# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 4628 | 0 | 1.0000 | Genomic Analysis of Molecular Bacterial Mechanisms of Resistance to Phage Infection. To optimize phage therapy, we need to understand how bacteria evolve against phage attacks. One of the main problems of phage therapy is the appearance of bacterial resistance variants. The use of genomics to track antimicrobial resistance is increasingly developed and used in clinical laboratories. For that reason, it is important to consider, in an emerging future with phage therapy, to detect and avoid phage-resistant strains that can be overcome by the analysis of metadata provided by whole-genome sequencing. Here, we identified genes associated with phage resistance in 18 Acinetobacter baumannii clinical strains belonging to the ST-2 clonal complex during a decade (Ab2000 vs. 2010): 9 from 2000 to 9 from 2010. The presence of genes putatively associated with phage resistance was detected. Genes detected were associated with an abortive infection system, restriction-modification system, genes predicted to be associated with defense systems but with unknown function, and CRISPR-Cas system. Between 118 and 171 genes were found in the 18 clinical strains. On average, 26% of these genes were detected inside genomic islands in the 2000 strains and 32% in the 2010 strains. Furthermore, 38 potential CRISPR arrays in 17 of 18 of the strains were found, as well as 705 proteins associated with CRISPR-Cas systems. A moderately higher presence of these genes in the strains of 2010 in comparison with those of 2000 was found, especially those related to the restriction-modification system and CRISPR-Cas system. The presence of these genes in genomic islands at a higher rate in the strains of 2010 compared with those of 2000 was also detected. Whole-genome sequencing and bioinformatics could be powerful tools to avoid drawbacks when a personalized therapy is applied. In this study, it allows us to take care of the phage resistance in A. baumannii clinical strains to prevent a failure in possible phage therapy. | 2021 | 35250902 |
| 4631 | 1 | 0.9999 | Genome Analysis of an Enterococcal Prophage, Entfac.MY. BACKGROUND: Bacteriophages are bacterial parasites. Unlike lytic bacteriophages, lysogenic bacteriophages do not multiply immediately after entering the host cells and may integrate their genomes into the bacterial genomes as prophages. Prophages can include various phenotypic and genotypic effects on the host bacteria. Enterococcus spp. are Gram-positive bacteria that cause infections in humans and animals. In recent decades, these bacteria have become resistant to various antimicrobials, including vancomycin. The aim of this study was to analyze genome of an enterococcal prophage. METHODS: In this study, Enterococcus faecium EntfacYE was isolated from biological samples and its genome was analyzed using next-generation sequencing method. RESULTS: Overall, 254 prophage genes were identified in the bacterial genome. The prophage included 39 housekeeping, 41 replication and regulation, 80 structural and packaging, and 48 lysis genes. Moreover, 46 genes with unknown functions were identified. All genes were annotated in DNA Data Bank of Japan. CONCLUSION: In general, most prophage genes were linked to packaging and structure (31.5%) gene group. However, genes with unknown functions included a high proportion (18.11%), which indicated necessity of further analyses. Genomic analysis of the prophages can be effective in better understanding of their roles in development of bacterial resistance to antibiotics. Moreover, identification and study of prophages can help researchers develop genetic engineering tools and novel infection therapies. | 2022 | 36061127 |
| 4629 | 2 | 0.9999 | Screening and in silico characterization of prophages in Helicobacter pylori clinical strains. The increase of antibiotic resistance calls for alternatives to control Helicobacter pylori, a Gram-negative bacterium associated with various gastric diseases. Bacteriophages (phages) can be highly effective in the treatment of pathogenic bacteria. Here, we developed a method to identify prophages in H. pylori genomes aiming at their future use in therapy. A polymerase chain reaction (PCR)-based technique tested five primer pairs on 74 clinical H. pylori strains. After the PCR screening, 14 strains most likely to carry prophages were fully sequenced. After that, a more holistic approach was taken by studying the complete genome of the strains. This study allowed us to identify 12 intact prophage sequences, which were then characterized concerning their morphology, virulence, and antibiotic-resistance genes. To understand the variability of prophages, a phylogenetic analysis using the sequences of all H. pylori phages reported to date was performed. Overall, we increased the efficiency of identifying complete prophages to 54.1 %. Genes with homology to potential virulence factors were identified in some new prophages. Phylogenetic analysis revealed a close relationship among H. pylori-phages, although there are phages with different geographical origins. This study provides a deeper understanding of H. pylori-phages, providing valuable insights into their potential use in therapy. | 2025 | 39368610 |
