# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9742 | 0 | 0.9929 | BOCS: DNA k-mer content and scoring for rapid genetic biomarker identification at low coverage. A single, inexpensive diagnostic test capable of rapidly identifying a wide range of genetic biomarkers would prove invaluable in precision medicine. Previous work has demonstrated the potential for high-throughput, label-free detection of A-G-C-T content in DNA k-mers, providing an alternative to single-letter sequencing while also having inherent lossy data compression and massively parallel data acquisition. Here, we apply a new bioinformatics algorithm - block optical content scoring (BOCS) - capable of using the high-throughput content k-mers for rapid, broad-spectrum identification of genetic biomarkers. BOCS uses content-based sequence alignment for probabilistic mapping of k-mer contents to gene sequences within a biomarker database, resulting in a probability ranking of genes on a content score. Simulations of the BOCS algorithm reveal high accuracy for identification of single antibiotic resistance genes, even in the presence of significant sequencing errors (100% accuracy for no sequencing errors, and >90% accuracy for sequencing errors at 20%), and at well below full coverage of the genes. Simulations for detecting multiple resistance genes within a methicillin-resistant Staphylococcus aureus (MRSA) strain showed 100% accuracy at an average gene coverage of merely 0.515, when the k-mer lengths were variable and with 4% sequencing error within the k-mer blocks. Extension of BOCS to cancer and other genetic diseases met or exceeded the results for resistance genes. Combined with a high-throughput content-based sequencing technique, the BOCS algorithm potentiates a test capable of rapid diagnosis and profiling of genetic biomarkers ranging from antibiotic resistance to cancer and other genetic diseases. | 2019 | 31173943 |
| 458 | 1 | 0.9927 | Genome sequencing of linezolid-resistant Streptococcus pneumoniae mutants reveals novel mechanisms of resistance. Linezolid is a member of a novel class of antibiotics, with resistance already being reported. We used whole-genome sequencing on three independent Streptococcus pneumoniae strains made resistant to linezolid in vitro in a step-by-step fashion. Analysis of the genome assemblies revealed mutations in the 23S rRNA gene in all mutants including, notably, G2576T, a previously recognized resistance mutation. Mutations in an additional 31 genes were also found in at least one of the three sequenced genomes. We concentrated on three new mutations that were found in at least two independent mutants. All three mutations were experimentally confirmed to be involved in antibiotic resistance. Mutations upstream of the ABC transporter genes spr1021 and spr1887 were correlated with increased expression of these genes and neighboring genes of the same operon. Gene inactivation supported a role for these ABC transporters in resistance to linezolid and other antibiotics. The hypothetical protein spr0333 contains an RNA methyltransferase domain, and mutations within that domain were found in all S. pneumoniae linezolid-resistant strains. Primer extension experiments indicated that spr0333 methylates G2445 of the 23S rRNA and mutations in spr0333 abolished this methylation. Reintroduction of a nonmutated version of spr0333 in resistant bacteria reestablished G2445 methylation and led to cells being more sensitive to linezolid and other antibiotics. Interestingly, the spr0333 ortholog was also mutated in a linezolid-resistant clinical Staphylococcus aureus isolate. Whole-genome sequencing and comparative analyses of S. pneumoniae resistant isolates was useful for discovering novel resistance mutations. | 2009 | 19351617 |
| 9741 | 2 | 0.9925 | ARGai 1.0: A GAN augmented in silico approach for identifying resistant genes and strains in E. coli using vision transformer. The emergence of infectious disease and antibiotic resistance in bacteria like Escherichia coli (E. coli) shows the necessity for novel computational techniques for identifying essential genes that contribute to resistance. The task of identifying resistant strains and multi-drug patterns in E. coli is a major challenge with whole genome sequencing (WGS) and next-generation sequencing (NGS) data. To address this issue, we suggest ARGai 1.0 a deep learning architecture enhanced with generative adversarial networks (GANs). We mitigate data scarcity difficulties by augmenting limited experimental datasets with synthetic data generated by GANs. Our in-silico method (augmentation with feature selection) improves the identification of resistance genes in E. coli by using feature extraction techniques to identify valuable features from actual and GAN-generated data. Employing comprehensive validation, we exhibit the effectiveness of our ARGai 1.0 in precisely identifying the informative and resistant genes. In addition, our ARGai 1.0 identifies the resistant strains with a classification accuracy of 98.96 % on Deep Convolutional Generative Adversarial Network (DCGAN) augmented data. Additionally, ARGai 1.0 achieves more than 98 % of sensitivity and specificity. We also benchmark our ARGai 1.0 with several state-of-the-art AI models for resistant strain classification. In the fight against antibiotic resistance, ARGai 1.0 offers a promising avenue for computational genomics. With implications for research and clinical practice, this work shows the potential of deep networks with GAN augmentation as a practical and successful method for gene identification in E. coli. | 2025 | 39813877 |
| 9766 | 3 | 0.9925 | Facile accelerated specific therapeutic (FAST) platform develops antisense therapies to counter multidrug-resistant bacteria. Multidrug-resistant (MDR) bacteria pose a grave concern to global health, which is perpetuated by a lack of new treatments and countermeasure platforms to combat outbreaks or antibiotic resistance. To address this, we have developed a Facile Accelerated Specific Therapeutic (FAST) platform that can develop effective peptide nucleic acid (PNA) therapies against MDR bacteria within a week. Our FAST platform uses a bioinformatics toolbox to design sequence-specific PNAs targeting non-traditional pathways/genes of bacteria, then performs in-situ synthesis, validation, and efficacy testing of selected PNAs. As a proof of concept, these PNAs were tested against five MDR clinical isolates: carbapenem-resistant Escherichia coli, extended-spectrum beta-lactamase Klebsiella pneumoniae, New Delhi Metallo-beta-lactamase-1 carrying Klebsiella pneumoniae, and MDR Salmonella enterica. PNAs showed significant growth inhibition for 82% of treatments, with nearly 18% of treatments leading to greater than 97% decrease. Further, these PNAs are capable of potentiating antibiotic activity in the clinical isolates despite presence of cognate resistance genes. Finally, the FAST platform offers a novel delivery approach to overcome limited transport of PNAs into mammalian cells by repurposing the bacterial Type III secretion system in conjunction with a kill switch that is effective at eliminating 99.6% of an intracellular Salmonella infection in human epithelial cells. | 2021 | 33712689 |
| 9745 | 4 | 0.9925 | Analysis of Identification Method for Bacterial Species and Antibiotic Resistance Genes Using Optical Data From DNA Oligomers. Bacterial antibiotic resistance is becoming a significant health threat, and rapid identification of antibiotic-resistant bacteria is essential to save lives and reduce the spread of antibiotic resistance. This paper analyzes the ability of machine learning algorithms (MLAs) to process data from a novel spectroscopic diagnostic device to identify antibiotic-resistant genes and bacterial species by comparison to available bacterial DNA sequences. Simulation results show that the algorithms attain from 92% accuracy (for genes) up to 99% accuracy (for species). This novel approach identifies genes and species by optically reading the percentage of A, C, G, T bases in 1000s of short 10-base DNA oligomers instead of relying on conventional DNA sequencing in which the sequence of bases in long oligomers provides genetic information. The identification algorithms are robust in the presence of simulated random genetic mutations and simulated random experimental errors. Thus, these algorithms can be used to identify bacterial species, to reveal antibiotic resistance genes, and to perform other genomic analyses. Some MLAs evaluated here are shown to be better than others at accurate gene identification and avoidance of false negative identification of antibiotic resistance. | 2020 | 32153541 |
| 5835 | 5 | 0.9924 | Rapid and Ultrasensitive Detection of Mutations and Genes Relevant to Antimicrobial Resistance in Bacteria. The worldwide emergence of multidrug-resistant (MDR) bacteria is associated with significant morbidity, mortality, and healthcare costs. Rapid and accurate diagnostic methods to detect antibiotic resistance are critical for antibiotic stewardship and infection control measurements. Here a cantilever nanosensor-based diagnostic assay is shown to detect single nucleotide polymorphisms (SNPs) and genes associated with antibiotic resistance in Gram negative (Pseudomonas aeruginosa) and positive (Enterococcus faecium) bacteria, representing frequent causes for MDR infections. Highly specific RNA capture probes for SNPs (ampR(D135G) or ampR(G154R) ) or resistance genes (vanA, vanB, and vanD) allow to detect the binding of bacterial RNA within less than 5 min. Serial dilutions of bacterial RNA indicate an unprecedented sensitivity of 10 fg µL(-1) total RNA corresponding to less than ten bacterial cells for SNPs and 1 fg µL(-1) total RNA for vanD detection equivalent to single bacterial cell sensitivity. | 2021 | 33552553 |
| 9735 | 6 | 0.9924 | Arms race and fluctuating selection dynamics in Pseudomonas aeruginosa bacteria coevolving with phage OMKO1. Experimental evolution studies have examined coevolutionary dynamics between bacteria and lytic phages, where two models for antagonistic coevolution dominate: arms-race dynamics (ARD) and fluctuating-selection dynamics (FSD). Here, we tested the ability for Pseudomonas aeruginosa to coevolve with phage OMKO1 during 10 passages in the laboratory, whether ARD versus FSD coevolution occurred, and how coevolution affected a predicted phenotypic trade-off between phage resistance and antibiotic sensitivity. We used a unique "deep" sampling design, where 96 bacterial clones per passage were obtained from the three replicate coevolving communities. Next, we examined phenotypic changes in growth ability, susceptibility to phage infection and resistance to antibiotics. Results confirmed that the bacteria and phages coexisted throughout the study with one community undergoing ARD, whereas the other two showed evidence for FSD. Surprisingly, only the ARD bacteria demonstrated the anticipated trade-off. Whole genome sequencing revealed that treatment populations of bacteria accrued more de novo mutations, relative to a control bacterial population. Additionally, coevolved bacteria presented mutations in genes for biosynthesis of flagella, type-IV pilus and lipopolysaccharide, with three mutations fixing contemporaneously with the occurrence of the phenotypic trade-off in the ARD-coevolved bacteria. Our study demonstrates that both ARD and FSD coevolution outcomes are possible in a single interacting bacteria-phage system and that occurrence of predicted phage-driven evolutionary trade-offs may depend on the genetics underlying evolution of phage resistance in bacteria. These results are relevant for the ongoing development of lytic phages, such as OMKO1, in personalized treatment of human patients, as an alternative to antibiotics. | 2022 | 36168737 |
| 5068 | 7 | 0.9924 | Ultrasensitive Label-Free Detection of Unamplified Multidrug-Resistance Bacteria Genes with a Bimodal Waveguide Interferometric Biosensor. Infections by multidrug-resistant bacteria are becoming a major healthcare emergence with millions of reported cases every year and an increasing incidence of deaths. An advanced diagnostic platform able to directly detect and identify antimicrobial resistance in a faster way than conventional techniques could help in the adoption of early and accurate therapeutic interventions, limiting the actual negative impact on patient outcomes. With this objective, we have developed a new biosensor methodology using an ultrasensitive nanophotonic bimodal waveguide interferometer (BiMW), which allows a rapid and direct detection, without amplification, of two prevalent and clinically relevant Gram-negative antimicrobial resistance encoding sequences: the extended-spectrum betalactamase-encoding gene blaCTX-M-15 and the carbapenemase-encoding gene blaNDM-5 We demonstrate the extreme sensitivity and specificity of our biosensor methodology for the detection of both gene sequences. Our results show that the BiMW biosensor can be employed as an ultrasensitive (attomolar level) and specific diagnostic tool for rapidly (less than 30 min) identifying drug resistance. The BiMW nanobiosensor holds great promise as a powerful tool for the control and management of healthcare-associated infections by multidrug-resistant bacteria. | 2020 | 33086716 |
| 8839 | 8 | 0.9923 | Bacteriophage infection drives loss of β-lactam resistance in methicillin-resistant Staphylococcus aureus. Bacteriophage (phage) therapy is a promising means to combat drug-resistant bacterial pathogens. Infection by phage can select for mutations in bacterial populations that confer resistance against phage infection. However, resistance against phage can yield evolutionary trade-offs of biomedical relevance. Here, we report the discovery that infection by certain staphylococcal phages sensitizes different strains of methicillin-resistant Staphylococcus aureus (MRSA) to β-lactams, a class of antibiotics against which MRSA is typically resistant. MRSA cells that survive infection by these phages display significant reductions in minimal inhibitory concentration against different β-lactams compared to uninfected bacteria. Transcriptomic profiling reveals that these evolved MRSA strains possess highly modulated transcriptional profiles, where numerous genes involved in S. aureus virulence are downregulated. Phage-treated MRSA exhibited attenuated virulence phenotypes in the form of reduced hemolysis and clumping. Despite sharing similar phenotypes, whole-sequencing analysis revealed that the different MRSA strains evolved unique genetic profiles during infection. These results suggest complex evolutionary trajectories in MRSA during phage predation and open up new possibilities to reduce drug resistance and virulence in MRSA infections. | 2025 | 40637714 |
| 3768 | 9 | 0.9923 | The Concerted Action of Two B3-Like Prophage Genes Excludes Superinfecting Bacteriophages by Blocking DNA Entry into Pseudomonas aeruginosa. In this study, we describe seven vegetative phage genomes homologous to the historic phage B3 that infect Pseudomonas aeruginosa Like other phage groups, the B3-like group contains conserved (core) and variable (accessory) open reading frames (ORFs) grouped at fixed regions in their genomes; however, in either case, many ORFs remain without assigned functions. We constructed lysogens of the seven B3-like phages in strain Ps33 of P. aeruginosa, a novel clinical isolate, and assayed the exclusion phenotype against a variety of temperate and virulent superinfecting phages. In addition to the classic exclusion conferred by the phage immunity repressor, the phenotype observed in B3-like lysogens suggested the presence of other exclusion genes. We set out to identify the genes responsible for this exclusion phenotype. Phage Ps56 was chosen as the study subject since it excluded numerous temperate and virulent phages. Restriction of the Ps56 genome, cloning of several fragments, and resection of the fragments that retained the exclusion phenotype allowed us to identify two core ORFs, so far without any assigned function, as responsible for a type of exclusion. Neither gene expressed separately from plasmids showed activity, but the concurrent expression of both ORFs is needed for exclusion. Our data suggest that phage adsorption occurs but that phage genome translocation to the host's cytoplasm is defective. To our knowledge, this is the first report on this type of exclusion mediated by a prophage in P. aeruginosaIMPORTANCEPseudomonas aeruginosa is a Gram-negative bacterium frequently isolated from infected immunocompromised patients, and the strains are resistant to a broad spectrum of antibiotics. Recently, the use of phages has been proposed as an alternative therapy against multidrug-resistant bacteria. However, this approach may present various hurdles. This work addresses the problem that pathogenic bacteria may be lysogenized by phages carrying genes encoding resistance against secondary infections, such as those used in phage therapy. Discovering phage genes that exclude superinfecting phages not only assigns novel functions to orphan genes in databases but also provides insight into selection of the proper phages for use in phage therapy. | 2020 | 32461312 |
| 8401 | 10 | 0.9923 | LSTrAP-Crowd: prediction of novel components of bacterial ribosomes with crowd-sourced analysis of RNA sequencing data. BACKGROUND: Bacterial resistance to antibiotics is a growing health problem that is projected to cause more deaths than cancer by 2050. Consequently, novel antibiotics are urgently needed. Since more than half of the available antibiotics target the structurally conserved bacterial ribosomes, factors involved in protein synthesis are thus prime targets for the development of novel antibiotics. However, experimental identification of these potential antibiotic target proteins can be labor-intensive and challenging, as these proteins are likely to be poorly characterized and specific to few bacteria. Here, we use a bioinformatics approach to identify novel components of protein synthesis. RESULTS: In order to identify these novel proteins, we established a Large-Scale Transcriptomic Analysis Pipeline in Crowd (LSTrAP-Crowd), where 285 individuals processed 26 terabytes of RNA-sequencing data of the 17 most notorious bacterial pathogens. In total, the crowd processed 26,269 RNA-seq experiments and used the data to construct gene co-expression networks, which were used to identify more than a hundred uncharacterized genes that were transcriptionally associated with protein synthesis. We provide the identity of these genes together with the processed gene expression data. CONCLUSIONS: We identified genes related to protein synthesis in common bacterial pathogens and thus provide a resource of potential antibiotic development targets for experimental validation. The data can be used to explore additional vulnerabilities of bacteria, while our approach demonstrates how the processing of gene expression data can be easily crowd-sourced. | 2020 | 32883264 |
| 9211 | 11 | 0.9923 | Use of Staby(®) technology for development and production of DNA vaccines free of antibiotic resistance gene. The appearance of new viruses and the cost of developing certain vaccines require that new vaccination strategies now have to be developed. DNA vaccination seems to be a particularly promising method. For this application, plasmid DNA is injected into the subject (man or animal). This plasmid DNA encodes an antigen that will be expressed by the cells of the subject. In addition to the antigen, the plasmid also encodes a resistance to an antibiotic, which is used during the construction and production steps of the plasmid. However, regulatory agencies (FDA, USDA and EMA) recommend to avoid the use of antibiotics resistance genes. Delphi Genetics developed the Staby(®) technology to replace the antibiotic-resistance gene by a selection system that relies on two bacterial genes. These genes are small in size (approximately 200 to 300 bases each) and consequently encode two small proteins. They are naturally present in the genomes of bacteria and on plasmids. The technology is already used successfully for production of recombinant proteins to achieve higher yields and without the need of antibiotics. In the field of DNA vaccines, we have now the first data validating the innocuousness of this Staby(®) technology for eukaryotic cells and the feasibility of an industrial production of an antibiotic-free DNA vaccine. Moreover, as a proof of concept, mice have been successfully vaccinated with our antibiotic-free DNA vaccine against a deadly disease, pseudorabies (induced by Suid herpesvirus-1). | 2013 | 24051431 |
| 8855 | 12 | 0.9923 | Transposon Insertion Sequencing Elucidates Novel Gene Involvement in Susceptibility and Resistance to Phages T4 and T7 in Escherichia coli O157. Experiments using bacteriophage (phage) to infect bacterial strains have helped define some basic genetic concepts in microbiology, but our understanding of the complexity of bacterium-phage interactions is still limited. As the global threat of antibiotic resistance continues to increase, phage therapy has reemerged as an attractive alternative or supplement to treating antibiotic-resistant bacterial infections. Further, the long-used method of phage typing to classify bacterial strains is being replaced by molecular genetic techniques. Thus, there is a growing need for a complete understanding of the precise molecular mechanisms underpinning phage-bacterium interactions to optimize phage therapy for the clinic as well as for retrospectively interpreting phage typing data on the molecular level. In this study, a genomics-based fitness assay (TraDIS) was used to identify all host genes involved in phage susceptibility and resistance for a T4 phage infecting Shiga-toxigenic Escherichia coli O157. The TraDIS results identified both established and previously unidentified genes involved in phage infection, and a subset were confirmed by site-directed mutagenesis and phenotypic testing of 14 T4 and 2 T7 phages. For the first time, the entire sap operon was implicated in phage susceptibility and, conversely, the stringent starvation protein A gene (sspA) was shown to provide phage resistance. Identifying genes involved in phage infection and replication should facilitate the selection of bespoke phage combinations to target specific bacterial pathogens.IMPORTANCE Antibiotic resistance has diminished treatment options for many common bacterial infections. Phage therapy is an alternative option that was once popularly used across Europe to kill bacteria within humans. Phage therapy acts by using highly specific viruses (called phages) that infect and lyse certain bacterial species to treat the infection. Whole-genome sequencing has allowed modernization of the investigations into phage-bacterium interactions. Here, using E. coli O157 and T4 bacteriophage as a model, we have exploited a genome-wide fitness assay to investigate all genes involved in defining phage resistance or susceptibility. This knowledge of the genetic determinants of phage resistance and susceptibility can be used to design bespoke phage combinations targeted to specific bacterial infections for successful infection eradication. | 2018 | 30042196 |
| 3767 | 13 | 0.9923 | Transposon insertion sequencing reveals novel hypermutator genes in Acinetobacter baumannii. Mutation rates in bacteria are an important determinant of adaptation to new environments and success in different niches. In some bacterial pathogens, "hypermutator" variants-most often associated with mutations in components of the DNA mismatch repair system-are associated with increased antibiotic resistance and poorer patient outcomes. We report the serendipitous finding of novel hypermutator genes in Acinetobacter baumannii through genome-scale mutant fitness screening. Exposure of a transposon insertion mutant library of A. baumannii to extended weak antibiotic selection resulted in selection for mutations that directly increased fitness as expected, but also revealed genes where transposon insertion indirectly increased fitness due to elevated general mutation rates. Three novel hypermutator genes were confirmed in A. baumannii: nusB, encoding a transcription antiterminator; ABUW_0208, encoding a hypothetical protein; and ABUW_2121, which encodes a sulfite transporter. We find selection for hypermutator variants in transposon insertion sequencing (TIS) data sets from diverse bacteria under various antibiotic treatments. Our results expand the range of biological functions linked to hypermutator phenotypes in bacteria and provide a workflow for the identification of putative hypermutators by TIS.IMPORTANCEAll organisms have the capacity for evolution through mutation. Bacteria with high mutation rates have a survival advantage in some stressful environments because they generate beneficial mutations more frequently. "Hypermutators" are bacterial strains that carry gene inactivations that increase general mutation rates. These variants are important in chronic infections, as their increased genetic diversity allows higher drug resistance and prolonged survival in the host. Only a few different hypermutator genes are known, and there is no high-throughput method for their identification. We have made the serendipitous finding that hypermutator genes can be identified by genome-wide mutant fitness screening under specific selection conditions. We have identified novel hypermutator alleles in the notorious hospital pathogen Acinetobacter baumannii and show that hypermutator variants can be detected in screens of a wide range of pathogens. | 2025 | 40576344 |
