# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 4344 | 0 | 1.0000 | Phenetic Comparison of Prokaryotic Genomes Using k-mers. Bacterial genomics studies are getting more extensive and complex, requiring new ways to envision analyses. Using the Ray Surveyor software, we demonstrate that comparison of genomes based on their k-mer content allows reconstruction of phenetic trees without the need of prior data curation, such as core genome alignment of a species. We validated the methodology using simulated genomes and previously published phylogenomic studies of Streptococcus pneumoniae and Pseudomonas aeruginosa. We also investigated the relationship of specific genetic determinants with bacterial population structures. By comparing clusters from the complete genomic content of a genome population with clusters from specific functional categories of genes, we can determine how the population structures are correlated. Indeed, the strain clustering based on a subset of k-mers allows determination of its similarity with the whole genome clusters. We also applied this methodology on 42 species of bacteria to determine the correlational significance of five important bacterial genomic characteristics. For example, intrinsic resistance is more important in P. aeruginosa than in S. pneumoniae, and the former has increased correlation of its population structure with antibiotic resistance genes. The global view of the pangenome of bacteria also demonstrated the taxa-dependent interaction of population structure with antibiotic resistance, bacteriophage, plasmid, and mobile element k-mer data sets. | 2017 | 28957508 |
| 4624 | 1 | 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 |
| 4375 | 2 | 0.9998 | Evidence of a large novel gene pool associated with prokaryotic genomic islands. Microbial genes that are "novel" (no detectable homologs in other species) have become of increasing interest as environmental sampling suggests that there are many more such novel genes in yet-to-be-cultured microorganisms. By analyzing known microbial genomic islands and prophages, we developed criteria for systematic identification of putative genomic islands (clusters of genes of probable horizontal origin in a prokaryotic genome) in 63 prokaryotic genomes, and then characterized the distribution of novel genes and other features. All but a few of the genomes examined contained significantly higher proportions of novel genes in their predicted genomic islands compared with the rest of their genome (Paired t test = 4.43E-14 to 1.27E-18, depending on method). Moreover, the reverse observation (i.e., higher proportions of novel genes outside of islands) never reached statistical significance in any organism examined. We show that this higher proportion of novel genes in predicted genomic islands is not due to less accurate gene prediction in genomic island regions, but likely reflects a genuine increase in novel genes in these regions for both bacteria and archaea. This represents the first comprehensive analysis of novel genes in prokaryotic genomic islands and provides clues regarding the origin of novel genes. Our collective results imply that there are different gene pools associated with recently horizontally transmitted genomic regions versus regions that are primarily vertically inherited. Moreover, there are more novel genes within the gene pool associated with genomic islands. Since genomic islands are frequently associated with a particular microbial adaptation, such as antibiotic resistance, pathogen virulence, or metal resistance, this suggests that microbes may have access to a larger "arsenal" of novel genes for adaptation than previously thought. | 2005 | 16299586 |
| 9405 | 3 | 0.9998 | 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 |
| 4380 | 4 | 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 |
| 4381 | 5 | 0.9998 | Specific Gene Loci of Clinical Pseudomonas putida Isolates. Pseudomonas putida are ubiquitous inhabitants of soils and clinical isolates of this species have been seldom described. Clinical isolates show significant variability in their ability to cause damage to hosts because some of them are able to modulate the host's immune response. In the current study, comparisons between the genomes of different clinical and environmental strains of P. putida were done to identify genetic clusters shared by clinical isolates that are not present in environmental isolates. We show that in clinical strains specific genes are mostly present on transposons, and that this set of genes exhibit high identity with genes found in pathogens and opportunistic pathogens. The set of genes prevalent in P. putida clinical isolates, and absent in environmental isolates, are related with survival under oxidative stress conditions, resistance against biocides, amino acid metabolism and toxin/antitoxin (TA) systems. This set of functions have influence in colonization and survival within human tissues, since they avoid host immune response or enhance stress resistance. An in depth bioinformatic analysis was also carried out to identify genetic clusters that are exclusive to each of the clinical isolates and that correlate with phenotypical differences between them, a secretion system type III-like was found in one of these clinical strains, a determinant of pathogenicity in Gram-negative bacteria. | 2016 | 26820467 |
