# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9923 | 0 | 1.0000 | Antibiotic Resistance Genes Online (ARGO): a Database on vancomycin and beta-lactam resistance genes. Vancomycin and beta-lactams are antibiotics that inhibit gram positive bacteria by interfering with cell wall synthesis. However, continuous use of antibiotics results in the emergence of multi-drug resistant (MDR) bacterial strains. Here, we describe ARGO, a database containing gene sequences conferring resistance to these two classes of antibiotics. It is designed as a resource to enhance research on the prevalence and spread of antibiotic resistance genes. ARGO is the first attempt to compile the resistance gene sequence data with state specific information. AVAILABILITY: AGRO is available for free at http://www.argodb.org/ | 2005 | 17597841 |
| 4839 | 1 | 0.9996 | beta-Lactamases: protein evolution in real time. The evolution and spread of bacteria resistant to beta-lactam antibiotics has progressed at an alarming rate. Bacteria may acquire resistance to a given drug by mutation of pre-existing genes or by the acquisition of new genes from other bacteria. One ongoing example of these mechanisms is the evolution of new variants of the TEM and SHV beta-lactamases with altered substrate specificity. | 1998 | 9746943 |
| 4455 | 2 | 0.9996 | 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 |
| 9916 | 3 | 0.9996 | Collateral sensitivity associated with antibiotic resistance plasmids. Collateral sensitivity (CS) is a promising alternative approach to counteract the rising problem of antibiotic resistance (ABR). CS occurs when the acquisition of resistance to one antibiotic produces increased susceptibility to a second antibiotic. Recent studies have focused on CS strategies designed against ABR mediated by chromosomal mutations. However, one of the main drivers of ABR in clinically relevant bacteria is the horizontal transfer of ABR genes mediated by plasmids. Here, we report the first analysis of CS associated with the acquisition of complete ABR plasmids, including the clinically important carbapenem-resistance conjugative plasmid pOXA-48. In addition, we describe the conservation of CS in clinical E. coli isolates and its application to selectively kill plasmid-carrying bacteria. Our results provide new insights that establish the basis for developing CS-informed treatment strategies to combat plasmid-mediated ABR. | 2021 | 33470194 |
| 4456 | 4 | 0.9995 | Predictive analysis of transmissible quinolone resistance indicates Stenotrophomonas maltophilia as a potential source of a novel family of Qnr determinants. BACKGROUND: Predicting antibiotic resistance before it emerges at clinical settings constitutes a novel approach for preventing and fighting resistance of bacterial pathogens. To analyse the possibility that novel plasmid-encoded quinolone resistance determinants (Qnr) can emerge and disseminate among bacterial pathogens, we searched the presence of those elements in nearly 1000 bacterial genomes and metagenomes. RESULTS: We have found a number of novel potential qnr genes in the chromosomes of aquatic bacteria and in metagenomes from marine organisms. Functional studies of the Stenotrophomonas maltophilia Smqnr gene show that plasmid-encoded SmQnr confers quinolone resistance upon its expression in a heterologous host. CONCLUSION: Altogether, the data presented in our work support the notion that predictive studies on antibiotic resistance are feasible, using currently available information on bacterial genomes and with the aid of bioinformatic and functional tools. Our results confirm that aquatic bacteria can be the origin of plasmid-encoded Qnr, and highlight the potential role of S. maltophilia as a source of novel Qnr determinants. | 2008 | 18793450 |
| 4319 | 5 | 0.9995 | Threat and Control of tet(X)-Mediated Tigecycline-Resistant Acinetobacter sp. Bacteria. Tigecycline is regarded as one of the last-resort antibiotics against multidrug-resistant (MDR) Acinetobacter sp. bacteria. Recently, the tigecycline-resistant Acinetobacter sp. isolates mediated by tet(X) genes have emerged as a class of global pathogens for humans and food-producing animals. However, the genetic diversities and treatment options were not systematically discussed in the era of One Health. In this review, we provide a detailed illustration of the evolution route, distribution characteristics, horizontal transmission, and rapid detection of tet(X) genes in diverse Acinetobacter species. We also detail the application of chemical drugs, plant extracts, phages, antimicrobial peptides (AMPs), and CRISPR-Cas technologies for controlling tet(X)-positive Acinetobacter sp. pathogens. Despite excellent activities, the antibacterial spectrum and application safety need further evaluation and resolution. It is noted that deep learning is a promising approach to identify more potent antimicrobial compounds. | 2025 | 41097540 |
