Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Genome-wide methylome analysis of two strains belonging to the hypervirulent Neisseria meningitidis serogroup W ST-11 clonal complex

Abstract

A rising incidence of meningococcal serogroup W disease has been evident in many countries worldwide. Serogroup W isolates belonging to the sequence type (ST)-11 clonal complex have been associated with atypical symptoms and increased case fatality rates. The continued expansion of this clonal complex in the later part of the 2010s has been largely due to a shift from the so-called original UK strain to the 2013 strain. Here we used single-molecule real-time (SMRT) sequencing to determine the methylomes of the two major serogroup W strains belonging to ST-11 clonal complex. Five methylated motifs were identified in this study, and three of the motifs, namely 5′-GATC-3′, 5′-GAAGG-3′, 5′-GCGCGC-3′, were found in all 13 isolates investigated. The results showed no strain-specific motifs or difference in active restriction modification systems between the two strains. Two phase variable methylases were identified and the enrichment or depletion of the methylation motifs generated by these methylases varied between the two strains. Results from this work give further insight into the low diversity of methylomes in highly related strains and encourage further research to decipher the role of regions with under- or overrepresented methylation motifs.

Introduction

Neisseria meningitidis (the meningococcus) is a Gram-negative bacterium carried asymptomatically in the nasopharynx in about 10% of the general population1. This obligate commensal bacterium has the potential of crossing the mucosal membrane into the bloodstream causing life-threatening septicaemia as well as the blood–brain barrier causing meningitis2. Meningococci are divided into different serogroups based on the chemical composition of the surrounding capsule, and most invasive cases are caused by serogroups A, B, C, W, X and Y3.

Invasive meningococcal disease due to meningococcal serogroup W (MenW) emerged in Sub-Saharan Africa following the outbreak in Hajj pilgrims in 20004 and later on also in South Africa5 and South America6. The increase of MenW, more specifically multi locus sequence typing (ST)-11 clonal complex, was first reported in the UK in 20097 and subsequently rapidly expanded to the rest of Europe8 and later across all continents9. MenW ST-11 clonal complex has in recent years been shown to be more virulent than before with higher morbidity and case fatality rates, atypical clinical features, and an older affected population9,10. Whole-genome sequencing has revealed two strains belonging to the ST-11 clonal complex, one which predominated in the UK before 2013, referred to as the original UK strain, and one that emerged after 2013, the 2013-strain11, which has predominated in Sweden since 201312. The two strains are highly similar and only 30 genetic differences have been found between the two strains11. In 2015, the 2013 strain was responsible for an outbreak of MenW disease among scouts participating in a World Scout Jamboree in Japan with 33,000 participants from 162 countries11. Three scouts and one non-attending close contact from Scotland and two scouts from Sweden developed meningococcal disease13.

Although DNA methylation is best known for its roles in prokaryotic defence and genetic flux, it has also been shown to have roles in gene expression14,15 and virulence16. Methylation is widespread in eukaryotes and prokaryotes in the form of N6-methyladenine (m6A) and C5-methylcytosine (m5C), whereas N4-methylcytosine (m4C) is only found in bacteria and archaea17,18. Traditionally, DNA methylation studies have been performed using bisulfite sequencing, which can only detect m5C. Genome-wide patterns of methylation in bacteria can however now be studied using Single molecule real-time (SMRT) PacBio sequencing which has the potential to detect all three ways of methylation, but is often unreliable for m5C-containing motifs19.

DNA methylation is driven by DNA methyltransferases (MTases), which are enzymes that catalyse the transfer of a methyl group to a nucleobase20. MTases together with restriction endonucleases (REases) form restriction-modification systems (RMS), which act as a defence mechanism against the invasion of foreign DNA in prokaryotes21. REases cleave double stranded DNA at specific sequences, and methyl groups are added by MTases to specific target sequences (motifs) to prevent degradation by the REases. RMS are grouped into four classes depending on subunit composition, cleavage position, sequence specificity and cofactor requirements22. Type I systems consist of three subunit proteins: R (restriction), M (modification), and S (specificity)23. Type II systems are the most common and consist of individual MTase and REase enzymes that bind to and cleave at the same position, or close to that sequence. Type III systems are composed of two protein subunits, Mod and Res, which recognize non-palindromic motifs22. Type IV systems only cleave methylated DNA and show only weak specificity24. Only Type I-III RMS have been found in Neisseria25,26.

Meningococci are known for their numerous phase variable genes and differential gene expression could provide a possible explanation for phenotypic differences, which could have an impact on the emergence of different strains27,28,29. The aim of the present study was to compare both the methylomes and the RMS gene loci of the 2013 strain to the original UK strain using SMRT sequencing technology to provide a more comprehensive insight into the pathobiology of the ST-11 clonal complex.

Methods

Bacterial isolates

Thirteen isolates belonging to the original UK strain (n = 3) and the 2013 strain (n = 10), all collected in Sweden between the years 2011 and 2016, were included. Four isolates (15-193, 15-198, 15-215 and 15-236) belonging to the 2013 strain were part of a previously reported Jamboree associated outbreak 11. One of the isolates, 15-193, caused invasive disease whereas the others were carriage isolates collected during prophylactic antibiotic treatment to halt the outbreak.

Isolates were cultured on chocolate agar at 37 °C in a 5% CO2 enriched atmosphere overnight and archived at − 70 °C. Genomic DNA was extracted using the Wizard Genomic DNA purification kit (Promega) according to the manufacturer’s instructions.

Single-molecule real-time (SMRT) DNA sequencing

The isolates were sequenced using SMRT sequencing on a PacBio RS II. Reads were assembled de novo using HGAP v3 (Pacific Biosciences, SMRT Analysis Software v2.3.0, smrtanalysis_2.3.0.140936.p5.167094). For sequencing and assembly metrics, see Supplementary Tables 1 and 2. One isolate, 14-627, was sequenced with coverage > 1000 × in order to increase the sensitivity and attempt to find the difficult to detect m5C methylation. Quiver30 was used to correct sequencing errors in the assemblies by mapping the raw SMRT sequencing reads back to the assembly. A second polish was performed using Illumina MiSeq 500 bp reads in CLC Genomics Workbench v 20.0 (Qiagen). Mimimus2 software from the Amos package31 was used to circularize the genomes. SMRT sequencing yielded circular chromosomes with the median genome length 2,183,867 nucleotides and a median number of predicted coding sequences (CDS) of 2,158 (Supplementary Table 2).

Table 1 A schematic overview of the putative restriction modification systems (RMS) predicted by SEQWARE in N. meningitidis serogroup W, isolate 15-193 used as a representative.

Analysis of genomes

PacBio assemblies were annotated in two ways: (1) using the NCBI Prokaryotic Genome Annotation Pipeline as part of the NCBI submission32 (2) using the PubMLST Neisseria database (http://pubMLST.org/neisseria/) where genome data were also deposited. Genes in PubMLST were labelled using the locus tag prefix “NEIS”.

Illumina reads from the 13 isolates from a previous study12 were mapped onto the MC58 reference genome32 using CLC Genomics Workbench v 20.0 (Qiagen). A SNP tree was created using default parameters and the Neighbor Joining algorithm in CLC Genomics Workbench.

Detection and specificity of putative restriction modification systems (RMS)

Putative RMS associated with the different methyltransferase recognition motifs identified were searched using SEQWARE routines as described previously33, and deposited in the Restriction Enzyme Database, REBASE24 together with the motif summary files, which were also deposited in GenBank (BioProject PRJNA476247). The predicted activity or inactivity of different RMS genes was investigated by aligning the sequences for each gene encoding the respective MTases and REases in CLC Genomics Workbench v 20.0 and searching for frameshifts or insertion transposases that could introduce premature stop codons.

Analysis of DNA methylation

The analysis platform SMRT Portal v2.3.0 was used to identify modified positions and for the genome-wide analysis of modified motifs. After examination of results from analysis with default settings, the analysis was rerun with quality value (QV) 60 and 100 (up to 200 for high coverage samples) to limit motif finding to high confidence hits and remove some of the unusual motifs. The distribution of methylated bases and positions of predicted methyltransferases were visualized using plots created with Circa (http://omgenomics.com/circa).

Determination of motif-rich and poor regions

5′-ACACC-3′ and 5′-CGAAT-3′ motif distribution over the genomes were calculated using DistAMo webapp34. DistAMo scores motif frequency on the basis of codon redundancy. For example, if a motif exists in a query, but it could be replaced with a different sequence to yield the same codon, then that motif is scored as enriched. Conversely, if a motif could be substituted with another sequence to yield the same codon, but the motif does not exist in the query, then that region is scored as depleted. Z-scores are applied to genes and defined window sizes, with scores ≤  − 2 and ≥ 2 marked as significant. Window sizes, ranging from 50 to 500 kb and increasing incrementally by 50 kb, were used. The genes displaying significant values were investigated for function by translating the DNA sequences into protein FASTA-sequences and run in eggNOG-mapper35 with a minimum % of query coverage set to 80%. The clusters of orthologous groups (COG) functional category (https://www.ncbi.nlm.nih.gov/research/cog) was subsequently used to determine the function of each depleted or enriched gene. Regions displaying significant values were considered differentially enriched or depleted between the two strains and were subsequently investigated visually using Artemis36.

MspJI cleavage

MspJI was used to enzymatically verify the activity of predicted m5C methylation. The enzyme cleaves at a fixed distance (12/16 bases) away from m5C modifications, and the resulting fragments around the modified site (typically 30–32 bp long) are sequenced to determine the recognition site. MspJI cleavage was performed as previously described37. In short, DNA was digested with MspJI (New England Biolabs) and short fragments (< 100 bp) were purified using the Monarch PCR and DNA Cleanup Kit (New England Biolabs). Libraries were constructed using the NEBNext Ultra II DNA Library Prep Kit for Illumina (New England Biolabs) and sequenced. The bioinformatics analysis was performed as previously described37.

Results

Predicted restriction modification systems and associated DNA methylation

Analysis of the genomes using SEQWARE revealed 13 putative DNA MTase-encoding genes, representing a total of 11 RMS (Table 1) of Type II (n = 9) and Type III (n = 2). No Type I or Type IV systems were predicted. Based on homology to other characterized MTases, the targets sites of the MTases could be predicted.

Type II

m6A

Five m6A MTases belonging to three Type II RMS and two Type III RMS were predicted (Table 1).

The dam MTase was found intact in all 13 MenW isolates and a double-strand methylation was detected on the corresponding motif 5′-GATC-3′ by SMRT sequencing. The dam MTase has been reported to be replaced by the dam replacement gene drg in many meningococcal hyper-invasive lineages but absent from ST-11 clonal complexes38.

The RMS responsible for methylating 5′-GGTGA-3′ and its complement 5′-CCACT-3′ is made up of one m6A MTase (encoded by the NEIS2854 locus) and one m5C MTase (encoded by the NEIS2910 locus). In N. gonorrhoeae, the two MTases are followed by a REase to form the NgoAXVI system. In concordance with previous studies on N. meningitidis39, the MenW genomes in the present study contained an open reading frame (ORF) of the m6A MTase (encoded by NEIS2854) that was interrupted by a truncated galE gene involved in lipooligosaccharide (LOS) synthesis (Table 1). Downstream of this RMS are genes also involved in capsule synthesis, so it is therefore believed that a segment of these genes have recombined with the m6A MTase. Consistent with the interruption of the m6A MTase gene, and inconsistent detection of m5C by SMRT sequencing, no signal could be detected with SMRT sequencing for either of the motifs.

The MTase encoded by the NEIS0295 locus is likely responsible for the methylation of 5′-GAAGG-3′ detected by SMRT sequencing (Table 1; Fig. 1), in agreement with prediction by SEQWARE. A transposase inserted within the REase gene was found in all 13 genomes (Table 1). Transposases located both upstream and downstream of this RMS indicates that this system is mobile. A BLASTn search against the NCBI database and in the PubMLST database revealed that the inserted transposase in the REase gene is common among N. meningitidis isolates belonging to the ST-11 clonal complex.

Figure 1
figure1

Restriction-modification systems in the 13 isolates belonging to the N. meningitidis 2013 strain marked in blue and original UK strain in orange. Active genes (without inactivating mutations) are coloured: blue = active methylase, red = active restriction endonuclease (REase), purple = active very-short repair endonuclease. Motifs detected by single-molecule real-time sequencing or MspJI cleavage are black, grey = MspJI data not available. The tree on the left shows the phylogeny of the isolates based on single-nucleotide polymorphisms. Isolates from the Jamboree outbreak are marked on the right hand side in a black box, carriage isolates are marked with a star-shaped symbol.

m5C

Of the 11 predicted Type II MTases present in the 11 MenW strains, 6 are annotated as m5C in REBASE. Using MspJI (see Materials and Methods), we were able to search m5C activities in 6 of the 13 isolates, and all 6 isolates exhibited the same 4 motifs, only one of which was detected with SMRT sequencing, namely 5'-GCGCGC-3' (Table 1; Fig. 1).

The m5C modified base is very unstable and can undergo spontaneous deamination, resulting in a T-G mismatch, which can be repaired by very short repair endonucleases (VSR)40. Two RMS including VSR were detected in the MenW isolates; the NmeDI RMS containing a VSR and an REase predicted to recognize 5′-RCCGGY-3′ was found between the phenylalanyl-tRNA synthetase genes pheS and pheT (Table 1). The MTase M.Nme15193ORF2195 had no predicted target motif in REBASE but a BLAST search showed an 86% match to M.NmeDI, which in the study by Kwiatek et al41 was shown to recognize the degenerate sequence 5′-RCCGGB-3′ or in most reported cases 5′-RCCGGY-3′24. The other VSR-containing RMS was NmeAI, flanked by the NEIS1987 locus encoding the putative DNA helicase. M.NmeAI recognizes the sequence 5′-CCGG-3′41. ST-11 clonal complex meningococci often harbour NmeAI and NmeDI and lack the third RMS system NmeBI more often associated with ST-32 clonal complex isolates42. No methylation was detected in 5′-RCCGGY-3′ or 5′-CCGG-3′ by SMRT sequencing but activity was detected with MspJI cleavage.

The RMS with a MTase recognizing 5′-CCAGA-3′ was flanked by the hldA and hldD genes encoding a kinase and epimerase, respectively, which are LOS biosynthetic genes involved in ADP-heptose biosynthesis. The presence of the genes involved in this RMS is common among N. meningitidis in the PubMLST Neisseria database, mainly ST-11 clonal complex (24%), ST-41/44 clonal complex (17%) and ST-23 clonal complex (9%). A BLAST search revealed that this RMS is mainly restricted to N. meningitidis among the Neisseria species but also included two hits to N. lactamica. No methylation was detected by SMRT sequencing but the presence of 5′-CCAGA-3′ could be confirmed by MspJI cleavage (Table 1).

The 5′-GGNNCC-3′ motif was not detected by SMRT sequencing or MspJI enzymatic cleavage due to the inactivation through premature stop codons of the MTase M.Nme15193ORF5155P (NEIS1180) and REase Nme15123ORF5150P (NEIS1181) belonging to the NlaIV RMS. This RMS is one of the two most commonly occurring systems in N. meningitidis43 and also present in N. gonorrhoeae, N. lactamica, N. flavescens and N. polysacchareae44,45. The RMS is flanked by the genes leuD and leuB involved in leucine biosynthesis.

The only m5C motif detected by SMRT sequencing was 5′-GCGCGCGCR-3′, which is most likely a miscall for the motif 5′-GCGCGC-3′ as predicted by SEQWARE and detected by MspJI cleavage. Such miscalls by the PacBio software often occur with motifs containing m5C. The RMS consists of a REase and a MTase, both of which were complete in all of the isolates and therefore should be active. The genes were present mainly among N. meningitidis in the PubMLST Neisseria database, most commonly among ST-11 clonal complex (41%) and ST-41/44 clonal complex (28%) isolates. The genes in this RMS are flanked by a transposase upstream and a tRNA synthetase downstream of the RMS (Table 1).

Type III

Two type III RMS were predicted by SEQWARE containing the two phase variable MTases, ModA and ModB. All isolates had the modA12 and modB2 alleles, which are common among ST-11 clonal complex isolates (99% have this combination, 5.2% in other complexes)46. modB2 was switched off in 12 isolates due to the 5′-CCCAA-3′ repeat commonly known as the ON/OFF switch of this gene26. Only isolate 12-208 of the UK strain had an expressed modB2 although it should have been phase variable OFF, an indel corrected this to create a CDS. Additionally, modA12 was switched off in 11 isolates by the typical N. meningitidis 5′-AGCC-3′ repeat. Both motifs corresponding to the two Type III RMS were detected as methylated in one isolate in each strain (12-208 and 15-193), respectively, for which the modB2 and modA12 genes were switched off (Fig. 1).

Genome-wide analysis of modification profiles

The distribution of methylated positions in the 13 genomes was determined using SMRT sequencing. A total of five methylated motifs were detected, four m6A modified motifs (5′-GATC-3′, 5′-GAAGG-3′, 5′-CGAAT-3′ and 5′-ACACC-3′) and one m5C (5′-GCGCGCGC-3′), but again this extended sequence may reflect the difficulty of accurately calling m5C-containing motifs (Table 1, raw motif summaries in Supplementary Table 3). A minimum of 98.7% of m6A motifs were detected with SMRT sequencing and 19.2–60.2% of the m5C motif. This was expected as the kinetic signature of cytosine methylation is more subtle and therefore difficult to detect with SMRT sequencing19. This was also reflected in the interpulse duration ratios; the m6A modifications had a mean of 5.98 whereas the mean ratio for the m5C modification was 3.09 (Supplementary Table 3). Increased SMRT sequencing coverage in isolate 14-627 did not result in any additional m5C motifs being detected.

Comparative analysis of methylated motifs between the 2013- and original UK strain

The relative positions of the motifs in the genomes of two isolates representing the two MenW strains are shown in Fig. 2. The circular plots show a general even distribution of motifs throughout the genomes. No differential motifs were found between the two strains or pattern between the invasive Jamboree isolate and the carriers (Fig. 3).

Figure 2
figure2

Distribution of methylated bases in two N. meningitidis serogroup W isolates from the 2013 strain (top) and original UK strain (bottom), respectively. The relative positions of predicted methyltransferases are indicated on the outermost track: Type II, blue; Type III, maroon. The remaining coloured tracks display the location of methylated sites for each motif. From outer to inner: 5′-GATC-3′, green; 5′-GAAGG-3′, yellow; 5′-GCGCGC-3′ purple; 5′-ACACC-3′, grey; 5′-CGAAT-3′, pink. Tick marks display the genomic positions.

Figure 3
figure3

Phylogeny of the 13 N. meningitidis serogroup W isolates based on single-nucleotide polymorphisms (SNP), isolates belonging to the 2013 strain marked in blue and original UK strain in orange. Detected methylation motifs with single-molecule real-time sequencing are shown as black boxes. Isolates from the Jamboree outbreak are marked in a black box, carrier isolates are marked with a star-shaped symbol.

The only differences in motifs between isolates were 5′-ACACC-3′ and 5′-CGAAT-3′ which were encoded by the phase variable modA12 and modB genes, respectively. The motif frequencies of the two differentially expressed modA12 and modB were determined based on codon flexibility as protein-coding recruitments are the most common among selective forces on DNA sequence. Motif frequency was scored based on codon redundancy, motifs were scored as enriched if another sequence yielded the same codon and regions scored as depleted if another sequence could be substituted by the motif to yield the same codon but did not exist. Because regions with a high motif density are also regions with a high DNA methylation rate, the distribution of the enriched and depleted regions was determined and generally a similar pattern between the two strains was seen regarding both motifs (Supplementary Figure 1). However, there was one apparent difference in 5′-ACACC-3′ depleted regions between the two strains around 130 kb in the genomes, represented by a region of transposases.

A complete list of all loci that were significantly depleted or enriched and their corresponding z-scores are shown in Supplementary Tables 4 and 5. Seventy-nine loci were significantly enriched and 13 loci depleted of the 5′-ACACC-3′ motif in the 2013 strain (Fig. 4A; Supplementary Table 4) compared to 106 loci enriched and 5 loci depleted of the 5′-CGAAT-3′ motif in the original UK strain (Fig. 4B; Supplementary Table 5). Only minor differences in regions with significantly overrepresented/underrepresented motifs were found between the two strains and these were mainly in hypothetical genes, metabolic genes and genes involved in cellular process and signaling (Fig. 4). The major known functions of the loci with increased/decreased amounts of 5′-ACACC-3′ motif (Fig. 5A) were evenly distributed between functions of cellular processes and signaling, information storage and processing and metabolism, but highest in loci involved in replication, recombination and repair, in this case represented by transposases. The major functions of the loci with increased/decreased amounts of 5′-CGAAT-3′ motif (Fig. 5B) were on the contrary frequently found in loci with metabolic functions, specifically energy production and conversion, but also in loci with translational, ribosomal structure and biogenesis functions.

Figure 4
figure4

Venn diagram of the number of genes that had an overrepresentation (red font) and underrepresentation (blue font) of (a) 5′-ACACC-3′ motifs and (b) 5′-CGAAT-3′ motifs in each N. meningitidis strain (2013 strain in blue circles and original UK strain in orange circles). Pie charts show the functions of the genes in which the under and overrepresented motifs were found.

Figure 5
figure5

The Clusters of Orthologous Groups of proteins (COG) function classification of genes that were underrepresented (diagonal lines) or overrepresented (filled) of (a) the 5′-ACACC-3′ motif and (b) the 5′-CGAAT-3′ motif in the N. meningitidis 2013 strain and UK original strain. Yellow = metabolism, brown = information and storage processing, blue = cellular process and signalling, green = metabolism/cellular process and signalling.

Discussion

Meningococcal disease caused by serogroup W has been previously uncommon (< 5%)47 but has in the recent decade spread to all continents and become the dominant serogroup in parts of Europe, South America and Sub-Saharan Africa9, causing higher morbidity and mortality. This study represents the first description of the complete methylome of the two strains ‘2013 strain’ and the ‘original UK strain’ from the globally disseminated MenW ST-11 clonal complex.

The analysed meningococcal genomes showed 13 MTases and target sequences were assigned, but only 5 motifs were detected as methylated with SMRT sequencing. Six out of the 13 MTases were associated with cytosine methylation, more specifically m5C methylation. Cytosine methylation is difficult to detect using SMRT sequencing and although high sequencing coverage is recommended to increase the level of cytosine methylation detection this did not reveal any additional m5C methylation when attempted on one of the isolates in this study. Instead, enzymatic cleavage with MspJI was successfully performed on 6 of the 13 isolates to verify the m5C methylations associated with active MTases.

Among the 5 methylated motifs identified in this study, no strain-specific associations were seen and three of the motifs, namely 5′-GATC-3′, 5′-GAAGG-3′, 5′-GCGCGC-3′, were found in all 13 isolates. Four of the isolates included in the study were part of a Jamboree outbreak in Japan in 2015, one isolate was from an invasive case and the other three were collected from asymptomatic carriers in connection with the administration of antibiotic prophylaxis. No differences in methylation were seen between the invasive case and the carriers, however, it cannot be excluded that these three teenagers having been administrated prophylaxis could have developed invasive disease without the antibiotic treatment. Comparing methylation motifs with other serogroups is difficult as few studies have been performed on the entire methylome of meningococci, methylated motifs found in both MenW genomes in the present study and MenY genomes in our previous study48, showed that only 5′-GATC-3′ and 5′-ACACC-3′ were shared between the two serogroups. In addition, a study by Sater et al49 on serogroup A isolates, only the motifs 5′-CCGG-3′ and 5′-ACACC-3′ were shared with the serogroup W isolates in the present study.

In addition to investigating differences in methylated motifs between the two strains, we examined the two differentially methylated motifs for areas of local depletion or enrichment across the genomes. Only minor differences were found between the two strains, mainly in genes with unknown function. Among the genes with a known function, the 5′-ACACC-3′ motif was enriched in metabolic genes and 5′-CGAAT-3′ in genes involved in cellular process and signalling followed by metabolic genes. It is possible that these differences in methylation could have an effect on the transcription of these genes. Few genes were depleted, however, transposases were overrepresented in both overall depletion in all isolates and in difference in 5′-ACACC-3 depleted regions between the two strains. Transposases are involved in genome integration processes such as genomic rearrangements and gene duplications and the difference in presence of methylation in these genes might act as a genome stabilizing force. The function of methylation depletion or enrichment in prokaryotes remains largely unknown and therefore poorly investigated, however, increased depletion of methylation in transposases has also been described in viruses50.

We identified 11 complete RMS belonging to Type II and III in the 13 MenW isolates. All of the RMS were compiled in a typical ST-11 clonal complex manner previously described in N. meningitidis or confirmed through BLAST searches. The distribution of RMS are considered lineage-specific and could be involved in the restriction of DNA transfer between different lineages42. Budroni et al43 showed a correlation between the presence/absence of RMS and the phylogenetic structure of meningococci. Whole-genome sequencing of isolates belonging to different clonal complexes were divided into different phylogenetic clades according to the topology, resulting in clades of two clonal complexes. The phylogenetic clades had a specific set of RMS and since the stretch of gene conversion events was found to be longer in isolates within the same phylogenetic clade than between different clades, this suggests that RMS are important in the genesis and persistence of phylogenetic clades.

Neisseria meningitidis contain a number of phase variable DNA MTases (Mod), associated with Type III restriction-modification systems, which mediate epigenetic regulation by which meningococcal cells can alter complex phenotypes26,51,52,53. Mod expression may affect carriage or invasion by providing a mechanism that enables cells to variably express complex phenotypes and thereby facilitate a transition from carriage to invasive disease depending on environmental changes. N. meningitidis can harbour three different mod genes: modA, modB, and modD51,52. These share a similar overall structure but different mod alleles methylate different DNA sequences52,53,54 and regulate different phasevarions51,52. The genomes in this study all harboured the modA12 and modB2 alleles. modA12 containing N. meningitidis isolates with an expressed Mod protein have been associated with increased sensitivity to several antibiotics55 as well as differential expression when grown under iron-limiting conditions in six genes, some involved in iron-binding52. Random, reversible, hypermutation of repetitive DNA tracts within the open reading frame (ORF) of mod genes lead to frame shift mutations and ON/OFF switching of Mod expression. Only one of the isolates included in this study had modA12 ON and two isolates had modB2 ON. Inversely, the 5′-CGAAT-3′ and 5′-ACACC-3′ motifs were detected as methylated although the corresponding MTases encoded by the modB2 and modA12 genes were in OFF status in one isolate each. It is important to note that the samples ON/OFF status does not necessarily reflect the natural ON/OFF status and ratio of an in vivo bacterial population. Except for the modB2 and modA12 associated methylations, all MTases without stop codons and therefore predicted to be expressed, resulted in methylations that were detected by either SMRT sequencing or enzymatic cleavage with MspJI (Fig. 1). Previous studies on P. luminiscens56 and E. coli57,58 have found no major difference in methylation between various growth conditions, although this was not tested in the present study, the general overall concordance between the ON status of the genes that were not phase variable with the detected methylations suggest that this could also be the case for N. meningitidis.

In summary, this study is the first description of the complete methylomes of two strains belonging to the rapidly expanding MenW ST-11 clonal complex. No differences in motifs were found between the two strains of MenW, however, some regions, mainly involving transposases, were differentially enriched or depleted of specific methylation motifs arising from phase variable MTases. Previous studies on N. meningitidis have shown that the RMS are lineage-associated, the results from this study confirm these findings. Because the isolates in the present study belong to the same larger lineage structure, no differences in RMS were found between the strains. Overall, studies on methylomes such as this provide a framework for future investigation into the role of epigenetics in the evolution and disease pathogenicity of certain strains of this and other organisms.

Data availability

All genomes and methylation data (including motif summaries) have been deposited in Genbank under BioProject number PRJNA476247, genome accession Nos. CP030814-CP030826. Methylation data and motif summaries have also been deposited in REBASE. All genomes were also submitted to the PubMLST Neisseria database (http://pubMLST.org/neisseria/), identification numbers are shown in Supplementary Table 2.

References

  1. 1.

    Yazdankhah, S. P. & Caugant, D. A. Neisseria meningitidis: An overview of the carriage state. J. Med. Microbiol. 53, 821–832. https://doi.org/10.1099/jmm.0.45529-0 (2004).

    Article  PubMed  Google Scholar 

  2. 2.

    Caugant, D. A. Genetics and evolution of Neisseria meningitidis: Importance for the epidemiology of meningococcal disease. Infect. Genet. Evol. 8, 558–565. https://doi.org/10.1016/j.meegid.2008.04.002 (2008).

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Stephens, D. S., Greenwood, B. & Brandtzaeg, P. Epidemic meningitis, meningococcaemia, and Neisseria meningitidis. Lancet 369, 2196–2210. https://doi.org/10.1016/S0140-6736(07)61016-2 (2007).

    Article  PubMed  Google Scholar 

  4. 4.

    Taha, M. K. et al. Serogroup W135 meningococcal disease in Hajj pilgrims. Lancet 356, 2159. https://doi.org/10.1016/S0140-6736(00)03502-9 (2000).

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    von Gottberg, A. et al. Emergence of endemic serogroup W135 meningococcal disease associated with a high mortality rate in South Africa. Clin. Infect. Dis. 46, 377–386. https://doi.org/10.1086/525260 (2008).

    Article  Google Scholar 

  6. 6.

    Abad, R., Lopez, E. L., Debbag, R. & Vazquez, J. A. Serogroup W meningococcal disease: Global spread and current affect on the Southern Cone in Latin America. Epidemiol. Infect. 142, 2461–2470. https://doi.org/10.1017/S0950268814001149 (2014).

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Ladhani, S. N. et al. Increase in endemic Neisseria meningitidis capsular group W sequence type 11 complex associated with severe invasive disease in England and Wales. Clin. Infect. Dis. 60, 578–585. https://doi.org/10.1093/cid/ciu881 (2015).

    CAS  Article  PubMed  Google Scholar 

  8. 8.

    Krone, M. et al. Increase of invasive meningococcal serogroup W disease in Europe, 2013 to 2017. Euro Surveill https://doi.org/10.2807/1560-7917.ES.2019.24.14.1800245 (2016).

    Article  Google Scholar 

  9. 9.

    Booy, R., Gentile, A., Nissen, M., Whelan, J. & Abitbol, V. Recent changes in the epidemiology of Neisseria meningitidis serogroup W across the world, current vaccination policy choices and possible future strategies. Hum. Vaccin. Immunother. 15, 470–480. https://doi.org/10.1080/21645515.2018.1532248 (2019).

    Article  PubMed  Google Scholar 

  10. 10.

    Campbell, H. et al. Presentation with gastrointestinal symptoms and high case fatality associated with group W meningococcal disease (MenW) in teenagers, England, July 2015 to January 2016. Euro Surveill https://doi.org/10.2807/1560-7917.ES.2016.21.12.30175 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Lucidarme, J. et al. An international invasive meningococcal disease outbreak due to a novel and rapidly expanding serogroup W strain, Scotland and Sweden, July to August 2015. Euro Surveill https://doi.org/10.2807/1560-7917.es.2016.21.45.30395 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Eriksson, L. et al. Whole-genome sequencing of emerging invasive Neisseria meningitidis serogroup W in Sweden. J. Clin. Microb. https://doi.org/10.1128/JCM.01409-17 (2018).

    Article  Google Scholar 

  13. 13.

    Smith-Palmer, A. et al. Outbreak of Neisseria meningitidis capsular group W among scouts returning from the World Scout Jamboree, Japan, 2015. Euro Surveill https://doi.org/10.2807/1560-7917.ES.2016.21.45.30392 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Seib, K. L., Jen, F. E., Scott, A. L., Tan, A. & Jennings, M. P. Phase variation of DNA methyltransferases and the regulation of virulence and immune evasion in the pathogenic Neisseria. Pathog Dis. https://doi.org/10.1093/femspd/ftx080 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Srikhanta, Y. N., Maguire, T. L., Stacey, K. J., Grimmond, S. M. & Jennings, M. P. The phasevarion: A genetic system controlling coordinated, random switching of expression of multiple genes. Proc. Natl. Acad. Sci. U. S. A. 102, 5547–5551. https://doi.org/10.1073/pnas.0501169102 (2005).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Wion, D. & Casadesus, J. N6-methyl-adenine: An epigenetic signal for DNA-protein interactions. Nat. Rev. Microbiol. 4, 183–192. https://doi.org/10.1038/nrmicro1350 (2006).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. 17.

    Vanyushin, B. F., Mazin, A. L., Vasilyev, V. K. & Belozersky, A. N. The content of 5-methylcytosine in animal DNA: The species and tissue specificity. Biochim. Biophys. Acta 299, 397–403. https://doi.org/10.1016/0005-2787(73)90264-5 (1973).

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Korlach, J. & Turner, S. W. Going beyond five bases in DNA sequencing. Curr. Opin. Struct. Biol. 22, 251–261. https://doi.org/10.1016/j.sbi.2012.04.002 (2012).

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Flusberg, B. A. et al. Direct detection of DNA methylation during single-molecule, real-time sequencing. Nat. Methods 7, 461–465. https://doi.org/10.1038/nmeth.1459 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  20. 20.

    Lu, S. C. S-Adenosylmethionine. Int. J. Biochem. Cell Biol. 32, 391–395. https://doi.org/10.1016/s1357-2725(99)00139-9 (2000).

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Vasu, K. & Nagaraja, V. Diverse functions of restriction-modification systems in addition to cellular defense. Microbiol. Mol. Biol. Rev. 77, 53–72. https://doi.org/10.1128/MMBR.00044-12 (2013).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Roberts, R. J. et al. A nomenclature for restriction enzymes, DNA methyltransferases, homing endonucleases and their genes. Nucleic Acids Res. 31, 1805–1812. https://doi.org/10.1093/nar/gkg274 (2003).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Murray, N. E. Type I restriction systems: Sophisticated molecular machines (a legacy of Bertani and Weigle). Microbiol. Mol. Biol. Rev. 64, 412–434. https://doi.org/10.1128/mmbr.64.2.412-434.2000 (2000).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Roberts, R. J., Vincze, T., Posfai, J. & Macelis, D. REBASE—A database for DNA restriction and modification: enzymes, genes and genomes. Nucleic Acids Res. 43, D298-299. https://doi.org/10.1093/nar/gku1046 (2015).

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Rotman, E. & Seifert, H. S. The genetics of Neisseria species. Annu. Rev. Genet. 48, 405–431. https://doi.org/10.1146/annurev-genet-120213-092007 (2014).

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Srikhanta, Y. N., Fox, K. L. & Jennings, M. P. The phasevarion: phase variation of type III DNA methyltransferases controls coordinated switching in multiple genes. Nat. Rev. Microbiol. 8, 196–206. https://doi.org/10.1038/nrmicro2283 (2010).

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Bentley, S. D. et al. Meningococcal genetic variation mechanisms viewed through comparative analysis of serogroup C strain FAM18. PLoS Genet. 3, e23. https://doi.org/10.1371/journal.pgen.0030023 (2007).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  28. 28.

    Martin, P. et al. Experimentally revised repertoire of putative contingency loci in Neisseria meningitidis strain MC58: Evidence for a novel mechanism of phase variation. Mol. Microbiol. 50, 245–257. https://doi.org/10.1046/j.1365-2958.2003.03678.x (2003).

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Snyder, L. A. S., Butcher, S. A. & Saunders, N. J. Comparative whole-genome analyses reveal over 100 putative phase-variable genes in the pathogenic Neisseria spp. Microbiology (Reading) 147, 2321–2332. https://doi.org/10.1099/00221287-147-8-2321 (2001).

    CAS  Article  Google Scholar 

  30. 30.

    Chin, C. S. et al. Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data. Nat. Methods 10, 563–569. https://doi.org/10.1038/nmeth.2474 (2013).

    CAS  Article  PubMed  Google Scholar 

  31. 31.

    Treangen, T. J., Sommer, D. D., Angly, F. E., Koren, S. & Pop, M. Next generation sequence assembly with AMOS. Curr. Protoc. Bioinform. https://doi.org/10.1002/0471250953.bi1108s33 (2011).

    Article  Google Scholar 

  32. 32.

    Tatusova, T. et al. NCBI prokaryotic genome annotation pipeline. Nucleic Acids Res 44, 6614–6624. https://doi.org/10.1093/nar/gkw569 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Murray, I. A. et al. The methylomes of six bacteria. Nucleic Acids Res. 40, 11450–11462. https://doi.org/10.1093/nar/gks891 (2012).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Sobetzko, P. et al. DistAMo: a web-based tool to characterize DNA-motif distribution on bacterial chromosomes. Front. Microbiol. 7, 283. https://doi.org/10.3389/fmicb.2016.00283 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Huerta-Cepas, J. et al. eggNOG 5.0: A hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res 47, D309–D314. https://doi.org/10.1093/nar/gky1085 (2019).

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Rutherford, K. et al. Artemis: Sequence visualization and annotation. Bioinformatics 16, 944–945 (2000).

    CAS  Article  Google Scholar 

  37. 37.

    Cohen-Karni, D. et al. The MspJI family of modification-dependent restriction endonucleases for epigenetic studies. Proc. Natl. Acad. Sci. U. S. A. 108, 11040–11045. https://doi.org/10.1073/pnas.1018448108 (2011).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Jolley, K. A., Sun, L., Moxon, E. R. & Maiden, M. C. Dam inactivation in Neisseria meningitidis: Prevalence among diverse hyperinvasive lineages. BMC Microbiol. 4, 34. https://doi.org/10.1186/1471-2180-4-34 (2004).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Gunn, J. S. & Stein, D. C. The Neisseria gonorrhoeae S.NgoVIII restriction/modification system: A type IIs system homologous to the Haemophilus parahaemolyticus HphI restriction/modification system. Nucleic Acids Res. 25, 4147–4152. https://doi.org/10.1093/nar/25.20.4147 (1997).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    Kow, Y. W. Repair of deaminated bases in DNA. Free Radic. Biol. Med. 33, 886–893. https://doi.org/10.1016/s0891-5849(02)00902-4 (2002).

    CAS  Article  PubMed  Google Scholar 

  41. 41.

    Kwiatek, A., Kobes, M., Olejnik, K. & Piekarowicz, A. DNA methyltransferases from Neisseria meningitidis and Neisseria gonorrhoeae FA1090 associated with mismatch nicking endonucleases. Microbiology (Reading) 150, 1713–1722. https://doi.org/10.1099/mic.0.27011-0 (2004).

    CAS  Article  Google Scholar 

  42. 42.

    Claus, H., Friedrich, A., Frosch, M. & Vogel, U. Differential distribution of novel restriction-modification systems in clonal lineages of Neisseria meningitidis. J. Bacteriol. 182, 1296–1303. https://doi.org/10.1128/jb.182.5.1296-1303.2000 (2000).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Budroni, S. et al. Neisseria meningitidis is structured in clades associated with restriction modification systems that modulate homologous recombination. Proc. Natl. Acad. Sci. U. S. A. 108, 4494–4499. https://doi.org/10.1073/pnas.1019751108 (2011).

    ADS  Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Ambur, O. H., Frye, S. A., Nilsen, M., Hovland, E. & Tonjum, T. Restriction and sequence alterations affect DNA uptake sequence-dependent transformation in Neisseria meningitidis. PLoS ONE 7, e39742. https://doi.org/10.1371/journal.pone.0039742 (2012).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Sanchez-Buso, L., Golparian, D., Parkhill, J., Unemo, M. & Harris, S. R. Genetic variation regulates the activation and specificity of restriction-modification systems in Neisseria gonorrhoeae. Sci. Rep. 9, 14685. https://doi.org/10.1038/s41598-019-51102-2 (2019).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Tan, A. et al. Distribution of the type III DNA methyltransferases modA, modB and modD among Neisseria meningitidis genotypes: Implications for gene regulation and virulence. Sci. Rep. 6, 21015. https://doi.org/10.1038/srep21015 (2016).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Rosenstein, N. E. et al. The changing epidemiology of meningococcal disease in the United States, 1992–1996. J. Infect. Dis. 180, 1894–1901. https://doi.org/10.1086/315158 (1999).

    CAS  Article  PubMed  Google Scholar 

  48. 48.

    Stenmark, B. et al. Complete genome and methylome analysis of Neisseria meningitidis associated with increased serogroup Y disease. Sci. Rep. 10, 3644. https://doi.org/10.1038/s41598-020-59509-y (2020).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  49. 49.

    Sater, M. R. et al. DNA methylation assessed by SMRT sequencing is linked to mutations in Neisseria meningitidis Isolates. PLoS ONE 10, e0144612. https://doi.org/10.1371/journal.pone.0144612 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Coy, S. R. et al. SMRT sequencing of Paramecium bursaria Chlorella virus-1 reveals diverse methylation stability in adenines targeted by restriction modification systems. Front. Microbiol. 11, 887. https://doi.org/10.3389/fmicb.2020.00887 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  51. 51.

    Seib, K. L. et al. A novel epigenetic regulator associated with the hypervirulent Neisseria meningitidis clonal complex 41/44. FASEB J. 25, 3622–3633. https://doi.org/10.1096/fj.11-183590 (2011).

    CAS  Article  PubMed  Google Scholar 

  52. 52.

    Srikhanta, Y. N. et al. Phasevarions mediate random switching of gene expression in pathogenic Neisseria. PLoS Pathog. 5, e1000400. https://doi.org/10.1371/journal.ppat.1000400 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Seib, K. L. et al. Specificity of the ModA11, ModA12 and ModD1 epigenetic regulator N(6)-adenine DNA methyltransferases of Neisseria meningitidis. Nucleic Acids Res. 43, 4150–4162. https://doi.org/10.1093/nar/gkv219 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Adamczyk-Poplawska, M., Lower, M. & Piekarowicz, A. Characterization of the NgoAXP: phase-variable type III restriction-modification system in Neisseria gonorrhoeae. FEMS Microbiol. Lett. 300, 25–35. https://doi.org/10.1111/j.1574-6968.2009.01760.x (2009).

    CAS  Article  PubMed  Google Scholar 

  55. 55.

    Jen, F. E., Seib, K. L. & Jennings, M. P. Phasevarions mediate epigenetic regulation of antimicrobial susceptibility in Neisseria meningitidis. Antimicrob. Agents Chemother. 58, 4219–4221. https://doi.org/10.1128/AAC.00004-14 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Payelleville, A. et al. The complete methylome of an entomopathogenic bacterium reveals the existence of loci with unmethylated Adenines. Sci. Rep. 8, 12091. https://doi.org/10.1038/s41598-018-30620-5 (2018).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Westphal, L. L., Sauvey, P., Champion, M. M., Ehrenreich, I. M. & Finkel, S. E. Genomewide dam methylation in Escherichia coli during long-term stationary phase. mSystems https://doi.org/10.1128/mSystems.00130-16 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Cohen, N. R. et al. A role for the bacterial GATC methylome in antibiotic stress survival. Nat. Genet. 48, 581–586. https://doi.org/10.1038/ng.3530 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This study was funded by ALF, Region Örebro County, Sweden. The sequencing service was provided by the Norwegian Sequencing Centre (www.sequencing.uio.no), a national technology platform hosted by the University of Oslo and supported by the "Functional Genomics" and "Infrastructure" programs of the Research Council of Norway and the Southeastern Regional Health Authorities.

Funding

Open access funding provided by Örebro University.

Author information

Affiliations

Authors

Contributions

B.S.: Conceptualization, formal analysis, investigation, writing of the original draft. L.E.: Formal analysis, review and editing of the text. B.P.A.: Formal analysis, validation, resources, investigation, review and editing of the text. A.F.: Formal analysis, validation, resources, investigation. S.T.H.: Conceptualization, methodology, review and editing of the text. R.J.R.: Conceptualization, methodology, Investigation, review and editing of the text. P.M.: Conceptualization, methodology, funding acquisition, review and editing of the text.

Corresponding author

Correspondence to Bianca Stenmark.

Ethics declarations

Competing interests

RJR, BPA, and AF work for New England Biolabs, a company that sells research reagents including restriction enzymes and DNA methyltransferases to the scientific community. The commercial affiliation of these authors does not alter our adherence policies on sharing data and materials. All other authors have no conflicts to declare.

Additional information

Publisher's note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Stenmark, B., Eriksson, L., Thulin Hedberg, S. et al. Genome-wide methylome analysis of two strains belonging to the hypervirulent Neisseria meningitidis serogroup W ST-11 clonal complex. Sci Rep 11, 6239 (2021). https://doi.org/10.1038/s41598-021-85266-7

Download citation

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing