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Journal ArticleDOI

In Silico Detection and Typing of Plasmids using PlasmidFinder and Plasmid Multilocus Sequence Typing

TL;DR: Two easy-to-use Web tools for in silico detection and characterization of whole-genome sequence (WGS) and whole-plasmid sequence data from members of the family Enterobacteriaceae are designed and developed.
Abstract: In the work presented here, we designed and developed two easy-to-use Web tools for in silico detection and characterization of whole-genome sequence (WGS) and whole-plasmid sequence data from members of the family Enterobacteriaceae. These tools will facilitate bacterial typing based on draft genomes of multidrug-resistant Enterobacteriaceae species by the rapid detection of known plasmid types. Replicon sequences from 559 fully sequenced plasmids associated with the family Enterobacteriaceae in the NCBI nucleotide database were collected to build a consensus database for integration into a Web tool called PlasmidFinder that can be used for replicon sequence analysis of raw, contig group, or completely assembled and closed plasmid sequencing data. The PlasmidFinder database currently consists of 116 replicon sequences that match with at least at 80% nucleotide identity all replicon sequences identified in the 559 fully sequenced plasmids. For plasmid multilocus sequence typing (pMLST) analysis, a database that is updated weekly was generated from www.pubmlst.org and integrated into a Web tool called pMLST. Both databases were evaluated using draft genomes from a collection of Salmonella enterica serovar Typhimurium isolates. PlasmidFinder identified a total of 103 replicons and between zero and five different plasmid replicons within each of 49 S . Typhimurium draft genomes tested. The pMLST Web tool was able to subtype genomic sequencing data of plasmids, revealing both known plasmid sequence types (STs) and new alleles and ST variants. In conclusion, testing of the two Web tools using both fully assembled plasmid sequences and WGS-generated draft genomes showed them to be able to detect a broad variety of plasmids that are often associated with antimicrobial resistance in clinically relevant bacterial pathogens.

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Citations
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Book ChapterDOI
TL;DR: The PlasmidFinder database currently includes 133 unique plasmid replicon sequences and has been continuously updated to include novel replicons detected in more recently sequenced plasmids associated with the family Enterobacteriaceae.
Abstract: PlasmidFinder and in silico plasmid multiLocus sequence typing (pMLST) are two easy-to-use web tools for detection and characterization of plasmid sequences in whole-genome sequencing (WGS) data from Enterobacteriaceae. These tools have been adopted worldwide and facilitate plasmid detection and typing based on draft genomes of multi-drug-resistant Enterobacteriaceae. The PlasmidFinder database currently includes 133 unique plasmid replicon sequences. It was built starting with 126 sequences devised on fully sequenced plasmids available at the NCBI nucleotide database in 2014 and has been continuously updated to include novel replicons detected in more recently sequenced plasmids associated with the family Enterobacteriaceae. PlasmidFinder is usable for replicon sequence analysis of raw as well as assembled sequencing data. For pMLST analysis, a weekly updated database was generated from www.pubmlst.org and integrated into a web tool called in silico pMLST.

209 citations

Journal ArticleDOI
18 Aug 2017
TL;DR: This study shows that it is possible to automatically predict small plasmids, and benchmark algorithms for automated plasmid sequence reconstruction from short-read sequencing data had the highest precision, but was restricted by the contents of its database and the contig length obtained from de novo assembly.
Abstract: To benchmark algorithms for automated plasmid sequence reconstruction from short-read sequencing data, we selected 42 publicly available complete bacterial genome sequences spanning 12 genera, containing 148 plasmids. We predicted plasmids from short-read data with four programs (PlasmidSPAdes, Recycler, cBar and PlasmidFinder) and compared the outcome to the reference sequences. PlasmidSPAdes reconstructs plasmids based on coverage differences in the assembly graph. It reconstructed most of the reference plasmids (recall=0.82), but approximately a quarter of the predicted plasmid contigs were false positives (precision=0.75). PlasmidSPAdes merged 84 % of the predictions from genomes with multiple plasmids into a single bin. Recycler searches the assembly graph for sub-graphs corresponding to circular sequences and correctly predicted small plasmids, but failed with long plasmids (recall=0.12, precision=0.30). cBar, which applies pentamer frequency analysis to detect plasmid-derived contigs, showed a recall and precision of 0.76 and 0.62, respectively. However, cBar categorizes contigs as plasmid-derived and does not bin the different plasmids. PlasmidFinder, which searches for replicons, had the highest precision (1.0), but was restricted by the contents of its database and the contig length obtained from de novo assembly (recall=0.36). PlasmidSPAdes and Recycler detected putative small plasmids ( 50 kbp) containing repeated sequences remains challenging and limits the high-throughput analysis of plasmids from short-read whole-genome sequencing data.

200 citations

Journal ArticleDOI
TL;DR: It is asserted that further large-scale comparative and functional genomics studies are urgently needed to better understand the biology of this clinically important bacterium.

199 citations

Journal ArticleDOI
TL;DR: Findings point towards promiscuous spread of the mcr-1 gene by efficient horizontal gene transfer dominated by a limited number of plasmid incompatibility types.
Abstract: To understand the dynamics behind the worldwide spread of the mcr-1 gene, we determined the population structure of Escherichia coli and of mobile genetic elements (MGEs) carrying the mcr-1 gene. After a systematic review of the literature we included 65 E. coli whole genome sequences (WGS), adding 6 recently sequenced travel related isolates, and 312 MLST profiles. We included 219 MGEs described in 7 Enterobacteriaceae species isolated from human, animal and environmental samples. Despite a high overall diversity, 2 lineages were observed in the E. coli population that may function as reservoirs of the mcr-1 gene, the largest of which was linked to ST10, a sequence type known for its ubiquity in human faecal samples and in food samples. No genotypic clustering by geographical origin or isolation source was observed. Amongst a total of 13 plasmid incompatibility types, the IncI2, IncX4 and IncHI2 plasmids accounted for more than 90% of MGEs carrying the mcr-1 gene. We observed significant geographical clustering with regional spread of IncHI2 plasmids in Europe and IncI2 in Asia. These findings point towards promiscuous spread of the mcr-1 gene by efficient horizontal gene transfer dominated by a limited number of plasmid incompatibility types.

194 citations

References
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Journal ArticleDOI
TL;DR: A web server providing a convenient way of identifying acquired antimicrobial resistance genes in completely sequenced isolates was created, and the method was evaluated on WGS chromosomes and plasmids of 30 isolates.
Abstract: Objectives Identification of antimicrobial resistance genes is important for understanding the underlying mechanisms and the epidemiology of antimicrobial resistance. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available in routine diagnostic laboratories and is anticipated to substitute traditional methods for resistance gene identification. Thus, the current challenge is to extract the relevant information from the large amount of generated data.

3,956 citations


"In Silico Detection and Typing of P..." refers methods in this paper

  • ...To extract the relevant information from the large amount of data generated, a Web-based tool, ResFinder, for the identification of acquired or intrinsically present antimicrobial resistance genes in whole-genome data was recently developed (15)....

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Journal ArticleDOI
TL;DR: NCBI’s Conserved Domain Database (CDD) is a resource for the annotation of protein sequences with the location of conserved domain footprints, and functional sites inferred from these footprints.
Abstract: NCBI's Conserved Domain Database (CDD) is a resource for the annotation of protein sequences with the location of conserved domain footprints, and functional sites inferred from these footprints. CDD includes manually curated domain models that make use of protein 3D structure to refine domain models and provide insights into sequence/structure/function relationships. Manually curated models are organized hierarchically if they describe domain families that are clearly related by common descent. As CDD also imports domain family models from a variety of external sources, it is a partially redundant collection. To simplify protein annotation, redundant models and models describing homologous families are clustered into superfamilies. By default, domain footprints are annotated with the corresponding superfamily designation, on top of which specific annotation may indicate high-confidence assignment of family membership. Pre-computed domain annotation is available for proteins in the Entrez/Protein dataset, and a novel interface, Batch CD-Search, allows the computation and download of annotation for large sets of protein queries. CDD can be accessed via http://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml.

2,934 citations


"In Silico Detection and Typing of P..." refers background in this paper

  • ...In particular, the replicase proteins showing the pfam02387 or pfam01051 conserved domains were assigned to the FII and FIB groups, respectively (31)....

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Journal ArticleDOI
TL;DR: Results indicated that the inc/rep PCR method demonstrates high specificity and sensitivity in detecting replicons on reference plasmids and also revealed the presence of recurrent and common plasmid in epidemiologically unrelated Salmonella isolates of different serotypes.