| 4663 | 6 | 0.9998 | Pan-genomics of Ochrobactrum species from clinical and environmental origins reveals distinct populations and possible links. Ochrobactrum genus is comprised of soil-dwelling Gram-negative bacteria mainly reported for bioremediation of toxic compounds. Since last few years, mainly two species of this genus, O. intermedium and O. anthropi were documented for causing infections mostly in the immunocompromised patients. Despite such ubiquitous presence, study of adaptation in various niches is still lacking. Thus, to gain insights into the niche adaptation strategies, pan-genome analysis was carried out by comparing 67 genome sequences belonging to Ochrobactrum species. Pan-genome analysis revealed it is an open pan-genome indicative of the continuously evolving nature of the genus. The presence/absence of gene clusters also illustrated the unique presence of antibiotic efflux transporter genes and type IV secretion system genes in the clinical strains while the genes of solvent resistance and exporter pumps in the environmental strains. A phylogenomic investigation based on 75 core genes depicted better and robust phylogenetic resolution and topology than the 16S rRNA gene. To support the pan-genome analysis, individual genomes were also investigated for the mobile genetic elements (MGE), antibiotic resistance genes (ARG), metal resistance genes (MRG) and virulence factors (VF). The analysis revealed the presence of MGE, ARG, and MRG in all the strains which play an important role in the species evolution which is in agreement with the pan-genome analysis. The average nucleotide identity (ANI) based on the genetic relatedness between the Ochrobactrum species indicated a distinction between individual species. Interestingly, the ANI tool was able to classify the Ochrobactrum genomes to the species level which were assigned till the genus level on the NCBI database. | 2020 | 32428556 |
| 4345 | 7 | 0.9998 | 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 |
| 4626 | 8 | 0.9997 | 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 |
| 4343 | 9 | 0.9997 | Identifying lineage effects when controlling for population structure improves power in bacterial association studies. Bacteria pose unique challenges for genome-wide association studies because of strong structuring into distinct strains and substantial linkage disequilibrium across the genome(1,2). Although methods developed for human studies can correct for strain structure(3,4), this risks considerable loss-of-power because genetic differences between strains often contribute substantial phenotypic variability(5). Here, we propose a new method that captures lineage-level associations even when locus-specific associations cannot be fine-mapped. We demonstrate its ability to detect genes and genetic variants underlying resistance to 17 antimicrobials in 3,144 isolates from four taxonomically diverse clonal and recombining bacteria: Mycobacterium tuberculosis, Staphylococcus aureus, Escherichia coli and Klebsiella pneumoniae. Strong selection, recombination and penetrance confer high power to recover known antimicrobial resistance mechanisms and reveal a candidate association between the outer membrane porin nmpC and cefazolin resistance in E. coli. Hence, our method pinpoints locus-specific effects where possible and boosts power by detecting lineage-level differences when fine-mapping is intractable. | 2016 | 27572646 |
| 4629 | 10 | 0.9997 | 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 |
| 4623 | 11 | 0.9997 | Capturing the Resistome: a Targeted Capture Method To Reveal Antibiotic Resistance Determinants in Metagenomes. Identification of the nucleotide sequences encoding antibiotic resistance elements and determination of their association with antibiotic resistance are critical to improve surveillance and monitor trends in antibiotic resistance. Current methods to study antibiotic resistance in various environments rely on extensive deep sequencing or laborious culturing of fastidious organisms, both of which are heavily time-consuming operations. An accurate and sensitive method to identify both rare and common resistance elements in complex metagenomic samples is needed. Referencing the sequences in the Comprehensive Antibiotic Resistance Database, we designed a set of 37,826 probes to specifically target over 2,000 nucleotide sequences associated with antibiotic resistance in clinically relevant bacteria. Testing of this probe set on DNA libraries generated from multidrug-resistant bacteria to selectively capture resistance genes reproducibly produced higher numbers of reads on target at a greater length of coverage than shotgun sequencing. We also identified additional resistance gene sequences from human gut microbiome samples that sequencing alone was not able to detect. Our method to capture the resistome enables a sensitive means of gene detection in diverse environments where genes encoding antibiotic resistance represent less than 0.1% of the metagenome. | 2019 | 31611361 |
| 4374 | 12 | 0.9997 | Core genes can have higher recombination rates than accessory genes within global microbial populations. Recombination is essential to microbial evolution, and is involved in the spread of antibiotic resistance, antigenic variation, and adaptation to the host niche. However, assessing the impact of homologous recombination on accessory genes which are only present in a subset of strains of a given species remains challenging due to their complex phylogenetic relationships. Quantifying homologous recombination for accessory genes (which are important for niche-specific adaptations) in comparison to core genes (which are present in all strains and have essential functions) is critical to understanding how selection acts on variation to shape species diversity and genome structures of bacteria. Here, we apply a computationally efficient, non-phylogenetic approach to measure homologous recombination rates in the core and accessory genome using >100,000 whole genome sequences from Streptococcus pneumoniae and several additional species. By analyzing diverse sets of sequence clusters, we show that core genes often have higher recombination rates than accessory genes, and for some bacterial species the associated effect sizes for these differences are pronounced. In a subset of species, we find that gene frequency and homologous recombination rate are positively correlated. For S. pneumoniae and several additional species, we find that while the recombination rate is higher for the core genome, the mutational divergence is lower, indicating that divergence-based homologous recombination barriers could contribute to differences in recombination rates between the core and accessory genome. Homologous recombination may therefore play a key role in increasing the efficiency of selection in the most conserved parts of the genome. | 2022 | 35801696 |
| 4625 | 13 | 0.9997 | 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 |
| 5111 | 14 | 0.9997 | 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 |
| 3911 | 15 | 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 |
| 4828 | 16 | 0.9997 | Generating Transposon Insertion Libraries in Gram-Negative Bacteria for High-Throughput Sequencing. Transposon sequencing (Tn-seq) is a powerful method that combines transposon mutagenesis and massive parallel sequencing to identify genes and pathways that contribute to bacterial fitness under a wide range of environmental conditions. Tn-seq applications are extensive and have not only enabled examination of genotype-phenotype relationships at an organism level but also at the population, community and systems levels. Gram-negative bacteria are highly associated with antimicrobial resistance phenotypes, which has increased incidents of antibiotic treatment failure. Antimicrobial resistance is defined as bacterial growth in the presence of otherwise lethal antibiotics. The "last-line" antimicrobial colistin is used to treat Gram-negative bacterial infections. However, several Gram-negative pathogens, including Acinetobacter baumannii can develop colistin resistance through a range of molecular mechanisms, some of which were characterized using Tn-seq. Furthermore, signal transduction pathways that regulate colistin resistance vary within Gram-negative bacteria. Here we propose an efficient method of transposon mutagenesis in A. baumannii that streamlines generation of a saturating transposon insertion library and amplicon library construction by eliminating the need for restriction enzymes, adapter ligation, and gel purification. The methods described herein will enable in-depth analysis of molecular determinants that contribute to A. baumannii fitness when challenged with colistin. The protocol is also applicable to other Gram-negative ESKAPE pathogens, which are primarily associated with drug resistant hospital-acquired infections. | 2020 | 32716393 |
| 4631 | 17 | 0.9997 | 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 |
| 4665 | 18 | 0.9997 | A comprehensive survey of integron-associated genes present in metagenomes. BACKGROUND: Integrons are genomic elements that mediate horizontal gene transfer by inserting and removing genetic material using site-specific recombination. Integrons are commonly found in bacterial genomes, where they maintain a large and diverse set of genes that plays an important role in adaptation and evolution. Previous studies have started to characterize the wide range of biological functions present in integrons. However, the efforts have so far mainly been limited to genomes from cultivable bacteria and amplicons generated by PCR, thus targeting only a small part of the total integron diversity. Metagenomic data, generated by direct sequencing of environmental and clinical samples, provides a more holistic and unbiased analysis of integron-associated genes. However, the fragmented nature of metagenomic data has previously made such analysis highly challenging. RESULTS: Here, we present a systematic survey of integron-associated genes in metagenomic data. The analysis was based on a newly developed computational method where integron-associated genes were identified by detecting their associated recombination sites. By processing contiguous sequences assembled from more than 10 terabases of metagenomic data, we were able to identify 13,397 unique integron-associated genes. Metagenomes from marine microbial communities had the highest occurrence of integron-associated genes with levels more than 100-fold higher than in the human microbiome. The identified genes had a large functional diversity spanning over several functional classes. Genes associated with defense mechanisms and mobility facilitators were most overrepresented and more than five times as common in integrons compared to other bacterial genes. As many as two thirds of the genes were found to encode proteins of unknown function. Less than 1% of the genes were associated with antibiotic resistance, of which several were novel, previously undescribed, resistance gene variants. CONCLUSIONS: Our results highlight the large functional diversity maintained by integrons present in unculturable bacteria and significantly expands the number of described integron-associated genes. | 2020 | 32689930 |
| 9918 | 19 | 0.9997 | Linking plasmid-based beta-lactamases to their bacterial hosts using single-cell fusion PCR. The horizonal transfer of plasmid-encoded genes allows bacteria to adapt to constantly shifting environmental pressures, bestowing functional advantages to their bacterial hosts such as antibiotic resistance, metal resistance, virulence factors, and polysaccharide utilization. However, common molecular methods such as short- and long-read sequencing of microbiomes cannot associate extrachromosomal plasmids with the genome of the host bacterium. Alternative methods to link plasmids to host bacteria are either laborious, expensive, or prone to contamination. Here we present the One-step Isolation and Lysis PCR (OIL-PCR) method, which molecularly links plasmid-encoded genes with the bacterial 16S rRNA gene via fusion PCR performed within an emulsion. After validating this method, we apply it to identify the bacterial hosts of three clinically relevant beta-lactamases within the gut microbiomes of neutropenic patients, as they are particularly vulnerable multidrug-resistant infections. We successfully detect the known association of a multi-drug resistant plasmid with Klebsiella pneumoniae, as well as the novel associations of two low-abundance genera, Romboutsia and Agathobacter. Further investigation with OIL-PCR confirmed that our detection of Romboutsia is due to its physical association with Klebsiella as opposed to directly harboring the beta-lactamase genes. Here we put forth a robust, accessible, and high-throughput platform for sensitively surveying the bacterial hosts of mobile genes, as well as detecting physical bacterial associations such as those occurring within biofilms and complex microbial communities. | 2021 | 34282723 |