# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 9661 | 0 | 0.9987 | Pangenomes of human gut microbiota uncover links between genetic diversity and stress response. The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research. | 2024 | 39353429 |
| 5119 | 1 | 0.9986 | ROCker models for reliable detection and typing of short-read sequences carrying mcr, erm, mph, and lnu antibiotic resistance genes. Quantitative monitoring of emerging antimicrobial resistance genes (ARGs) using short-read sequences remains challenging due to the high frequency of amino acid functional domains and motifs shared with related but functionally distinct (non-target) proteins. To facilitate ARG monitoring efforts using unassembled short reads, we present novel ROCker models for mcr, mph, erm, and lnu ARG families, as well as models for variants of special public health concern within these families, including mcr-1, mphA, ermB, lnuF, lnuB, and lnuG genes. For this, we curated target gene sequence sets for model training and built these models using the recently updated ROCker V2 pipeline (Gerhardt et al., in review). To validate our models, we simulated reads from the whole genome of ARG-carrying isolates spanning a range of common read lengths and used them to challenge the filtering efficacy of ROCker versus common static filtering approaches, such as similarity searches using BLASTx with various e-value thresholds or hidden Markov models. ROCker models consistently showed F1 scores up to 10× higher (31% higher on average) and lower false-positive (by 30%, on average) and false-negative (by 16%, on average) rates based on 250 bp reads compared to alternative methods. The ROCker models and all related reference materials and data are freely available through http://enve-omics.ce.gatech.edu/rocker/models, further expanding the available model collection previously developed for other genes. Their application to short-read metagenomes, metatranscriptomes, and PCR amplicon data should facilitate more accurate classification and quantification of unassembled short-read sequences for these ARG families and specific genes.IMPORTANCEAntimicrobial resistance gene families encoding erm and mph genes confer resistance to the macrolide class of antimicrobials, which are used to treat a wide range of infections. Similarly, the mcr gene family confers resistance to polymyxin E (colistin), a drug of last resort for many serious drug-resistant bacterial infections, and the lnu gene family confers resistance to lincomycin, which is reserved for patients allergic to penicillin or where bacteria have developed resistance to other antimicrobials. Assessing the prevalence of these genes in clinical or environmental samples and monitoring their spread to new pathogens are thus important for quantifying the associated public health risk. However, detecting these and other resistance genes in short-read sequence data is technically challenging. Our ROCker bioinformatic pipeline achieves reliable detection and typing of broad-range target gene sequences in complex data sets, thus contributing toward solving an important problem in ongoing surveillance efforts of antimicrobial resistance. | 2025 | 41143534 |
| 3777 | 2 | 0.9985 | A Bioinformatic Analysis of Integrative Mobile Genetic Elements Highlights Their Role in Bacterial Adaptation. Mobile genetic elements (MGEs) contribute to bacterial adaptation and evolution; however, high-throughput, unbiased MGE detection remains challenging. We describe MGEfinder, a bioinformatic toolbox that identifies integrative MGEs and their insertion sites by using short-read sequencing data. MGEfinder identifies the genomic site of each MGE insertion and infers the identity of the inserted sequence. We apply MGEfinder to 12,374 sequenced isolates of 9 prevalent bacterial pathogens, including Mycobacterium tuberculosis, Staphylococcus aureus, and Escherichia coli, and identify thousands of MGEs, including candidate insertion sequences, conjugative transposons, and prophage elements. The MGE repertoire and insertion rates vary across species, and integration sites often cluster near genes related to antibiotic resistance, virulence, and pathogenicity. MGE insertions likely contribute to antibiotic resistance in laboratory experiments and clinical isolates. Additionally, we identified thousands of mobility genes, a subset of which have unknown function opening avenues for exploration. Future application of MGEfinder to commensal bacteria will further illuminate bacterial adaptation and evolution. | 2020 | 31862382 |
| 9850 | 3 | 0.9985 | Annotation and Comparative Genomics of Prokaryotic Transposable Elements. The data generated in nearly 30 years of bacterial genome sequencing has revealed the abundance of transposable elements (TE) and their importance in genome and transcript remodeling through the mediation of DNA insertions and deletions, structural rearrangements, and regulation of gene expression. Furthermore, what we have learned from studying transposition mechanisms and their regulation in bacterial TE is fundamental to our current understanding of TE in other organisms because much of what has been observed in bacteria is conserved in all domains of life. However, unlike eukaryotic TE, prokaryotic TE sequester and transmit important classes of genes that impact host fitness, such as resistance to antibiotics and heavy metals and virulence factors affecting animals and plants, among other acquired traits. This provides dynamism and plasticity to bacteria, which would otherwise be propagated clonally. The insertion sequences (IS), the simplest form of prokaryotic TE, are autonomous and compact mobile genetic elements. These can be organized into compound transposons, in which two similar IS can flank any DNA segment and render it transposable. Other more complex structures, called unit transposons, can be grouped into four major families (Tn3, Tn7, Tn402, Tn554) with specific genetic characteristics. This chapter will revisit the prominent structural features of these elements, focusing on a genomic annotation framework and comparative analysis. Relevant aspects of TE will also be presented, stressing their key position in genome impact and evolution, especially in the emergence of antimicrobial resistance and other adaptive traits. | 2024 | 38819561 |
| 4375 | 4 | 0.9985 | 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 |
| 4515 | 5 | 0.9985 | Novel Conserved Genotypes Correspond to Antibiotic Resistance Phenotypes of E. coli Clinical Isolates. Current efforts to understand antibiotic resistance on the whole genome scale tend to focus on known genes even as high throughput sequencing strategies uncover novel mechanisms. To identify genomic variations associated with antibiotic resistance, we employed a modified genome-wide association study; we sequenced genomic DNA from pools of E. coli clinical isolates with similar antibiotic resistance phenotypes using SOLiD technology to uncover single nucleotide polymorphisms (SNPs) unanimously conserved in each pool. The multidrug-resistant pools were genotypically similar to SMS-3-5, a previously sequenced multidrug-resistant isolate from a polluted environment. The similarity was evenly spread across the entire genome and not limited to plasmid or pathogenicity island loci. Among the pools of clinical isolates, genomic variation was concentrated adjacent to previously reported inversion and duplication differences between the SMS-3-5 isolate and the drug-susceptible laboratory strain, DH10B. SNPs that result in non-synonymous changes in gyrA (encoding the well-known S83L allele associated with fluoroquinolone resistance), mutM, ligB, and recG were unanimously conserved in every fluoroquinolone-resistant pool. Alleles of the latter three genes are tightly linked among most sequenced E. coli genomes, and had not been implicated in antibiotic resistance previously. The changes in these genes map to amino acid positions in alpha helices that are involved in DNA binding. Plasmid-encoded complementation of null strains with either allelic variant of mutM or ligB resulted in variable responses to ultraviolet light or hydrogen peroxide treatment as markers of induced DNA damage, indicating their importance in DNA metabolism and revealing a potential mechanism for fluoroquinolone resistance. Our approach uncovered evidence that additional DNA binding enzymes may contribute to fluoroquinolone resistance and further implicate environmental bacteria as a reservoir for antibiotic resistance. | 2013 | 23824211 |
| 8377 | 6 | 0.9985 | Genome-Wide Association Analyses in the Model Rhizobium Ensifer meliloti. Genome-wide association studies (GWAS) can identify genetic variants responsible for naturally occurring and quantitative phenotypic variation. Association studies therefore provide a powerful complement to approaches that rely on de novo mutations for characterizing gene function. Although bacteria should be amenable to GWAS, few GWAS have been conducted on bacteria, and the extent to which nonindependence among genomic variants (e.g., linkage disequilibrium [LD]) and the genetic architecture of phenotypic traits will affect GWAS performance is unclear. We apply association analyses to identify candidate genes underlying variation in 20 biochemical, growth, and symbiotic phenotypes among 153 strains of Ensifer meliloti For 11 traits, we find genotype-phenotype associations that are stronger than expected by chance, with the candidates in relatively small linkage groups, indicating that LD does not preclude resolving association candidates to relatively small genomic regions. The significant candidates show an enrichment for nucleotide polymorphisms (SNPs) over gene presence-absence variation (PAV), and for five traits, candidates are enriched in large linkage groups, a possible signature of epistasis. Many of the variants most strongly associated with symbiosis phenotypes were in genes previously identified as being involved in nitrogen fixation or nodulation. For other traits, apparently strong associations were not stronger than the range of associations detected in permuted data. In sum, our data show that GWAS in bacteria may be a powerful tool for characterizing genetic architecture and identifying genes responsible for phenotypic variation. However, careful evaluation of candidates is necessary to avoid false signals of association.IMPORTANCE Genome-wide association analyses are a powerful approach for identifying gene function. These analyses are becoming commonplace in studies of humans, domesticated animals, and crop plants but have rarely been conducted in bacteria. We applied association analyses to 20 traits measured in Ensifer meliloti, an agriculturally and ecologically important bacterium because it fixes nitrogen when in symbiosis with leguminous plants. We identified candidate alleles and gene presence-absence variants underlying variation in symbiosis traits, antibiotic resistance, and use of various carbon sources; some of these candidates are in genes previously known to affect these traits whereas others were in genes that have not been well characterized. Our results point to the potential power of association analyses in bacteria, but also to the need to carefully evaluate the potential for false associations. | 2018 | 30355664 |
| 3778 | 7 | 0.9985 | ggMOB: Elucidation of genomic conjugative features and associated cargo genes across bacterial genera using genus-genus mobilization networks. Horizontal gene transfer mediated by conjugation is considered an important evolutionary mechanism of bacteria. It allows organisms to quickly evolve new phenotypic properties including antimicrobial resistance (AMR) and virulence. The frequency of conjugation-mediated cargo gene exchange has not yet been comprehensively studied within and between bacterial taxa. We developed a frequency-based network of genus-genus conjugation features and candidate cargo genes from whole-genome sequence data of over 180,000 bacterial genomes, representing 1,345 genera. Using our method, which we refer to as ggMOB, we revealed that over half of the bacterial genomes contained one or more known conjugation features that matched exactly to at least one other genome. Moreover, the proportion of genomes containing these conjugation features varied substantially by genus and conjugation feature. These results and the genus-level network structure can be viewed interactively in the ggMOB interface, which allows for user-defined filtering of conjugation features and candidate cargo genes. Using the network data, we observed that the ratio of AMR gene representation in conjugative versus non-conjugative genomes exceeded 5:1, confirming that conjugation is a critical force for AMR spread across genera. Finally, we demonstrated that clustering genomes by conjugation profile sometimes correlated well with classical phylogenetic structuring; but that in some cases the clustering was highly discordant, suggesting that the importance of the accessory genome in driving bacterial evolution may be highly variable across both time and taxonomy. These results can advance scientific understanding of bacterial evolution, and can be used as a starting point for probing genus-genus gene exchange within complex microbial communities that include unculturable bacteria. ggMOB is publicly available under the GNU licence at https://ruiz-hci-lab.github.io/ggMOB/. | 2022 | 36568361 |
| 4638 | 8 | 0.9985 | Comprehensive Scanning of Prophages in Lactobacillus: Distribution, Diversity, Antibiotic Resistance Genes, and Linkages with CRISPR-Cas Systems. Prophage integration, release, and dissemination exert various effects on host bacteria. In the genus Lactobacillus, they may cause bacteriophage contamination during fermentation and even regulate bacterial populations in the gut. However, little is known about their distribution, genetic architecture, and relationships with their hosts. Here, we conducted prophage prediction analysis on 1,472 genomes from 16 different Lactobacillus species and found prophage fragments in almost all lactobacilli (99.8%), with 1,459 predicted intact prophages identified in 64.1% of the strains. We present an uneven prophage distribution among Lactobacillus species; multihabitat species retained more prophages in their genomes than restricted-habitat species. Characterization of the genome features, average nucleotide identity, and landscape visualization presented a high genome diversity of Lactobacillus prophages. We detected antibiotic resistance genes in more than 10% of Lactobacillus prophages and validated that the occurrence of resistance genes conferred by prophage integration was possibly associated with phenotypic resistance in Lactobacillus plantarum. Furthermore, our broad and comprehensive examination of the distribution of CRISPR-Cas systems across the genomes predicted type I and type III systems as potential antagonistic elements of Lactobacillus prophage. IMPORTANCE Lactobacilli are inherent microorganisms in the human gut and are widely used in the food processing industries due to their probiotic properties. Prophages were reportedly hidden in numerous Lactobacillus genomes and can potentially contaminate entire batches of fermentation or modulate the intestinal microecology once they are released. Therefore, a comprehensive scanning of prophages in Lactobacillus is essential for the safety evaluation and application development of probiotic candidates. We show that prophages are widely distributed among lactobacilli; however, intact prophages are more common in multihabitat species and display wide variations in genome feature, integration site, and genomic organization. Our data of the prophage-mediated antibiotic resistance genes (ARGs) and the resistance phenotype of lactobacilli provide evidence for deciphering the putative role of prophages as vectors of the ARGs. Furthermore, understanding the association between prophages and CRISPR-Cas systems is crucial to appreciate the coevolution of phages and Lactobacillus. | 2021 | 34060909 |
| 8413 | 9 | 0.9985 | Investigating mechanisms underlying genetic resistance to Salmon Rickettsial Syndrome in Atlantic salmon using RNA sequencing. BACKGROUND: Salmon Rickettsial Syndrome (SRS), caused by Piscirickettsia salmonis, is one of the primary causes of morbidity and mortality in Atlantic salmon aquaculture, particularly in Chile. Host resistance is a heritable trait, and functional genomic studies have highlighted genes and pathways important in the response of salmon to the bacteria. However, the functional mechanisms underpinning genetic resistance are not yet well understood. In the current study, a large population of salmon pre-smolts were challenged with P. salmonis, with mortality levels recorded and samples taken for genotyping. In parallel, head kidney and liver samples were taken from animals of the same population with high and low genomic breeding values for resistance, and used for RNA-Sequencing to compare their transcriptome profile both pre and post infection. RESULTS: A significant and moderate heritability (h(2) = 0.43) was shown for the trait of binary survival. Genome-wide association analyses using 38 K imputed SNP genotypes across 2265 animals highlighted that resistance is a polygenic trait. Several thousand genes were identified as differentially expressed between controls and infected samples, and enriched pathways related to the host immune response were highlighted. In addition, several networks with significant correlation with SRS resistance breeding values were identified, suggesting their involvement in mediating genetic resistance. These included apoptosis, cytoskeletal organisation, and the inflammasome. CONCLUSIONS: While resistance to SRS is a polygenic trait, this study has highlighted several relevant networks and genes that are likely to play a role in mediating genetic resistance. These genes may be future targets for functional studies, including genome editing, to further elucidate their role underpinning genetic variation in host resistance. | 2021 | 33676414 |
| 9405 | 10 | 0.9985 | 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 |
| 474 | 11 | 0.9985 | Novel antibiotic resistance profiles in bacteria isolated from oil fly larvae Helaeomyia petrolei living in the La Brea Tar Pits. Larvae from the petroleum oil fly, Helaeomyia petrolei, live in the asphaltene and polyaromatic hydrocarbon rich asphalt seeps of Rancho La Brea, Los Angeles, California. These larvae pass high amounts of viscous asphalt through their digestive system, and their gut microbiota is exposed to these extreme conditions. Environmental stress response mechanisms can co-select for antibiotic resistance, and in the current study we used 16S rRNA and genomic sequencing along with the Comprehensive Antibiotic Resistance Database (CARD) tools to characterize antibiotic resistance profiles from six bacteria previously isolated from the oil fly larval intestinal tract, linking phenotypic and genotypic resistance profiles. The isolates contain a core set of antibiotic resistance determinants along with determinants that are rarely found in these species. Comparing these oil fly isolates to the phenotypic prevalence data generated by the CARD Resistance Gene Identifier revealed sixteen instances where the oil fly bacteria appeared to carry a resistance not seen in related taxa in the database, suggesting a novel suite of resistance families in the oil fly isolates compared to other members of the same taxa. Results highlight the functional duality of genes that simultaneously code for antibiotic resistance and survival under extreme conditions, and expand our understanding of the ecological and evolutionary role of antibiotic resistance genes in environmental habitats. | 2024 | 39718641 |
| 9663 | 12 | 0.9985 | The structure of temperate phage-bacteria infection networks changes with the phylogenetic distance of the host bacteria. With their ability to integrate into the bacterial chromosome and thereby transfer virulence or drug-resistance genes across bacterial species, temperate phage play a key role in bacterial evolution. Thus, it is paramount to understand who infects whom to be able to predict the movement of DNA across the prokaryotic world and ultimately the emergence of novel (drug-resistant) pathogens. We empirically investigated lytic infection patterns among Vibrio spp. from distinct phylogenetic clades and their derived temperate phage. We found that across distantly related clades, infections occur preferentially within modules of the same clade. However, when the genetic distance of the host bacteria decreases, these clade-specific infections disappear. This indicates that the structure of temperate phage-bacteria infection networks changes with the phylogenetic distance of the host bacteria. | 2018 | 30429242 |
| 7690 | 13 | 0.9985 | Novel Antibiotic Resistance Determinants from Agricultural Soil Exposed to Antibiotics Widely Used in Human Medicine and Animal Farming. Antibiotic resistance has emerged globally as one of the biggest threats to human and animal health. Although the excessive use of antibiotics is recognized as accelerating the selection for resistance, there is a growing body of evidence suggesting that natural environments are "hot spots" for the development of both ancient and contemporary resistance mechanisms. Given that pharmaceuticals can be entrained onto agricultural land through anthropogenic activities, this could be a potential driver for the emergence and dissemination of resistance in soil bacteria. Using functional metagenomics, we interrogated the "resistome" of bacterial communities found in a collection of Canadian agricultural soil, some of which had been receiving antibiotics widely used in human medicine (macrolides) or food animal production (sulfamethazine, chlortetracycline, and tylosin) for up to 16 years. Of the 34 new antibiotic resistance genes (ARGs) recovered, the majority were predicted to encode (multi)drug efflux systems, while a few share little to no homology with established resistance determinants. We characterized several novel gene products, including putative enzymes that can confer high-level resistance against aminoglycosides, sulfonamides, and broad range of beta-lactams, with respect to their resistance mechanisms and clinical significance. By coupling high-resolution proteomics analysis with functional metagenomics, we discovered an unusual peptide, PPP(AZI 4), encoded within an alternative open reading frame not predicted by bioinformatics tools. Expression of the proline-rich PPP(AZI 4) can promote resistance against different macrolides but not other ribosome-targeting antibiotics, implicating a new macrolide-specific resistance mechanism that could be fundamentally linked to the evolutionary design of this peptide.IMPORTANCE Antibiotic resistance is a clinical phenomenon with an evolutionary link to the microbial pangenome. Genes and protogenes encoding specialized and potential resistance mechanisms are abundant in natural environments, but understanding of their identity and genomic context remains limited. Our discovery of several previously unknown antibiotic resistance genes from uncultured soil microorganisms indicates that soil is a significant reservoir of resistance determinants, which, once acquired and "repurposed" by pathogenic bacteria, can have serious impacts on therapeutic outcomes. This study provides valuable insights into the diversity and identity of resistance within the soil microbiome. The finding of a novel peptide-mediated resistance mechanism involving an unpredicted gene product also highlights the usefulness of integrating proteomics analysis into metagenomics-driven gene discovery. | 2017 | 28625995 |
| 5102 | 14 | 0.9985 | Pipeline for Antimicrobial Resistance Gene Quantification from Host Tissue. Antibiotics are frequently used in food production animals to control disease and improve productivity, but this promotes the development of antimicrobial resistance (AMR) and subsequent broader spread of AMR bacteria throughout food chain, endangering the well-being and health of both animals and humans. In humans, the gut microbiome harbors a diverse range of AMR bacteria, known as the resistome. To effectively mitigate AMR in food animals requires first determining the expression and abundance of AMR-related genes in the gut resistome. Currently, such knowledge in regard to food animals is largely lacking. Gut tissue RNA sequencing (GTRS) can capture metabolically active transcripts from both the host and the microbes attached to the gut epithelium. Ideally, AMR genes can be quantified using GTRS data, making it possible to study the relationship between host and microbe. For the majority of these GTRS studies, only host transcriptome changes have been reported, while the microbial AMR remains largely unexamined, mainly due to the lack of easily implementable bioinformatics tools. Here we present a straightforward workflow to accomplish that using common command-line bioinformatics tools. With this pipeline, the host is considered noise, and host data are filtered out from the microbial reads. Transcript quantification of the AMR genes is then performed. The pipeline then continues through AMR transcript quantification, differential gene expression, and SNP analysis. Using open-source tools, we made this analytical pipeline easy to implement and able to generate results ready to be incorporated into publishable reports. Published 2025. This article is a U.S. Government work and is in the public domain in the USA. Basic Protocol: Running the gene quantification pipeline Support Protocol 1: Downloading FASTQ files from the NCBI database Support Protocol 2: Building a genome reference index of the host Support Protocol 3: Differential gene expression analysis Support Protocol 4: Single-nucleotide polymorphism (SNP) analysis. | 2025 | 40145236 |
| 8385 | 15 | 0.9985 | Function and Phylogeny of Bacterial Butyryl Coenzyme A:Acetate Transferases and Their Diversity in the Proximal Colon of Swine. Studying the host-associated butyrate-producing bacterial community is important, because butyrate is essential for colonic homeostasis and gut health. Previous research has identified the butyryl coenzyme A (CoA):acetate-CoA transferase (EC 2.3.8.3) as a gene of primary importance for butyrate production in intestinal ecosystems; however, this gene family (but) remains poorly defined. We developed tools for the analysis of butyrate-producing bacteria based on 12 putative but genes identified in the genomes of nine butyrate-producing bacteria obtained from the swine intestinal tract. Functional analyses revealed that eight of these genes had strong But enzyme activity. When but paralogues were found within a genome, only one gene per genome encoded strong activity, with the exception of one strain in which no gene encoded strong But activity. Degenerate primers were designed to amplify the functional but genes and were tested by amplifying environmental but sequences from DNA and RNA extracted from swine colonic contents. The results show diverse but sequences from swine-associated butyrate-producing bacteria, most of which clustered near functionally confirmed sequences. Here, we describe tools and a framework that allow the bacterial butyrate-producing community to be profiled in the context of animal health and disease. IMPORTANCE: Butyrate is a compound produced by the microbiota in the intestinal tracts of animals. This compound is of critical importance for intestinal health, and yet studying its production by diverse intestinal bacteria is technically challenging. Here, we present an additional way to study the butyrate-producing community of bacteria using one degenerate primer set that selectively targets genes experimentally demonstrated to encode butyrate production. This work will enable researchers to more easily study this very important bacterial function that has implications for host health and resistance to disease. | 2016 | 27613689 |
| 9555 | 16 | 0.9985 | Bacteria.guru: Comparative Transcriptomics and Co-Expression Database for Bacterial Pathogens. While bacteria can be beneficial to our health, their deadly pathogenic potential has been an ever-present concern exacerbated by the emergence of drug-resistant strains. As such, there is a pressing urgency for an enhanced understanding of their gene function and regulation, which could mediate the development of novel antimicrobials. Transcriptomic analyses have been established as insightful and indispensable to the functional characterization of genes and identification of new biological pathways, but in the context of bacterial studies, they remain limited to species-specific datasets. To address this, we integrated the genomic and transcriptomic data of the 17 most notorious and researched bacterial pathogens, creating bacteria.guru, an interactive database that can identify, visualize, and compare gene expression profiles, coexpression networks, functionally enriched clusters, and gene families across species. Through illustrating antibiotic resistance mechanisms in P. aeruginosa, we demonstrate that bacteria.guru could potentially aid in discovering multi-faceted antibiotic targets and, overall, facilitate future bacterial research. AVAILABILITY: The database and coexpression networks are freely available from https://bacteria.guru/. Sample annotations can be found in the supplemental data. | 2022 | 34838806 |
| 3782 | 17 | 0.9985 | CRISPR spacers acquired from plasmids primarily target backbone genes, making them valuable for predicting potential hosts and host range. In recent years, there has been a surge in metagenomic studies focused on identifying plasmids in environmental samples. Although these studies have unearthed numerous novel plasmids, enriching our understanding of their environmental roles, a significant gap remains: the scarcity of information regarding the bacterial hosts of these newly discovered plasmids. Furthermore, even when plasmids are identified within bacterial isolates, the reported host is typically limited to the original isolate, with no insights into alternative hosts or the plasmid's potential host range. Given that plasmids depend on hosts for their existence, investigating plasmids without the knowledge of potential hosts offers only a partial perspective. This study introduces a method for identifying potential hosts and host ranges for plasmids through alignment with CRISPR spacers. To validate the method, we compared the PLSDB plasmids database with the CRISPR spacers database, yielding host predictions for 46% of the plasmids. When compared with reported hosts, our predictions achieved 84% concordance at the family level and 99% concordance at the phylum level. Moreover, the method frequently identified multiple potential hosts for a plasmid, thereby enabling predictions of alternative hosts and the host range. Notably, we found that CRISPR spacers predominantly target plasmid backbone genes while sparing functional genes, such as those linked to antibiotic resistance, aligning with our hypothesis that CRISPR spacers are acquired from plasmid-specific regions rather than insertion elements from diverse sources. Finally, we illustrate the network of connections among different bacterial taxa through plasmids, revealing potential pathways for horizontal gene transfer.IMPORTANCEPlasmids are notorious for their role in distributing antibiotic resistance genes, but they may also carry and distribute other environmentally important genes. Since plasmids are not free-living entities and rely on host bacteria for survival and propagation, predicting their hosts is essential. This study presents a method for predicting potential hosts for plasmids and offers insights into the potential paths for spreading functional genes between different bacteria. Understanding plasmid-host relationships is crucial for comprehending the ecological and clinical impact of plasmids and implications for various biological processes. | 2024 | 39508585 |
| 9649 | 18 | 0.9984 | Bacteria of the order Burkholderiales are original environmental hosts of type II trimethoprim resistance genes (dfrB). It is consensus that clinically relevant antibiotic resistance genes have their origin in environmental bacteria, including the large pool of primarily benign species. Yet, for the vast majority of acquired antibiotic resistance genes, the original environmental host(s) has not been identified to date. Closing this knowledge gap could improve our understanding of how antimicrobial resistance proliferates in the bacterial domain and shed light on the crucial step of initial resistance gene mobilization in particular. Here, we combine information from publicly available long- and short-read environmental metagenomes as well as whole-genome sequences to identify the original environmental hosts of dfrB, a family of genes conferring resistance to trimethoprim. Although this gene family stands in the shadow of the more widespread, structurally different dfrA, it has recently gained attention through the discovery of several new members. Based on the genetic context of dfrB observed in long-read metagenomes, we predicted bacteria of the order Burkholderiales to function as original environmental hosts of the predominant gene variants in both soil and freshwater. The predictions were independently confirmed by whole-genome datasets and statistical correlations between dfrB abundance and taxonomic composition of environmental bacterial communities. Our study suggests that Burkholderiales in general and the family Comamonadaceae in particular represent environmental origins of dfrB genes, some of which now contribute to the acquired resistome of facultative pathogens. We propose that our workflow centered on long-read environmental metagenomes allows for the identification of the original hosts of further clinically relevant antibiotic resistance genes. | 2024 | 39658215 |
| 4665 | 19 | 0.9984 | 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 |