Abstract
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.
Similar content being viewed by others
Introduction
Neisseria meningitidis, the meningococcus, is a human-specific bacterium that exists as a commensal in approximately 10% of the population1; however, some meningococci are associated with severe pathology with rapid disease onset of sepsis and/or meningitis2,3. Although certain host factors have been identified that contribute to disease susceptibility (including age, medical conditions and genetic factors2,4,5), the precise mechanisms that determine invasive potential and that mediate transition of a given meningococcus from carriage to invasive disease remain unclear. Invasive isolates are typically characterized as one of six capsule-based meningococcal serogroups (A, B, C, X, Y and W). These are globally distributed with varying rates of disease incidence6. Meningococci are characterized at the genetic level by multi locus sequence typing (MLST), which uses sequences of seven housekeeping genes to determine isolate sequence type (ST)7. Groups of closely related STs are termed clonal complexes (cc) and these are good surrogates of bacterial lineage. A subset of clonal complexes, known as hyperinvasive (or hypervirulent) lineages, is responsible for the majority of disease worldwide. These hyperinvasive lineages are significantly overrepresented in collections of invasive isolates (i.e. those from blood or cerebrospinal fluid) relative to collections of asymptomatic carriage isolates (i.e., those from the nasopharynx), and include cc4/5, cc8, cc11, cc32, cc41/44, and cc2697,8,9,10. On the other hand, meningococci isolated from asymptomatic carriers consist of highly diverse genotypes with some clonal complexes, such as cc23, cc35, cc106 and cc116, very rarely if ever associated with invasion10. Even amongst the hyperinvasive lineages, different genotypes often vary in pathogenicity; for example within the cc41/44 lineage, ST-41 meningococci are more commonly associated with disease, and ST-44 with carriage10.
Attempts to identify the specific factors responsible for differential virulence of N. meningitidis strains have been largely unsuccessful. Whilst numerous factors important for virulence have been identified (e.g. capsule, pili, lipooligosaccharide (LOS) and opacity proteins)11, there are no virulence factors that clearly distinguish highly pathogenic isolates that cause invasive disease from less pathogenic isolates. Many proteins considered to be key virulence determinants are also present in N. meningitidis carriage isolates and commensal Neisseria species12,13,14. Indeed, most meningococcal isolates have a similar overall genome composition, consisting of 79% core genes, 21% accessory genes and less than 0.1% strain specific genes15, with a core meningococcal genome of approximately 1600 genes15,16. Restriction-modification systems are among the few isolate and clonal complex-specific genes identified15,17. Other genetic elements associated with invasive isolates include the hmbR hemoglobin receptor gene18 and a prophage12,19,20; however, the mechanistic contribution of these factors to virulence is unclear. Consequently, the pathogenic potential of isolates is hypothesized to be a polygenetic phenomenon arising from varied adhesin and metabolic gene content, and expression differences21,22.
While meningococci are considered to have relatively few transcriptional regulators when compared to other bacterial species23, they do contain numerous phase variable genes24,25,26 and differential gene expression provides a possible explanation for phenotypic differences. Furthermore, N. meningitidis contain a number of phase variable DNA methyltransferases (Mod), associated with type III restriction-modification systems, which mediate epigenetic regulation27,28,29,30. Random, reversible, hypermutation of repetitive DNA tracts within the open reading frame of mod genes lead to frame-shift mutations and the ON/OFF switching of Mod expression (i.e., phase variation). Mod phase variation results in distinct bacterial populations with different patterns of genome methylation, and altered expression of specific sets of genes. These phase variable regulons have been defined as phasevarions29,31. Mod phasevarions studied to date in pathogenic Neisseria have been shown to contain genes encoding outer membrane proteins, stress response proteins and other metabolic components27,28. These phasevarions represent an epigenetic mechanism by which meningococcal cells can alter complex phenotypes, which may affect carriage or invasion.
Three mod genes have been described in N. meningitidis: modA, modB, and modD27,28. These share a similar overall structure, with N-terminal simple DNA repeats, N- and C-terminal domains that mediate DNA methylation, and a central DNA recognition domain (DRD) that determines the recognition and methylation site of the enzyme (See Fig. 1a). For each of the modA, modB, and modD genes, different alleles have been identified that have conserved N- and C-terminal domains (>90% amino acid identity), but which vary in the DRD sequence (>95% amino acid identity within alleles, and typically <40% identity among alleles). Different mod alleles (i.e. DRD variants) methylate different DNA sequences28,30,32 and regulate different phasevarions27,28. The modA gene has the highest known allelic diversity, with 20 known alleles (modA1-20), many of which are found in Haemophilus influenzae (modA1-10, modA14-17, modA20) and/or N. meningitidis (modA4, modA11-13, modA15, modA18-19)28,33. In contrast, only four modB alleles have been reported: modB1, modB228, modB334 and modB415. The modB gene has only been found in Neisseria species to-date, with modB1 found in N. meningitidis and N. gonorrhoeae, modB2 and modB4 in N. meningitidis28, and modB3 in Neisseria lactamica29. The modD gene also appears to be Neisseria specific, and has five known alleles: modD1 and modD2 in N. meningitidis, modD3 in N. lactamica, modD4 in Neisseria cinerea and modD5 in Neisseria mucosa27. To date, the DNA methylation target sequences of N. meningitidis ModA11, ModA12 and ModD130; N. gonorrhoeae ModA13 and ModB128,32; H. influenzae ModA1, ModA2, ModA4, ModA5, ModA9 and ModA1035; and M. catarrhalis ModM2 and ModM3 have been determined36, with a unique site methylated by each allele. This study surveyed the distribution and combination of mod genes and their associated alleles in four N. meningitidis isolate collections, and identified their association with certain hyperinvasive lineages. These data are consistent with Mod proteins playing a role in the survival of meningococci in the different environments encountered during colonization and invasion in the human host.