| 4313 | 6 | 0.9995 | Molecular epidemiology of clinically significant antibiotic resistance genes. Antimicrobials were first introduced into medical practice a little over 60 years ago and since that time resistant strains of bacteria have arisen in response to the selective pressure of their use. This review uses the paradigm of the evolution and spread of beta-lactamases and in particular beta-lactamases active against antimicrobials used to treat Gram-negative infections. The emergence and evolution particularly of CTX-M extended-spectrum beta-lactamases (ESBLs) is described together with the molecular mechanisms responsible for both primary mutation and horizontal gene transfer. Reference is also made to other significant antibiotic resistance genes, resistance mechanisms in Gram-negative bacteria, such as carbepenamases, and plasmid-mediated fluoroquinolone resistance. The pathogen Staphylococcus aureus is reviewed in detail as an example of a highly successful Gram-positive bacterial pathogen that has acquired and developed resistance to a wide range of antimicrobials. The role of selective pressures in the environment as well as the medical use of antimicrobials together with the interplay of various genetic mechanisms for horizontal gene transfer are considered in the concluding part of this review. | 2008 | 18311156 |
| 4325 | 7 | 0.9995 | Research Updates of Plasmid-Mediated Aminoglycoside Resistance 16S rRNA Methyltransferase. With the wide spread of multidrug-resistant bacteria, a variety of aminoglycosides have been used in clinical practice as one of the effective options for antimicrobial combinations. However, in recent years, the emergence of high-level resistance against pan-aminoglycosides has worsened the status of antimicrobial resistance, so the production of 16S rRNA methyltransferase (16S-RMTase) should not be ignored as one of the most important resistance mechanisms. What is more, on account of transferable plasmids, the horizontal transfer of resistance genes between pathogens becomes easier and more widespread, which brings challenges to the treatment of infectious diseases and infection control of drug-resistant bacteria. In this review, we will make a presentation on the prevalence and genetic environment of 16S-RMTase encoding genes that lead to high-level resistance to aminoglycosides. | 2022 | 35884160 |
| 4671 | 8 | 0.9995 | Detection by metagenomic functional analysis and improvement by experimental evolution of β-lactams resistance genes present in oil contaminated soils. The spread of antibiotic resistance genes has become a global health concern identified by the World Health Organization as one of the greatest threats to health. Many of antimicrobial resistance determinants found in bacterial pathogens originate from environmental bacteria, so identifying the genes that confer resistance to antibiotics in different habitats is mandatory to better understand resistance mechanisms. Soil is one of the most diverse environments considered reservoir of antimicrobial resistance genes. The aim of this work is to study the presence of genes that provide resistance to antibiotics used in clinical settings in two oil contaminated soils by metagenomic functional analysis. Using fosmid vectors that efficiently transcribe metagenomic DNA, we have selected 12 fosmids coding for two class A β-lactamases, two subclass B1 and two subclass B3 metallo-β-lactamases, one class D β-lactamase and three efflux pumps that confer resistance to cefexime, ceftriaxone, meropenem and/or imipenem. In some of them, detection of the resistance required heterologous expression from the fosmid promoter. Although initially, these environmental genes only provide resistance to low concentrations of antibiotics, we have obtained, by experimental evolution, fosmid derivatives containing β-lactamase ORFs with a single base substitution, which substantially increase their β-lactamase activity and resistance level. None of the mutations affect β-lactamase coding sequences and are all located upstream of them. These results demonstrate the presence of enzymes that confer resistance to relevant β-lactams in these soils and their capacity to rapidly adapt to provide higher resistance levels. | 2022 | 35768448 |
| 5111 | 9 | 0.9995 | 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 |
| 9917 | 10 | 0.9995 | Fluorescence-Based Detection of Natural Transformation in Drug-Resistant Acinetobacter baumannii. Acinetobacter baumannii is a nosocomial agent with a high propensity for developing resistance to antibiotics. This ability relies on horizontal gene transfer mechanisms occurring in the Acinetobacter genus, including natural transformation. To study natural transformation in bacteria, the most prevalent method uses selection for the acquisition of an antibiotic resistance marker in a target chromosomal locus by the recipient cell. Most clinical isolates of A. baumannii are resistant to multiple antibiotics, limiting the use of such selection-based methods. Here, we report the development of a phenotypic and selection-free method based on flow cytometry to detect transformation events in multidrug-resistant (MDR) clinical A. baumannii isolates. To this end, we engineered a translational fusion between the abundant and conserved A. baumannii nucleoprotein (HU) and the superfolder green fluorescent protein (sfGFP). The new method was benchmarked against the conventional antibiotic selection-based method. Using this new method, we investigated several parameters affecting transformation efficiencies and identified conditions of transformability one hundred times higher than those previously reported. Using optimized transformation conditions, we probed natural transformation in a set of MDR clinical and nonclinical animal A. baumannii isolates. Regardless of their origin, the majority of the isolates displayed natural transformability, indicative of a conserved trait in the species. Overall, this new method and optimized protocol will greatly facilitate the study of natural transformation in the opportunistic pathogen A. baumanniiIMPORTANCE Antibiotic resistance is a pressing global health concern with the rise of multiple and panresistant pathogens. The rapid and unfailing resistance to multiple antibiotics of the nosocomial agent Acinetobacter baumannii, notably to carbapenems, prompt to understand the mechanisms behind acquisition of new antibiotic resistance genes. Natural transformation, one of the horizontal gene transfer mechanisms in bacteria, was only recently described in A. baumannii and could explain its ability to acquire resistance genes. We developed a reliable method to probe and study natural transformation mechanism in A. baumannii More broadly, this new method based on flow cytometry will allow experimental detection and quantification of horizontal gene transfer events in multidrug-resistant A. baumannii. | 2018 | 30012729 |
| 4835 | 11 | 0.9995 | Genetic and biochemical basis of resistance of Enterobacteriaceae to beta-lactam antibiotics. Resistance to beta-lactam drugs is usually determined by genes mediating the production of beta-lactamases. These genes can be located on resistance plasmids or on the chromosome. Resistance to drugs which have been available for many years is mostly transposable. Although the origin of these genes is not known, it is possible to draw a hypothetical flow diagram of the evolution of resistance genes in general. The mechanism of resistance although mediated in Gram-negative bacteria mostly by beta-lactamases cannot be simply described as the hydrolytic function of the enzyme. It is a complex interaction involving the affinity of the drug for the target and the lactamase, the amount of drug in the periplasmic space, the amount of enzyme and the number of lethal target sites. Usually one of these factors is predominant. | 1986 | 3491818 |
| 9827 | 12 | 0.9995 | Evolution of bacterial resistance to antibiotics during the last three decades. Bacterial resistance to antibiotics is often plasmid-mediated and the associated genes encoded by transposable elements. These elements play a central role in evolution by providing mechanisms for the generation of diversity and, in conjunction with DNA transfer systems, for the dissemination of resistances to other bacteria. At the University Hospital of Zaragoza, extensive efforts have been made to define both the dissemination and evolution of antibiotic resistance by studying the transferable R plasmids and transposable elements. Here we describe the research on bacterial resistance to antibiotics in which many authors listed in the references have participated. The aspects of bacterial resistance dealt with are: (i) transferable resistance mediated by R plasmids in Gram-negative bacteria, (ii) R plasmid-mediated resistance to apramycin and hygromycin in clinical strains, (iii) the transposon Tn1696 and the integron In4, (iv) expression of Escherichia coli resistance genes in Haemophilus influenzae, (v) aminoglycoside-modifying-enzymes in the genus Mycobacterium with no relation to resistance, and (vi) macrolide-resistance and new mechanisms developed by Gram-positive bacteria. | 1998 | 10943375 |
| 4897 | 13 | 0.9995 | Rapid diagnosis of tuberculosis. Detection of drug resistance mechanisms. Tuberculosis is still a serious public health problem, with 10.8 million new cases and 1.8 million deaths worldwide in 2015. The diversity among members of the Mycobacterium tuberculosis complex, the causal agent of tuberculosis, is conducive to the design of different methods for rapid diagnosis. Mutations in the genes involved in resistance mechanisms enable the bacteria to elude the treatment. We have reviewed the methods for the rapid diagnosis of M. tuberculosis complex and the detection of susceptibility to drugs, both of which are necessary to prevent the onset of new resistance and to establish early, appropriate treatment. | 2017 | 28318570 |
| 5112 | 14 | 0.9995 | Genome-Based Prediction of Bacterial Antibiotic Resistance. Clinical microbiology has long relied on growing bacteria in culture to determine antimicrobial susceptibility profiles, but the use of whole-genome sequencing for antibiotic susceptibility testing (WGS-AST) is now a powerful alternative. This review discusses the technologies that made this possible and presents results from recent studies to predict resistance based on genome sequences. We examine differences between calling antibiotic resistance profiles by the simple presence or absence of previously known genes and single-nucleotide polymorphisms (SNPs) against approaches that deploy machine learning and statistical models. Often, the limitations to genome-based prediction arise from limitations of accuracy of culture-based AST in addition to an incomplete knowledge of the genetic basis of resistance. However, we need to maintain phenotypic testing even as genome-based prediction becomes more widespread to ensure that the results do not diverge over time. We argue that standardization of WGS-AST by challenge with consistently phenotyped strain sets of defined genetic diversity is necessary to compare the efficacy of methods of prediction of antibiotic resistance based on genome sequences. | 2019 | 30381421 |
| 4249 | 15 | 0.9995 | Detection of essential genes in Streptococcus pneumoniae using bioinformatics and allelic replacement mutagenesis. Although the emergence and spread of antimicrobial resistance in major bacterial pathogens for the past decades poses a growing challenge to public health, discovery of novel antimicrobial agents from natural products or modification of existing antibiotics cannot circumvent the problem of antimicrobial resistance. The recent development of bacterial genomics and the availability of genome sequences allow the identification of potentially novel antimicrobial agents. The cellular targets of new antimicrobial agents must be essential for the growth, replication, or survival of the bacterium. Conserved genes among different bacterial genomes often turn out to be essential (1, 2). Thus, the combination of comparative genomics and the gene knock-out procedure can provide effective ways to identify the essential genes of bacterial pathogens (3). Identification of essential genes in bacteria may be utilized for the development of new antimicrobial agents because common essential genes in diverse pathogens could constitute novel targets for broad-spectrum antimicrobial agents. | 2008 | 18392984 |
| 5113 | 16 | 0.9995 | Identification of bacterial antibiotic resistance genes in next-generation sequencing data (review of literature). The spread of antibiotic-resistant human bacterial pathogens is a serious threat to modern medicine. Antibiotic susceptibility testing is essential for treatment regimens optimization and preventing dissemination of antibiotic resistance. Therefore, development of antibiotic susceptibility testing methods is a priority challenge of laboratory medicine. The aim of this review is to analyze the capabilities of the bioinformatics tools for bacterial whole genome sequence data processing. The PubMed database, Russian scientific electronic library eLIBRARY, information networks of World health organization and European Society of Clinical Microbiology and Infectious Diseases (ESCMID) were used during the analysis. In this review, the platforms for whole genome sequencing, which are suitable for detection of bacterial genetic resistance determinants, are described. The classic step of genetic resistance determinants searching is an alignment between the query nucleotide/protein sequence and the subject (database) nucleotide/protein sequence, which is performed using the nucleotide and protein sequence databases. The most commonly used databases are Resfinder, CARD, Bacterial Antimicrobial Resistance Reference Gene Database. The results of the resistance determinants searching in genome assemblies is more correct in comparison to results of the searching in contigs. The new resistance genes searching bioinformatics tools, such as neural networks and machine learning, are discussed in the review. After critical appraisal of the current antibiotic resistance databases we designed a protocol for predicting antibiotic resistance using whole genome sequence data. The designed protocol can be used as a basis of the algorithm for qualitative and quantitative antimicrobial susceptibility testing based on whole genome sequence data. | 2021 | 34882354 |
| 4253 | 17 | 0.9995 | Molecular mechanisms of polymyxin resistance and detection of mcr genes. Antibiotic resistance is an ever-increasing global problem. Major commercial antibiotics often fail to fight common bacteria, and some pathogens have become multi-resistant. Polymyxins are potent bactericidal antibiotics against gram-negative bacteria. Known resistance to polymyxin includes intrinsic, mutational and adaptive mechanisms, with the recently described horizontally acquired resistance mechanisms. In this review, we present several strategies for bacteria to develop enhanced resistance to polymyxins, focusing on changes in the outer membrane, efflux and other resistance determinants. Better understanding of the genes involved in polymyxin resistance may pave the way for the development of new and effective antimicrobial agents. We also report novel in silico tested primers for PCR assay that may be able distinguish colistin-resistant isolates carrying the plasmid-encoded mcr genes and will assist in combating the spread of colistin resistance in bacteria. | 2019 | 30439931 |
| 4142 | 18 | 0.9995 | Antimicrobial Resistance in Pasteurellaceae of Veterinary Origin. Members of the highly heterogeneous family Pasteurellaceae cause a wide variety of diseases in humans and animals. Antimicrobial agents are the most powerful tools to control such infections. However, the acquisition of resistance genes, as well as the development of resistance-mediating mutations, significantly reduces the efficacy of the antimicrobial agents. This article gives a brief description of the role of selected members of the family Pasteurellaceae in animal infections and of the most recent data on the susceptibility status of such members. Moreover, a review of the current knowledge of the genetic basis of resistance to antimicrobial agents is included, with particular reference to resistance to tetracyclines, β-lactam antibiotics, aminoglycosides/aminocyclitols, folate pathway inhibitors, macrolides, lincosamides, phenicols, and quinolones. This article focusses on the genera of veterinary importance for which sufficient data on antimicrobial susceptibility and the detection of resistance genes are currently available (Pasteurella, Mannheimia, Actinobacillus, Haemophilus, and Histophilus). Additionally, the role of plasmids, transposons, and integrative and conjugative elements in the spread of the resistance genes within and beyond the aforementioned genera is highlighted to provide insight into horizontal dissemination, coselection, and persistence of antimicrobial resistance genes. The article discusses the acquisition of diverse resistance genes by the selected Pasteurellaceae members from other Gram-negative or maybe even Gram-positive bacteria. Although the susceptibility status of these members still looks rather favorable, monitoring of their antimicrobial susceptibility is required for early detection of changes in the susceptibility status and the newly acquired/developed resistance mechanisms. | 2018 | 29916344 |
| 4340 | 19 | 0.9995 | Predicting antimicrobial susceptibility from the bacterial genome: A new paradigm for one health resistance monitoring. The laboratory identification of antibacterial resistance is a cornerstone of infectious disease medicine. In vitro antimicrobial susceptibility testing has long been based on the growth response of organisms in pure culture to a defined concentration of antimicrobial agents. By comparing individual isolates to wild-type susceptibility patterns, strains with acquired resistance can be identified. Acquired resistance can also be detected genetically. After many decades of research, the inventory of genes underlying antimicrobial resistance is well known for several pathogenic genera including zoonotic enteric organisms such as Salmonella and Campylobacter and continues to grow substantially for others. With the decline in costs for large scale DNA sequencing, it is now practicable to characterize bacteria using whole genome sequencing, including the carriage of resistance genes in individual microorganisms and those present in complex biological samples. With genomics, we can generate comprehensive, detailed information on the bacterium, the mechanisms of antibiotic resistance, clues to its source, and the nature of mobile DNA elements by which resistance spreads. These developments point to a new paradigm for antimicrobial resistance detection and tracking for both clinical and public health purposes. | 2021 | 33010049 |