Dataset Information

Whole genome sequencing of group A Streptococcus: development and evaluation of an automated pipeline for emmgene typing.

ABSTRACT: Streptococcus pyogenes group A Streptococcus (GAS) is the most common cause of bacterial throat infections, and can cause mild to severe skin and soft tissue infections, including impetigo, erysipelas, necrotizing fasciitis, as well as systemic and fatal infections including septicaemia and meningitis. Estimated annual incidence for invasive group A streptococcal infection (iGAS) in industrialised countries is approximately three per 100,000 per year. Typing is currently used in England and Wales to monitor bacterial strains of S. pyogenes causing invasive infections and those isolated from patients and healthcare/care workers in cluster and outbreak situations. Sequence analysis of the emm gene is the currently accepted gold standard methodology for GAS typing. A comprehensive database of emm types observed from superficial and invasive GAS strains from England and Wales informs outbreak control teams during investigations. Each year the Bacterial Reference Department, Public Health England (PHE) receives approximately 3,000 GAS isolates from England and Wales. In April 2014 the Bacterial Reference Department, PHE began genomic sequencing of referred S. pyogenes isolates and those pertaining to selected elderly/nursing care or maternity clusters from 2010 to inform future reference services and outbreak analysis (n = 3, 047). In line with the modernizing strategy of PHE, we developed a novel bioinformatics pipeline that can predict emmtypes using whole genome sequence (WGS) data. The efficiency of this method was measured by comparing the emmtype assigned by this method against the result from the current gold standard methodology; concordance to emmsubtype level was observed in 93.8% (2,852/3,040) of our cases, whereas in 2.4% (n = 72) of our cases concordance was observed to emm type level. The remaining 3.8% (n = 117) of our cases corresponded to novel types/subtypes, contamination, laboratory sample transcription errors or problems arising from high sequence similarity of the allele sequence or low mapping coverage. De novo assembly analysis was performed in the two latter groups (n = 72 + 117) and was able to diagnose the problem and where possible resolve the discordance (60/72 and 20/117, respectively). Overall, we have demonstrated that our WGS emm-typing pipeline is a reliable and robust system that can be implemented to determine emm type for the routine service.

SUBMITTER: Kapatai G

PROVIDER: S-EPMC5410157 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Whole genome sequencing of group A Streptococcus: development and evaluation of an automated pipeline for emmgene typing.

Kapatai Georgia G Coelho Juliana J Platt Steven S Chalker Victoria J VJ

PeerJ 20170427

Streptococcus pyogenes group A Streptococcus (GAS) is the most common cause of bacterial throat infections, and can cause mild to severe skin and soft tissue infections, including impetigo, erysipelas, necrotizing fasciitis, as well as systemic and fatal infections including septicaemia and meningitis. Estimated annual incidence for invasive group A streptococcal infection (iGAS) in industrialised countries is approximately three per 100,000 per year. Typing is currently used in En ...[more]

PMID: 28462035

Similar Datasets

Project description:Streptococcus pneumoniae typically express one of 92 serologically distinct capsule polysaccharide (cps) types (serotypes). Some of these serotypes are closely related to each other; using the commercially available typing antisera, these are assigned to common serogroups containing types that show cross-reactivity. In this serotyping scheme, factor antisera are used to allocate serotypes within a serogroup, based on patterns of reactions. This serotyping method is technically demanding, requires considerable experience and the reading of the results can be subjective. This study describes the analysis of the S. pneumoniae capsular operon genetic sequence to determine serotype distinguishing features and the development, evaluation and verification of an automated whole genome sequence (WGS)-based serotyping bioinformatics tool, PneumoCaT (Pneumococcal Capsule Typing). Initially, WGS data from 871 S. pneumoniae isolates were mapped to reference cps locus sequences for the 92 serotypes. Thirty-two of 92 serotypes could be unambiguously identified based on sequence similarities within the cps operon. The remaining 60 were allocated to one of 20 'genogroups' that broadly correspond to the immunologically defined serogroups. By comparing the cps reference sequences for each genogroup, unique molecular differences were determined for serotypes within 18 of the 20 genogroups and verified using the set of 871 isolates. This information was used to design a decision-tree style algorithm within the PneumoCaT bioinformatics tool to predict to serotype level for 89/94 (92 + 2 molecular types/subtypes) from WGS data and to serogroup level for serogroups 24 and 32, which currently comprise 2.1% of UK referred, invasive isolates submitted to the National Reference Laboratory (NRL), Public Health England (June 2014-July 2015). PneumoCaT was evaluated with an internal validation set of 2065 UK isolates covering 72/92 serotypes, including 19 non-typeable isolates and an external validation set of 2964 isolates from Thailand (n = 2,531), USA (n = 181) and Iceland (n = 252). PneumoCaT was able to predict serotype in 99.1% of the typeable UK isolates and in 99.0% of the non-UK isolates. Concordance was evaluated in UK isolates where further investigation was possible; in 91.5% of the cases the predicted capsular type was concordant with the serologically derived serotype. Following retesting, concordance increased to 99.3% and in most resolved cases (97.8%; 135/138) discordance was shown to be caused by errors in original serotyping. Replicate testing demonstrated that PneumoCaT gave 100% reproducibility of the predicted serotype result. In summary, we have developed a WGS-based serotyping method that can predict capsular type to serotype level for 89/94 serotypes and to serogroup level for the remaining four. This approach could be integrated into routine typing workflows in reference laboratories, reducing the need for phenotypic immunological testing.

Project description:BackgroundThere are more than 300 known red blood cell (RBC) antigens and 33 platelet antigens that differ between individuals. Sensitisation to antigens is a serious complication that can occur in prenatal medicine and after blood transfusion, particularly for patients who require multiple transfusions. Although pre-transfusion compatibility testing largely relies on serological methods, reagents are not available for many antigens. Methods based on single-nucleotide polymorphism (SNP) arrays have been used, but typing for ABO and Rh-the most important blood groups-cannot be done with SNP typing alone. We aimed to develop a novel method based on whole-genome sequencing to identify RBC and platelet antigens.MethodsThis whole-genome sequencing study is a subanalysis of data from patients in the whole-genome sequencing arm of the MedSeq Project randomised controlled trial (NCT01736566) with no measured patient outcomes. We created a database of molecular changes in RBC and platelet antigens and developed an automated antigen-typing algorithm based on whole-genome sequencing (bloodTyper). This algorithm was iteratively improved to address cis-trans haplotype ambiguities and homologous gene alignments. Whole-genome sequencing data from 110 MedSeq participants (30 × depth) were used to initially validate bloodTyper through comparison with conventional serology and SNP methods for typing of 38 RBC antigens in 12 blood-group systems and 22 human platelet antigens. bloodTyper was further validated with whole-genome sequencing data from 200 INTERVAL trial participants (15 × depth) with serological comparisons.FindingsWe iteratively improved bloodTyper by comparing its typing results with conventional serological and SNP typing in three rounds of testing. The initial whole-genome sequencing typing algorithm was 99·5% concordant across the first 20 MedSeq genomes. Addressing discordances led to development of an improved algorithm that was 99·8% concordant for the remaining 90 MedSeq genomes. Additional modifications led to the final algorithm, which was 99·2% concordant across 200 INTERVAL genomes (or 99·9% after adjustment for the lower depth of coverage).InterpretationBy enabling more precise antigen-matching of patients with blood donors, antigen typing based on whole-genome sequencing provides a novel approach to improve transfusion outcomes with the potential to transform the practice of transfusion medicine.FundingNational Human Genome Research Institute, Doris Duke Charitable Foundation, National Health Service Blood and Transplant, National Institute for Health Research, and Wellcome Trust.

Dataset Information

Whole genome sequencing of group A Streptococcus: development and evaluation of an automated pipeline for emmgene typing.

Publications

Whole genome sequencing of group A <i>Streptococcus</i>: development and evaluation of an automated pipeline for <i>emm</i>gene typing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets