# | Rank | Similarity | Title + Abs. | Year | PMID |
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| 0 | 1 | 2 | 3 | 4 | 5 |
| 5098 | 0 | 0.9895 | Feature selection and aggregation for antibiotic resistance GWAS in Mycobacterium tuberculosis: a comparative study. INTRODUCTION: Drug resistance (DR) of pathogens remains a global healthcare concern. In contrast to other bacteria, acquiring mutations in the core genome is the main mechanism of drug resistance for Mycobacterium tuberculosis (MTB). For some antibiotics, the resistance of a particular isolate can be reliably predicted by identifying specific mutations, while for other antibiotics the knowledge of resistance mechanisms is limited. Statistical machine learning (ML) methods are used to infer new genes implicated in drug resistance leveraging large collections of isolates with known whole-genome sequences and phenotypic states for different drugs. However, high correlations between the phenotypic states for commonly used drugs complicate the inference of true associations of mutations with drug phenotypes by ML approaches. METHODS: Recently, several new methods have been developed to select a small subset of reliable predictors of the dependent variable, which may help reduce the number of spurious associations identified. In this study, we evaluated several such methods, namely, logistic regression with different regularization penalty functions, a recently introduced algorithm for solving the best-subset selection problem (ABESS) and "Hungry, Hungry SNPos" (HHS) a heuristic algorithm specifically developed to identify resistance-associated genetic variants in the presence of resistance co-occurrence. We assessed their ability to select known causal mutations for resistance to a specific drug while avoiding the selection of mutations in genes associated with resistance to other drugs, thus we compared selected ML models for their applicability for MTB genome wide association studies. RESULTS AND DISCUSSION: In our analysis, ABESS significantly outperformed the other methods, selecting more relevant sets of mutations. Additionally, we demonstrated that aggregating rare mutations within protein-coding genes into markers indicative of changes in PFAM domains improved prediction quality, and these markers were predominantly selected by ABESS, suggesting their high informativeness. However, ABESS yielded lower prediction accuracy compared to logistic regression methods with regularization. | 2025 | 40606161 |
| 4342 | 1 | 0.9889 | Evolution and diversity of clonal bacteria: the paradigm of Mycobacterium tuberculosis. BACKGROUND: Mycobacterium tuberculosis complex species display relatively static genomes and 99.9% nucleotide sequence identity. Studying the evolutionary history of such monomorphic bacteria is a difficult and challenging task. PRINCIPAL FINDINGS: We found that single-nucleotide polymorphism (SNP) analysis of DNA repair, recombination and replication (3R) genes in a comprehensive selection of M. tuberculosis complex strains from across the world, yielded surprisingly high levels of polymorphisms as compared to house-keeping genes, making it possible to distinguish between 80% of clinical isolates analyzed in this study. Bioinformatics analysis suggests that a large number of these polymorphisms are potentially deleterious. Site frequency spectrum comparison of synonymous and non-synonymous variants and Ka/Ks ratio analysis suggest a general negative/purifying selection acting on these sets of genes that may lead to suboptimal 3R system activity. In turn, the relaxed fidelity of 3R genes may allow the occurrence of adaptive variants, some of which will survive. Furthermore, 3R-based phylogenetic trees are a new tool for distinguishing between M. tuberculosis complex strains. CONCLUSIONS/SIGNIFICANCE: This situation, and the consequent lack of fidelity in genome maintenance, may serve as a starting point for the evolution of antibiotic resistance, fitness for survival and pathogenicity, possibly conferring a selective advantage in certain stressful situations. These findings suggest that 3R genes may play an important role in the evolution of highly clonal bacteria, such as M. tuberculosis. They also facilitate further epidemiological studies of these bacteria, through the development of high-resolution tools. With many more microbial genomes being sequenced, our results open the door to 3R gene-based studies of adaptation and evolution of other, highly clonal bacteria. | 2008 | 18253486 |
| 9075 | 2 | 0.9889 | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter. BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype . | 2023 | 37474912 |
| 8472 | 3 | 0.9887 | Genetic architecture of resistance to plant secondary metabolites in Photorhabdus entomopathogenic bacteria. BACKGROUND: Entomopathogenic nematodes of the genus Heterorhabditis establish a symbiotic association with Photorhabdus bacteria. Together, they colonize and rapidly kill insects, making them important biological control agents against agricultural pests. Improving their biocontrol traits by engineering resistance to plant secondary metabolites (benzoxazinoids) in Photorhabdus symbiotic bacteria through experimental evolution has been shown to increase their lethality towards benzoxazinoid-defended larvae of the western corn rootworm, a serious crop pest of maize, and it is therefore a promising approach to develop more efficient biocontrol agents to manage this pest. To enhance our understanding of the genetic bases of benzoxazinoid resistance in Photorhabdus bacteria, we conducted an experimental evolution experiment with a phylogenetically diverse collection of Photorhabdus strains from different geographic origins. We cultured 27 different strains in medium containing 6-methoxy-2-benzoxazolinone (MBOA), a highly active benzoxazinoid breakdown product, for 35 24 h-cycles to select for benzoxazinoid-resistant strains. Then, we carried out genome-wide sequence comparisons to uncover the genetic alterations associated with benzoxazinoid resistance. Lastly, we evaluated the resistance of the newly isolated resistant Photorhabdus strains to eight additional bioactive compounds, including 2-benzoxazolinone (BOA), nicotine, caffeine, 6-chloroacetyl-2-benzoxazolinone (CABOA), digitoxin, fenitrothion, ampicillin, and kanamycin. RESULTS: We found that benzoxazinoid resistance evolves rapidly in Photorhabdus in a strain-specific manner. Across the different Photorhabdus strains, a total of nineteen nonsynonymous point mutations, two stop codon gains, and one frameshift were associated with higher benzoxazinoid resistance. The different genetic alterations were polygenic and occurred in genes coding for the EnvZ/OmpR two-component regulatory system, the different subunits of the DNA-directed RNA polymerase, and the AcrABZ-TolC multidrug efflux pump. Apart from increasing MBOA resistance, the different mutations were also associated with cross-resistance to 2-benzoxazolinone (BOA), nicotine, caffeine, and 6-chloroacetyl-2-benzoxazolinone (CABOA) and with collateral sensitivity to fenitrothion, ampicillin, and kanamycin. Targeted mutagenesis will provide a deeper mechanistic understanding, including the relative contribution of the different mutation types. CONCLUSIONS: Our study reveals several genomic features that are associated with resistance to xenobiotics in this important group of biological control agents and enhances the availability of molecular tools to develop better biological control agents, which is essential for more sustainable and ecologically friendly agricultural practices. | 2025 | 41168779 |
| 9082 | 4 | 0.9885 | GeneMates: an R package for detecting horizontal gene co-transfer between bacteria using gene-gene associations controlled for population structure. BACKGROUND: Horizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries. It is frequently mediated by mobile genetic elements (MGEs), which may capture, maintain, and rearrange mobile genes and co-mobilise them between bacteria, causing horizontal gene co-transfer (HGcoT). This physical linkage between mobile genes poses a great threat to public health as it facilitates dissemination and co-selection of clinically important genes amongst bacteria. Although rapid accumulation of bacterial whole-genome sequencing data since the 2000s enables study of HGcoT at the population level, results based on genetic co-occurrence counts and simple association tests are usually confounded by bacterial population structure when sampled bacteria belong to the same species, leading to spurious conclusions. RESULTS: We have developed a network approach to explore WGS data for evidence of intraspecies HGcoT and have implemented it in R package GeneMates ( github.com/wanyuac/GeneMates ). The package takes as input an allelic presence-absence matrix of interested genes and a matrix of core-genome single-nucleotide polymorphisms, performs association tests with linear mixed models controlled for population structure, produces a network of significantly associated alleles, and identifies clusters within the network as plausible co-transferred alleles. GeneMates users may choose to score consistency of allelic physical distances measured in genome assemblies using a novel approach we have developed and overlay scores to the network for further evidence of HGcoT. Validation studies of GeneMates on known acquired antimicrobial resistance genes in Escherichia coli and Salmonella Typhimurium show advantages of our network approach over simple association analysis: (1) distinguishing between allelic co-occurrence driven by HGcoT and that driven by clonal reproduction, (2) evaluating effects of population structure on allelic co-occurrence, and (3) direct links between allele clusters in the network and MGEs when physical distances are incorporated. CONCLUSION: GeneMates offers an effective approach to detection of intraspecies HGcoT using WGS data. | 2020 | 32972363 |
