are a broad phenomenon encompassing many more traits than just antibiotic resistance. Further research will be required to determine the influence of ecology, host repair mechanisms, conjugation, and plasmid host range on the formation and influence of mosaic plasmids. AUTHOR SUMMARY: Plasmids are extrachromosomal genetic entities that are found in many prokaryotes. They serve as flexible storage for genes, and individual cells can make substantial changes to their characteristics by acquiring, losing, or modifying a plasmid. In some pathogenic bacteria, such as Escherichia coli, antibiotic resistance genes are known to spread primarily on plasmids. By analyzing a database of 8592 plasmid sequences we determined that many of these plasmids have exchanged genes with each other, becoming mosaics of genes from different sources. We next separated these plasmids into groups based on the organism they were isolated from and found that different groups had different fractions of mosaic plasmids. This result was unexpected and suggests that the mechanisms and selective pressures causing mosaic plasmids do not occur evenly over all species. It also suggests that plasmids may provide different levels of potential variation to different species. This work uncovers a previously unrecognized pattern in plasmids across prokaryotes, that could lead to new insights into the evolutionary role that plasmids play. | 2019 | 30797764 |
| 4375 | 14 | 0.9994 | Evidence of a large novel gene pool associated with prokaryotic genomic islands. Microbial genes that are "novel" (no detectable homologs in other species) have become of increasing interest as environmental sampling suggests that there are many more such novel genes in yet-to-be-cultured microorganisms. By analyzing known microbial genomic islands and prophages, we developed criteria for systematic identification of putative genomic islands (clusters of genes of probable horizontal origin in a prokaryotic genome) in 63 prokaryotic genomes, and then characterized the distribution of novel genes and other features. All but a few of the genomes examined contained significantly higher proportions of novel genes in their predicted genomic islands compared with the rest of their genome (Paired t test = 4.43E-14 to 1.27E-18, depending on method). Moreover, the reverse observation (i.e., higher proportions of novel genes outside of islands) never reached statistical significance in any organism examined. We show that this higher proportion of novel genes in predicted genomic islands is not due to less accurate gene prediction in genomic island regions, but likely reflects a genuine increase in novel genes in these regions for both bacteria and archaea. This represents the first comprehensive analysis of novel genes in prokaryotic genomic islands and provides clues regarding the origin of novel genes. Our collective results imply that there are different gene pools associated with recently horizontally transmitted genomic regions versus regions that are primarily vertically inherited. Moreover, there are more novel genes within the gene pool associated with genomic islands. Since genomic islands are frequently associated with a particular microbial adaptation, such as antibiotic resistance, pathogen virulence, or metal resistance, this suggests that microbes may have access to a larger "arsenal" of novel genes for adaptation than previously thought. | 2005 | 16299586 |
| 9886 | 15 | 0.9994 | Development of an antimicrobial resistance plasmid transfer gene database for enteric bacteria. Introduction: Type IV secretion systems (T4SSs) are integral parts of the conjugation process in enteric bacteria. These secretion systems are encoded within the transfer (tra) regions of plasmids, including those that harbor antimicrobial resistance (AMR) genes. The conjugal transfer of resistance plasmids can lead to the dissemination of AMR among bacterial populations. Methods: To facilitate the analyses of the conjugation-associated genes, transfer related genes associated with key groups of AMR plasmids were identified, extracted from GenBank and used to generate a plasmid transfer gene dataset that is part of the Virulence and Plasmid Transfer Factor Database at FDA, serving as the foundation for computational tools for the comparison of the conjugal transfer genes. To assess the genetic feature of the transfer gene database, genes/proteins of the same name (e.g., traI/TraI) or predicted function (VirD4 ATPase homologs) were compared across the different plasmid types to assess sequence diversity. Two analyses tools, the Plasmid Transfer Factor Profile Assessment and Plasmid Transfer Factor Comparison tools, were developed to evaluate the transfer genes located on plasmids and to facilitate the comparison of plasmids from multiple sequence files. To assess the database and associated tools, plasmid, and whole genome sequencing (WGS) data were extracted from GenBank and previous WGS experiments in our lab and assessed using the analysis tools. Results: Overall, the plasmid transfer database and associated tools proved to be very useful for evaluating the different plasmid types, their association with T4SSs, and increased our understanding how conjugative plasmids contribute to the dissemination of AMR genes. | 2023 | 38033626 |
| 9894 | 16 | 0.9994 | Mechanisms of Evolution in High-Consequence Drug Resistance Plasmids. The dissemination of resistance among bacteria has been facilitated by the fact that resistance genes are usually located on a diverse and evolving set of transmissible plasmids. However, the mechanisms generating diversity and enabling adaptation within highly successful resistance plasmids have remained obscure, despite their profound clinical significance. To understand these mechanisms, we have performed a detailed analysis of the mobilome (the entire mobile genetic element content) of a set of previously sequenced carbapenemase-producing Enterobacteriaceae (CPE) from the National Institutes of Health Clinical Center. This analysis revealed that plasmid reorganizations occurring in the natural context of colonization of human hosts were overwhelmingly driven by genetic rearrangements carried out by replicative transposons working in concert with the process of homologous recombination. A more complete understanding of the molecular mechanisms and evolutionary forces driving rearrangements in resistance plasmids may lead to fundamentally new strategies to address the problem of antibiotic resistance. IMPORTANCE: The spread of antibiotic resistance among Gram-negative bacteria is a serious public health threat, as it can critically limit the types of drugs that can be used to treat infected patients. In particular, carbapenem-resistant members of the Enterobacteriaceae family are responsible for a significant and growing burden of morbidity and mortality. Here, we report on the mechanisms underlying the evolution of several plasmids carried by previously sequenced clinical Enterobacteriaceae isolates from the National Institutes of Health Clinical Center (NIH CC). Our ability to track genetic rearrangements that occurred within resistance plasmids was dependent on accurate annotation of the mobile genetic elements within the plasmids, which was greatly aided by access to long-read DNA sequencing data and knowledge of their mechanisms. Mobile genetic elements such as transposons and integrons have been strongly associated with the rapid spread of genes responsible for antibiotic resistance. Understanding the consequences of their actions allowed us to establish unambiguous evolutionary relationships between plasmids in the analysis set. | 2016 | 27923922 |
| 4345 | 17 | 0.9994 | Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. Traditional genetic association studies are very difficult in bacteria, as the generally limited recombination leads to large linked haplotype blocks, confounding the identification of causative variants. Beta-lactam antibiotic resistance in Streptococcus pneumoniae arises readily as the bacteria can quickly incorporate DNA fragments encompassing variants that make the transformed strains resistant. However, the causative mutations themselves are embedded within larger recombined blocks, and previous studies have only analysed a limited number of isolates, leading to the description of "mosaic genes" as being responsible for resistance. By comparing a large number of genomes of beta-lactam susceptible and non-susceptible strains, the high frequency of recombination should break up these haplotype blocks and allow the use of genetic association approaches to identify individual causative variants. Here, we performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) and indels that could confer beta-lactam non-susceptibility using 3,085 Thai and 616 USA pneumococcal isolates as independent datasets for the variant discovery. The large sample sizes allowed us to narrow the source of beta-lactam non-susceptibility from long recombinant fragments down to much smaller loci comprised of discrete or linked SNPs. While some loci appear to be universal resistance determinants, contributing equally to non-susceptibility for at least two classes of beta-lactam antibiotics, some play a larger role in resistance to particular antibiotics. All of the identified loci have a highly non-uniform distribution in the populations. They are enriched not only in vaccine-targeted, but also non-vaccine-targeted lineages, which may raise clinical concerns. Identification of single nucleotide polymorphisms underlying resistance will be essential for future use of genome sequencing to predict antibiotic sensitivity in clinical microbiology. | 2014 | 25101644 |
| 4344 | 18 | 0.9994 | Phenetic Comparison of Prokaryotic Genomes Using k-mers. Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets. | 2017 | 28957508 |
| 5111 | 19 | 0.9994 | Antimicrobial Resistance Prediction for Gram-Negative Bacteria via Game Theory-Based Feature Evaluation. The increasing prevalence of antimicrobial-resistant bacteria drives the need for advanced methods to identify antimicrobial-resistance (AMR) genes in bacterial pathogens. With the availability of whole genome sequences, best-hit methods can be used to identify AMR genes by differentiating unknown sequences with known AMR sequences in existing online repositories. Nevertheless, these methods may not perform well when identifying resistance genes with sequences having low sequence identity with known sequences. We present a machine learning approach that uses protein sequences, with sequence identity ranging between 10% and 90%, as an alternative to conventional DNA sequence alignment-based approaches to identify putative AMR genes in Gram-negative bacteria. By using game theory to choose which protein characteristics to use in our machine learning model, we can predict AMR protein sequences for Gram-negative bacteria with an accuracy ranging from 93% to 99%. In order to obtain similar classification results, identity thresholds as low as 53% were required when using BLASTp. | 2019 | 31597945 |