| 6266 | 3 | 0.9999 | Bacterial gene loss as a mechanism for gain of antimicrobial resistance. Acquisition of exogenous DNA by pathogenic bacteria represents the basis for much of the acquired antimicrobial resistance in pathogenic bacteria. A more extreme mechanism to avoid the effect of an antibiotic is to delete the drug target, although this would be predicted to be rare since drug targets are often essential genes. Here, we review and discuss the description of a novel mechanism of resistance to the cephalosporin drug ceftazidime caused by loss of a penicillin-binding protein (PBP) in a Gram-negative bacillus (Burkholderia pseudomallei). This organism causes melioidosis across south-east Asia and northern Australia, and is usually treated with two or more weeks of ceftazidime followed by oral antibiotics for three to six months. Comparison of clinical isolates from six patients with melioidosis found initial ceftazidime-susceptible isolates and subsequent ceftazidime-resistant variants. The latter failed to grow on commonly used culture media, rendering these isolates difficult to detect in the diagnostic laboratory. Genomic analysis using pulsed-field gel electrophoresis and array based genomic hybridisation revealed a large-scale genomic deletion comprising 49 genes in the ceftazidime-resistant strains. Mutational analysis of wild-type B. pseudomallei demonstrated that ceftazidime resistance was due to deletion of a gene encoding a PBP 3 present within the region of genomic loss. This provides one explanation for ceftazidime treatment failure, and may be a frequent but undetected event in patients with melioidosis. | 2012 | 23022568 |
| 4929 | 4 | 0.9998 | Comparative genomics analysis of Acinetobacter baumannii multi-drug resistant and drug sensitive strains in China. The incidence of multidrug-resistant Acinetobacter baumannii has posed a major challenge for clinical treatment. There is still a significant gap in understanding the mechanism causing multi-drug resistance (MDR). In this study, the genomes of 10 drug sensitive and 10 multi-drug resistant A.baumannii strains isolated from a hospital in China were sequenced and compared. The antibiotic resistance genes, virulence factors were determined and CRIPSR-Cas system along with prophages were detected. The results showed that MDR strains are significantly different from the drug sensitive strains in the CARD entries, patterns of sequences matching up to plasmids, VFDB entries and CRISPR-Cas system. MDR strains contain unique CARD items related to antibiotic resistance which are absent in sensitive strains. Furthermore, sequences from genomes of MDR strains can match up with plasmids from more diversified bacteria genera compared to drug sensitive strains. MDR strains also contain a lower level of CRISPR genes and larger amount of prophages, along with higher levels of spacer sequences. These findings provide new experimental evidences for the study of the antibiotic resistance mechanism of A. baumannii. | 2022 | 35307599 |
| 4380 | 5 | 0.9998 | Comparative genome analysis of ciprofloxacin-resistant Pseudomonas aeruginosa reveals genes within newly identified high variability regions associated with drug resistance development. The alarming rise of ciprofloxacin-resistant Pseudomonas aeruginosa has been reported in several clinical studies. Though the mutation of resistance genes and their role in drug resistance has been researched, the process by which the bacterium acquires high-level resistance is still not well understood. How does the genomic evolution of P. aeruginosa affect resistance development? Could the exposure of antibiotics to the bacteria enrich genomic variants that lead to the development of resistance, and if so, how are these variants distributed through the genome? To answer these questions, we performed 454 pyrosequencing and a whole genome analysis both before and after exposure to ciprofloxacin. The comparative sequence data revealed 93 unique resistance strain variation sites, which included a mutation in the DNA gyrase subunit A gene. We generated variation-distribution maps comparing the wild and resistant types, and isolated 19 candidates from three discrete resistance-associated high variability regions that had available transposon mutants, to perform a ciprofloxacin exposure assay. Of these region candidates with transposon disruptions, 79% (15/19) showed a reduction in the ability to gain high-level resistance, suggesting that genes within these high variability regions might enrich for certain functions associated with resistance development. | 2013 | 23808957 |