| 9076 | 5 | 0.9885 | 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 |
| 2497 | 6 | 0.9885 | Rapid Simultaneous Detection of the Clinically Relevant Carbapenemase Resistance Genes blaKPC, blaOXA48, blaVIM and blaNDM with the Newly Developed Ready-to-Use qPCR CarbaScan LyoBead. Antibiotic resistance, in particular the dissemination of carbapenemase-producing organisms, poses a significant threat to global healthcare. This study introduces the qPCR CarbaScan LyoBead assay, a robust, accurate, and efficient tool for detecting key carbapenemase genes, including blaKPC, blaNDM, blaOXA-48, and blaVIM. The assay utilizes lyophilized beads, a technological advancement that enhances stability, simplifies handling, and eliminates the need for refrigeration. This feature renders it particularly well-suited for point-of-care diagnostics and resource-limited settings. The assay's capacity to detect carbapenemase genes directly from bacterial colonies without the need for extensive sample preparation has been demonstrated to streamline workflows and enable rapid diagnostic results. The assay demonstrated 100% specificity and sensitivity across a diverse range of bacterial strains, including multiple allelic variants of target genes, facilitating precise identification of resistance mechanisms. Bacterial strains of the species Acinetobacter baumannii, Citrobacter freundii, Escherichia coli, Enterobacter cloacae, Klebsiella pneumoniae and Pseudomonas aeruginosa were utilized as reference material for assay development (n = 9) and validation (n = 28). It is notable that the assay's long shelf life and minimal operational complexity further enhance its utility for large-scale implementation in healthcare, food safety, and environmental monitoring. The findings emphasize the necessity of continuous surveillance and the implementation of rapid diagnostic methods for the effective detection of resistance genes. Furthermore, the assay's potential applications in other fields, such as toxin-antitoxin system research and monitoring of resistant bacteria in the community, highlight its versatility. In conclusion, the qPCR CarbaScan LyoBead assay is a valuable tool that can contribute to the urgent need to combat antibiotic resistance and improve global public health outcomes. | 2025 | 39940986 |
| 9070 | 7 | 0.9885 | 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 |
| 5097 | 8 | 0.9885 | Comparing Graph Sample and Aggregation (SAGE) and Graph Attention Networks in the Prediction of Drug-Gene Associations of Extended-Spectrum Beta-Lactamases in Periodontal Infections and Resistance. INTRODUCTION: Gram-negative bacteria exhibit more antibiotic resistance than gram-positive bacteria due to their cell wall structure and composition differences. Porins, or protein channels in these bacteria, can allow small, hydrophilic antibiotics to diffuse, affecting their susceptibility. Mutations in porin protein genes can also impair antibiotic entry. Predicting drug-gene associations of extended-spectrum beta-lactamases (ESBLs) is crucial as they confer resistance to beta-lactam antibiotics, challenging the treatment of infections. This aids clinicians in selecting suitable treatments, optimizing drug usage, enhancing patient outcomes, and controlling antibiotic resistance in healthcare settings. Graph-based neural networks can predict drug-gene associations in periodontal infections and resistance. The aim of the study was to predict drug-gene associations of ESBLs in periodontal infections and resistance. METHODS: The study focuses on analyzing drug-gene associations using probes and drugs. The data was converted into graph language, assigning nodes and edges for drugs and genes. Graph neural networks (GNNs) and similar algorithms were implemented using Google Colab and Python. Cytoscape and CytoHubba are open-source software platforms used for network analysis and visualization. GNNs were used for tasks like node classification, link prediction, and graph-level prediction. Three graph-based models were used: graph convolutional network (GCN), Graph SAGE, and graph attention network (GAT). Each model was trained for 200 epochs using the Adam optimizer with a learning rate of 0.01 and a weight decay of 5e-4. RESULTS: The drug-gene association network has 57 nodes, 79 edges, and a 2.730 characteristic path length. Its structure, organization, and connectivity are analyzed using the GCN and Graph SAGE, which show high accuracy, precision, recall, and an F1-score of 0.94. GAT's performance metrics are lower, with an accuracy of 0.68, precision of 0.47, recall of 0.68, and F1-score of 0.56, suggesting that it may not be as effective in capturing drug-gene relationships. CONCLUSION: Compared to ESBLs, both GCN and Graph SAGE demonstrate excellent performance with accuracy, precision, recall, and an F1-score of 0.94. These results indicate that GCN and Graph SAGE are highly effective in predicting drug-gene associations related to ESBLs. GCN and Graph SAGE outperform GAT in predicting drug-gene associations for ESBLs. Improvements include data augmentation, regularization, and cross-validation. Ethical considerations, fairness, and open-source implementations are crucial for future research in precision periodontal treatment. | 2024 | 39347119 |
| 9760 | 9 | 0.9884 | Mutations leading to ceftolozane/tazobactam and imipenem/cilastatin/relebactam resistance during in vivo exposure to ceftazidime/avibactam in Pseudomonas aeruginosa. Identifying resistance mechanisms to novel antimicrobials informs treatment strategies during infection and antimicrobial development. Studying resistance that develops during the treatment of an infection can provide the most clinically relevant mutations conferring resistance, but cross-sectional studies frequently identify multiple candidate resistance mutations without resolving the driver mutation. We performed whole-genome sequencing of longitudinal Pseudomonas aeruginosa from a patient whose P. aeruginosa developed imipenem/cilastatin/relebactam and ceftolozane/tazobactam resistance during ceftazidime/avibactam treatment. This analysis determined new mutations that arose in isolates resistant to both imipenem/cilastatin/relebactam and ceftolozane/tazobactam. Mutations in penicillin-binding protein 3 ftsI, the MexAB-OprM repressor nalD, and a virulence regulator pvdS were found in resistant isolates. Importantly, drug efflux was not increased in the resistant isolate compared to the most closely related susceptible isolates. We conclude that mutations in peptidoglycan synthesis genes can alter the efficacy of multiple antimicrobials. IMPORTANCE: Antibiotic resistance is a significant challenge for physicians trying to treat infections. The development of novel antibiotics to treat resistant infections has not been prioritized for decades, limiting treatment options for infections caused by many high-priority pathogens. Cross-resistance, when one mutation provides resistance to multiple antibiotics, is most problematic. Mutations that cause cross-resistance need to be considered when developing new antibiotics to guide developers toward drugs with different targets, and thus a better likelihood of efficacy. This work was undertaken to determine the mutation that caused resistance to three antibiotics for highly resistant Pseudomonas aeruginosa infection treatment while the bacteria were exposed to only one of these agents. The findings provide evidence that drug developers should endeavor to find effective antibiotics with new targets and that medical providers should utilize medications with different mechanisms of action in bacteria that have become resistant to even one of these three agents. | 2025 | 39932323 |
| 4394 | 10 | 0.9883 | Signatures of Selection at Drug Resistance Loci in Mycobacterium tuberculosis. Tuberculosis (TB) is the leading cause of death by an infectious disease, and global TB control efforts are increasingly threatened by drug resistance in Mycobacterium tuberculosis. Unlike most bacteria, where lateral gene transfer is an important mechanism of resistance acquisition, resistant M. tuberculosis arises solely by de novo chromosomal mutation. Using whole-genome sequencing data from two natural populations of M. tuberculosis, we characterized the population genetics of known drug resistance loci using measures of diversity, population differentiation, and convergent evolution. We found resistant subpopulations to be less diverse than susceptible subpopulations, consistent with ongoing transmission of resistant M. tuberculosis. A subset of resistance genes ("sloppy targets") were characterized by high diversity and multiple rare variants; we posit that a large genetic target for resistance and relaxation of purifying selection contribute to high diversity at these loci. For "tight targets" of selection, the path to resistance appeared narrower, evidenced by single favored mutations that arose numerous times in the phylogeny and segregated at markedly different frequencies in resistant and susceptible subpopulations. These results suggest that diverse genetic architectures underlie drug resistance in M. tuberculosis and that combined approaches are needed to identify causal mutations. Extrapolating from patterns observed for well-characterized genes, we identified novel candidate variants involved in resistance. The approach outlined here can be extended to identify resistance variants for new drugs, to investigate the genetic architecture of resistance, and when phenotypic data are available, to find candidate genetic loci underlying other positively selected traits in clonal bacteria. IMPORTANCEMycobacterium tuberculosis, the causative agent of tuberculosis (TB), is a significant burden on global health. Antibiotic treatment imposes strong selective pressure on M. tuberculosis populations. Identifying the mutations that cause drug resistance in M. tuberculosis is important for guiding TB treatment and halting the spread of drug resistance. Whole-genome sequencing (WGS) of M. tuberculosis isolates can be used to identify novel mutations mediating drug resistance and to predict resistance patterns faster than traditional methods of drug susceptibility testing. We have used WGS from natural populations of drug-resistant M. tuberculosis to characterize effects of selection for advantageous mutations on patterns of diversity at genes involved in drug resistance. The methods developed here can be used to identify novel advantageous mutations, including new resistance loci, in M. tuberculosis and other clonal pathogens. | 2018 | 29404424 |
| 6161 | 11 | 0.9883 | Unraveling radiation resistance strategies in two bacterial strains from the high background radiation area of Chavara-Neendakara: A comprehensive whole genome analysis. This paper reports the results of gamma irradiation experiments and whole genome sequencing (WGS) performed on vegetative cells of two radiation resistant bacterial strains, Metabacillus halosaccharovorans (VITHBRA001) and Bacillus paralicheniformis (VITHBRA024) (D10 values 2.32 kGy and 1.42 kGy, respectively), inhabiting the top-ranking high background radiation area (HBRA) of Chavara-Neendakara placer deposit (Kerala, India). The present investigation has been carried out in the context that information on strategies of bacteria having mid-range resistance for gamma radiation is inadequate. WGS, annotation, COG and KEGG analyses and manual curation of genes helped us address the possible pathways involved in the major domains of radiation resistance, involving recombination repair, base excision repair, nucleotide excision repair and mismatch repair, and the antioxidant genes, which the candidate could activate to survive under ionizing radiation. Additionally, with the help of these data, we could compare the candidate strains with that of the extremely radiation resistant model bacterium Deinococccus radiodurans, so as to find the commonalities existing in their strategies of resistance on the one hand, and also the rationale behind the difference in D10, on the other. Genomic analysis of VITHBRA001 and VITHBRA024 has further helped us ascertain the difference in capability of radiation resistance between the two strains. Significantly, the genes such as uvsE (NER), frnE (protein protection), ppk1 and ppx (non-enzymatic metabolite production) and those for carotenoid biosynthesis, are endogenous to VITHBRA001, but absent in VITHBRA024, which could explain the former's better radiation resistance. Further, this is the first-time study performed on any bacterial population inhabiting an HBRA. This study also brings forward the two species whose radiation resistance has not been reported thus far, and add to the knowledge on radiation resistant capabilities of the phylum Firmicutes which are abundantly observed in extreme environment. | 2024 | 38857267 |
| 9068 | 12 | 0.9883 | 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 |
| 5119 | 13 | 0.9882 | 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 |
| 2590 | 14 | 0.9882 | Combining stool and stories: exploring antimicrobial resistance among a longitudinal cohort of international health students. BACKGROUND: Antimicrobial resistance (AMR) is a global public health concern that requires transdisciplinary and bio-social approaches. Despite the continuous calls for a transdisciplinary understanding of this problem, there is still a lack of such studies. While microbiology generates knowledge about the biomedical nature of bacteria, social science explores various social practices related to the acquisition and spread of these bacteria. However, the two fields remain disconnected in both methodological and conceptual levels. Focusing on the acquisition of multidrug resistance genes, encoding extended-spectrum betalactamases (CTX-M) and carbapenemases (NDM-1) among a travelling population of health students, this article proposes a methodology of 'stool and stories' that combines methods of microbiology and sociology, thus proposing a way forward to a collaborative understanding of AMR. METHODS: A longitudinal study with 64 health students travelling to India was conducted in 2017. The study included multiple-choice questionnaires (n = 64); a collection of faecal swabs before travel (T0, n = 45), in the first week in India (T1, n = 44), the second week in India (T2, n = 41); and semi-structured interviews (n = 11). Stool samples were analysed by a targeted metagenomic approach. Data from semi-structured interviews were analysed using the method of thematic analysis. RESULTS: The incidence of ESBL- and carbapenemase resistance genes significantly increased during travel indicating it as a potential risk; for CTX-M from 11% before travel to 78% during travel and for NDM-1 from 2% before travel to 11% during travel. The data from semi-structured interviews showed that participants considered AMR mainly in relation to individual antibiotic use or its presence in a clinical environment but not to travelling. CONCLUSION: The microbiological analysis confirmed previous research showing that international human mobility is a risk factor for AMR acquisition. However, sociological methods demonstrated that travellers understand AMR primarily as a clinical problem and do not connect it to travelling. These findings indicate an important gap in understanding AMR as a bio-social problem raising a question about the potential effectiveness of biologically driven AMR stewardship programs among travellers. Further development of the 'stool and stories' approach is important for a transdisciplinary basis of AMR stewardship. | 2021 | 34579656 |
| 5110 | 15 | 0.9882 | Surveillance of carbapenem-resistant organisms using next-generation sequencing. The genomic data generated from next-generation sequencing (NGS) provides nucleotide-level resolution of bacterial genomes which is critical for disease surveillance and the implementation of prevention strategies to interrupt the spread of antimicrobial resistance (AMR) bacteria. Infection with AMR bacteria, including Gram-negative Carbapenem-Resistant Organisms (CRO), may be acute and recurrent-once they have colonized a patient, they are notoriously difficult to eradicate. Through phylogenetic tools that assess the single nucleotide polymorphisms (SNPs) within a pathogen genome dataset, public health scientists can estimate the genetic identity between isolates. This information is used as an epidemiologic proxy of a putative outbreak. Pathogens with minimal to no differences in SNPs are likely to be the same strain attributable to a common source or transmission between cases. These genomic comparisons enhance public health response by prompting targeted intervention and infection control measures. This methodology overview demonstrates the utility of phenotypic and molecular assays, antimicrobial susceptibility testing (AST), NGS, publicly available genomics databases, and open-source bioinformatics pipelines for a tiered workflow to detect resistance genes and potential clusters of illness. These methods, when used in combination, facilitate a genomic surveillance workflow for detecting potential AMR bacterial outbreaks to inform epidemiologic investigations. Use of this workflow helps to target and focus epidemiologic resources to the cases with the highest likelihood of being related. | 2023 | 37255756 |
| 9601 | 16 | 0.9882 | Phage steering in the presence of a competing bacterial pathogen. The rise of antibiotic-resistant bacteria has necessitated the development of alternative therapeutic strategies, such as bacteriophage therapy, where viruses infect bacteria, reducing bacterial burden. However, rapid bacterial resistance to phage treatment remains a critical challenge, potentially leading to failure. Phage steering, which leverages the evolutionary dynamics between phage and bacteria, offers a novel solution by driving bacteria to evolve away from virulence factors or resistance mechanisms. In this study, we examined whether phage steering using bacteriophage Luz19 could function in the presence of a competing pathogen, Staphylococcus aureus (SA) (USA300), while targeting Pseudomonas aeruginosa (PAO1). Through in vitro co-evolution experiments with and without the competitor, we observed that Luz19 consistently steered P. aeruginosa away from the Type IV pilus (T4P), a key virulence factor, without interference from SA. Genomic analyses revealed mutations in T4P-associated genes, including pilR and pilZ, which conferred phage resistance. Our findings suggest that phage steering remains effective even in polymicrobial environments, providing a promising avenue for enhancing bacteriophage therapy efficacy in complex infections.IMPORTANCEPhage steering-using phages that bind essential virulence or resistance-associated structures-offers a promising solution by selecting for resistance mutations that attenuate pathogenic traits. However, it remains unclear whether this strategy remains effective in polymicrobial contexts, where interspecies interactions may alter selective pressures. Here, we demonstrate that Pseudomonas aeruginosa evolves phage resistance via loss-of-function mutations in Type IV pilus (T4P) when challenged with the T4P-binding phage Luz19 and that this evolutionary trajectory is preserved even in the presence of a competing pathogen, Staphylococcus aureus. Phage resistance was phenotypically confirmed via twitching motility assays and genotypically via whole-genome sequencing. These findings support the robustness of phage steering under interspecies competition, underscoring its translational potential for managing complex infections-such as those seen in cystic fibrosis-where microbial diversity is the norm. | 2025 | 40492711 |
| 5115 | 17 | 0.9882 | 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 |
| 9759 | 18 | 0.9882 | Rapid emergence of resistance to broad-spectrum direct antimicrobial activity of avibactam. Avibactam (AVI) is a diazabicyclooctane (DBO) β-lactamase inhibitor used clinically in combination with ceftazidime. At concentrations higher than those typically achieved in vivo, it also has broad-spectrum direct antibacterial activity against Enterobacterales strains, including metallo-β-lactamase-producing isolates, mediated by inhibition of penicillin-binding protein 2 (PBP2). This activity has some mechanistic similarities to that of more potent novel DBOs (zidebactam and nacubactam) in late clinical development. We found that resistance to AVI emerged readily, with a mutation frequency of 2 × 10(-6) to 8 × 10(-5). Whole-genome sequencing of resistant isolates revealed a heterogeneous mutational target that permitted bacterial survival and replication despite PBP2 inhibition, in line with prior studies of PBP2-targeting drugs. While such mutations are believed to act by upregulating the bacterial stringent response, we found a similarly high mutation frequency in bacteria deficient in components of the stringent response, although we observed a different set of mutations in these strains. Although avibactam-resistant strains had increased lag time, suggesting a fitness cost that might render them less problematic in clinical infections, there was no statistically significant difference in growth rates between susceptible and resistant strains. The finding of rapid emergence of resistance to avibactam as the result of a large and complex mutational target adds to our understanding of resistance to PBP2-targeting drugs and has potential implications for novel DBOs with potent direct antibacterial activity, which are being developed with the goal of expanding cell wall-active treatment options for multidrug-resistant gram-negative infections.IMPORTANCEAvibactam (AVI) is the first in a class of novel β-lactamase inhibitor antibiotics called diazabicyclooctanes (DBOs). In addition to its ability to inhibit bacterial β-lactamase enzymes that can destroy β-lactam antibiotics, we found that AVI had direct antibacterial activity, at concentrations higher than those used clinically, against even highly multidrug-resistant bacteria. This activity is the result of inhibition of the bacterial enzyme penicillin-binding protein 2 (PBP2). Resistance to other drugs that inhibit PBP2 occurs through mutations that involve upregulation of the bacterial "stringent response" to stress. We found that bacteria developed resistance to AVI at a high rate, as a result of mutations in stringent response genes. We also found that bacteria with impairments in the stringent response could still develop resistance to AVI through different mutations. Our findings indicate the importance of studying how resistance will emerge to newer, more potent DBOs in development and early clinical use. | 2025 | 40503840 |
| 9086 | 19 | 0.9882 | Emergence and selection of isoniazid and rifampin resistance in tuberculosis granulomas. Drug resistant tuberculosis is increasing world-wide. Resistance against isoniazid (INH), rifampicin (RIF), or both (multi-drug resistant TB, MDR-TB) is of particular concern, since INH and RIF form part of the standard regimen for TB disease. While it is known that suboptimal treatment can lead to resistance, it remains unclear how host immune responses and antibiotic dynamics within granulomas (sites of infection) affect emergence and selection of drug-resistant bacteria. We take a systems pharmacology approach to explore resistance dynamics within granulomas. We integrate spatio-temporal host immunity, INH and RIF dynamics, and bacterial dynamics (including fitness costs and compensatory mutations) in a computational framework. We simulate resistance emergence in the absence of treatment, as well as resistance selection during INH and/or RIF treatment. There are four main findings. First, in the absence of treatment, the percentage of granulomas containing resistant bacteria mirrors the non-monotonic bacterial dynamics within granulomas. Second, drug-resistant bacteria are less frequently found in non-replicating states in caseum, compared to drug-sensitive bacteria. Third, due to a steeper dose response curve and faster plasma clearance of INH compared to RIF, INH-resistant bacteria have a stronger influence on treatment outcomes than RIF-resistant bacteria. Finally, under combination therapy with INH and RIF, few MDR bacteria are able to significantly affect treatment outcomes. Overall, our approach allows drug-specific prediction of drug resistance emergence and selection in the complex granuloma context. Since our predictions are based on pre-clinical data, our approach can be implemented relatively early in the treatment development process, thereby enabling pro-active rather than reactive responses to emerging drug resistance for new drugs. Furthermore, this quantitative and drug-specific approach can help identify drug-specific properties that influence resistance and use this information to design treatment regimens that minimize resistance selection and expand the useful life-span of new antibiotics. | 2018 | 29746491 |