Distribution of the type III DNA methyltransferases modA, modB and modD among Neisseria meningitidis genotypes: implications for gene regulation and virulence.

Neisseria meningitidis is a human-specific bacterium that varies in invasive potential. All meningococci are carried in the nasopharynx, and most genotypes are very infrequently associated with invasive meningococcal disease; however, those belonging to the 'hyperinvasive lineages' are more frequently associated with sepsis or meningitis. Genome content is highly conserved between carriage and disease isolates, and differential gene expression has been proposed as a major determinant of the hyperinvasive phenotype. Three phase variable DNA methyltransferases (ModA, ModB and ModD), which mediate epigenetic regulation of distinct phase variable regulons (phasevarions), have been identified in N. meningitidis. Each mod gene has distinct alleles, defined by their Mod DNA recognition domain, and these target and methylate different DNA sequences, thereby regulating distinct gene sets. Here 211 meningococcal carriage and >1,400 disease isolates were surveyed for the distribution of meningococcal mod alleles. While modA11-12 and modB1-2 were found in most isolates, rarer alleles (e.g., modA15, modB4, modD1-6) were specific to particular genotypes as defined by clonal complex. This suggests that phase variable Mod proteins may be associated with distinct phenotypes and hence invasive potential of N. meningitidis strains.

Genomic epidemiology of age-associated meningococcal lineages in national surveillance: an observational cohort study.

BACKGROUND: Invasive meningococcal disease (IMD) is a worldwide health issue that is potentially preventable with vaccination. In view of its sporadic nature and the high diversity of Neisseria meningitidis, epidemiological surveillance incorporating detailed isolate characterisation is crucial for effective control and understanding the evolving epidemiology of IMD. The Meningitis Research Foundation Meningococcus Genome Library (MRF-MGL) exploits whole-genome sequencing (WGS) for this purpose and presents data on a comprehensive and coherent IMD isolate collection from England and Wales via the internet. We assessed the contribution of these data to investigating IMD epidemiology. METHODS: WGS data were obtained for all 899 IMD isolates available for England and Wales in epidemiological years 2010-11 and 2011-12. The data had been annotated at 1720 loci, analysed, and disseminated online. Information was also available on meningococcal population structure and vaccine (Bexsero, GlaxoSmithKline, Brentford, Middlesex, UK) antigen variants, which enabled the investigation of IMD-associated genotypes over time and by patients' age groups. Population genomic analyses were done with a hierarchical gene-by-gene approach. FINDINGS: The methods used by MRF-MGL efficiently characterised IMD isolates and information was provided in plain language. At least 20 meningococcal lineages were identified, three of which (hyperinvasive clonal complexes 41/44 [lineage 3], 269 [lineage 2], and 23 [lineage 23]) were responsible for 528 (59%) of IMD isolates. Lineages were highly diverse and showed evidence of extensive recombination. Specific lineages were associated with IMD in particular age groups, with notable diversity in the youngest and oldest individuals. The increased incidence of IMD from 1984 to 2010 in England and Wales was due to successive and concurrent epidemics of different lineages. Genetically, 74% of isolates were characterised as encoding group B capsules: 16% group Y, 6% group W, and 3% group C. Exact peptide matches for individual Bexsero vaccine antigens were present in up to 26% of isolates. INTERPRETATION: The MRF-MGL represents an effective, broadly applicable model for the storage, analysis, and dissemination of WGS data that can facilitate real-time genomic pathogen surveillance. The data revealed information crucial to effective deployment and assessment of vaccines against N meningitidis. FUNDING: Meningitis Research Foundation, Wellcome Trust, Public Health England, European Union.

Genomic resolution of an aggressive, widespread, diverse and expanding meningococcal serogroup B, C and W lineage.

OBJECTIVES: Neisseria meningitidis is a leading cause of meningitis and septicaemia. The hyperinvasive ST-11 clonal complex (cc11) caused serogroup C (MenC) outbreaks in the US military in the 1960s and UK universities in the 1990s, a global Hajj-associated serogroup W (MenW) outbreak in 2000-2001, and subsequent MenW epidemics in sub-Saharan Africa. More recently, endemic MenW disease has expanded in South Africa, South America and the UK, and MenC cases have been reported among European and North American men who have sex with men (MSM). Routine typing schemes poorly resolve cc11 so we established the population structure at genomic resolution. METHODS: Representatives of these episodes and other geo-temporally diverse cc11 meningococci (n = 750) were compared across 1546 core genes and visualised on phylogenetic networks. RESULTS: MenW isolates were confined to a distal portion of one of two main lineages with MenB and MenC isolates interspersed elsewhere. An expanding South American/UK MenW strain was distinct from the 'Hajj outbreak' strain and a closely related endemic South African strain. Recent MenC isolates from MSM in France and the UK were closely related but distinct. CONCLUSIONS: High resolution 'genomic' multilocus sequence typing is necessary to resolve and monitor the spread of diverse cc11 lineages globally.

Genome-Based Characterization of Emergent Invasive Neisseria meningitidis Serogroup Y Isolates in Sweden from 1995 to 2012.

Invasive meningococcal disease (IMD) caused by Neisseria meningitidis serogroup Y has increased in Europe, especially in Scandinavia. In Sweden, serogroup Y is now the dominating serogroup, and in 2012, the serogroup Y disease incidence was 0.46/100,000 population. We previously showed that a strain type belonging to sequence type 23 was responsible for the increased prevalence of this serogroup in Sweden. The objective of this study was to investigate the serogroup Y emergence by whole-genome sequencing and compare the meningococcal population structure of Swedish invasive serogroup Y strains to those of other countries with different IMD incidence. Whole-genome sequencing was performed on invasive serogroup Y isolates from 1995 to 2012 in Sweden (n = 186). These isolates were compared to a collection of serogroup Y isolates from England, Wales, and Northern Ireland from 2010 to 2012 (n = 143), which had relatively low serogroup Y incidence, and two isolates obtained in 1999 in the United States, where serogroup Y remains one of the major causes of IMD. The meningococcal population structures were similar in the investigated regions; however, different strain types were prevalent in each geographic region. A number of genes known or hypothesized to have an impact on meningococcal virulence were shown to be associated with different strain types and subtypes. The reasons for the IMD increase are multifactorial and are influenced by increased virulence, host adaptive immunity, and transmission. Future genome-wide association studies are needed to reveal additional genes associated with serogroup Y meningococcal disease, and this work would benefit from a complete serogroup Y meningococcal reference genome.

Specificity of the ModA11, ModA12 and ModD1 epigenetic regulator N(6)-adenine DNA methyltransferases of Neisseria meningitidis.

Phase variation (random ON/OFF switching) of gene expression is a common feature of host-adapted pathogenic bacteria. Phase variably expressed N(6)-adenine DNA methyltransferases (Mod) alter global methylation patterns resulting in changes in gene expression. These systems constitute phase variable regulons called phasevarions. Neisseria meningitidis phasevarions regulate genes including virulence factors and vaccine candidates, and alter phenotypes including antibiotic resistance. The target site recognized by these Type III N(6)-adenine DNA methyltransferases is not known. Single molecule, real-time (SMRT) methylome analysis was used to identify the recognition site for three key N. meningitidis methyltransferases: ModA11 (exemplified by M.NmeMC58I) (5'-CGY M6A: G-3'), ModA12 (exemplified by M.Nme77I, M.Nme18I and M.Nme579II) (5'-AC M6A: CC-3') and ModD1 (exemplified by M.Nme579I) (5'-CC M6A: GC-3'). Restriction inhibition assays and mutagenesis confirmed the SMRT methylome analysis. The ModA11 site is complex and atypical and is dependent on the type of pyrimidine at the central position, in combination with the bases flanking the core recognition sequence 5'-CGY M6A: G-3'. The observed efficiency of methylation in the modA11 strain (MC58) genome ranged from 4.6% at 5'-GCGC M6A: GG-3' sites, to 100% at 5'-ACGT M6A: GG-3' sites. Analysis of the distribution of modified sites in the respective genomes shows many cases of association with intergenic regions of genes with altered expression due to phasevarion switching.

Defining the estimated core genome of bacterial populations using a Bayesian decision model.

The bacterial core genome is of intense interest and the volume of whole genome sequence data in the public domain available to investigate it has increased dramatically. The aim of our study was to develop a model to estimate the bacterial core genome from next-generation whole genome sequencing data and use this model to identify novel genes associated with important biological functions. Five bacterial datasets were analysed, comprising 2096 genomes in total. We developed a Bayesian decision model to estimate the number of core genes, calculated pairwise evolutionary distances (p-distances) based on nucleotide sequence diversity, and plotted the median p-distance for each core gene relative to its genome location. We designed visually-informative genome diagrams to depict areas of interest in genomes. Case studies demonstrated how the model could identify areas for further study, e.g. 25% of the core genes with higher sequence diversity in the Campylobacter jejuni and Neisseria meningitidis genomes encoded hypothetical proteins. The core gene with the highest p-distance value in C. jejuni was annotated in the reference genome as a putative hydrolase, but further work revealed that it shared sequence homology with beta-lactamase/metallo-beta-lactamases (enzymes that provide resistance to a range of broad-spectrum antibiotics) and thioredoxin reductase genes (which reduce oxidative stress and are essential for DNA replication) in other C. jejuni genomes. Our Bayesian model of estimating the core genome is principled, easy to use and can be applied to large genome datasets. This study also highlighted the lack of knowledge currently available for many core genes in bacterial genomes of significant global public health importance.

Resolution of a meningococcal disease outbreak from whole-genome sequence data with rapid Web-based analysis methods.

The increase in the capacity and reduction in cost of whole-genome sequencing methods present the imminent prospect of such data being used routinely in real time for investigations of bacterial disease outbreaks. For this to be realized, however, it is necessary that generic, portable, and robust analysis frameworks be available, which can be readily interpreted and used in real time by microbiologists, clinicians, and public health epidemiologists. We have achieved this with a set of analysis tools integrated into the PubMLST.org website, which can in principle be used for the analysis of any pathogen. The approach is demonstrated with genomic data from isolates obtained during a well-characterized meningococcal disease outbreak at the University of Southampton, United Kingdom, that occurred in 1997. Whole-genome sequence data were collected, de novo assembled, and deposited into the PubMLST Neisseria BIGSdb database, which automatically annotated the sequences. This enabled the immediate and backwards-compatible classification of the isolates with a number of schemes, including the following: conventional, extended, and ribosomal multilocus sequence typing (MLST, eMLST, and rMLST); antigen gene sequence typing (AGST); analysis based on genes conferring antibiotic susceptibility. The isolates were also compared to a reference isolate belonging to the same clonal complex (ST-11) at 1,975 loci. Visualization of the data with the NeighborNet algorithm, implemented in SplitsTree 4 within the PubMLST website, permitted complete resolution of the outbreak and related isolates, demonstrating that multiple closely related but distinct strains were simultaneously present in asymptomatic carriage and disease, with two causing disease and one responsible for the outbreak itself.