| 4630 | 6 | 0.9998 | Genome Analysis of the Enterococcus faecium Entfac.YE Prophage. BACKGROUND: Bacteriophages are viruses that infect bacteria. Bacteriophages are widely distributed in various environments. The prevalence of bacteriophages in water sources, especially wastewaters, is naturally high. These viruses affect evolution of most bacterial species. Bacteriophages are able to integrate their genomes into the chromosomes of their hosts as prophages and hence transfer resistance genes to the bacterial genomes. Enterococci are commensal bacteria that show high resistance to common antibiotics. For example, prevalence of vancomycin-resistant enterococci has increased within the last decades. METHODS: Enterococcal isolates were isolated from clinical samples and morphological, phenotypical, biochemical, and molecular methods were used to identify and confirm their identity. Bacteriophages extracted from water sources were then applied to isolated Enterococcus faecium (E. faecium). In the next step, the bacterial genome was completely sequenced and the existing prophage genome in the bacterial genome was analyzed. RESULTS: In this study, E. faecium EntfacYE was isolated from a clinical sample. The EntfacYE genome was analyzed and 88 prophage genes were identified. The prophage content included four housekeeping genes, 29 genes in the group of genes related to replication and regulation, 25 genes in the group of genes related to structure and packaging, and four genes belonging to the group of genes associated with lysis. Moreover, 26 genes were identified with unknown functions. CONCLUSION: In conclusion, genome analysis of prophages can lead to a better understanding of their roles in the rapid evolution of bacteria. | 2022 | 35509366 |
| 9922 | 7 | 0.9998 | De novo acquisition of antibiotic resistance in six species of bacteria. Bacteria can become resistant to antibiotics in two ways: by acquiring resistance genes through horizontal gene transfer and by de novo development of resistance upon exposure to non-lethal concentrations. The importance of the second process, de novo build-up, has not been investigated systematically over a range of species and may be underestimated as a result. To investigate the DNA mutation patterns accompanying the de novo antibiotic resistance acquisition process, six bacterial species encountered in the food chain were exposed to step-wise increasing sublethal concentrations of six antibiotics to develop high levels of resistance. Phenotypic and mutational landscapes were constructed based on whole-genome sequencing at two time points of the evolutionary trajectory. In this study, we found that (1) all of the six strains can develop high levels of resistance against most antibiotics; (2) increased resistance is accompanied by different mutations for each bacterium-antibiotic combination; (3) the number of mutations varies widely, with Y. enterocolitica having by far the most; (4) in the case of fluoroquinolone resistance, a mutational pattern of gyrA combined with parC is conserved in five of six species; and (5) mutations in genes coding for efflux pumps are widely encountered in gram-negative species. The overall conclusion is that very similar phenotypic outcomes are instigated by very different genetic changes. The outcome of this study may assist policymakers when formulating practical strategies to prevent development of antimicrobial resistance in human and veterinary health care.IMPORTANCEMost studies on de novo development of antimicrobial resistance have been performed on Escherichia coli. To examine whether the conclusions of this research can be applied to more bacterial species, six species of veterinary importance were made resistant to six antibiotics, each of a different class. The rapid build-up of resistance observed in all six species upon exposure to non-lethal concentrations of antimicrobials indicates a similar ability to adjust to the presence of antibiotics. The large differences in the number of DNA mutations accompanying de novo resistance suggest that the mechanisms and pathways involved may differ. Hence, very similar phenotypes can be the result of various genotypes. The implications of the outcome are to be considered by policymakers in the area of veterinary and human healthcare. | 2025 | 39907470 |
| 4455 | 8 | 0.9998 | 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 |
| 4942 | 9 | 0.9998 | Nanopore-based enrichment of antimicrobial resistance genes - a case-based study. Rapid screening of hospital admissions to detect asymptomatic carriers of resistant bacteria can prevent pathogen outbreaks. However, the resulting isolates rarely have their genome sequenced due to cost constraints and long turn-around times to get and process the data, limiting their usefulness to the practitioner. Here we used real-time, on-device target enrichment ("adaptive") sequencing as a highly multiplexed assay covering 1,147 antimicrobial resistance genes. We compared its utility against standard and metagenomic sequencing, focusing on an isolate of Raoultella ornithinolytica harbouring three carbapenemases (NDM, KPC, VIM). Based on this experimental data, we then modelled the influence of several variables on the enrichment results and predicted the large effect of nucleotide identity (higher is better) and read length (shorter is better). Lastly, we showed how all relevant resistance genes are detected using adaptive sequencing on a miniature ("Flongle") flow cell, motivating its use in a clinical setting to monitor similar cases and their surroundings. | 2023 | 36949817 |
