Neisseria meningitidis - Eurosurveillance

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Table Meningococcal whole genome sequencing data linked to published studies, deposited in the PubMLST Neisseria database as of November 2012 Clonal complex Number of genome sequences Number of STs Serogroups diversity of some clonal complexes (e.g. cc1) and the interrelationships of others, e.g. cc8 and cc11 clonal complexes, and the relationships of the ET-15 and ET-37 variants within cc11. Conclusions and future prospects Nucleotide sequences are a universal language that can be interpreted in a number of ways. For clinical and epidemiological purposes, sequences from clinical specimens have to be rapidly and effectively translated into a meaningful term or set of terms that define those properties of the aetiological agents of disease that direct medical and public health action. One of the factors behind the success of seven-locus MLST was the introduction of standard sets of nomenclature that reflected the structure of microbial populations and their phenotypic properties. For organisms with well-established and accepted MLST and other typing schemes in place, the impact of the application of WGS data will be to rapidly identify properties such as strain type. In some cases, novel nomenclature may be required, but this is a process that has to be approached with care, if confusion in the wider clinical community is to be avoided. The suite of database subsites on PubMLST, which now includes a site that catalogues the ribosomal diversity across the whole domain for the purposes of rMLST typing [44,52], provides an example of how WGS data can be used to efficiently designate specimens to current strain types. It can be also used to establish additional typing schemes which can coexist with each other side PorA variant combinations FetA variants cc11 31 6 C (22), W (4), B(2), NG (1), NA (2) 8 8 cc41/44 20 12 B (14), NA (5), NG (1) 10 5 cc32 17 4 B (14), C (1), NG (1), NA (1) 10 5 cc5 16 5 A (16) 3 5 cc4 14 1 A (14) 4 1 cc1 13 3 A (13) 4 5 cc8 9 5 B (5), C (3), NA (1) 6 5 cc18 5 4 B (4), C (1) 5 4 cc23 5 2 Y (5) 3 2 cc22 4 1 W (4) 1 2 cc167 4 4 Y (4) 1 2 cc269 4 3 B (2), NA (2) 4 3 cc37 2 2 B (2) 1 2 NA: not available; NG: non-groupable; ST: sequence type. The table shows the clonal complex and indicates the diversity of ST, serogroup and typing antigens. Only clonal complexes represented by two or more genomes are included. by side, as there is no limit to the number of loci and schemes that can be defined. As the database stores the sequence information that is available for an isolate, be that a single read or a whole genome, it means that it is possible to seamlessly compare isolates for which different types of information are available, achieving backwards compatibility with previous typing schemes, as well as compatibility with diagnostic tests that may target only one or a few loci. The extent to which isolates can be compared depends only on the quality of the sequence data available for the locus in question, but given that clinical specimens are often imperfect, it is important for clinical and epidemiological purposes that incomplete or partial information can be used. While many studies place short-read data in a sequence read archive, this is not easily accessible or readily analysed. PubMLST curators do proactively assemble short-read data and incorporate the resultant contigs into the database where metadata are available. Links are made to the sequence read archive within PubMLST isolate records so that original data can be retrieved and analysed when required. While the Neisseria databases described are exemplars, databases for other species can be hosted on request and the open-source BIGSdb software is freely available for local installation. The first analyses of WGS data on bacterial specimens relied on SNP analysis of closely related bacteria, with mapping of sequence reads to a predefined reference genome. These have required pre-analysis of the samples by an approach such as MLST to limit the extent 34 www.eurosurveillance.org
Figure 3 Relationships of 139 Neisseria meningitidis genomes in the PubMLST Neisseria database, generated with Genome Comparator and Neighbor-net from allelic profiles data for rMLST loci cc23 cc167 cc8 cc18 r: ribosomal; MLST: multilocus sequence typing. The locations of isolates belonging to major clonal complexes identified by conventional MLST are indicated (cc1, etc.). The figure illustrates relationships not apparent from seven-locus MLST, including the diversity of some clonal complexes (e.g. cc1) and the interrelationships of others, e.g. cc8 and cc11 clonal complexes, and the relationships of the ET-15 and ET-37 variants within cc11. www.eurosurveillance.org ET-15 cc11 ET-37 ST-44 ST-41 cc41/44 cc37 cc32 cc1 cc269 cc4 cc22 cc5 35
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Acknowledgments We gratefully thank
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epidemiologically relevant variants
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Perspectives The need for ethical r
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News ECDC starts pilot phase for co
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