1
Introduction
Neisseria meningitidis (Nm) is a Gram-negative diplococcus that normally resides in
the human nasopharynx in 8–25% of the worldwide population [1]. Despite its prevalence
as a harmless, commensal organism, Nm can occasionally invade the pharyngeal mucosal
epithelium causing septicemia and life-threatening disease. Many studies have tried
to identify and understand the factors that are responsible for the onset of such
a virulent phenotype [2,3]. Despite these efforts, however, we are still missing evidence
for unambiguous causative elements.
The meningococcal carriage state is a result of the successful commensal relationship
between the host and the bacterium and is likely to be influenced by additional latent
factors like host's diet and microbiome composition. While living in this equilibrium
state, Nm can be transmitted among susceptible individuals through direct contact
or respiratory droplets. Under normal circumstances, Nm cells attempting to traverse
the epithelial barrier to access the bloodstream are readily cleared by the host's
immune defenses [4]. In those rare cases of immune evasion, however, the disease is
fulminant developing within hours and leading to death if untreated within 2 days
[5]; without inducing a shedding state in the diseased individual. Such bacterial
cells are unlikely to be transmitted to new hosts, de facto running into an evolutionary
dead end for Nm. Based on this notion, invasive meningococcal disease (IMD) has to
be assumed as the result of a dysfunctional relationship with the host [6].
Investigations on factors interfering with the commensal relationship between Nm and
its host, which could lead to the onset of IMD, have focused both on the host and
on the pathogen side. Studies in humans have identified several genetic and immunological
factors associated to the susceptibility to, and severity of meningococcal disease.
These factors relate to the host's mucosal barrier, pattern recognition receptors
of the innate immune system, antimicrobial peptides, proinflammatory mediators, components
of the adaptive immune system, complement response and fibrinolysis. A comprehensive
review is provided in Dale et al. [2]. However, none of those factors could unambiguously
discriminate healthy carrier from infected individuals, meaning that host predisposition
alone cannot fully explain Nm ability to cause disease.
Similarly, several Nm properties have been identified to be associated with an increased
propensity to cause IMD. Among the 12 Nm serogroups characterized to date, only a
subset (A, B, C, W, X and Y) have been typically associated with IMD, accounting alone
for >90% of meningococcal invasive disease worldwide [7,8]. Epidemiological studies
further identified specific genotypic lineages (clonal complexes) occurring with significantly
higher frequency within IMD-causing than carriage isolates [3], suggesting that the
ability to cause IMD is contributed by the specific genetic makeup of some Nm strains.
Nonetheless, comparative studies of virulent and apathogenic strains failed to identify
virulence factors (surface determinants and genes involved in host-pathogen interaction)
that could unambiguously discriminate between the two phenotypes [9,10].
In line with this, a recent study investigating the evolution of Nm within the host,
found that genomic changes, primarily affecting surface components involved in host-pathogen
interaction, occur frequently in Nm during the asymptomatic carriage phase and that
these are likely to contribute to the shift to a pathogenic phenotype [11,12]. Overall,
collected evidences suggest that the presence of virulence factors in the meningococcal
genome is not a sufficient condition for developing virulent traits but is rather
the ability to promote phenotypic variation, through the stochastic assortment of
the repertoire of such factors, which could explain the occasional and unpredictable
onset of IMD.
A main driver of phenotypic variability in Nm is represented by Simple Sequence Repeats
(SSRs), contiguous iterations of short DNA motifs that are highly prone to slipped
strand mispairing during chromosome replication. Such unstable elements are capable
to stochastically silent gene expression by introducing frameshifts in the reading
frame or to modulate gene expression by altering the gene's transcriptional promoter
[13,14]. Each Nm isolate carries on average 2000 genes and >4000 SSRs in its genome.
A recent genomic analysis showed that 10 to 15% of Nm genes are possible targets of
the regulation mediated by these repeats, with high frequency stochastic variation
experimentally confirmed for 115 genes [15]. The extraordinary abundance of such variability
hotspots has been described to be higher than what found in other prokaryotes [16]
and in respect to random expectations [17], indicating that Nm relies on SSRs as a
pivotal mechanism of evolution and rapid adaptation to fluctuating environmental conditions.
In this review, a series of argumentations will be presented supporting the hypothesis
that IMD originates from the interplay between bacterial virulence and variability
factors (chromosomic elements promoting high-frequency phenotypic switching).
2
Host Susceptibility to Meningococcal Disease
Despite the fact that meningococcal disease is predominant in individuals lacking
preexisting immunity (defined as the presence of bactericidal antibodies in the plasma)
to this pathogen, only a minority of these develop IMD [18]. Individuals lacking adaptive
immunity against Nm necessarily rely on their innate immune system to prevent a systemic
infection. Consequently, it was hypothesized that the apparently random onset of meningococcal
disease could actually be due to host genetic factors, linked to the innate immune
system, which may be associated to an increased susceptibility [2]. In line with this
theory, a number of retrospective case-control studies identified multiple immune-related
genes whose specific haplotypes, or polymorphisms, segregated susceptible and non-susceptible
individuals with statistical significance. Specifically, altered susceptibility to
meningococcal infection has been associated with specific alleles of genes coding
for cell-surface receptors (CECAM3 and CECAM6) [19], pattern recognition receptors
(TLR4 and TLR9) [20,21], complement pathway regulators (CFH and CFHR3) [22,23], antimicrobial
peptides (DEFB1) [24] and pro-inflammatory cytokines (IL1RN and TNF-α) [25,26]. Robustness
of these results, however, was generally hampered by underpowered sample sizes, inconsistency
between patient inclusion criteria or failure to account for factors known to be associated
with susceptibility. Consequently, some of the identified associations were weak [27,28]
or could not be confirmed in independent validation cohorts [29] and further investigation
is needed to clear up their truthfulness.
Despite the shortcomings, however, some innate immune genes involved in inflammatory
response (IL1B, IL1RN and TNF [25,26]) and the complement cascade (CFH, CFHR3 [22,23])
were shown to have a pivotal role in host genetic predisposition to IMD. Complement
factor H (CFH), for example, is a regulator of the complement pathway activation that
function by either increasing the decay rate of the alternative pathway C3 convertase
C3bBb or by acting as cofactor for Factor I mediated C3b cleavage. Remarkably, Nm
has adapted to avoid complement-mediated killing by recruiting CFH molecules on its
surface through the production of a CFH ligand called factor H binding protein (fHbp)
[30]. Based on this evidence, it is postulated that high plasma levels of CFH can
increase the chance of Nm survival in the blood, consequently leading to an increased
susceptibility to meningococcal infection. Haralambous et al. [22] conducted a study
to determine whether a single nucleotide polymorphism, located in the promoter region
of the CFH gene (C to T conversion at position −496), has a role in IMD susceptibility.
Genetic susceptibility was investigated in 2 independent studies, a case-control and
family based transmission-disequilibrium-test, using 2 separate cohorts of UK Caucasian
patients. A higher IMD susceptibility was found in patients homozygous for the C/C
genotype [odds ratio (OR) = 2.0, p = 0.001]. Such association was even stronger
for the cohort of patients infected with serogroup C isolates (OR = 2.9, p = 0.0002).
In conclusion, a number of genetic traits linked to IMD susceptibility have been identified
that can be used as markers for increased, or reduced, chance to develop IMD or disease
severity. Studies have also started providing mechanistic insights into IMD pathophysiology,
like the pivotal role of the complement system in preventing meningococcal septicemia.
However, the biology of the human interaction with his microbiota is complex and the
analysis of individual factors is unlikely to tell the whole story about host predisposition
to develop IMD. CFH, for example, is not the only regulator of the complement activation
pathway. Other regulators exist that control different stages of the complement cascade
and it may be the specific combination of all these factors, rather than each of them
individually, to determine the fate of host-pathogen interaction following meningococcal
acquisition.
3
Neisseria Meningitidis Virulence Factors
The investigation of genetic elements that could be associated to, and explain, a
Nm pathogenic phenotype has received considerable attention in recent years [9,10].
The meningococcus is the best characterized member of the Neisseria genus. Following
the introduction of the multilocus sequence typing system (MLST) [31] and the advent
of high throughput sequencing technologies, it became possible to appreciate that
Nm species is characterized by extensive genetic diversity and dynamic changes in
DNA content and organization [32,33]. Despite this heterogeneity, however, the population
is structured in groups of closely related strains, called clonal complexes [31] which,
in turn, are clustered together into phylogenetic clades, a top-level population compartment
[34].
Molecular epidemiology studies based on MLST typing revealed a strong association
between certain bacterial lineages and invasive disease, with a minority of clonal
complexes being responsible for the majority of IMD cases worldwide [35]. As an example,
the sequence type 5 (ST-5) complex, represented almost exclusively by serogroup A
strains, showed a disease to carriage ratio of 19.5, while the ST-8 complex, mainly
represented by B and C serogroups, reached 24.5. Even within the same clonal complex,
individual lineages can show different virulence levels. A meta-analysis, based on
information retrieved from the pubMLST database (www.pubmlst.org), showed that the
ST-41 is characterized by an increased likelihood to cause IMD compared to other members
of the ST-41/44 complex. Similarly, clonal complexes can also be significantly associated
with asymptomatic carriage, as is the case of ST-23, which was observed to reach disease
to carriage ratios as low as <0.1 [3]. Similar disproportions were also observed in
time- and population-matched strain collections [36]. The observed variance in IMD
rates across different clonal complexes suggests that the ability to cause infection
is mainly an intrinsic characteristic of the meningococcus and, as such, it is encoded
in its genome.
Analysis of the first ever decoded genome sequence of an Nm isolate (strain MC58)
[37] identified a list of 104 genes coding for putative virulence factors. Successively,
others have been proposed through comparative pathogenomics studies or after the genomic
sequencing of new Nm strains (a comprehensive list of meningococcal known and putative
virulence factors is reported in Table 1). Association between those genes and meningococcal
virulence was based on the ability of the encoded proteins to impact the bacterial
surface phenotype and its interaction with the human nasopharyngeal epithelia.
Table 1
List of virulence factors identified in Nm and their association with repeat elements.
Consolidated list of Nm virulence factors retrieved from Ampattu BJ et al. (2017)
[56], Criss A et al. (2012) [57], Echenique-Rivera H et al. (2011) [58], Schoen C
et al. (2006) [59], Schoen C et al. (2008) [10], Snyder L et al. (2006) [9], Tettelin
H et al. (2000) [37] publications and the virulence factor database (VFDB) [60]. In
the table is reported their association with repeat elements in Nm. Both known and
putative virulence factors are listed. ND: no homologue detected in MC58 genome.
Table 1
Virulence factor
Function
Gene symbol
N meningitidis MC58
Association with repeat elements
Adhesion and penetration protein
Adherence
app
NMB1985
Yes [15]
Adhesion
Adherence
hsf
NMB0992
Yes [54]
Lipooligosaccharide (LOS) sialylation
Adherence
lst
NMB0922
LOS synthesis
Adherence
kdtA/waaA
NMB0014
LOS synthesis
Adherence
lgtA
NMB1929
Yes [15,43]
LOS synthesis
Adherence
lgtB
NMB1928
LOS synthesis
Adherence
lgtC
ND
Yes [43]
LOS synthesis
Adherence
lgtE
NMB1926
Yes [15]
LOS synthesis
Adherence
lgtF
NMB1704
LOS synthesis
Adherence
lgtG
NMB2032
Yes [15,43]
LOS synthesis
Adherence
lgtH
ND
Yes [43,54]
LOS synthesis
Adherence
rfaC
NMB2156
LOS synthesis
Adherence
rfaE
NMB0825
LOS synthesis
Adherence
rfaF
NMB1527
LOS synthesis
Adherence
rfaK
NMB1705
Lipopolysaccharide (LPS) synthesis
Adherence
lptA
NMB1638
LPSsynthesis
Adherence
lpxA
NMB0178
LPS synthesis
Adherence
lpxB
NMB0199
LPS synthesis
Adherence
lpxC
NMB0017
LPS synthesis
Adherence
lpxD
NMB0180
LPS synthesis
Adherence
rfaD
NMB0828
Neisseria adhesion A
Adherence
nadA
NMB1994
Yes [15,43]
Phosphoglucomutase/LOS synthesis
Adherence
pgm
NMB0790
Pilin glycosylation
Adherence
pglA
NMB0218
Yes [43,54]
Pilin glycosylation
Adherence
pglB
NMB1820
Pilin glycosylation
Adherence
pglC
NMB1821
Pilin glycosylation
Adherence
pglD
NMB1822
Quinolinate synthetase
Adherence
NEIS1772
NMB0394
Type IV pili
Adherence
pilC
NMB0049
Yes [15,43,54,55]
Type IV pili
Adherence
pilD
NMB0332
Type IV pili
Adherence
pilE
NMB0018
Type IV pili
Adherence
pilF
NMB0329
Type IV pili
Adherence
pilG
NMB0333
Type IV pili
Adherence
pilH
NMB0886
Type IV pili
Adherence
pilI
NMB0887
Type IV pili
Adherence
pilJ
NMB0888
Type IV pili
Adherence
pilK
NMB0889
Type IV pili
Adherence
pilM
NMB1808
Type IV pili
Adherence
pilN
NMB1809
Type IV pili
Adherence
pilO
NMB1810
Type IV pili
Adherence
pilP
NMB1811
Type IV pili
Adherence
pilQ
NMB1812
Yes [15]
Type IV pili
Adherence
pilS
NMB0020
Yes [15]
Type IV pili
Adherence
pilT2
NMB0768
Type IV pili
Adherence
pilT
NMB0052
Type IV pili
Adherence
pilU
NMB0051
Type IV pili
Adherence
pilV
NMB0547
Type IV pili
Adherence
pilW
NMB1309
Type IV pili
Adherence
pilX
NMB0890
Yes [43,54]
Type IV pili
Adherence
pilZ
NMB0770
Lactate permease
Colonization
lctP
NMB0543
Lipoprotein NlpD
Colonization
NEIS1418
NMB1483
FarAB
Efflux pump
farA
NMB0318
FarAB
Efflux pump
farB
NMB0319
MtrCDE
Efflux pump
mtrC
NMB1716
Yes [15]
MtrCDE
Efflux pump
mtrD
NMB1715
MtrCDE
Efflux pump
mtrE
NMB1714
Capsule
Immune evasion
ctrA
NMB0071
Capsule
Immune evasion
ctrB
NMB0072
Capsule
Immune evasion
ctrC
NMB0073
Capsule
Immune evasion
ctrD
NMB0074
Capsule
Immune evasion
ctrG
NMB0065
Capsule
Immune evasion
lipA
NMB0082
Capsule
Immune evasion
lipB
NMB0083
Capsule
Immune evasion
mynA/sacA
ND
Capsule
Immune evasion
mynB/sacB
ND
Capsule
Immune evasion
mynC/sacC
ND
Capsule
Immune evasion
mynD/sacD
ND
Capsule
Immune evasion
siaA/synA
NMB0070
Capsule
Immune evasion
siaB/synB
NMB0069
Capsule
Immune evasion
siaC/synC
NMB0068
Capsule
Immune evasion
siaD/synD
NMB0067
Yes [15,43]
Capsule
Immune evasion
synE
ND
Drug resistance
Immune evasion
ermE
NMB0393
Yes [15]
Protease
Immune evasion
NEIS2103
NMB2127
T-cell stimulating protein
Immune evasion
tspB
NMB1548
Factor H binding protein
Immune modulator
fHbp
NMB1870
Neisserial surface protein A
Immune modulator
nspA
NMB0663
Class 5 outer membrane protein
Invasion
opc
NMB1053
Yes [15,43,54]
Other outer membrane proteins
Invasion
rmpM
NMB0382
Yes [15]
Other outer membrane proteins
Invasion
mlp
NMB1898
Other outer membrane proteins
Invasion
Omp85
NMB0182
Other outer membrane proteins
Invasion
OmpH
NMB0181
Other outer membrane proteins
Invasion
NEIS1917
NMB1946
Regulation of capsule expression
Invasion
misS/phoQ
NMB0594
Regulation of capsule expression
Invasion
misR/phoP
NMB0595
Type I secretion protein
Invasion
tolC
NMB1737
VacJ-related protein
Invasion
NEIS1933
NMB1961
Opacity protein
Invasion
opa
NMB0442
Yes [15,43,54]
PorA
Invasion
porA
NMB1429
Yes [15,43,54]
PORB
Invasion
PORB
NMB2039
Yes [43,54]
Infectivity potentiator
Invasion
NEIS0982
NMB0995
Infectivity potentiator
Invasion
NEIS1487
NMB1567
ABC transporter
Iron uptake systems
fbpA
NMB0634
ABC transporter
Iron uptake systems
fbpB
NMB0633
ABC transporter
Iron uptake systems
fbpC
NMB0632
ABC transporter
Iron uptake systems
NEIS1964
NMB1989
ABC transporter
Iron uptake systems
NEIS1965
NMB1990
ABC transporter
Iron uptake systems
NEIS1966
NMB1991
ABC transporter
Iron uptake systems
fetB2
NMB1880
Bacterioferritin
Iron uptake systems
bfrA
NMB1207
Bacterioferritin
Iron uptake systems
bfrB
NMB1206
Bacterioferritin
Iron uptake systems
bcp
NMB0750
Control of iron homeostasis genes
Iron uptake systems
fur
NMB0205
Ferric enterobactin transport protein A/ferric-repressed protein B
Iron uptake systems
fetA/frpB
NMB1988
Yes [15,43,54]
Ferrochelatase
Iron uptake systems
hemH
NMB0718
Hemoglobin receptor
Iron uptake systems
hmbR
NMB1668
Yes [15,43,54]
Hemagglutinin/hemolysin
Iron uptake systems
NMB0493
Hemagglutinin/hemolysin
Iron uptake systems
NMB0497
Hemagglutinin/hemolysin
Iron uptake systems
NMB1214
Hemagglutinin/hemolysin
Iron uptake systems
NMB1779
Heme uptake
Iron uptake systems
hpuA
ND
Yes [43,54]
Heme uptake
Iron uptake systems
hpuB
ND
Hemolysin
Iron uptake systems
NMB0496
Hemolysin
Iron uptake systems
NEIS1560
NMB1646
Hemolysin activator
Iron uptake systems
NEIS1658
NMB1738
Hemolysin activator
Iron uptake systems
tpsB
NMB1780
Iron uptake system component
Iron uptake systems
NEIS0012
NMB0035
Lactoferrin-binding protein
Iron uptake systems
lbpA
NMB1540
Yes [43]
Lactoferrin-binding protein
Iron uptake systems
lbpB
NMB1541
Yes [15,43,54]
Ton system
Iron uptake systems
exbB
NMB1729
Ton system
Iron uptake systems
exbD
NMB1728
Ton system
Iron uptake systems
NEIS1887 (fhuA)
NMB0293
Ton system
Iron uptake systems
NEIS1282
NMB1346
Ton system
Iron uptake systems
NEIS2529
NMB1449
Yes [15]
Ton system
Iron uptake systems
NEIS0387
NMB1829
Ton system
Iron uptake systems
NEIS0338
NMB1882
Ton system
Iron uptake systems
tonB
NMB1730
Transferrin-binding protein
Iron uptake systems
tbpA
NMB0461
Yes [54]
Transferrin-binding protein
Iron uptake systems
tbpB
NMB0460
Yes [15,43,54]
Transferrin-binding protein
Iron uptake systems
NHBA
NMB2132
Yes [55]
3R-hydroxymyristoyl ACP dehydrase
Other
fabZ
NMB0179
Carboxyl-terminal processing protease
Other
prc
NMB1332
Hypohetical protein
Other
NEIS0695
NMB0741
Hypohetical protein
Other
NEIS0436
NMB1786
Hypohetical protein
Other
NEIS1028
NMB1064
Nitric oxide reductase
Other
norB
NMB1622
Nucleotides metabolism
Other
NMB0757
Putative integral membrane protein
Other
NEIS0377
NMB1840
Serine protease
Other
nalP
NMB1969
Yes [54]
Transcriptional regulator
Other
mtrR
NMB1717
Uncharacterized protein
Other
NMB1828
VapD-like protein
Other
NMB1753
IgA protease
Stress response
iga
NMB0700
Yes [15,54]
Iron-sulphur protein
Stress response
NEIS1371
NMB1436
Iron-sulphur protein
Stress response
NEIS1372
NMB1437
Iron-sulphur protein
Stress response
NEIS1373
NMB1438
Catalase
Stress response
katA
NMB0216
Endonuclease
Stress response
nth
NMB0533
Manganese transport system
Stress response
mntA
NMB0588
Manganese transport system
Stress response
mntB
NMB0587
Manganese transport system
Stress response
mntC
NMB0586
Methionine sulphoxide reductase
Stress response
msrA/B(pilB)
NMB0044
Nitrite reductase
Stress response
pan1
NMB1623
Recombinational repair protein
Stress response
recN
NMB0740
Yes [15]
Superoxide dismutase
Stress response
sodB
NMB0884
Superoxide dismutase
Stress response
sodC
NMB1398
FrpC operon protein
Toxin
NMB0364
FrpC operon protein
Toxin
NMB0365
FrpC operon protein
Toxin
NMB0584
FrpC operon protein
Toxin
NMB1409
FrpC operon protein
Toxin
NMB1412
FrpC operon protein
Toxin
NMB1414
Neisseria ADP-ribosylating enzyme
Toxin
narE
NMB1343
Putative toxin-activating protein
Toxin
NMB1210
Putative toxin-activating protein
Toxin
NMB1763
RTX toxin
Toxin
frpA
NMB0585
RTX toxin
Toxin
frpC
NMB1415
Yes [54]
Oxidoreductase
Stress protein
dsbA-1
NMB0278
Oxidoreductase
Stress protein
dsbA-2
NMB0294
Oxidoreductase
Stress protein
dsbA-3
NMB0407
As additional genomic sequences became available, various attempts to characterize
the genetic elements associated with an invasive phenotype were made. These focused
both on the exploration of nucleotide sequence variation at shared loci and on the
variation in the gene content. Comparisons of the meningococcal gene repertoire with
those of other, less pathogenic, Neisseria species failed to identify consistent differences.
Moreover, despite the different trophism of human colonization, Nm was found to share
most of its genetic content with N. lactamica and N. gonorrhoeae [9,38]. Similarly,
genome wide association studies comparing pathogenic and apathogenic strains could
not reveal unambiguous evidences of the presence of indispensable virulence factors
[9,10]. The capsule region, containing clusters of genes encoding the ability to synthesize
the polysaccharide layer, has been regarded as the main meningococcal virulence determinant,
given the fact that 5 (A, B, C, W and Y) of the 12 serogroups known to date are responsible
for the vast majority of IMD cases [7]. Additionally, a putative phage element was
found to be significantly associated with meningococcal disease. Despite the strong
association however, more that 50% of healthy carriers in the analyzed population
were colonized with an Nm isolate carrying the phage element within their genome [39].
Overall, collected evidences indicate that the propensity to cause disease is a multifactorial
property, which depends on combinations of genes and genetic elements that, individually,
are commonly found also in non-pathogenic lineages.
4
Neisseria Meningitidis Genome Variability Factors
Nm, like other obligate commensals, must face several hurdles in order to successfully
colonize a genetically and immunologically diverse host population. During meningococcal
transmission, only a small minority of colonizing cells is likely to be transmitted
to the new host. In the peculiar environmental settings provided by the new hosting
organism, newly transmitted cells must be able to adhere to endothelial cells while
also scavenging nutrients and avoid host's defense mechanisms. It is postulated that
the highly mutable genome characterizing the meningococcal species has evolved in
response to the need to survive in such a dynamic environment. The ability to quickly
generate many different phenotypes, in fact, allows for the exploration of alternative
phenotypic solutions from which the fittest can be selected for survival and subsequent
transmission [40,41].
Based on this theory, it would be intuitive to expect a positive selection for an
increased mutation rate in bacterial species that are subjected to major environmental
fluctuations. However, deleterious mutations have a higher chance to occur compared
to beneficial ones and a generalized increase in genome mutability would inevitably
result in an evolutionary dead-end. Presumably to meet this challenge, organisms like
Nm have evolved strategies to focus high mutation rates in those genes that are involved
in critical interactions with the host, without increasing the overall mutability
of their genome [40,42]. Since the first Nm genome sequences became available it soon
became evident that this species have accumulated thousands of repetitive sequence
elements in its genome, ranging from basic homopolymeric tandem repeats to complete
gene clusters duplications [43]. The different types of repetitive elements, which
are listed in Table 2, function as variability hotspots as they can be prone to slipped
strand mispairing during chromosomal replication, promote the uptake of exogenous
DNA or function as hotspots for chromosomal rearrangements. It has been proposed that
the coexistence within bacterial genomes of such “contingency” chromosomic regions
and more stable “housekeeping” regions could facilitate the efficient exploration
of phenotypic solutions to unpredictable aspects of the host environment, while minimizing
deleterious effects on bacterial fitness [40,41]. Several putative virulence genes
have been reported to be associated with one or more of these repeat elements (Table
1).
Table 2
Families of repeat elements characterizing the Nm genome.
Table 2
Repeat element
Composition
Putative function
Reference
ATR (AT-rich repeats)
183-bp A + T-rich sequence whose ends form an imperfect 35-bp inverted repeat
Modulation of gene expression
Parkhill J et al., Nature (2010) and Ampattu BJ et al., (2017)
Coding tandem repeats
Tandem repeats that do not disrupt the reading frame (repeat unit composed of 3 bp
or multiples of 3 bp)
Generation of differing protein isoforms
Jordan P et al., BMC Microbiol (2003)
CREE (Correia repeat enclosed elements)
156-bp sequence bounded by a 26-bp inverted repeat
Modulation of gene expression
Correia FF et al., J Biol Chem (1988)
DUS (DNA uptake sequence)
10-bp sequence5′-GCCGTCTGAA-3′
Recognition and uptake of exogenous DNA
Goodman SD and Scocca JJ, Proc Natl Acad Sci USA (1988)
NIME (neisserial intergenic mosaic elements)
Repeat units of 50–150 bp (RS elements), each flanked by 20-bp inverted repeats (dRS3
elements)
Pilin genes recombination
Parkhill J et al., Nature (2010)
SSR (simple sequence repeats)
1- to 10-bp motifs that are repeated in tandem
Modulation of gene expression
Saunders NJ et al., Mol Mircobiol (2000)
REP 2
120–150 bp sequence containing ribosome-binding-site-like conserved AAGGA motif
Modulation of gene expression
Parkhill J et a.l, Nature (2010)
REP 3
60-bp conserved sequence occurring next to CREE elements
Unknown
Parkhill J et al., Nature (2010)
REP 4
26-bp conserved sequence occurring next to CREE elements
Unknown
Parkhill J et al., Nature (2010)
REP 5
20-bp conserved sequence occurring next to CREE elements
Unknown
Parkhill J et al., Nature (2010)
A major contribution to Nm genotypic variability is provided by SSRs, extended stretches
of repeated nucleotide motifs that are highly prone to replication errors [17]. SSRs
located within gene coding sequences or in the proximity of their promoters can either
modulate the level of gene expression or produce alternate protein variants through
a number of mechanisms [41,44,45] (Fig. 1). A recent comparative genomic study performed
by our group highlighted an unappreciated potential for SSR-mediated phase variation
to promote phenotypic variation [15]. Each meningococcal strain was found to contain
an average of 4243 SSRs in its genome, which if normalized for the typical chromosome
size (≈2.2 million nucleotides) account for the extraordinary SSRs density of one
repeat every 520 nucleotides. This enrichment for SSRs in Nm was found to be unusually
high compared to other prokaryotes [16] or random expectation [17]. Subsequent in
vitro testing allowed to appreciate that a substantial portion of these SSRs underwent
length polymorphisms in strains grown overnight in non-selective conditions. Within
this short time frame, these SSRs element could destabilize the chromosomic regions
related to 115 different genes, possibly leading to a modulation of their expression
or complete silencing. Even in the simplest case of an on/off type of regulation,
the random combinatorial switching of these 115 contingency genes could already produce
an enormous amount of alternative phenotypes (2115). In line with the aforementioned
within-host evolution theory, these genes are enriched for cell surface determinants
relevant to bacteria-host interaction [15].
Fig. 1
Schematic representation of putative SSRs modes of action.
A: Variable number simple sequence repeat (VNSSR) causing translational start site
switching. B: VNSSR causing the loss of a membrane-spanning domain. C: VNSSR leading
to the loss of the peptide C-terminal region. D: VNSSR introducing changes in the
peptide sequence. E: VNSSR influencing the gene promoter. F: VNSSR introducing an
inactivating frame shift. Dark grey arrows represent open reading frames. Black arrows
marked with ATG represent in-frame ATG translational start sites. Light grey boxes
represent the annotated functional domains. Stripped boxes represent VNSSRs and the
related tags indicate the repeat unit motif along with the minimum and maximum number
of repetitions observed in the 20 analyzed genomes. Numbers below each gene indicate
the position relative to the annotated translational tart site. Reproduced from Siena
et al. [15].
Fig. 1
5
Interplay between Virulence and Variability Factors in Invasive Meningococcal Disease
A recent study conducted by Klughammer et al. [11] investigated the within-host genetic
changes occurring in meningococcus by comparing the genomic sequences of throat-blood
isolate pairs from four patients suffering from acute IMD. Even if based on a limited
number of cases, this study showed that strains that could penetrate the nasopharyngeal
epithelium (i.e. pathogenic strains) were characterized by mutations predominantly
affecting the biogenesis of the meningococcal type IV pilus, a main surface determinant.
Not a single set of mutations was shared by all the analyzed strain pairs, underlying
the stochastic nature of these events. Moreover, mutations were primarily contributed
by the variability factors described above, 8 (73%) of which were represented by length
polymorphisms occurring at SSRs sites. Even though the association between genetic
elements capable of promoting phenotypic variation and pathogenic traits has been
hypothesized long ago [40], this study represents the first experimental confirmation.
Meningococcal disease has been proposed to occur within few days after the acquisition
of a new Nm isolate in the nasopharynx [1,46]. This fast-track from acquisition to
invasive disease is compatible with the short time required by SSRs to modulate gene
expression and promote phenotypic variation. Evidences collected by Klughammer et
al. confirm that length polymorphisms at SSR loci are indeed capable of generating
the genetic diversity observed in the throat-blood isolate pairs during nasopharyngeal
carriage and suggest that IMD likely results of the within-host evolution of the colonizing
isolate, which is driven by the specific interplay between virulence and variability
factors. A cartoon summarizing this process is shown in Fig. 2. According to this
hypothesis, only one, or a limited number of bacterial cells are successfully transmitted
to the new host. After colonization of the human mucosa, the founder cells start proliferating
while also trying to increase their fitness by exploring alternative phenotypic solutions,
which are generated by SSRs and similar variability factors. During this process,
chances are that the random reassortment of proteins relevant to the interaction with
the host would produce a pathogenic variant capable of crossing the nasopharyngeal
epithelium, access the bloodstream and cause systemic infection.
Fig. 2
Proposed model for the onset of invasive meningococcal disease.
Following transmission and colonization of the human nasopharynx, the founder clone
starts proliferating. During this phase, extensive phenotypic variation is generated
by the stochastic reassortment of virulence factors (surface determinants and genes
involved in host-pathogen interaction) driven by meningococcal chromosomic variability
factors (step 1). This exploration of new phenotypic solutions can lead to the accidental
onset of a virulent variant (step 2), which is able to penetrate the nasopharyngeal
epithelial barrier and cause septicemia (step 3).
Fig. 2
As a further support to this hypothesis is the fact that the associations between
virulence and variability factors characterized to date (Table 1) almost exclusively
involve genes coding for proteins that are involved in the interaction with the host
and that are located to the cell outer membrane and, as such, are potential targets
of hosts immune defense mechanisms. These can be broadly categorized into evasins,
adhesins, lipopolysaccharide (LPS) biosynthesis and iron acquisition proteins.
Evasins are a family of proteins whose function is to help escaping the host immune
defenses. Capsular polysaccharides constitute a barrier that enables bacteria to resist
phagocytosis and complement mediated killing. In Nm the capsule production is controlled
by a peptide encoded by siaD, a gene whose expression is controlled by transcriptional
slippage of an intragenic homopolymeric tract [15,43].
Adhesins are a family of proteins involved in Nm adherence to the human epithelium
and in tissue trophism. Due to the cell surface localization of these proteins, most
adhesins induce antibody responses during natural infection. Opacity proteins provide
an example of such function in Nm and for some of them the expression was found to
be regulated by variable sequence repeats, like is the case of opa and opc [43,47].
LPS is a major constituent of the outer surface of Gram-negative bacteria and is intimately
involved in every stage of Nm interaction with its host. Among the functions mediated
by the LPS layer are attachment of bacterial cells to host membranes and resistance
to the innate immune system. Seven lgt genes (lgtA, lgtB, lgtC, lgtE, lgtF, lgtG and
lgtH), encoding for glycosyltransferases, act in different combinations to generate
alternative LPS structures in Nm. As reported in Table 1, five of these genes are
under the stochastic control of repeat elements.
Finally, one of the needs of most pathogenic bacteria is to scavenge resources from
the external environment. Nm, for example, relies on exogenous acquisition of iron
in order to maintain its fitness [48]; a need that induced this pathogen to develop
alternative and partially redundant mechanisms for iron scavenging [49]. These involve
numerous surface-expressed proteins that are targeted by the human immune system [47,50].
Phase variation of these loci can therefore result in antigenic variation similar
to that proposed for the Opa genes, with deep implication in the establishment of
IMD.
6
Summary and Outlook
Overall, several attempts were made to better understand Nm biology and unravel the
mechanisms leading to IMD. Different host factors have been associated to altered
levels of susceptibility to meningococcal infection, however none of them can accurately
predict whether a given subject will develop IMD or not. Similarly, no genetic factors
have been identified in Nm that could clearly and unequivocally distinguish between
pathogenic and harmless Nm isolates. Nonetheless, recent findings seem to suggest
that the coexistence and interaction between genetic “variability” factors, capable
of increasing the mutability of specific chromosomic regions, and “virulence” factors,
encoding for bacterial-host interaction functions, is likely the key trigger of Nm
pathogenicity. This multifactorial nature of IMD is further complicated by Nm living
within a dynamic and diverse host population, characterized by different levels of
pre-existing immunity and different susceptibility to meningococcal disease. This
introduces an additional layer of complexity and greatly expands the space of variables
to be accounted for. A further, practical challenge comes from the difficulty to obtain
blood-throat isolate pairs to be used in comparative studies, due to the low IMD incidence
and immediate antibiotic treatment of hospitalized patients.
In conclusion, much progress has been made in understanding the mechanisms underlying
the origin of IMD. In this regard, the interplay between “virulence” and “variability”
factors is emerging as a key driver of the transition from a commensal to virulent
Nm phenotype. Despite this, however, challenges like the complexity of Nm pathogenesis
and the difficulties in data collection are still preventing from reconstructing the
whole picture. There is little doubt that the road to understanding the origin of
IMD will necessarily go through large-scale genomic comparisons of commensal and virulent
Nm strains; de facto following the direction set by Klughammer and coworkers [11].
These will likely be facilitated by the most recent sequencing technologies, which
allow for the characterization and study of bacterial isolates directly from clinical
samples, like blood or cerebrospinal fluid [[51], [52], [53]]. In our vision, these
studies will be foundational to advance our understanding of the origin of IMD.
Conflict of Interest
This work was sponsored by GlaxoSmithKline Biologicals SA. ES and DM are employees
of the GSK group of companies. MB is an employee of Randstad Italia spa, working as
a contractor for GSK. ES is listed as an inventor on a patent on meningococcal polypeptide
sequences, owned by the GSK group of companies. The authors report no additional conflicts
of interest.
Authors Contribution
ES and MB drafted the manuscript. DM provided intellectual input. All authors approved
the final manuscript.