| 4627 | 10 | 0.9998 | Antibiotic resistance mechanisms of Myroides sp. Bacteria of the genus Myroides (Myroides spp.) are rare opportunistic pathogens. Myroides sp. infections have been reported mainly in China. Myroides sp. is highly resistant to most available antibiotics, but the resistance mechanisms are not fully elucidated. Current strain identification methods based on biochemical traits are unable to identify strains accurately at the species level. While 16S ribosomal RNA (rRNA) gene sequencing can accurately achieve this, it fails to give information on the status and mechanisms of antibiotic resistance, because the 16S rRNA sequence contains no information on resistance genes, resistance islands or enzymes. We hypothesized that obtaining the whole genome sequence of Myroides sp., using next generation sequencing methods, would help to clarify the mechanisms of pathogenesis and antibiotic resistance, and guide antibiotic selection to treat Myroides sp. infections. As Myroides sp. can survive in hospitals and the environment, there is a risk of nosocomial infections and pandemics. For better management of Myroides sp. infections, it is imperative to apply next generation sequencing technologies to clarify the antibiotic resistance mechanisms in these bacteria. | 2016 | 26984839 |
| 4930 | 11 | 0.9998 | Whole-genome sequencing based characterization of antimicrobial resistance in Enterococcus. Whole-genome sequencing (WGS) has transformed our understanding of antimicrobial resistance, yielding new insights into the genetics underlying resistance. To date, most studies using WGS to study antimicrobial resistance have focused on gram-negative bacteria in the family Enterobacteriaceae, such as Salmonella spp. and Escherichia coli, which have well-defined resistance mechanisms. In contrast, relatively few studies have been performed on gram-positive organisms. We sequenced 197 strains of Enterococcus from various animal and food sources, including 100 Enterococcus faecium and 97 E. faecalis. From analyzing acquired resistance genes and known resistance-associated mutations, we found that resistance genotypes correlated with resistance phenotypes in 96.5% of cases for the 11 drugs investigated. Some resistances, such as those to tigecycline and daptomycin, could not be investigated due to a lack of knowledge of mechanisms underlying these phenotypes. This study showed the utility of WGS for predicting antimicrobial resistance based on genotype alone. | 2018 | 29617860 |
| 4759 | 12 | 0.9998 | Recent advances in rapid antimicrobial susceptibility testing systems. INTRODUCTION: Until recently antimicrobial susceptibility testing (AST) methods based on the demonstration of phenotypic susceptibility in 16-24 h remained largely unchanged. AREAS COVERED: Advances in rapid phenotypic and molecular-based AST systems. EXPERT OPINION: AST has changed over the past decade, with many rapid phenotypic and molecular methods developed to demonstrate phenotypic or genotypic resistance, or biochemical markers of resistance such as β-lactamases associated with carbapenem resistance. Most methods still require isolation of bacteria from specimens before both legacy and newer methods can be used. Bacterial identification by MALDI-TOF mass spectroscopy is now widely used and is often key to the interpretation of rapid AST results. Several PCR arrays are available to detect the most frequent pathogens associated with bloodstream infections and their major antimicrobial resistance genes. Many advances in whole-genome sequencing of bacteria and fungi isolated by culture as well as directly from clinical specimens have been made but are not yet widely available. High cost and limited throughput are the major obstacles to uptake of rapid methods, but targeted use, continued development and decreasing costs are expected to result in more extensive use of these increasingly useful methods. | 2021 | 33926351 |
| 4839 | 13 | 0.9998 | 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 |
| 5111 | 14 | 0.9998 | 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 |
| 4626 | 15 | 0.9998 | Prophages Present in Acinetobacter pittii Influence Bacterial Virulence, Antibiotic Resistance, and Genomic Rearrangements. Introduction: Antibiotic resistance and virulence are common among bacterial populations, posing a global clinical challenge. The bacterial species Acinetobacter pittii, an infectious agent in clinical environments, has shown increasing rates of antibiotic resistance. Viruses that integrate as prophages into A. pittii could be a potential cause of this pathogenicity, as they often contain antibiotic resistance or virulence factor gene sequences. Methods: In this study, we analyzed 25 A. pittii strains for potential prophages. Using virulence factor databases, we identified many common and virulent prophages in A. pittii. Results: The analysis also included a specific catalogue of the virulence factors and antibiotic resistance genes contributed by A. pittii prophages. Finally, our results illustrate multiple similarities between A. pittii and its bacterial relatives with regard to prophage integration sites and prevalence. Discussion: These findings provide a broader insight into prophage behavior that can be applied to future studies on similar species in the Acinetobacter calcoaceticus-baumannii complex. | 2022 | 36161193 |
| 3808 | 16 | 0.9998 | Expression Profiling of Antibiotic-Resistant Bacteria Obtained by Laboratory Evolution. To elucidate the mechanisms of antibiotic resistance, integrating phenotypic and genotypic features in resistant strains is important. Here, we describe the expression profiling of antibiotic-resistant Escherichia coli strains obtained by laboratory evolution, and a method for extracting a small number of genes whose expression changes can contribute to the acquisition of resistance. | 2017 | 27873258 |
| 5977 | 17 | 0.9998 | Methods to determine antibiotic resistance gene silencing. The occurrence of antibiotic-resistant bacteria is an increasingly serious problem world-wide. In addition, to phenotypically resistant bacteria, a threat may also be posed by isolates with silent, but intact, antibiotic resistance genes. Such isolates, which have recently been described, possess wild-type genes that are not expressed, but may convert to resistance by activating expression of the silent genes. They may therefore compromise the efficacy of antimicrobial treatment, particularly if their presence has not been diagnosed. This chapter describes the detection of silent resistance genes by PCR and DNA sequencing. A method to detect five potentially silent acquired resistance genes; aadA, bla (OXA-2), strAB, sul1, and tet(A) is described. First, the susceptibility of the isolates to the relevant antibiotics is determined by an appropriate susceptibility testing method, such as E-test. Then the presence of the genes is investigated by PCR followed by agarose gel electrophoresis of the amplification products. If a resistance gene is detected in a susceptible isolate, the entire open-reading frame and promoter sequence of the gene is amplified by PCR and their DNA sequences obtained. The DNA sequences are then compared to those of known resistant isolates, to detect mutations that may account for susceptibility. If no mutations are detected the expression of the gene is investigated by RT-PCR following RNA extraction. The methods described here can be applied to all acquired resistance genes for which sequence and normal expression data are available. | 2010 | 20401584 |
| 4624 | 18 | 0.9998 | Deciphering the distance to antibiotic resistance for the pneumococcus using genome sequencing data. Advances in genome sequencing technologies and genome-wide association studies (GWAS) have provided unprecedented insights into the molecular basis of microbial phenotypes and enabled the identification of the underlying genetic variants in real populations. However, utilization of genome sequencing in clinical phenotyping of bacteria is challenging due to the lack of reliable and accurate approaches. Here, we report a method for predicting microbial resistance patterns using genome sequencing data. We analyzed whole genome sequences of 1,680 Streptococcus pneumoniae isolates from four independent populations using GWAS and identified probable hotspots of genetic variation which correlate with phenotypes of resistance to essential classes of antibiotics. With the premise that accumulation of putative resistance-conferring SNPs, potentially in combination with specific resistance genes, precedes full resistance, we retrogressively surveyed the hotspot loci and quantified the number of SNPs and/or genes, which if accumulated would confer full resistance to an otherwise susceptible strain. We name this approach the 'distance to resistance'. It can be used to identify the creep towards complete antibiotics resistance in bacteria using genome sequencing. This approach serves as a basis for the development of future sequencing-based methods for predicting resistance profiles of bacterial strains in hospital microbiology and public health settings. | 2017 | 28205635 |
| 5076 | 19 | 0.9998 | Diagnostic microarray for human and animal bacterial diseases and their virulence and antimicrobial resistance genes. Rapid diagnosis and treatment of disease is often based on the identification and characterization of causative agents derived from phenotypic characteristics. Current methods can be laborious and time-consuming, often requiring many skilled personnel and a large amount of lab space. The objective of our study was to develop a spotted microarray for rapid identification and characterization of bacterial pathogens and their antimicrobial resistance genes. Our spotted microarray consists of 489 70mer probes that detect 40 bacterial pathogens of medical, veterinary and zoonotic importance (including 15 NIAID Category A, B and C pathogens); associated genes that encode resistance for antimicrobial and metal resistance; and DNA elements that are important for horizontal gene transfer among bacteria. High specificity and reliability of the microarray was achieved for bacterial pathogens of animal and human importance by validating MDR pathogenic bacteria as pure cultures or by following their inoculation in complex and highly organic sample matrices, such as soil and manure. | 2010 | 20035807 |