Results
Distribution of mod genes and alleles
To investigate the distribution of mod genes and alleles in N. meningitidis (Fig. 1), 1,689 isolates were surveyed, comprising 211 carriage and 1,478 disease isolates from four collections originating in diverse geographic locations (including the USA, UK, Czech Republic, and Australia) and time periods (1993–2013). These analyses determined that a modA gene was present in all isolates examined (although two isolates possessed only fragments of modA). A modB gene was identified in 78% (1,298) of isolates, while a modD gene was present in only 25% (423) of isolates (Fig. 2). Overall, 364 isolates contained modA only, 900 isolates contained both modA and modB, and 398 isolates contained modA, modB and modD genes. The number of DNA repeat units among isolates ranged from 2–34 tetranucleotide repeats in modA; 2–28 pentanucleotide repeats in modB; and 2–15 pentanucleotide repeats in modD (Fig. 1). Phase variation of tetranucleotide repeat tracts containing ≥3 repeat units occurs at a high frequency37, and the majority of these mod genes are predicted to be phase variable (>98% of fully assembled alleles contain ≥3 repeat units).
For each of the three mod genes, common and rare mod alleles (DRD variants) were found (Figs 1 and 2). The majority of modA positive isolates contained modA12 (1,159 isolates, 70%) or modA11 (456 isolates, 27.5%), with modA15 comprising 2% of modA positive isolates (38 isolates) (Figs 1b and 2b). All other modA alleles were found at low frequency in the dataset, two of which, modA2 and modA6, had not been reported in N. meningitidis before. In addition, several minor variations in the conserved regions of the modA11 and modA12 were seen among the isolates. The most frequent of these was a 15-nucleotide deletion (encoding [S(A/V)KNQ]) in the region encoding the C-terminus of ModA (Fig. 1b), found in 67% of modA11 alleles and 59% of modA12 alleles (Fig. 2b). This deletion removed 5 amino acids from the full length of the protein. In addition, the N-terminal, phase variable DNA repeat sequences were altered in some isolates. The typical modA repeat unit in N. meningitidis was 5′-AGCC-3′, however modA11 in 27 isolates (6% of modA11 isolates; 1.6% of total modA positive isolates) had 5′-AGTC-3′ repeats (Fig. 2b).
For modB, the most common alleles were modB1 (543 isolates, representing 42% of all modB positive isolates) and modB2 (642 isolates, 49%), with modB4 present in 7.6% of modB positive isolates (Figs 1c and 2c). All other modB alleles were found at low frequency, including two new alleles (modB5 and modB6), which have not previously been defined. The modB5 and modB6 DRDs shared 11–48% identity at the deduced amino acid level with other modB alleles (Fig. 1c). Both were present at low frequency, with 9 modB5 isolates (0.7%) and 1 modB6 isolate (0.08%) identified. For modB1 and modB2, the typical repeat unit was 5′-CCCAA-3′, with an alternate 5′-GCCAA-3′ repeat tract seen in 17% of modB1 alleles and 13% of all modB2 (Fig. 2c). modB3 had both 5′-CCCAA-3′ and 5′-TCCAA-3′ repeats, and modB4 and modB5 typically contained 5′-GCCAA-3′ repeats.
The majority of modD positive isolates contained the modD1 allele (316 isolates, 75%), or modD6 (72 isolates, 17%; Figs 1d and 2d). All other modD alleles were found at low frequency, including modD3 that has not been reported in N. meningitidis before, modD6 that was previously identified in N. meningitidis 6938 but mis-categorized as modD238,39, and modD7 that has not previously been identified. The novel modD7 allele was present in 5 isolates (1.2% of modD positive isolates), and shared 7–15% identity with other modD alleles over the length of the DRD (Fig. 1d). In addition, this allele had an extended DRD, with an additional 47 amino acids at the C-terminal end of the DRD, compared to other modD alleles (Fig. 1d).
Associations among different mod alleles were also identified. For example, of those meningococci containing only modA and modB, 71% of isolates with modB1 also contained modA11, while 96% of isolates with modB2, and 89% of isolates with other modB alleles, were associated with modA12. Furthermore, 86% of isolates with a modD gene also contained modA12 and modB2, which rose to 97% in isolates containing the modD1 allele.
Specific mod genes are associated with distinct clonal complexes
Examination of the distribution of mod in the dataset demonstrated that most mod genes and alleles were associated with specific sequence types and clonal complexes (Table 1). ModA11, modA12, modB1 and modB2 alleles were found in multiple clonal complexes and the majority of isolates from the same clonal complex contained the same allele. For example, modA11 was present in cc32 (97% of cc32 isolates) and cc116 (85%), whereas modA12 was present in cc11 (99%) and cc23 (97%) isolates. The C-terminal deletion variations were also clonal complex associated, with the modA11 C-terminal deletion found in cc35 (82%), cc53 (91%) and cc269 (85%), and the modA12 C-terminal deletion found in cc41/44 (97%) and cc213 (89%) meningococci. The modB1 allele was found in cc269 (86%), and cc32 (100%), and the modB2 allele was associated with cc41/44 (76%) and cc11 (100%) isolates; however, modB was absent in all cc23, cc53, cc92, cc106, cc116 and cc461 meningococci examined. ModB1 and modB2 sequences with non-typical repeat tracts were frequently found in cc60 (82%) and cc22 (81%), respectively. On the other hand, the less common alleles were associated with a single clonal complex, for example, modA15 was associated with cc92 (present in 95% of cc92 meningococci vs. 0.1% of other clonal complexes, p < 0.0001), modB4 with cc213 (90% vs. 0.3%, p < 0.0001), and modD1 with cc41/44 (80% vs. 0%, p < 0.0001) (Table 1).
Further associations between mod alleles and clonal complexes were identified when mod allelic combinations were mapped onto a Ribosomal Multilocus Sequence Typing (rMLST) network of the twelve most frequently represented clonal complexes in this dataset (cc106, cc11, cc116, cc18, cc213, cc22, cc23, cc269, cc32, cc41/44, cc53 and cc92) with certain combinations more evident than others (Fig. 3, Supplementary Table 1). For example, modA11 alone (i.e., without modB or modD) was present in 91% of cc53 and 85% of cc116 isolates (vs. 1.8% of isolates from other complexes; p < 0.0001), modA12 alone was present in 100% of cc106, 99% of cc23 and 100% of cc461 isolates (vs. 1.7% in other complexes, p < 0.0001), while modA15 alone was present in 95% of cc92 isolates (vs. 0.1% in other complexes; p < 0.0001). The modA11-modB1 combination was found in 89% of cc269 and 99% of cc32 isolates (vs. 1.2% in other complexes, p < 0.0001); while the modA12-modB2 combination was found in 99% of cc11 isolates (vs. 5.2% in other complexes, p < 0.0001); however, the mod- clonal complex associations were not always completely conserved. For example, cc18 isolates did not share a common allelic combination, and cc41/44 isolates were clustered into two groups, one including ST-41 and the other ST-44 isolates. The ST-41 cluster was associated with modA12, modB2 and modD1 (78% of isolates, with this combination not seen in other complexes, p < 0.0001) whereas the ST-44 cluster was associated with modA12 and modB2 but lacked modD1 (16% of ST-44 isolates vs. 3.8% in other complexes, p < 0.0001; Fig. 3). Similarly, most cc22 isolates contained the modA12-modB2-modD6 combination, but a smaller cluster of isolates had modA12-modB1-modD6. The majority of cc269 isolates possessed modA11-modB1, however one cluster was associated with modA11-modB2 (Fig. 3).
Specific mod genes and combinations are associated with invasive or carriage meningococci
Given that different mod alleles regulate distinct sets of genes (phasevarions) that affect the phenotype of the isolate, the distribution of mod alleles relative to the isolate’s disease outcome (i.e., invasive disease or carriage) was considered. Several associations were observed among mod alleles and invasive or carried meningococci, and these associations were particularly strong for atypical alleles and allelic combinations. For example, modA11 and modB2 were more commonly associated with invasive, rather than carriage, isolates (respectively, 29% vs. 13% for modA11 (p < 0.0001); 40% vs. 28% for modB2 (p = 0.002); Table 2). The modA12-modB2-modD1 combination was associated with cc41/44 invasive isolates (20% invasive vs. 0% carriage, p < 0.0001), while carriage isolates from this clonal complex possessed modA12-modB1 but lacked modD1 (87% carriage vs. 9% invasive with modA12-modB1, p < 0.0001) (Fig. 3). The modA12-modB4 combination was associated with cc213 invasive isolates and was only found in two carriage isolates of different sequence types (6.5% of invasive isolates vs. 1% carriage, p = 0.0004). Also, the modA11-modB1 combination was associated with invasive isolates, and present in hyperinvasive lineages cc32 and cc269 (22% of invasive vs. 2.4% carriage isolates, p < 0.0001). The atypical modA15 allele was usually found alone and in cc92 carriage isolates (12% of total carriage isolates vs. 0.2% of invasive isolates, p < 0.0001).
Discussion
The phase variable type III DNA methyltransferases encoded by the modA, modB and modD genes are a global control mechanism by which N. meningitidis can randomly alter the expression of distinct sets of genes, known as phasevarions29. Several alleles of each of the mod genes have been characterized, based on differences in the region encoding the DNA recognition domain (DRD), each of which methylates a different sequence and mediates the epigenetic regulation of different sets of genes28,30. Many isolates contain multiple mod genes (i.e., have multiple phasevarions) which can phase vary independently. This enables the reversible induction of polygenetic phenotypes, which increases bacterial adaptability to distinct ecological environments and may affect invasive capacity. For example, the phase variable ON/OFF switching of meningococcal ModD1 alters resistance to oxidative stress27, while phase variation of ModA11 and ModA12 results in altered antibiotic resistance40. Similarly, previous studies of the gonococcal ModA13 phasevarion have shown that ON/OFF variants have distinct phenotypes for biofilm formation, resistance to antimicrobials, and survival in primary human cervical epithelial cells28.
Our analysis of the distribution of mod genes and alleles in meningococci isolated from carriage and invasive disease revealed high levels of diversity in type III DNA methyltransferases and their respective DRD regions, and identified associations between mod alleles and clonal complexes. These clonal complexes included both hyperinvasive lineages, responsible for the majority of disease worldwide (e.g., cc11, cc32, cc41/44, and cc269), as well as those that are rarely associated with invasive disease (e.g., cc35, cc92, cc106 and cc116)7,8,9,10,41. While some alleles, such as modA12, were found in both hyperinvasive (cc11 and cc41/44) and non-invasive (cc106) lineages, some alleles were more commonly associated with one or the other. For example, in terms of hyperinvasive lineages, modA11 was associated with cc32 isolates, modB1 with cc269 and cc32 isolates, and modD1 with cc41/44 isolates. This is consistent with previous studies conducted in smaller datasets27,28. The modA11-modB1 combination was associated with hyperinvasive lineages cc32 and cc269; and the modA12-modB2-modD1 combination with the hyperinvasive ST-41 cluster. On the other hand, the modA15 allele was predominantly found in isolates of the cc92 lineage, which is a non-invasive lineage. Furthermore, the distribution of mod alleles relative to the disease outcome or phenotype of each isolate (i.e., invasive or carriage) showed associations of atypical alleles and allelic combinations with invasive or non-invasive meningococci. For example, modA11-modB1, modA12-modB2-modD1 and modA12-modB4 combinations were associated with invasive isolates, while modA15 or the modA12-modB1 combination were associated with isolates from carriage collections. While the mod alleles could be considered a marker of clonal complex rather than infection outcome, it is important to note that there is not always a strict correlation between clonal complex and infection outcome. This is highlighted within the cc41/44 lineage that contains two central STs, where ST-41 meningococci are commonly associated with invasive disease, while ST-44 are typically associated with carriage10. The distribution of modD1 in this clonal complex is specifically associated with invasive disease; modD1 is present in 84% of cc41/44 invasive isolates (105/105 ST-41 and 203/259 other STs) compared to 0% of cc41/44 carriage isolates (0/8 ST-44 and 0/22 other STs). Future experimental work will clarify whether the observed associations directly correspond to a difference in the phenotype and virulence of strains. An increased focus should also be placed on collecting and sequencing carriage isolates, as to date these are underrepresented in the available meningococcal isolate panels.
Several questions remain regarding the evolution of mod diversity, the frequency of mod allele mobilization, and whether the repertoire is being neutrally inherited, or selectively maintained. These data suggest that the more commonly found alleles (e.g., modA11, modA12, modB1 and modB2), along with their allelic combinations, may have been acquired early in the evolution of N. meningitidis, and have been successively inherited by vertical transmission from progenitor cells that have differentiated into multiple clonal complexes. The rarer alleles, and differences in mod allele combinations, may have arisen from more recent horizontal gene transfer (HGT) and recombination events common to Neisseria13,38,39,41,42,43. For example, the discovery of single isolates containing the modA2, modA4, modA6, and two isolates with modD3 alleles is consistent with HGT in N. meningitidis. Transfer and replacement of alleles is possibly enhanced by the structure of the mod genes, as the conserved flanking regions may facilitate homologous recombination and replacement of the central variable DRD. This has previously been reported for the modA gene, with sequence analysis suggesting some DRDs originated from other bacterial species33. Similarly, the distribution of several alleles (e.g., modA2, modA6, modD3 identified in N. meningitidis for the first time) suggests horizontal mobilization of DNA from outside the species44,45,46, as these alleles have been previously identified in H. influenzae, N. polysaccharea and N. lactamica27,29,33. In order to investigate the temporal and geographical nature of the associations seen, more diverse and long-term isolate collections are needed. However, it can be noted that the some associations, such as that seen between cc11 isolates and modA12 and modB1, are consistent in all the collections over the time period, while others are more specific to certain locations but may reflect the invasive or carriage focus of the collections, for example, the cc92 carriage isolates associated with the modA15 allele are largely isolates from 1993 from the Czech carriage study: whereas modD1 is associated with invasive isolates from the UK and Australian collections.
The evolution and biological significance of the 15-nucleotide C-terminal deletion and the DNA repeat tract variants are unknown. The C-terminal deletion does not affect the well-described conserved motifs of type III Mods, such as the catalytic region (DPPY) and the S-adenosyl-L-methionine methyl donor-binding pocket (FXGXG) (See Fig. 1a)29,47,48, and ModA12 has been shown by methylome analysis to be functional in strains with (M0579) or without (B6116/77) this deletion30. It is noteworthy, however, that the typical 5′-AGCC-3′ modA repeat tract is recognized by the ModD methyltransferase DNA recognition domain. Previous studies propose that methylation within gene coding regions may alter transcription45: this may suggest that variations arise as a mechanism to circumvent methylation of the repeat tract.
Previous studies posit that meningococcal restriction-modification systems, such as the type III systems that the mod genes are part of, are clade associated, and maintain barriers to gene transfer between groups15; however, other studies suggest that genome recombination is more frequent than expected38, and that restriction-modification systems do not necessarily prevent genetic transfer, either because they are being mobilized themselves, or due to transient or inefficient function39. This latter point may be particularly true for the mod alleles, given that Mod is phase variable and the restriction enzyme is dependent on the presence of Mod in type III restriction-modification systems, and that inactivating mutations can be found in the cognate restriction enzymes in some systems28,49. If this is indeed the case, then the selective maintenance of the mod allele repertoire may be attributable to the epigenetic regulatory functions of Mod, as has previously been suggested to explain the dominance of the modA12 allele in N. meningitidis33. To support this hypothesis, full characterization of strains, and the phasevarions regulated by Mod proteins is needed. These studies will clarify the significance of mod allele and clonal complex associations, and how ON/OFF switching affects the phenotype of N. meningitidis, especially in light of the fact that isolates can contain up to three distinct mod alleles and phasevarions. Given that each mod allele can phase vary independently, each isolate can give rise to eight possible distinct sub-populations. These variants would appear genetically identical, differing only in the loss or gain of a few repeat units in the mod gene, but would have profound differences in gene expression and potentially in their invasive phenotype. It is also important to note that the potential fluidity of allelic exchange of mod alleles means that with a single gene recombination event, N. meningitidis strains may acquire a new mod allele and the ability to regulate genes in a different phasevarion, and consequently display a different phenotypic profile.
In terms of mod allele associations with invasive meningococci, it is important to note that disease does not increase the fitness of meningococci as there is no corresponding benefit to transmission50. However, if certain Mod proteins do increase the invasiveness of certain clonal complexes, the fact that Mod expression is phase variable would allow the Mod regulatory system to be maintained. For example, even under conditions where Mod ON is deleterious or increases the probability of invasion, cells with Mod in phase OFF may persist, in which case, selective pressure against mod is removed without affecting the future function of the Mod regulatory system or bacterial fitness. Accordingly, these alleles provide a mechanism that enables cells to variably express complex phenotypes, which may facilitate a transition from carriage to invasion and vice versa depending on environmental changes. If so, this may help elucidate how transmissibility and virulence are linked in meningococcal lineages43. Hence, the study of these regulators, and how they change over time, may provide critical insights into how and why N. meningitidis cells generate distinct phenotypes without overt changes in gene content, and how this may mediate transition from carriage to invasive disease. While it is tempting to speculate on the ON vs. OFF status of the Mods from the available genome sequences, it is important to note that the samples used for sequencing were not collected for this purpose and are therefore not an accurate reflection of the natural ON/OFF status and ratio of the in vivo bacterial population. Therefore, unlike past epidemiological studies that typically isolate and characterize single meningococcal colonies from patient samples, future studies will require direct and unbiased sequencing, or the isolation of representative populations, of bacteria from blood, cerebrospinal fluid and the nasopharynx. The characterization of the presence and expression state of individual mod alleles in these samples will help determine the significance of mod allele distribution relative to meningococcal carriage and disease.
Methods
N. meningitidis isolate collections
Four N. meningitidis isolate collections were analyzed in this study: i) 20 previously characterized whole-genome sequences (WGS) from 18 disease and two carriage isolates12,15,25,51,52,53; ii) WGS from 54 disease and 209 carriage isolates from the Czech Republic41,43; iii) WGS data from 1380 disease isolates in the Meningitis Research Foundation (MRF) Meningococcus Genome Library (MGL) (www.meningitis.org/current-projects/genome)62; and, iv) 50 disease isolates from Australia54.
Screening for mod genes
The mod genes were identified by bioinformatic analysis of WGS data using the BIGSdb platform hosted on pubmlst.org/neisseria55. Locus records for modA (NEIS1310), modB (NEIS1194) and modD (NEIS2364) were generated in the PubMLST database (http://pubmlst.org/neisseria)55 using previously identified reference modA and modB nucleotide sequences from N. meningitidis MC5828,53 and the modD sequence from N. meningitidis M057915,27. The BIGSdb ‘Scan Tag’ tool56 was implemented for the identification of mod loci within WGS data of each isolate, returning BLAST matches greater than 30% alignment and 50% identity to the sequences stored in locus records. The nucleotide diversity of mod loci required that hits be exported to MEGA657 for manual alignment with previously identified (see reference alleles below) full length mod coding sequences and DNA recognition domain (DRD) based alleles. For example, alignment gaps were inserted in the phase variable repeat region of phase OFF sequences to allow comparison with the full-length translated amino acid sequence. Trimmed sequences were uploaded to the appropriate locus record for storage where they were assigned unique numeric identifiers (allele id numbers), and grouped into variants based on the DRD (corresponding to the mod alleles described below). Database alleles were flagged with information such as phase-variation status and where the open reading frame was interrupted due to insertions, deletions or point mutations (other than changes to the number of phase variable repeat units), and database alleles were assigned the flags ‘internal stop codon’ and ‘frameshift’ where necessary. These interrupted alleles were not included in the analysis of invasive versus carriage meningococci. The BIGSdb ‘autotagger’ and ‘autodefiner’ tools56 were then used to identify mod genes within genomic data stored for each isolate, allowing tagging of nucleotide positions and database allele id numbers.
The mod loci were frequently present on different contiguous sequences of a genome assembly due to break points within phase variable regions or insertion sequences: this permitted identification of the presence of a mod gene and its allele, but not assignment of a database allele id number. In these cases, a database flag was inserted at these genomic positions to indicate a partial assembly, and isolates were considered to contain mod genes but were not included in subsequent allele analyses. This process was performed iteratively until no new alleles of the three mod genes could be identified in the genomes; at this stage, genomes without tagged mod genes were investigated using implementations of the BIGSdb BLAST tool (parameters: word size 11; reward 2; penalty -3; gap open 5; gap extend 2). For each locus variant, six hits were investigated per isolate, regardless of E-value significance, and 1000 bp of flanking sequence were extracted with the hit for investigation in MEGA6; new alleles were uploaded to the database as before, otherwise genomes were tagged as ‘missing’ mod loci.
To screen for mod genes and alleles in the Australian disease isolates (no WGS available), PCR and sequencing analyses was performed as previously described27,28. MLST analysis was performed in accordance with the scheme guidelines (http://pubmlst.org/neisseria/info/)55.
Sequence alignments were performed using ClustalW58 and were exported into Jalview59 to generate alignment Figures. The Neighbor-Net graph was generated in SplitsTree460 from allelic distances among the 49 rMLST loci of unique ribosomal Sequence Types (rSTs) (n = 639)61 among clonal complexes comprising >10 isolates in the dataset. rSTs (available at http://pubmlst.org) were annotated with the combination of mod alleles present in isolates, and clusters were labeled according to the clonal complexes of these isolates. 186 isolates were not assigned to a known clonal complex.
Statistical analyses were carried out using 2-tailed Fisher’s Exact tests (Graphpad Software Inc., San Diego, CA, USA), with p-values of p < 0.05 taken to indicate statistical significance.
mod gene/allele reference sequences
The modA, modB, or modD genes were defined by >90% sequence identity along the length of the deduced amino acid sequence, excluding the variable DRD, to the modA11 and modB1 genes of N. meningitidis MC5828, or the modD1 gene of M057927. The alleles of each mod gene were defined by ≥95% amino acid identity across the DRD to the reference sequences listed below.
For modA, reference sequences were as previously described28,33: modA2, H. influenzae (Hi) strain 723; modA4, Hi 3579; modA6, Hi C1626; modA11, N. meningitidis (Nm) MC58; modA12, Nm Z2491; modA15, Hi R3570; modA18, Nm NGE28; modA19, Nm 053422. For modA allele alignments, sequences from the following isolates were used for the full-length gene reference: modA2, Hi 86-028NP; modA4, Hi R2846; modA6, Hi PittEE. For modA15 and modA18, no full-length genes were available in GenBank, and isolates M12 240232 and M11 240002 from the MRF MGL have been used, respectively.
For modB, reference sequences were as previously described29: modB1, Nm MC58; modB2, Nm Z2491; modB3, N. lactamica (Nl) 020-60. For modB4, Nm M01-24035515. For newly described modB5 and modB6, GenBank database matches were identified in N. polysaccharea 43768 (NEIPOLOT_01008) for modB5; and Nm 81858 (NM81858_1294) for modB6.
For modD, reference sequences were as previously described27: modD1, Nm M0579; modD3, Nl ST640; modD4, N. cinerea 14655; modD5, N. mucosa 25996. For modD2, Nm 61103 (NM61103_0875). For modD6, Nm 693838. For modD7, the Czech isolate Nm 0001/9343 was used from the MRF MGL as no similar sequences were identified in GenBank.
Additional Information
How to cite this article: 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; doi: 10.1038/srep21015 (2016).
References
Caugant, D. A. & Maiden, M. C. J. Meningococcal carriage and disease—Population biology and evolution. Vaccine 27, Supplement 2, B64–B70 (2009).
Hill, Darryl J., Griffiths, Natalie J., Borodina, E. & Virji, M. Cellular and molecular biology of Neisseria meningitidis colonization and invasive disease. Clin. Sci. 118, 547–564 (2010).
Rosenstein, N. E., Perkins, B. A., Stephens, D. S., Popovic, T. & Hughes, J. M. Meningococcal Disease. New Engl. J. Med . 344, 1378–1388 (2001).
Emonts, M., Hazelzet, J. A., de Groot, R. & Hermans, P. W. M. Host genetic determinants of Neisseria meningitidis infections. Lancet Infect. Dis. 3, 565–577 (2003).
Dale, A. P. & Read, R. C. Genetic susceptibility to meningococcal infection. Expert Rev. Anti Infect. Ther . 11, 187–199 (2013).
Jafri, R. et al. Global epidemiology of invasive meningococcal disease. Popul. Health Metr . 11, 17 (2013).
Maiden, M. C. et al. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc. Natl. Acad. Sci. USA 95, 3140–3145 (1998).
Maiden, M. C. J. Population genomics: diversity and virulence in the Neisseria . Curr. Opin. Microbiol. 11, 467–471 (2008).
Brehony, C., Jolley, K. A. & Maiden, M. C. J. Multilocus sequence typing for global surveillance of meningococcal disease. FEMS Microbiol. Rev. 31, 15–26 (2007).
Yazdankhah, S. P. et al. Distribution of serogroups and genotypes among disease-associated and carried isolates of Neisseria meningitidis from the Czech Republic, Greece, and Norway. J. Clin. Microbiol. 42, 5146–5153 (2004).
Rouphael, N. G. & Stephens, D. S. Neisseria meningitidis: biology, microbiology, and epidemiology. Methods Mol. Biol. 799, 1–20 (2012).
Schoen, C. et al. Whole-genome comparison of disease and carriage strains provides insights into virulence evolution in Neisseria meningitidis . Proc. Natl. Acad. Sci. USA 105, 3473–3478 (2008).
Marri, P. R. et al. Genome sequencing reveals widespread virulence gene exchange among human Neisseria species. PLoS ONE 5, e11835 (2010).
Snyder, L. & Saunders, N. The majority of genes in the pathogenic Neisseria species are present in non-pathogenic Neisseria lactamica, including those designated as ‘virulence genes’. BMC Genomics 7, 128 (2006).
Budroni, S. et al. Neisseria meningitidis is structured in clades associated with restriction modification systems that modulate homologous recombination. Proc. Natl. Acad. Sci. USA 108, 4494–4499 (2011).
Bratcher, H., Corton, C., Jolley, K., Parkhill, J. & Maiden, M. A gene-by-gene population genomics platform: de novo assembly, annotation and genealogical analysis of 108 representative Neisseria meningitidis genomes. BMC Genomics 15, 1138 (2014).
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 (2000).
Harrison, O. B. et al. Epidemiological evidence for the role of the hemoglobin receptor, HmbR, in meningococcal virulence. J. Infect. Dis. 200, 94–98 (2009).
Bille, E. et al. Association of a bacteriophage with meningococcal disease in young adults. PLoS ONE 3, e3885 (2008).
Bille, E. et al. A chromosomally integrated bacteriophage in invasive meningococci. J. Exp. Med. 201, 1905–1913 (2005).
Joseph, B. et al. Comparative genome biology of a serogroup B carriage and disease strain supports a polygenic nature of Meningococcal virulence. J. Bacteriol. 192, 5363–5377 (2010).
Schoen, C., Kischkies, L., Elias, J. & Ampattu, B. J. Metabolism and virulence in Neisseria meningitidis. Front. Cell. Infect. Microbiol . 4, 114 (2014).
Mellin, J. R. & Hill, S. In Neisseria: Molecular Mechanisms of Pathogenesis (eds Caroline Attardo Genco & Lee Wetzler ) Ch. 1, 3–18 (Caister Academic Press, 2010).
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 147, 2321–2332 (2001).
Bentley, S. D. et al. Meningococcal genetic variation mechanisms viewed through comparative analysis of serogroup C strain FAM18. PLoS Genet. 3, e23 (2007).
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 (2003).
Seib, K. L. et al. A novel epigenetic regulator associated with the hypervirulent Neisseria meningitidis clonal complex 41/44. FASEB J. 25, 3622–3633 (2011).
Srikhanta, Y. N. et al. Phasevarions mediate random switching of gene expression in pathogenic Neisseria. PLoS Path . 5, e1000400 (2009).
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 (2010).
Seib, K. L. et al. Specificity of the ModA11, ModA12 and ModD1 epigenetic regulator N6-adenine DNA methyltransferases of Neisseria meningitidis . Nucleic Acids Res. 43, 4150–4162 (2015).
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. USA 102, 5547–5551 (2005).
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 (2009).
Gawthorne, J. A., Beatson, S. A., Srikhanta, Y. N., Fox, K. L. & Jennings, M. P. Origin of the diversity in DNA recognition domains in phasevarion associated modA genes of pathogenic Neisseria and Haemophilus influenzae . PLoS ONE 7, e32337 (2012).
Fox, K. L., Srikhanta, Y. N. & Jennings, M. P. Phase variable type III restriction-modification systems of host-adapted bacterial pathogens. Mol. Microbiol. 65, 1375–1379 (2007).
Atack, J. M. et al. A biphasic epigenetic switch controls immunoevasion, virulence and niche adaptation in non-typeable Haemophilus influenzae. Nat. Commun. 6, 7828 (2015).
Blakeway, L. V. et al. ModM DNA methyltransferase methylome analysis reveals a potential role for Moraxella catarrhalis phasevarions in otitis media. FASEB J. 28, 5197–5207 (2014).
Farabaugh, P. J., Schmeissner, U., Hofer, M. & Miller, J. H. Genetic studies of the lac repressor. VII. On the molecular nature of spontaneous hotspots in the lacI gene of Escherichia coli . J. Mol. Biol. 126, 847–857 (1978).
Hao, W. et al. Extensive genomic variation within clonal complexes of Neisseria meningitidis . Genome Biol. Evol . 3, 1406–1418 (2011).
Kong, Y. et al. Homologous recombination drives both sequence diversity and gene content variation in Neisseria meningitidis . Genome Biol. Evol . 5, 1611–1627 (2013).
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 (2014).
Jolley, K. A. et al. Carried meningococci in the Czech Republic: a diverse recombining population. J. Clin. Microbiol. 38, 4492–4498 (2000).
Putonti, C., Nowicki, B., Shaffer, M., Fofanov, Y. & Nowicki, S. Where does Neisseria acquire foreign DNA from: an examination of the source of genomic and pathogenic islands and the evolution of the Neisseria genus. BMC Evol. Biol. 13, 184 (2013).
Jolley, K. A., Wilson, D. J., Kriz, P., Mcvean, G. & Maiden, M. C. J. The influence of mutation, recombination, population history, and selection on patterns of genetic diversity in Neisseria meningitidis . Mol. Biol. Evol. 22, 562–569 (2005).
Furuta, Y. & Kobayashi, I. Movement of DNA sequence recognition domains between non-orthologous proteins. Nucleic Acids Res. 40, 9218–9232 (2012).
Furuta, Y. et al. Methylome diversification through changes in DNA methyltransferase sequence specificity. PLoS Genet. 10, e1004272 (2014).
Kroll, J. S., Wilks, K. E., Farrant, J. L. & Langford, P. R. Natural genetic exchange between Haemophilus and Neisseria: Intergeneric transfer of chromosomal genes between major human pathogens. Proc. Natl. Acad. Sci. USA 95, 12381–12385 (1998).
Ahmad, I. & Rao, D. N. Functional Analysis of Conserved Motifs inEcoP15I DNA Methyltransferase. J. Mol. Biol. 259, 229–240 (1996).
Malone, T., Blumenthal, R. M. & Cheng, X. Structure-guided analysis reveals nine sequence motifs conserved among DNA amino-methyl-transferases, and suggests a catalytic mechanism for these enzymes. J. Mol. Biol. 253, 618–632 (1995).
Fox, K. L. et al. Haemophilus influenzae phasevarions have evolved from type III DNA restriction systems into epigenetic regulators of gene expression. Nucleic Acids Res. 35, 5242–5252 (2007).
Buckee, C. O. et al. Role of selection in the emergence of lineages and the evolution of virulence in Neisseria meningitidis . Proc. Natl. Acad. Sci. USA 105, 15082–15087 (2008).
Parkhill, J. et al. Complete DNA sequence of a serogroup A strain of Neisseria meningitidis Z2491. Nature 404, 502–506 (2000).
Peng, J. et al. Characterization of ST-4821 complex, a unique Neisseria meningitidis clone. Genomics 91, 78–87 (2008).
Tettelin, H. et al. Complete genome sequence of Neisseria meningitidis serogroup B Strain MC58. Science 287, 1809–1815 (2000).
Berrington, A. W. et al. Phase variation in meningococcal lipooligosaccharide biosynthesis genes. FEMS Immunol. Med. Microbiol. 34, 267–275 (2002).
Jolley, K. & Maiden, M. BIGSdb: Scalable analysis of bacterial genome variation at the population level. BMC Bioinformatics 11, 595 (2010).
Jolley, K. A. & Maiden, M. C. Automated extraction of typing information for bacterial pathogens from whole genome sequence data: Neisseria meningitidis as an exemplar. Euro Surveill . 18, 20379 (2013).
Tamura, K. et al. MEGA5: Molecular Evolutionary Genetics Analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 28, 2731–2739 (2011).
Goujon, M. et al. A new bioinformatics analysis tools framework at EMBL–EBI. Nucleic Acids Res. 38, W695–W699 (2010).
Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. & Barton, G. J. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191 (2009).
Huson, D. H. & Bryant, D. Application of phylogenetic networks in evolutionary studies. Mol. Biol. Evol. 23, 254–267 (2006).
Jolley, K. A. et al. Resolution of a meningococcal disease outbreak from whole-genome sequence data with rapid Web-based analysis methods. J. Clin. Microbiol. 50, 3046–3053 (2012).
Hill, D. M. et al. Genomic epidemiology of age-associated meningococcal lineages in national surveillance: an observational cohort study. Lancet Infect Dis. 15, 1420–1428 (2015).
Acknowledgements
This publication made use of: the Meningitis Research Foundation Meningococcus Genome Library ((http://www.meningitis.org/research/genome), developed by Public Health England, the Wellcome Trust Sanger Institute and the University of Oxford, and funded by the Meningitis Research Foundation); and PubMLST ((http://pubmlst.org/neisseria/info/), developed by Keith Jolley, sited at the University of Oxford, and funded by the Wellcome Trust and European Union). This work was supported by the Australian National Health and Medical Research Council (NHMRC) [NHMRC Early Career Fellowship to Y.N.S; Program Grants 565526 and 1071659 to M.P.J.; Project Grant 1021631 and Career Development Fellowship 1045235 to K.L.S.], The Meningitis Research Foundation [D.M.C.H] and the Wellcome Trust [M.C.J.M].
Author information
Authors and Affiliations
Contributions
K.L.S., M.P.J. and M.C.J.M. designed the study. A.T., D.M.C.H., O.B.H. and Y.S. provided data. A.T., D.M.C.H. and K.L.S. wrote the draft manuscript. All authors analyzed the data, and contributed to the final manuscript.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Supplementary information
Rights and permissions
This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
About this article
Cite this article
Tan, A., Hill, D., Harrison, O. 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 (2016). https://doi.org/10.1038/srep21015
Received:
Accepted:
Published:
DOI: https://doi.org/10.1038/srep21015
This article is cited by
-
Genome-wide methylome analysis of two strains belonging to the hypervirulent Neisseria meningitidis serogroup W ST-11 clonal complex
Scientific Reports (2021)
-
Complete genome and methylome analysis of Neisseria meningitidis associated with increased serogroup Y disease
Scientific Reports (2020)
-
Genetic variation regulates the activation and specificity of Restriction-Modification systems in Neisseria gonorrhoeae
Scientific Reports (2019)
-
First genome sequencing and comparative analyses of Corynebacterium pseudotuberculosis strains from Mexico
Standards in Genomic Sciences (2018)
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.