Whole genome sequencing of Streptococcus pneumoniae: development, evaluation and verification of targets for serogroup and serotype prediction using an automated pipeline.

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.

Comparison of the Legionella pneumophila population structure as determined by sequence-based typing and whole genome sequencing.

BACKGROUND: Legionella pneumophila is an opportunistic pathogen of humans where the source of infection is usually from contaminated man-made water systems. When an outbreak of Legionnaires' disease caused by L. pneumophila occurs, it is necessary to discover the source of infection. A seven allele sequence-based typing scheme (SBT) has been very successful in providing the means to attribute outbreaks of L. pneumophila to a particular source or sources. Particular sequence types described by this scheme are known to exhibit specific phenotypes. For instance some types are seen often in clinical cases but are rarely isolated from the environment and vice versa. Of those causing human disease some types are thought to be more likely to cause more severe disease. It is possible that the genetic basis for these differences are vertically inherited and associated with particular genetic lineages within the population. In order to provide a framework within which to test this hypothesis and others relating to the population biology of L. pneumophila, a set of genomes covering the known diversity of the organism is required. RESULTS: Firstly, this study describes a means to group L. pneumophila strains into pragmatic clusters, using a methodology that takes into consideration the genetic forces operating on the population. These clusters can be used as a standardised nomenclature, so those wishing to describe a group of strains can do so. Secondly, the clusters generated from the first part of the study were used to select strains rationally for whole genome sequencing (WGS). The data generated was used to compare phylogenies derived from SBT and WGS. In general the SBT sequence type (ST) accurately reflects the whole genome-based genotype. Where there are exceptions and recombination has resulted in the ST no longer reflecting the genetic lineage described by the whole genome sequence, the clustering technique employed detects these sequence types as being admixed, indicating their mixed inheritance. CONCLUSIONS: We conclude that SBT is usually a good proxy for the genetic lineage described by the whole genome, and therefore utility of SBT is still suitable until the technology and economics of high throughput sequencing reach the point where routine WGS of L. pneumophila isolates for outbreak investigation is feasible.

Public health value of next-generation DNA sequencing of enterohemorrhagic Escherichia coli isolates from an outbreak.

In 2009, an outbreak of enterohemorrhagic Escherichia coli (EHEC) on an open farm infected 93 persons, and approximately 22% of these individuals developed hemolytic-uremic syndrome (HUS). Genome sequencing was used to investigate outbreak-derived animal and human EHEC isolates. Phylogeny based on the whole-genome sequence was used to place outbreak isolates in the context of the overall E. coli species and the O157:H7 sequence type 11 (ST11) subgroup. Four informative single nucleotide polymorphisms (SNPs) were identified and used to design an assay to type 122 other outbreak isolates. The SNP phylogeny demonstrated that the outbreak strain was from a lineage distinct from previously reported O157:H7 ST11 EHEC and was not a member of the hypervirulent clade 8. The strain harbored determinants for two Stx2 verotoxins and other putative virulence factors. When linked to the epidemiological information, the sequence data indicate that gross contamination of a single outbreak strain occurred across the farm prior to the first clinical report of HUS. The most likely explanation for these results is that a single successful strain of EHEC spread from a single introduction through the farm by clonal expansion and that contamination of the environment (including the possible colonization of several animals) led ultimately to human cases.

External quality assessment of a DNA sequence-based scheme for epidemiological typing of Legionella pneumophila by an international network of laboratories.

We report the results of an international external quality assessment (EQA) program to assess the performance of laboratories in genotyping Legionella pneumophila isolates using the standard European Working Group for Legionella Infections sequence-based typing protocol. Three coded distributions of L. pneumophila isolates were sent to laboratories in 12, 14, and 20 countries, respectively. The data were returned by 11 of 16, 18 of 19, and 27 of 29 centers, respectively. Incomplete submission of data resulted in exclusion from certain aspects of the analyses. The number of centers achieving 100% score, for all loci tested, rose successively from 50% (5 of 10) for the first EQA distribution, to 56% (9 of 16) for the second EQA distribution, to 76% (19 of 25) for the third EQA distribution. A number of additional centers made only a few errors (one to three) in each distribution. Sequence data from the first two distributions were collected in flat text file format and using specially developed software, the sequence quality tool (SQT), in the third distribution. The SQT allows users to upload trace files in standard file formats, automates basecalling using phred and phrap software, contig assembly, trimming, and matching against a reference library. The program described here allow users an independent measure of sequence quality, and such schemes are vital in order to identify strengths and weakness in centers responsible for the generation of genotyping data in legionella outbreak investigation. The present study demonstrates that DNA sequence data can be highly reproducible but, when independently assessed, in practice frequently falls short of this goal. However, experience and training in the methodology results in increased performance.