Dataset Information

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

ABSTRACT: BACKGROUND:Multi-locus sequence typing (MLST) is a standard typing technique used to associate a sequence type (ST) to a bacterial isolate. When the output of whole genome sequencing (WGS) of a sample is available the ST can be assigned directly processing the read-set. Current approaches employ reads mapping (SRST2) against the MLST loci, k-mer distribution (stringMLST), selective assembly (GRAbB) or whole genome assembly (BIGSdb) followed by BLASTn sequence query. Here we present STRAIN (ST Reduced Assembly IdentificatioN), an R package that implements a hybrid strategy between assembly and mapping of the reads to assign the ST to an isolate starting from its read-sets. RESULTS:Analysis of 540 publicly accessible Illumina read sets showed STRAIN to be more accurate at correct allele assignment and new alleles identification compared to SRTS2, stringMLST and GRAbB. STRAIN assigned correctly 3666 out of 3780 alleles (capability to identify correct alleles 97%) and, when presented with samples containing new alleles, identified them in 3730 out of 3780 STs (capability to identify new alleles 98.7%) of the cases. On the same dataset the other tested tools achieved lower capability to identify correct alleles (from 28.5 to 96.9%) and lower capability to identify new alleles (from 1.1 to 97.1%). CONCLUSIONS:STRAIN is a new accurate method to assign the alleles and ST to an isolate by processing the raw reads output of WGS. STRAIN is also able to retrieve new allele sequences if present. Capability to identify correct and new STs/alleles, evaluated on a benchmark dataset, are higher than other existing methods. STRAIN is designed for single allele typing as well as MLST. Its implementation in R makes allele and ST assignment simple, direct and prompt to be integrated in wider pipeline of downstream bioinformatics analyses.

SUBMITTER: Dalsass M

PROVIDER: S-EPMC6873635 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

Dalsass Mattia M Bodini Margherita M Lambert Christophe C Mortier Marie-Cécile MC Romanelli Marco M Medini Duccio D Muzzi Alessandro A Brozzi Alessandro A

BMC bioinformatics 20191122 Suppl 9

<h4>Background</h4>Multi-locus sequence typing (MLST) is a standard typing technique used to associate a sequence type (ST) to a bacterial isolate. When the output of whole genome sequencing (WGS) of a sample is available the ST can be assigned directly processing the read-set. Current approaches employ reads mapping (SRST2) against the MLST loci, k-mer distribution (stringMLST), selective assembly (GRAbB) or whole genome assembly (BIGSdb) followed by BLASTn sequence query. Here we present STRAI ...[more]

PMID: 31757201

Similar Datasets

Project description:BackgroundMycoplasma anserisalpingitidis is a waterfowl pathogen that mainly infects geese, can cause significant economic losses and is present worldwide. With the advance of whole genome sequencing technologies, new methods are available for the researchers; one emerging methodology is the core genome Multi-Locus Sequence Typing (cgMLST). The core genome contains a high percentage of the coding DNA sequence (CDS) set of the studied strains. The cgMLST schemas are powerful genotyping tools allowing for the investigation of potential epidemics, and precise and reliable classification of the strains. Although whole genome sequences of M. anserisalpingitidis strains are available, to date, no cgMLST schema has been published for this species.ResultsIn this study, Illumina short reads of 81 M. anserisalpingitidis strains were used, including samples from Hungary, Poland, Sweden, and China. Draft genomes were assembled with the SPAdes software and analysed with the online available chewBBACA program. User made modifications in the program enabled analysis of mycoplasmas and provided similar results as the conventional SeqSphere+ software. The threshold of the presence of CDS in the strains was set to 93% due to the quality of the draft genomes, resulting in the most accurate and robust schema. Three hundred thirty-one CDSs constituted our cgMLST schema (representing 42,77% of the whole CDS set of M. anserisalpingitidis ATCC BAA-2147), and a Neighbor joining tree was created using the allelic profiles. The correlation was observed between the strains' cgMLST profile and geographical origin; however, strains from the same integration but different locations also showed close relationship. Strains isolated from different tissue samples of the same animal revealed highly similar cgMLST profiles.ConclusionsThe Neighbor joining tree from the cgMLST schema closely resembled the real-life spatial and temporal relationships of the strains. The incongruences between background data and the cgMLST profile in the strains from the same integration can be because of the higher probability of contacts between the flocks. This schema can help with the epidemiological investigation and can be used as a basis for further studies.

Project description:The MLST scheme currently used for Enterococcus faecium typing was designed in 2002 and is based on putative gene functions and Enterococcus faecalis gene sequences available at that time. As a result, the original MLST scheme does not correspond to the real genetic relatedness of E. faecium strains and often clusters genetically distant strains to the same sequence types (ST). Nevertheless, typing has a significant impact on the subsequent epidemiological conclusions and introduction of appropriate epidemiological measures, thus it is crucial to use a more accurate MLST scheme. Based on the genome analysis of 1,843 E. faecium isolates, a new scheme, consisting of 8 highly discriminative loci, was created in this study. These strains were divided into 421 STs using the new MLST scheme, as opposed to 223 STs assigned by the original MLST scheme. The proposed MLST has a discriminatory power of D = 0.983 (CI95% 0.981 to 0.984), compared to the original scheme's D = 0.919 (CI95% 0.911 to 0.927). Moreover, we identified new clonal complexes with our newly designed MLST scheme. The scheme proposed here is available within the PubMLST database. Although whole genome sequencing availability has increased rapidly, MLST remains an integral part of clinical epidemiology, mainly due to its high standardization and excellent robustness. In this study, we proposed and validated a new MLST scheme for E. faecium, which is based on genome-wide data and thus reflects the tested isolates' more accurate genetic similarity. IMPORTANCE Enterococcus faecium is one of the most important pathogens causing health care associated infections. One of the main reasons for its clinical importance is a rapidly spreading resistance to vancomycin and linezolid, which significantly complicates antibiotic treatment of infections caused by such resistant strains. Monitoring the spread and relationships between resistant strains causing severe conditions represents an important tool for implementing appropriate preventive measures. Therefore, there is an urgent need to establish a robust method enabling strain monitoring and comparison at the local, national, and global level. Unfortunately, the current, extensively used MLST scheme does not reflect the real genetic relatedness between individual strains and thus does not provide sufficient discriminatory power. This can lead directly to incorrect epidemiological measures due to insufficient accuracy and biased results.

Dataset Information

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

Publications

STRAIN: an R package for multi-locus sequence typing from whole genome sequencing data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets