# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 4389 | 0 | 1.0000 | Elucidating the mechanism of antimicrobial resistance in Mycobacterium tuberculosis using gene interaction networks. Antimicrobial resistance (AMR) in microorganisms is an urgent global health threat. AMR of Mycobacterium tuberculosis is associated with significant morbidity and mortality. It is of great importance to underpin the resistance pathways involved in the mechanisms of AMR and identify the genes that are directly involved in AMR. The focus of the current study was the bacteria M. tuberculosis, which carries AMR genes that give resistance that lead to multidrug resistance. We, therefore, built a network of 43 genes and examined for potential gene-gene interactions. Then we performed a clustering analysis and identified three closely related clusters that could be involved in multidrug resistance mechanisms. Through the bioinformatics pipeline, we consistently identified six-hub genes (dnaN, polA, ftsZ, alr, ftsQ, and murC) that demonstrated the highest number of interactions within the clustering analysis. This study sheds light on the multidrug resistance of MTB and provides a protocol for discovering genes that might be involved in multidrug resistance, which will improve the treatment of resistant strains of TB. | 2023 | 36858742 |
| 4390 | 1 | 0.9998 | Integrated Co-functional Network Analysis on the Resistance and Virulence Features in Acinetobacter baumannii. Acinetobacter baumannii is one of the most troublesome bacterial pathogens that pose major public health threats due to its rapidly increasing drug resistance property. It is not only derived from clinic setting but also emerges from aquaculture as a fish pathogen, which could pass the resistant genes in the food chain. Understanding the mechanism of antibiotic resistance development and pathogenesis will aid our battle with the infections caused by A. baumannii. In this study, we constructed a co-functional network by integrating multiple sources of data from A. baumannii and then used the k-shell decomposition to analyze the co-functional network. We found that genes involving in basic cellular physiological function, including genes for antibiotic resistance, tended to have high k-shell values and locate in the internal layer of our network. In contrast, the non-essential genes, such as genes associated with virulence, tended to have lower k-shell values and locate in the external layer. This finding allows us to fish out the potential antibiotic resistance factors and virulence factors. In addition, we constructed an online platform ABviresDB (https://acba.shinyapps.io/ABviresDB/) for visualization of the network and features of each gene in A. baumannii. The network analysis in this study will not only aid the study on A. baumannii but also could be referenced for the research of antibiotic resistance and pathogenesis in other bacteria. | 2020 | 33224132 |
| 9406 | 2 | 0.9998 | Proteomics as the final step in the functional metagenomics study of antimicrobial resistance. The majority of clinically applied antimicrobial agents are derived from natural products generated by soil microorganisms and therefore resistance is likely to be ubiquitous in such environments. This is supported by the fact that numerous clinically important resistance mechanisms are encoded within the genomes of such bacteria. Advances in genomic sequencing have enabled the in silico identification of putative resistance genes present in these microorganisms. However, it is not sufficient to rely on the identification of putative resistance genes, we must also determine if the resultant proteins confer a resistant phenotype. This will require an analysis pipeline that extends from the extraction of environmental DNA, to the identification and analysis of potential resistance genes and their resultant proteins and phenotypes. This review focuses on the application of functional metagenomics and proteomics to study antimicrobial resistance in diverse environments. | 2015 | 25784907 |
| 4364 | 3 | 0.9998 | Antibiotic resistance is prevalent in an isolated cave microbiome. Antibiotic resistance is a global challenge that impacts all pharmaceutically used antibiotics. The origin of the genes associated with this resistance is of significant importance to our understanding of the evolution and dissemination of antibiotic resistance in pathogens. A growing body of evidence implicates environmental organisms as reservoirs of these resistance genes; however, the role of anthropogenic use of antibiotics in the emergence of these genes is controversial. We report a screen of a sample of the culturable microbiome of Lechuguilla Cave, New Mexico, in a region of the cave that has been isolated for over 4 million years. We report that, like surface microbes, these bacteria were highly resistant to antibiotics; some strains were resistant to 14 different commercially available antibiotics. Resistance was detected to a wide range of structurally different antibiotics including daptomycin, an antibiotic of last resort in the treatment of drug resistant Gram-positive pathogens. Enzyme-mediated mechanisms of resistance were also discovered for natural and semi-synthetic macrolide antibiotics via glycosylation and through a kinase-mediated phosphorylation mechanism. Sequencing of the genome of one of the resistant bacteria identified a macrolide kinase encoding gene and characterization of its product revealed it to be related to a known family of kinases circulating in modern drug resistant pathogens. The implications of this study are significant to our understanding of the prevalence of resistance, even in microbiomes isolated from human use of antibiotics. This supports a growing understanding that antibiotic resistance is natural, ancient, and hard wired in the microbial pangenome. | 2012 | 22509370 |
| 4052 | 4 | 0.9998 | Functional metagenomics for the investigation of antibiotic resistance. Antibiotic resistance is a major threat to human health and well-being. To effectively combat this problem we need to understand the range of different resistance genes that allow bacteria to resist antibiotics. To do this the whole microbiota needs to be investigated. As most bacteria cannot be cultivated in the laboratory, the reservoir of antibiotic resistance genes in the non-cultivatable majority remains relatively unexplored. Currently the only way to study antibiotic resistance in these organisms is to use metagenomic approaches. Furthermore, the only method that does not require any prior knowledge about the resistance genes is functional metagenomics, which involves expressing genes from metagenomic clones in surrogate hosts. In this review the methods and limitations of functional metagenomics to isolate new antibiotic resistance genes and the mobile genetic elements that mediate their spread are explored. | 2014 | 24556726 |
| 4265 | 5 | 0.9998 | Bacteriophages as vehicles of the resistome in cystic fibrosis. Environmental microbial communities and human microbiota represent a huge reservoir of mobilizable genes, the 'mobilome', including a pool of genes encoding antimicrobial resistance, the 'resistome'. Whole-genome sequencing of bacterial genomes from cystic fibrosis (CF) patients has demonstrated that bacteriophages contribute significantly to bacterial genome alterations, and metagenomic analysis of respiratory tract DNA viral communities has revealed the presence of genes encoding antimicrobial resistance in bacteriophages of CF patients. CF airways should now be considered as the site of complex microbiota, where bacteriophages are vehicles for the adaptation of bacteria to this specific environment and for the emergence and selection of multidrug-resistant bacteria with chimeric repertoires. As phages are already known to be mobilized during chronic infection of the lungs of patients with CF, it seems particularly important to improve the understanding of the mechanisms of phage induction to prevent the spread of virulence and/or antimicrobial resistance determinants within the CF population as well as in the community. Such a modern point of view may be a seminal reflection for clinical practice in the future since current antimicrobial therapy guidelines in the context of CF may lead to the emergence of genes encoding antimicrobial resistance. | 2011 | 21816766 |
| 4050 | 6 | 0.9998 | Are Virulence and Antibiotic Resistance Genes Linked? A Comprehensive Analysis of Bacterial Chromosomes and Plasmids. Although pathogenic bacteria are the targets of antibiotics, these drugs also affect hundreds of commensal or mutualistic species. Moreover, the use of antibiotics is not only restricted to the treatment of infections but is also largely applied in agriculture and in prophylaxis. During this work, we tested the hypothesis that there is a correlation between the number and the genomic location of antibiotic resistance (AR) genes and virulence factor (VF) genes. We performed a comprehensive study of 16,632 reference bacterial genomes in which we identified and counted all orthologues of AR and VF genes in each of the locations: chromosomes, plasmids, or in both locations of the same genome. We found that, on a global scale, no correlation emerges. However, some categories of AR and VF genes co-occur preferentially, and in the mobilome, which supports the hypothesis that some bacterial pathogens are under selective pressure to be resistant to specific antibiotics, a fact that can jeopardize antimicrobial therapy for some human-threatening diseases. | 2022 | 35740113 |
| 4624 | 7 | 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 |
| 9922 | 8 | 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 |
| 4340 | 9 | 0.9998 | 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 |
| 4625 | 10 | 0.9998 | Resistome analysis of bloodstream infection bacterial genomes reveals a specific set of proteins involved in antibiotic resistance and drug efflux. Bacterial resistance to antibiotics is a global public health problem. Its association with bloodstream infections is even more severe and may easily evolve to sepsis. To improve our response to these bacteria, it is essential to gather thorough knowledge on the main pathogens along with the main mechanisms of resistance they carry. In this paper, we performed a large meta-analysis of 3872 bacterial genomes isolated from blood samples, from which we identified 71 745 antibiotic resistance genes (ARGs). Taxonomic analysis showed that Proteobacteria and Firmicutes phyla, and the species Klebsiella pneumoniae and Staphylococcus aureus were the most represented. Comparison of ARGs with the Resfams database showed that the main mechanism of antibiotic resistance is mediated by efflux pumps. Clustering analysis between resistome of blood and soil-isolated bacteria showed that there is low identity between transport and efflux proteins between bacteria from these environments. Furthermore, a correlation analysis among all features showed that K. pneumoniae and S. aureus formed two well-defined clusters related to the resistance mechanisms, proteins and antibiotics. A retrospective analysis has shown that the average number of ARGs per genome has gradually increased. The results demonstrate the importance of comprehensive studies to understand the antibiotic resistance phenomenon. | 2020 | 33575606 |
| 3829 | 11 | 0.9998 | Associations among Antibiotic and Phage Resistance Phenotypes in Natural and Clinical Escherichia coli Isolates. The spread of antibiotic resistance is driving interest in new approaches to control bacterial pathogens. This includes applying multiple antibiotics strategically, using bacteriophages against antibiotic-resistant bacteria, and combining both types of antibacterial agents. All these approaches rely on or are impacted by associations among resistance phenotypes (where bacteria resistant to one antibacterial agent are also relatively susceptible or resistant to others). Experiments with laboratory strains have shown strong associations between some resistance phenotypes, but we lack a quantitative understanding of associations among antibiotic and phage resistance phenotypes in natural and clinical populations. To address this, we measured resistance to various antibiotics and bacteriophages for 94 natural and clinical Escherichia coli isolates. We found several positive associations between resistance phenotypes across isolates. Associations were on average stronger for antibacterial agents of the same type (antibiotic-antibiotic or phage-phage) than different types (antibiotic-phage). Plasmid profiles and genetic knockouts suggested that such associations can result from both colocalization of resistance genes and pleiotropic effects of individual resistance mechanisms, including one case of antibiotic-phage cross-resistance. Antibiotic resistance was predicted by core genome phylogeny and plasmid profile, but phage resistance was predicted only by core genome phylogeny. Finally, we used observed associations to predict genes involved in a previously uncharacterized phage resistance mechanism, which we verified using experimental evolution. Our data suggest that susceptibility to phages and antibiotics are evolving largely independently, and unlike in experiments with lab strains, negative associations between antibiotic resistance phenotypes in nature are rare. This is relevant for treatment scenarios where bacteria encounter multiple antibacterial agents.IMPORTANCE Rising antibiotic resistance is making it harder to treat bacterial infections. Whether resistance to a given antibiotic spreads or declines is influenced by whether it is associated with altered susceptibility to other antibiotics or other stressors that bacteria encounter in nature, such as bacteriophages (viruses that infect bacteria). We used natural and clinical isolates of Escherichia coli, an abundant species and key pathogen, to characterize associations among resistance phenotypes to various antibiotics and bacteriophages. We found associations between some resistance phenotypes, and in contrast to past work with laboratory strains, they were exclusively positive. Analysis of bacterial genome sequences and horizontally transferred genetic elements (plasmids) helped to explain this, as well as our finding that there was no overall association between antibiotic resistance and bacteriophage resistance profiles across isolates. This improves our understanding of resistance evolution in nature, potentially informing new rational therapies that combine different antibacterials, including bacteriophages. | 2017 | 29089428 |
| 3911 | 12 | 0.9997 | Occurrence of beta-lactamases in bacteria. Our study highlights the escalating issue of beta-lactam resistance in nosocomial pathogens, driven by the broad spectrum of antibiotic-degrading enzymes and plasmid exchange. We catalogued known beta-lactamases across 230 bacterial genera, identified 2349 potential beta-lactamases across over 673 genera, and anticipate discovering many new types, underscoring the need for targeted gene analysis in combating resistance. This study also elucidates the complex relationship between the diversity and frequency of beta-lactamase genes across bacterial genera, highlighting the need for genus-specific approaches in combating antibiotic resistance and emphasizing these genes' significant global distribution and host-specific prevalence. We report many transcriptional regulators, transposases and other factors in the genomes of 20 different bacterial isolates, some of which are consistent with the ability of these species to adapt to different environments. Although we could not determine precisely which factors regulate the presence of beta-lactamases in specific bacteria, we found that the proportion of regulatory genes, the size of the genome, and other factors are not decisive. Further studies are needed to elucidate key aspects of this process. | 2024 | 38810790 |
| 4378 | 13 | 0.9997 | Gene network interaction analysis to elucidate the antimicrobial resistance mechanisms in the Clostridiumdifficile. Antimicrobial resistance has caused chaos worldwide due to the depiction of multidrug-resistant (MDR) infective microorganisms. A thorough examination of antimicrobial resistance (AMR) genes and associated resistant mechanisms is vital to solving this problem. Clostridium difficile (C. difficile) is an opportunistic nosocomial bacterial strain that has acquired exogenous AMR genes that confer resistance to antimicrobials such as erythromycin, azithromycin, clarithromycin, rifampicin, moxifloxacin, fluoroquinolones, vancomycin, and others. A network of interactions, including 20 AMR genes, was created and analyzed. In functional enrichment analysis, Cellular components (CC), Molecular Functions (MF), and Biological Processes (BP) were discovered to have substantial involvement. Mutations in the rpl genes, which encode ribosomal proteins, confer resistance in Gram-positive bacteria. Full erythromycin and azithromycin cross-resistance can be conferred if more than one of the abovementioned genes is present. In the enriched BP, rps genes related to transcriptional regulation and biosynthesis were found. The genes belong to the rpoB gene family, which has previously been related to rifampicin resistance. The genes rpoB, gyrA, gyrB, rpoS, rpl genes, rps genes, and Van genes are thought to be the hub genes implicated in resistance in C. difficile. As a result, new medications could be developed using these genes. Overall, our observations provide a thorough understanding of C. difficile AMR mechanisms. | 2023 | 36958645 |
| 4396 | 14 | 0.9997 | Insights into the processes that drive the evolution of drug resistance in Mycobacterium tuberculosis. At present, the successful transmission of drug-resistant Mycobacterium tuberculosis, including multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains, in human populations, threatens tuberculosis control worldwide. Differently from many other bacteria, M. tuberculosis drug resistance is acquired mainly through mutations in specific drug resistance-associated genes. The panel of mutations is highly diverse, but depends on the affected gene and M. tuberculosis genetic background. The variety of genetic profiles observed in drug-resistant clinical isolates underlines different evolutionary trajectories towards multiple drug resistance, although some mutation patterns are prominent. This review discusses the intrinsic processes that may influence drug resistance evolution in M. tuberculosis, such as mutation rate, drug resistance-associated mutations, fitness cost, compensatory mutations and epistasis. This knowledge should help to better predict the risk of emergence of highly resistant M. tuberculosis strains and to develop new tools and strategies to limit the development and spread of MDR and XDR strains. | 2018 | 30344622 |
| 4392 | 15 | 0.9997 | The Neglected Contribution of Streptomycin to the Tuberculosis Drug Resistance Problem. The airborne pathogen Mycobacterium tuberculosis is responsible for a present major public health problem worsened by the emergence of drug resistance. M. tuberculosis has acquired and developed streptomycin (STR) resistance mechanisms that have been maintained and transmitted in the population over the last decades. Indeed, STR resistant mutations are frequently identified across the main M. tuberculosis lineages that cause tuberculosis outbreaks worldwide. The spread of STR resistance is likely related to the low impact of the most frequent underlying mutations on the fitness of the bacteria. The withdrawal of STR from the first-line treatment of tuberculosis potentially lowered the importance of studying STR resistance. However, the prevalence of STR resistance remains very high, could be underestimated by current genotypic methods, and was found in outbreaks of multi-drug (MDR) and extensively drug (XDR) strains in different geographic regions. Therefore, the contribution of STR resistance to the problem of tuberculosis drug resistance should not be neglected. Here, we review the impact of STR resistance and detail well-known and novel candidate STR resistance mechanisms, genes, and mutations. In addition, we aim to provide insights into the possible role of STR resistance in the development of multi-drug resistant tuberculosis. | 2021 | 34946952 |
| 9920 | 16 | 0.9997 | Designing antibiotic cycling strategies by determining and understanding local adaptive landscapes. The evolution of antibiotic resistance among bacteria threatens our continued ability to treat infectious diseases. The need for sustainable strategies to cure bacterial infections has never been greater. So far, all attempts to restore susceptibility after resistance has arisen have been unsuccessful, including restrictions on prescribing [1] and antibiotic cycling [2], [3]. Part of the problem may be that those efforts have implemented different classes of unrelated antibiotics, and relied on removal of resistance by random loss of resistance genes from bacterial populations (drift). Here, we show that alternating structurally similar antibiotics can restore susceptibility to antibiotics after resistance has evolved. We found that the resistance phenotypes conferred by variant alleles of the resistance gene encoding the TEM β-lactamase (bla(TEM)) varied greatly among 15 different β-lactam antibiotics. We captured those differences by characterizing complete adaptive landscapes for the resistance alleles bla(TEM-50) and bla(TEM-85), each of which differs from its ancestor bla(TEM-1) by four mutations. We identified pathways through those landscapes where selection for increased resistance moved in a repeating cycle among a limited set of alleles as antibiotics were alternated. Our results showed that susceptibility to antibiotics can be sustainably renewed by cycling structurally similar antibiotics. We anticipate that these results may provide a conceptual framework for managing antibiotic resistance. This approach may also guide sustainable cycling of the drugs used to treat malaria and HIV. | 2013 | 23418506 |
| 3830 | 17 | 0.9997 | Resistance Gene Carriage Predicts Growth of Natural and Clinical Escherichia coli Isolates in the Absence of Antibiotics. Bacterial pathogens that carry antibiotic resistance alleles sometimes pay a cost in the form of impaired growth in antibiotic-free conditions. This cost of resistance is expected to be a key parameter for understanding how resistance spreads and persists in pathogen populations. Analysis of individual resistance alleles from laboratory evolution and natural isolates has shown they are typically costly, but these costs are highly variable and influenced by genetic variation at other loci. It therefore remains unclear how strongly resistance is linked to impaired antibiotic-free growth in bacteria from natural and clinical scenarios, where resistance alleles are likely to coincide with other types of genetic variation. To investigate this, we measured the growth of 92 natural and clinical Escherichia coli isolates across three antibiotic-free environments. We then tested whether variation of antibiotic-free growth among isolates was predicted by their resistance to 10 antibiotics, while accounting for the phylogenetic structure of the data. We found that isolates with similar resistance profiles had similar antibiotic-free growth profiles, but it was not simply that higher average resistance was associated with impaired growth. Next, we used whole-genome sequences to identify antibiotic resistance genes and found that isolates carrying a greater number of resistance gene types grew relatively poorly in antibiotic-free conditions, even when the resistance genes they carried were different. This suggests that the resistance of bacterial pathogens is linked to growth costs in nature, but it is the total genetic burden and multivariate resistance phenotype that predict these costs, rather than individual alleles or mean resistance across antibiotics.IMPORTANCE Managing the spread of antibiotic resistance in bacterial pathogens is a major challenge for global public health. Central to this challenge is understanding whether resistance is linked to impaired bacterial growth in the absence of antibiotics, because this determines whether resistance declines when bacteria are no longer exposed to antibiotics. We studied 92 isolates of the key bacterial pathogen Escherichia coli; these isolates varied in both their antibiotic resistance genes and other parts of the genome. Taking this approach, rather than focusing on individual genetic changes associated with resistance as in much previous work, revealed that growth without antibiotics was linked to the number of specialized resistance genes carried and the combination of antibiotics to which isolates were resistant but was not linked to average antibiotic resistance. This approach provides new insights into the genetic factors driving the long-term persistence of antibiotic-resistant bacteria, which is important for future efforts to predict and manage resistance. | 2019 | 30530714 |
| 9405 | 18 | 0.9997 | Functional Metagenomic Screening for Antimicrobial Resistance in the Oral Microbiome. A large proportion of bacteria, from a multitude of environments, are not yet able to be grown in the laboratory, and therefore microbiological and molecular biological investigations of these bacteria are challenging. A way to circumvent this challenge is to analyze the metagenome, the entire collection of DNA molecules that can be isolated from a particular environment or sample. This collection of DNA molecules can be sequenced and assembled to determine what is present and infer functional potential, or used as a PCR template to detect known target DNA and potentially unknown regions of DNA nearby those targets; however assigning functions to new or conserved hypothetical, functionally cryptic, genes is difficult. Functional metagenomics allows researchers to determine which genes are responsible for selectable phenotypes, such as resistance to antimicrobials and metabolic capabilities, without the prerequisite needs to grow the bacteria containing those genes or to already know which genes are of interest. It is estimated that a third of the resident species of the human oral cavity is not yet cultivable and, together with the ease of sample acquisition, makes this metagenome particularly suited to functional metagenomic studies. Here we describe the methodology related to the collection of saliva samples, extraction of metagenomic DNA, construction of metagenomic libraries, as well as the description of functional assays that have previously led to the identification of new genes conferring antimicrobial resistance. | 2021 | 34410638 |
| 3832 | 19 | 0.9997 | A population genomics approach to exploiting the accessory 'resistome' of Escherichia coli. The emergence of antibiotic resistance is a defining challenge, and Escherichia coli is recognized as one of the leading species resistant to the antimicrobials used in human or veterinary medicine. Here, we analyse the distribution of 2172 antimicrobial-resistance (AMR) genes in 4022 E. coli to provide a population-level view of resistance in this species. By separating the resistance determinants into 'core' (those found in all strains) and 'accessory' (those variably present) determinants, we have found that, surprisingly, almost half of all E. coli do not encode any accessory resistance determinants. However, those strains that do encode accessory resistance are significantly more likely to be resistant to multiple antibiotic classes than would be expected by chance. Furthermore, by studying the available date of isolation for the E. coli genomes, we have visualized an expanding, highly interconnected network that describes how resistances to antimicrobials have co-associated within genomes over time. These data can be exploited to reveal antimicrobial combinations that are less likely to be found together, and so if used in combination may present an increased chance of suppressing the growth of bacteria and reduce the rate at which resistance factors are spread. Our study provides a complex picture of AMR in the E. coli population. Although the incidence of resistance to all studied antibiotic classes has increased dramatically over time, there exist combinations of antibiotics that could, in theory, attack the entirety of E. coli, effectively removing the possibility that discrete AMR genes will increase in frequency in the population. | 2017 | 28785420 |