# | Rank | Similarity | Title + Abs. | Year | PMID |
|---|---|---|---|---|---|
| 0 | 1 | 2 | 3 | 4 | 5 |
| 3770 | 0 | 0.9149 | Detection of mobile genetic elements associated with antibiotic resistance in Salmonella enterica using a newly developed web tool: MobileElementFinder. OBJECTIVES: Antimicrobial resistance (AMR) in clinically relevant bacteria is a growing threat to public health globally. In these bacteria, antimicrobial resistance genes are often associated with mobile genetic elements (MGEs), which promote their mobility, enabling them to rapidly spread throughout a bacterial community. METHODS: The tool MobileElementFinder was developed to enable rapid detection of MGEs and their genetic context in assembled sequence data. MGEs are detected based on sequence similarity to a database of 4452 known elements augmented with annotation of resistance genes, virulence factors and detection of plasmids. RESULTS: MobileElementFinder was applied to analyse the mobilome of 1725 sequenced Salmonella enterica isolates of animal origin from Denmark, Germany and the USA. We found that the MGEs were seemingly conserved according to multilocus ST and not restricted to either the host or the country of origin. Moreover, we identified putative translocatable units for specific aminoglycoside, sulphonamide and tetracycline genes. Several putative composite transposons were predicted that could mobilize, among others, AMR, metal resistance and phosphodiesterase genes associated with macrophage survivability. This is, to our knowledge, the first time the phosphodiesterase-like pdeL has been found to be potentially mobilized into S. enterica. CONCLUSIONS: MobileElementFinder is a powerful tool to study the epidemiology of MGEs in a large number of genome sequences and to determine the potential for genomic plasticity of bacteria. This web service provides a convenient method of detecting MGEs in assembled sequence data. MobileElementFinder can be accessed at https://cge.cbs.dtu.dk/services/MobileElementFinder/. | 2021 | 33009809 |
| 4446 | 1 | 0.9089 | Gut Microbiome of an 11th Century A.D. Pre-Columbian Andean Mummy. The process of natural mummification is a rare and unique process from which little is known about the resulting microbial community structure. In the present study, we characterized the microbiome of paleofeces, and ascending, transverse and descending colon of an 11th century A.D. pre-Columbian Andean mummy by 16S rRNA gene high-throughput sequencing and metagenomics. Firmicutes were the most abundant bacterial group, with Clostridium spp. comprising up to 96.2% of the mummified gut, while Turicibacter spp. represented 89.2% of the bacteria identified in the paleofeces. Microbiome profile of the paleofeces was unique when compared to previously characterized coprolites that did not undergo natural mummification. We identified DNA sequences homologous to Clostridium botulinum, Trypanosoma cruzi and human papillomaviruses (HPVs). Unexpectedly, putative antibiotic-resistance genes including beta-lactamases, penicillin-binding proteins, resistance to fosfomycin, chloramphenicol, aminoglycosides, macrolides, sulfa, quinolones, tetracycline and vancomycin, and multi-drug transporters, were also identified. The presence of putative antibiotic-resistance genes suggests that resistance may not necessarily be associated with a selective pressure of antibiotics or contact with European cultures. Identification of pathogens and antibiotic-resistance genes in ancient human specimens will aid in the understanding of the evolution of pathogens as a way to treat and prevent diseases caused by bacteria, microbial eukaryotes and viruses. | 2015 | 26422376 |
| 9079 | 2 | 0.9086 | Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes. Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth. | 2019 | 31749830 |
| 5127 | 3 | 0.9080 | ResFinderFG v2.0: a database of antibiotic resistance genes obtained by functional metagenomics. Metagenomics can be used to monitor the spread of antibiotic resistance genes (ARGs). ARGs found in databases such as ResFinder and CARD primarily originate from culturable and pathogenic bacteria, while ARGs from non-culturable and non-pathogenic bacteria remain understudied. Functional metagenomics is based on phenotypic gene selection and can identify ARGs from non-culturable bacteria with a potentially low identity shared with known ARGs. In 2016, the ResFinderFG v1.0 database was created to collect ARGs from functional metagenomics studies. Here, we present the second version of the database, ResFinderFG v2.0, which is available on the Center of Genomic Epidemiology web server (https://cge.food.dtu.dk/services/ResFinderFG/). It comprises 3913 ARGs identified by functional metagenomics from 50 carefully curated datasets. We assessed its potential to detect ARGs in comparison to other popular databases in gut, soil and water (marine + freshwater) Global Microbial Gene Catalogues (https://gmgc.embl.de). ResFinderFG v2.0 allowed for the detection of ARGs that were not detected using other databases. These included ARGs conferring resistance to beta-lactams, cycline, phenicol, glycopeptide/cycloserine and trimethoprim/sulfonamide. Thus, ResFinderFG v2.0 can be used to identify ARGs differing from those found in conventional databases and therefore improve the description of resistomes. | 2023 | 37207327 |
| 5187 | 4 | 0.9072 | Recovery of 52 bacterial genomes from the fecal microbiome of the domestic cat (Felis catus) using Hi-C proximity ligation and shotgun metagenomics. We used Hi-C proximity ligation with shotgun sequencing to retrieve metagenome-assembled genomes (MAGs) from the fecal microbiomes of two domestic cats (Felis catus). The genomes were assessed for completeness and contamination, classified taxonomically, and annotated for putative antimicrobial resistance (AMR) genes. | 2023 | 37695121 |
| 9082 | 5 | 0.9071 | GeneMates: an R package for detecting horizontal gene co-transfer between bacteria using gene-gene associations controlled for population structure. BACKGROUND: Horizontal gene transfer contributes to bacterial evolution through mobilising genes across various taxonomical boundaries. It is frequently mediated by mobile genetic elements (MGEs), which may capture, maintain, and rearrange mobile genes and co-mobilise them between bacteria, causing horizontal gene co-transfer (HGcoT). This physical linkage between mobile genes poses a great threat to public health as it facilitates dissemination and co-selection of clinically important genes amongst bacteria. Although rapid accumulation of bacterial whole-genome sequencing data since the 2000s enables study of HGcoT at the population level, results based on genetic co-occurrence counts and simple association tests are usually confounded by bacterial population structure when sampled bacteria belong to the same species, leading to spurious conclusions. RESULTS: We have developed a network approach to explore WGS data for evidence of intraspecies HGcoT and have implemented it in R package GeneMates ( github.com/wanyuac/GeneMates ). The package takes as input an allelic presence-absence matrix of interested genes and a matrix of core-genome single-nucleotide polymorphisms, performs association tests with linear mixed models controlled for population structure, produces a network of significantly associated alleles, and identifies clusters within the network as plausible co-transferred alleles. GeneMates users may choose to score consistency of allelic physical distances measured in genome assemblies using a novel approach we have developed and overlay scores to the network for further evidence of HGcoT. Validation studies of GeneMates on known acquired antimicrobial resistance genes in Escherichia coli and Salmonella Typhimurium show advantages of our network approach over simple association analysis: (1) distinguishing between allelic co-occurrence driven by HGcoT and that driven by clonal reproduction, (2) evaluating effects of population structure on allelic co-occurrence, and (3) direct links between allele clusters in the network and MGEs when physical distances are incorporated. CONCLUSION: GeneMates offers an effective approach to detection of intraspecies HGcoT using WGS data. | 2020 | 32972363 |
| 7674 | 6 | 0.9071 | Insights into gut microbiomes in stem cell transplantation by comprehensive shotgun long-read sequencing. The gut microbiome is a diverse ecosystem, dominated by bacteria; however, fungi, phages/viruses, archaea, and protozoa are also important members of the gut microbiota. Exploration of taxonomic compositions beyond bacteria as well as an understanding of the interaction between the bacteriome with the other members is limited using 16S rDNA sequencing. Here, we developed a pipeline enabling the simultaneous interrogation of the gut microbiome (bacteriome, mycobiome, archaeome, eukaryome, DNA virome) and of antibiotic resistance genes based on optimized long-read shotgun metagenomics protocols and custom bioinformatics. Using our pipeline we investigated the longitudinal composition of the gut microbiome in an exploratory clinical study in patients undergoing allogeneic hematopoietic stem cell transplantation (alloHSCT; n = 31). Pre-transplantation microbiomes exhibited a 3-cluster structure, characterized by Bacteroides spp. /Phocaeicola spp., mixed composition and Enterococcus abundances. We revealed substantial inter-individual and temporal variabilities of microbial domain compositions, human DNA, and antibiotic resistance genes during the course of alloHSCT. Interestingly, viruses and fungi accounted for substantial proportions of microbiome content in individual samples. In the course of HSCT, bacterial strains were stable or newly acquired. Our results demonstrate the disruptive potential of alloHSCTon the gut microbiome and pave the way for future comprehensive microbiome studies based on long-read metagenomics. | 2024 | 38374282 |
| 346 | 7 | 0.9070 | Horizontal transfer of CS1 pilin genes of enterotoxigenic Escherichia coli. CS1 is one of a limited number of serologically distinct pili found in enterotoxigenic Escherichia coli (ETEC) strains associated with disease in people. The genes for the CS1 pilus are on a large plasmid, pCoo. We show that pCoo is not self-transmissible, although our sequence determination for part of pCoo shows regions almost identical to those in the conjugative drug resistance plasmid R64. When we introduced R64 into a strain containing pCoo, we found that pCoo was transferred to a recipient strain in mating. Most of the transconjugant pCoo plasmids result from recombination with R64, leading to acquisition of functional copies of all of the R64 transfer genes. Temporary coresidence of the drug resistance plasmid R64 with pCoo leads to a permanent change in pCoo so that it is now self-transmissible. We conclude that when R64-like plasmids are transmitted to an ETEC strain containing pCoo, their recombination may allow for spread of the pCoo plasmid to other enteric bacteria. | 2004 | 15126486 |
| 9986 | 8 | 0.9069 | Identification and characterization of thousands of bacteriophage satellites across bacteria. Bacteriophage-bacteria interactions are affected by phage satellites, elements that exploit phages for transfer between bacteria. Satellites can encode defense systems, antibiotic resistance genes, and virulence factors, but their number and diversity are unknown. We developed SatelliteFinder to identify satellites in bacterial genomes, detecting the four best described families: P4-like, phage inducible chromosomal islands (PICI), capsid-forming PICI, and PICI-like elements (PLE). We vastly expanded the number of described elements to ∼5000, finding bacterial genomes with up to three different families of satellites. Most satellites were found in Proteobacteria and Firmicutes, but some are in novel taxa such as Actinobacteria. We characterized the gene repertoires of satellites, which are variable in size and composition, and their genomic organization, which is very conserved. Phylogenies of core genes in PICI and cfPICI indicate independent evolution of their hijacking modules. There are few other homologous core genes between other families of satellites, and even fewer homologous to phages. Hence, phage satellites are ancient, diverse, and probably evolved multiple times independently. Given the many bacteria infected by phages that still lack known satellites, and the recent proposals for novel families, we speculate that we are at the beginning of the discovery of massive numbers and types of satellites. | 2023 | 36869669 |
| 9074 | 9 | 0.9069 | BacAnt: A Combination Annotation Server for Bacterial DNA Sequences to Identify Antibiotic Resistance Genes, Integrons, and Transposable Elements. Whole genome sequencing (WGS) of bacteria has become a routine method in diagnostic laboratories. One of the clinically most useful advantages of WGS is the ability to predict antimicrobial resistance genes (ARGs) and mobile genetic elements (MGEs) in bacterial sequences. This allows comprehensive investigations of such genetic features but can also be used for epidemiological studies. A plethora of software programs have been developed for the detailed annotation of bacterial DNA sequences, such as rapid annotation using subsystem technology (RAST), Resfinder, ISfinder, INTEGRALL and The Transposon Registry. Unfortunately, to this day, a reliable annotation tool of the combination of ARGs and MGEs is not available, and the generation of genbank files requires much manual input. Here, we present a new webserver which allows the annotation of ARGs, integrons and transposable elements at the same time. The pipeline generates genbank files automatically, which are compatible with Easyfig for comparative genomic analysis. Our BacAnt code and standalone software package are available at https://github.com/xthua/bacant with an accompanying web application at http://bacant.net. | 2021 | 34367079 |
| 5191 | 10 | 0.9068 | Draft genome sequences data of Mammaliicoccus lentus isolated from horse farm soil. Mammallicoccus lentus is a member of the commensal microflora of the Staphylococcaceae family, which colonizes the skin of several species of farm animals, including poultry and dairy animals (Huber et al., 2011; Zhang et al., 2009). The study of the members of the Staphylococcaceae family, such as the Mammaliicoccus genus, isolated from various sources is of great importance for agriculture and public health as contributes to the accumulation of knowledge and understanding of the mechanisms of antibiotic resistance gene transmission among bacterial pathogens. This thesis is supported by recent studies showing that some members of the Mammallicoccus genus serve as a reservoir of virulence and antibiotic resistance genes and may also be a source of horizontal gene transfer (Saraiva et al., 2021). Here, we present a draft genome sequence of Mammallicoccus lentus strain PVZ.22 from a horse farm soil sample. The sequencing was performed on the Illumina MiSeq platform. The genome was assembled using the Geneious software package. The genome contains 2,802,282 bp with a total of 2805 genes, 8 perfect and 12 strict AMR genes and 58 tRNAs genes. | 2023 | 38075610 |
| 9083 | 11 | 0.9067 | ARGNet: using deep neural networks for robust identification and classification of antibiotic resistance genes from sequences. BACKGROUND: Emergence of antibiotic resistance in bacteria is an important threat to global health. Antibiotic resistance genes (ARGs) are some of the key components to define bacterial resistance and their spread in different environments. Identification of ARGs, particularly from high-throughput sequencing data of the specimens, is the state-of-the-art method for comprehensively monitoring their spread and evolution. Current computational methods to identify ARGs mainly rely on alignment-based sequence similarities with known ARGs. Such approaches are limited by choice of reference databases and may potentially miss novel ARGs. The similarity thresholds are usually simple and could not accommodate variations across different gene families and regions. It is also difficult to scale up when sequence data are increasing. RESULTS: In this study, we developed ARGNet, a deep neural network that incorporates an unsupervised learning autoencoder model to identify ARGs and a multiclass classification convolutional neural network to classify ARGs that do not depend on sequence alignment. This approach enables a more efficient discovery of both known and novel ARGs. ARGNet accepts both amino acid and nucleotide sequences of variable lengths, from partial (30-50 aa; 100-150 nt) sequences to full-length protein or genes, allowing its application in both target sequencing and metagenomic sequencing. Our performance evaluation showed that ARGNet outperformed other deep learning models including DeepARG and HMD-ARG in most of the application scenarios especially quasi-negative test and the analysis of prediction consistency with phylogenetic tree. ARGNet has a reduced inference runtime by up to 57% relative to DeepARG. CONCLUSIONS: ARGNet is flexible, efficient, and accurate at predicting a broad range of ARGs from the sequencing data. ARGNet is freely available at https://github.com/id-bioinfo/ARGNet , with an online service provided at https://ARGNet.hku.hk . Video Abstract. | 2024 | 38725076 |
| 5188 | 12 | 0.9067 | Zoonotic bacterial and parasitic intestinal pathogens in foxes, raccoons and other predators from eastern Germany. In this study, we investigated faecal specimens from legally hunted and road-killed red foxes, raccoons, raccoon dogs, badgers and martens in Germany for parasites and selected zoonotic bacteria. We found that Baylisascaris procyonis, a zoonotic parasite of raccoons, had spread to northeastern Germany, an area previously presumed to be free of this parasite. We detected various pathogenic bacterial species from the genera Listeria, Clostridium (including baratii), Yersinia and Salmonella, which were analysed using whole-genome sequencing. One isolate of Yersinia enterocolitica contained a virulence plasmid. The Salmonella Cholerasuis isolate encoded an aminoglycoside resistance gene and a parC point mutation, conferring resistance to ciprofloxacin. We also found tetracycline resistance genes in Paeniclostridium sordellii and Clostridium baratii. Phylogenetic analyses revealed that the isolates were polyclonal, indicating the absence of specific wildlife-adapted clones. Predators, which scavenge from various sources including human settlements, acquire and spread zoonotic pathogens. Therefore, their role should not be overlooked in the One Health context. | 2024 | 38747071 |
| 8714 | 13 | 0.9066 | Tales from the tomb: the microbial ecology of exposed rock surfaces. Although a broad diversity of eukaryotic and bacterial taxa reside on rock surfaces where they can influence the weathering of rocks and minerals, these communities and their contributions to mineral weathering remain poorly resolved. To build a more comprehensive understanding of the diversity, ecology and potential functional attributes of microbial communities living on rock, we sampled 149 tombstones across three continents and analysed their bacterial and eukaryotic communities via marker gene and shotgun metagenomic sequencing. We found that geographic location and climate were important factors structuring the composition of these communities. Moreover, the tombstone-associated microbial communities varied as a function of rock type, with granite and limestone tombstones from the same cemeteries harbouring taxonomically distinct microbial communities. The granite and limestone-associated communities also had distinct functional attributes, with granite-associated bacteria having more genes linked to acid tolerance and chemotaxis, while bacteria on limestone were more likely to be lichen associated and have genes involved in photosynthesis and radiation resistance. Together these results indicate that rock-dwelling microbes exhibit adaptations to survive the stresses of the rock surface, differ based on location, climate and rock type, and seem pre-disposed to different ecological strategies (symbiotic versus free-living lifestyles) depending on the rock type. | 2018 | 29235707 |
| 6383 | 14 | 0.9065 | Metagenomic analysis of microbiological risk in bioaerosols during biowaste valorization using Musca domestica. Bioconversion using insects has gradually become a promising technology for biowaste management and protein production. However, knowledge about microbiological risk of insect related bioaerosols is sparse and conventional methods failed to provide higher resolved information of environmental microbe. In this study, a metagenomic analysis including microorganisms, antibiotic resistance genes (ARGs), virulence factor genes (VFGs), mobile gene elements (MGEs), and endotoxin distribution in bioaerosols during biowaste conversion via Musca domestica revealed that bioaerosols in Fly rearing room possess the highest ARGs abundances and MGEs diversity. Through a metagenome-assembled genomes (MAGs)-based pipeline, compelling evidence of ARGs/VFGs host assignment and ARG-VFG co-occurrence pattern were provided from metagenomic perspective. Bioaerosols in Bioconversion and Maggot separation zone were identified to own high density of MAGs carrying both ARGs and VFGs. Bacteria in Proteobacteria, Actinobacteriota, and Firmicutes phyla were predominate hosts of ARGs and VFGs. Multidrug-Motility, Multidrug-Adherence, and Beta lactam-Motility pairs were the most common ARG-VFG co-occurrence pattern in this study. Results obtained are of great significance for microbiological risk assessment during housefly biowaste conversion process. | 2023 | 36681377 |
| 4539 | 15 | 0.9062 | Dataset of 569 metagenome-assembled genomes from the caeca of multiple chicken breeds from commercial and backyard farming setups of Pakistan. This article focuses the recovery of prokaryotic organisms including bacteria and archaea from 9 different groups of chicken raised in different farm setups in Pakistan. The groups comprise of three different breeds (Broilers, White Layers, and Black Australorp) of chicken raised in different farming setups that include antibiotic-free control, commercial (open and controlled shed), and backyard farms. We have recovered 569 Metagenomics-Assembled Genomes (MAGs) with a completeness of ≥50 % and contamination of ≤10 %. For each MAG, functional annotations were obtained that include KEGG modules, carbohydrate active enzymes (CAZymes), peptidases, geochemical cycles, antibiotic resistance genes, stress genes, and virulence genes. Furthermore, two different sets of Single Copy Genes (SCGs) were used to construct the phylogenetic trees. Based on the reconstructed phylogeny, phylogenetic gain of each MAG is calculated to give an account of novelty. | 2024 | 38882194 |
| 9066 | 16 | 0.9060 | VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria. VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile. | 2018 | 28077405 |
| 6088 | 17 | 0.9060 | Complete Genome of Achromobacter xylosoxidans, a Nitrogen-Fixing Bacteria from the Rhizosphere of Cowpea (Vigna unguiculata [L.] Walp) Tolerant to Cucumber Mosaic Virus Infection. Achromobacter xylosoxidans is one of the nitrogen-fixing bacteria associated with cowpea rhizosphere across Africa. Although its role in improving soil fertility and inducing systemic resistance in plants against pathogens has been documented, there is limited information on its complete genomic characteristics from cowpea roots. Here, we report the complete genome sequence of A. xylosoxidans strain DDA01 isolated from the topsoil of a field where cowpea plants tolerant to cucumber mosaic virus (CMV) were grown in Ibadan, Nigeria. The genome of DDA01 was sequenced via Illumina MiSeq and contained 6,930,067 nucleotides with 67.55% G + C content, 73 RNAs, 59 tRNAs, and 6421 protein-coding genes, including those associated with nitrogen fixation, phosphate solubilization, Indole3-acetic acid production, and siderophore activity. Eleven genetic clusters for secondary metabolites, including alcaligin, were identified. The potential of DDA01 as a plant growth-promoting bacteria with genetic capabilities to enhance soil fertility for resilience against CMV infection in cowpea is discussed. To our knowledge, this is the first complete genome of diazotrophic bacteria obtained from cowpea rhizosphere in sub-Saharan Africa, with potential implications for improved soil fertility, plant disease resistance, and food security. | 2024 | 39278894 |
| 3771 | 18 | 0.9060 | RFPlasmid: predicting plasmid sequences from short-read assembly data using machine learning. Antimicrobial-resistance (AMR) genes in bacteria are often carried on plasmids and these plasmids can transfer AMR genes between bacteria. For molecular epidemiology purposes and risk assessment, it is important to know whether the genes are located on highly transferable plasmids or in the more stable chromosomes. However, draft whole-genome sequences are fragmented, making it difficult to discriminate plasmid and chromosomal contigs. Current methods that predict plasmid sequences from draft genome sequences rely on single features, like k-mer composition, circularity of the DNA molecule, copy number or sequence identity to plasmid replication genes, all of which have their drawbacks, especially when faced with large single-copy plasmids, which often carry resistance genes. With our newly developed prediction tool RFPlasmid, we use a combination of multiple features, including k-mer composition and databases with plasmid and chromosomal marker proteins, to predict whether the likely source of a contig is plasmid or chromosomal. The tool RFPlasmid supports models for 17 different bacterial taxa, including Campylobacter, Escherichia coli and Salmonella, and has a taxon agnostic model for metagenomic assemblies or unsupported organisms. RFPlasmid is available both as a standalone tool and via a web interface. | 2021 | 34846288 |
| 5125 | 19 | 0.9059 | Do we still need Illumina sequencing data? Evaluating Oxford Nanopore Technologies R10.4.1 flow cells and the Rapid v14 library prep kit for Gram negative bacteria whole genome assemblies. The best whole genome assemblies are currently built from a combination of highly accurate short-read sequencing data and long-read sequencing data that can bridge repetitive and problematic regions. Oxford Nanopore Technologies (ONT) produce long-read sequencing platforms and they are continually improving their technology to obtain higher quality read data that is approaching the quality obtained from short-read platforms such as Illumina. As these innovations continue, we evaluated how much ONT read coverage produced by the Rapid Barcoding Kit v14 (SQK-RBK114) is necessary to generate high-quality hybrid and long-read-only genome assemblies for a panel of carbapenemase-producing Enterobacterales bacterial isolates. We found that 30× long-read coverage is sufficient if Illumina data are available, and that more (at least 100× long-read coverage is recommended for long-read-only assemblies. Illumina polishing is still improving single nucleotide variants (SNVs) and INDELs in long-read-only assemblies. We also examined if antimicrobial resistance genes could be accurately identified in long-read-only data, and found that Flye assemblies regardless of ONT coverage detected >96% of resistance genes at 100% identity and length. Overall, the Rapid Barcoding Kit v14 and long-read-only assemblies can be an optimal sequencing strategy (i.e., plasmid characterization and AMR detection) but finer-scale analyses (i.e., SNV) still benefit from short-read data. | 2024 | 38354391 |