2,163 citations


"In Silico Detection and Typing of P..." refers methods in this paper

  • ...A collection of 24 previously characterized and fully FIG 1 Numbers of fully sequenced plasmids (y axis) classified into incompatibility groups occurring in the different bacterial species of the Enterobacteriaceae family....

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  • ...Since 2005, a PCR-based replicon typing (PBRT) scheme has been available that targets in multiplex PCRs the replicons of the major plasmid families occurring in members of the family Enterobacteriaceae (2)....

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  • ...Here, we present two free, easy-to-use Web tools, PlasmidFinder and pMLST, to analyze and classify plasmids from bacterial species of the family Enterobacteriaceae....

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  • ...Here, we describe the design of two new easy-to-use Web tools useful for the rapid identification of plasmids in Enterobacteriaceae species that are of interest for epidemiological and clinical microbiology investigations of the plasmid-associated spread of antimicrobial resistance....

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  • ...This method was initially developed to detect the replicons of plasmids belonging to the 18 major incompatibility (Inc) groups of Enterobacteriaceae species (3)....

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Journal ArticleDOI
TL;DR: The Bacterial Isolate Genome Sequence Database (BIGSDB) represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach.
Abstract: The opportunities for bacterial population genomics that are being realised by the application of parallel nucleotide sequencing require novel bioinformatics platforms These must be capable of the storage, retrieval, and analysis of linked phenotypic and genotypic information in an accessible, scalable and computationally efficient manner The Bacterial Isolate Genome Sequence Database (BIGSDB) is a scalable, open source, web-accessible database system that meets these needs, enabling phenotype and sequence data, which can range from a single sequence read to whole genome data, to be efficiently linked for a limitless number of bacterial specimens The system builds on the widely used mlstdbNet software, developed for the storage and distribution of multilocus sequence typing (MLST) data, and incorporates the capacity to define and identify any number of loci and genetic variants at those loci within the stored nucleotide sequences These loci can be further organised into 'schemes' for isolate characterisation or for evolutionary or functional analyses Isolates and loci can be indexed by multiple names and any number of alternative schemes can be accommodated, enabling cross-referencing of different studies and approaches LIMS functionality of the software enables linkage to and organisation of laboratory samples The data are easily linked to external databases and fine-grained authentication of access permits multiple users to participate in community annotation by setting up or contributing to different schemes within the database Some of the applications of BIGSDB are illustrated with the genera Neisseria and Streptococcus The BIGSDB source code and documentation are available at http://pubmlstorg/software/database/bigsdb/ Genomic data can be used to characterise bacterial isolates in many different ways but it can also be efficiently exploited for evolutionary or functional studies BIGSDB represents a freely available resource that will assist the broader community in the elucidation of the structure and function of bacteria by means of a population genomics approach

1,943 citations

Journal ArticleDOI
TL;DR: A Web-based method for MLST of 66 bacterial species based on whole-genome sequencing data that enables investigators to determine the sequence types of their isolates on the basis of WGS data.
Abstract: Accurate strain identification is essential for anyone working with bacteria. For many species, multilocus sequence typing (MLST) is considered the “gold standard” of typing, but it is traditionally performed in an expensive and time-consuming manner. As the costs of whole-genome sequencing (WGS) continue to decline, it becomes increasingly available to scientists and routine diagnostic laboratories. Currently, the cost is below that of traditional MLST. The new challenges will be how to extract the relevant information from the large amount of data so as to allow for comparison over time and between laboratories. Ideally, this information should also allow for comparison to historical data. We developed a Web-based method for MLST of 66 bacterial species based on WGS data. As input, the method uses short sequence reads from four sequencing platforms or preassembled genomes. Updates from the MLST databases are downloaded monthly, and the best-matching MLST alleles of the specified MLST scheme are found using a BLAST-based ranking method. The sequence type is then determined by the combination of alleles identified. The method was tested on preassembled genomes from 336 isolates covering 56 MLST schemes, on short sequence reads from 387 isolates covering 10 schemes, and on a small test set of short sequence reads from 29 isolates for which the sequence type had been determined by traditional methods. The method presented here enables investigators to determine the sequence types of their isolates on the basis of WGS data. This method is publicly available at www.cbs.dtu.dk/services/MLST.

1,620 citations


"In Silico Detection and Typing of P..." refers methods in this paper

  • ...If raw sequence reads are uploaded, they are first assembled (after the sequencing platform is given by the user) as described previously (16)....

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