| 4347 | 14 | 0.9923 | Going through phages: a computational approach to revealing the role of prophage in Staphylococcus aureus. Prophages have important roles in virulence, antibiotic resistance, and genome evolution in Staphylococcus aureus . Rapid growth in the number of sequenced S. aureus genomes allows for an investigation of prophage sequences at an unprecedented scale. We developed a novel computational pipeline for phage discovery and annotation. We combined PhiSpy, a phage discovery tool, with VGAS and PROKKA, genome annotation tools to detect and analyse prophage sequences in nearly 10 011 S . aureus genomes, discovering thousands of putative prophage sequences with genes encoding virulence factors and antibiotic resistance. To our knowledge, this is the first large-scale application of PhiSpy on a large-scale set of genomes (10 011 S . aureus ). Determining the presence of virulence and resistance encoding genes in prophage has implications for the potential transfer of these genes/functions to other bacteria via transduction and thus can provide insight into the evolution and spread of these genes/functions between bacterial strains. While the phage we have identified may be known, these phages were not necessarily known or characterized in S. aureus and the clustering and comparison we did for phage based on their gene content is novel. Moreover, the reporting of these genes with the S. aureus genomes is novel. | 2023 | 37424556 |
| 6208 | 15 | 0.9922 | Identification of bistable populations of Porphyromonas gingivalis that differ in epithelial cell invasion. Bistable populations of bacteria give rise to two or more subtypes that exhibit different phenotypes. We have explored whether the periodontal pathogen Porphyromonas gingivalis exhibits bistable invasive phenotypes. Using a modified cell invasion assay, we show for the first time that there are two distinct subtypes within a population of P. gingivalis strains NCTC 11834 and W50 that display differences in their ability to invade oral epithelial cells. The highly invasive subtype invades cells at 10-30-fold higher levels than the poorly invasive subtype and remains highly invasive for approximately 12-16 generations. Analysis of the gingipain activity of these subtypes revealed that the highly invasive type had reduced cell-associated arginine-specific protease activity. The role of Arg-gingipain activity in invasion was verified by enhancement of invasion by rgpAB mutations and by inclusion of an Arg-gingipain inhibitor in invasion assays using wild-type bacteria. In addition, a population of ΔrgpAB bacteria did not contain a hyperinvasive subtype. Screening of the protease activity of wild-type populations of both strains identified high and low protease subtypes which also showed a corresponding reduction or enhancement, respectively, of invasive capabilities. Microarray analysis of these bistable populations revealed a putative signature set of genes that includes oxidative stress resistance and iron transport genes, and which might be critical to invasion of or survival within epithelial cells. | 2010 | 20576685 |
| 5111 | 16 | 0.9922 | 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 |
| 3766 | 17 | 0.9922 | Identification of Genome-Wide Mutations in Ciprofloxacin-Resistant F. tularensis LVS Using Whole Genome Tiling Arrays and Next Generation Sequencing. Francisella tularensis is classified as a Class A bioterrorism agent by the U.S. government due to its high virulence and the ease with which it can be spread as an aerosol. It is a facultative intracellular pathogen and the causative agent of tularemia. Ciprofloxacin (Cipro) is a broad spectrum antibiotic effective against Gram-positive and Gram-negative bacteria. Increased Cipro resistance in pathogenic microbes is of serious concern when considering options for medical treatment of bacterial infections. Identification of genes and loci that are associated with Ciprofloxacin resistance will help advance the understanding of resistance mechanisms and may, in the future, provide better treatment options for patients. It may also provide information for development of assays that can rapidly identify Cipro-resistant isolates of this pathogen. In this study, we selected a large number of F. tularensis live vaccine strain (LVS) isolates that survived in progressively higher Ciprofloxacin concentrations, screened the isolates using a whole genome F. tularensis LVS tiling microarray and Illumina sequencing, and identified both known and novel mutations associated with resistance. Genes containing mutations encode DNA gyrase subunit A, a hypothetical protein, an asparagine synthase, a sugar transamine/perosamine synthetase and others. Structural modeling performed on these proteins provides insights into the potential function of these proteins and how they might contribute to Cipro resistance mechanisms. | 2016 | 27668749 |
| 9759 | 18 | 0.9922 | 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 |
| 4345 | 19 | 0.9922 | 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 |