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streptococcus bacteria capable of producing acids from dietary sugars play a major role in maintaining stability. In health, these non- MS bacteria, such as Actinomyces, are the major producers of
acids contributing to the decrease in pH. However, homeostatic mechanisms in the oral cavity,
such as saliva, bring the pH back to the neutral level. This dynamic stability stage occurs daily in
supragingival plaque. However, frequent and extended drops in pH due to indiscriminate consumption of sugars shift the community towards acidogenic bacteria (acidogenic stage). The acidophilic and aciduric bacteria of S. mutans thrive in this acidic environment, leading to the
replacement of low- pH non- mutans strains (aciduric stage).
The extended ecological plaque hypothesis emphasised that the community- wide effect is more
crucial than a few selected pathogens for the initiation and development of dental caries. However,
the exploration of the role of the caries microbiome has traditionally been limited by culturedependent and biochemical methods in the past. This hurdle was overcome by the advent of 16S
rRNA- based technologies. In the early days, researchers developed 16S rRNA- based microarrays
capable of detecting a relatively large number of oral microorganisms[21, 22]. With the advancement of technology over the last few decades, our understanding of the microbial aetiology of
dental caries has undergone a dramatic change. Therefore, in this chapter, we briefly discuss the
novel microbiome- dysbiosis- based concept in dental caries, focusing on recent studies. Excellent
reviews of various hypotheses can be found elsewhere.
18.3.3 Next- generation Sequencing inDental Caries
The first 16S rRNA- based sequencing project on the oral microbiome was published in 2008[23].
This study utilised a pyrosequencing approach to examine the salivary and supragingival plaque
microbiomes of healthy adults. Saliva and supragingival plaque samples were obtained from 71 to
98 healthy adults, respectively, and amplicons from the V6 hypervariable region were utilised.
Grouping the sequences into operational taxonomic units (OTUs) (at 6% dissimilarity) revealed
3621 and 6888 species- level phylotypes in saliva and plaque, respectively, offering new insights
into an expanded list of previously undiscovered microorganisms. Since then, a large number of
next- generation sequencing (NGS) studies have been employed to examine the oral microbiome in
relation to dental caries. Studies with interesting clinical implications are discussed below. A common observation from the foregoing studies is that dental caries cannot be attributed to a single
major pathogen, such as S. mutans. It is evident that microbial shift or dysbiosis is the reason
behind caries development. Hence, as opposed to a single or selected set of pathogens, the focus
should be at the community level to alleviate the dysbiotic microbiome.
Amplicon- based sequencing has several limitations. As techniques advance, the introduction of
whole- genome sequencing (WGS) has led to a true metagenomics approach. One of the first studies to conduct WGS is by Belda- Ferre etal. (2012), focusing on the metagenome of the human oral
cavity, particularly samples from supragingival dental plaque and cavities of dental caries [24].
This study is a landmark for several reasons. First, it clearly demonstrated that the dental caries
microbiome is not dominated by the classical cariogenic pathogen, S. mutans, highlighting the
polymicrobial nature of the disease. However, the significance of S. mutans should not be overlooked, as individuals who had never experienced dental caries lacked mutans streptococci but
exhibited a high abundance of other species. Secondly, it points out the question that ‘what are
they doing’ is more important than ‘who are there’. Metagenomics approach in the study enabled
the functional analysis of the species present in the community. The findings indicated that the
oral cavity functions distinctly from the gut. Individuals without a history of dental caries exhibited
an overrepresentation of various functional categories, including genes related to antimicrobial
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peptides and quorum sensing. Thirdly and interestingly, it was demonstrated that dominant bacteria in healthy individuals, when cultured can inhibit the growth of cariogenic bacteria. This indicated that commensal bacterial strains as probiotics may help promote oral health and prevent
dental caries. The limitation of this study is the lower number of subjects examined. However,
subsequent studies also pointed out that the shift in the microbial community towards different
functionalities is more related to cariogenic development rather than the emergence of new pathogenic species.
18.3.4 Caries Microbiome at Different Sites ofthe Caries Lesion
It is noteworthy that the microbiome associated with tooth surface is not uniform even at the
healthy status owing to differences in its surface topography of the tooth surface[15]. Therefore,
some researchers have been interested in examining the microbiome in pit and fissures of subjects
with or without dental caries. A study compared the pit and fissure sites of 20 adolescents with
active pit and fissure surface caries and a control group of 20 age- matched, caries- free teenage
subjects for control test[25]. Metagenomic sequencing of plaque samples was employed to investigate the relationship between the plaque microbiome which showed a similar diversity between
caries- active and caries- free groups. However, when considering individual species, the cariesactive group exhibited higher relative abundances of Actinomyces gerencseriae, Propionibacterium
acidifaciens, Prevotella multisaccharivorax, Streptococcus oralis, S. mutans, and Parascardovia denticolens. On the other hand, Neisseria elongata, Cardiobacterium hominis and Actinomyces johnsonii were relatively more abundant in the caries- free groups.
Another study investigated the microbiome linked to deep, shallow, and surface plaque samples[26]. The findings suggested that as caries deepen, microbial diversity decreases, but interactions among microbes increase. Hence, lowest diversity was observed in the deep caries lesion.
Initial caries microbiome was characterised by the bacteria Scardovia wiggsiae, S. mutans, and
P. acidifaciens. Interestingly, P. acidifaciens was identified as the distinguishing microbe between
initial and deep caries
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18.3.5 Longitudinal Studies onOral Microbiome Associated withCaries
The initiation and development of dental caries is a time- dependent process. Therefore, crosssectional studies investigating the relationship between caries microbiome and clinical parameters
only provide a snapshot of this process. Well- controlled longitudinal studies represent a more realistic picture of caries pathogenesis. However, these studies are sparse owing to the difficulty in
conducting and the associated cost. Few examples are highlighted below.
In a longitudinal study, Kahharova and colleagues (2023) examined the association of the salivary and dental plaque microbiome associations of children and various caries risk factors, including demographics, behavioural factors, and clinical data, throughout early childhood[27]. A total
of 266 children were examined in their early childhood from year 1 up to 6.5 years of age at various
time points. Concurrently, microbiological samples were collected. The saliva and plaque microbiome of children who remained caries- free (International Caries Detection and Assessment System
[ICDAS]=0) at all time points differed from the microbiome of children who had clinically confirmed early and advanced caries lesions. Notably, microbial and clinical parameters analyses
showed that the dysbiosis of the microbiome becomes evident 1–3 years before the clinical detection of caries lesions. Communities with dysbiotic microbial compositions, dominated by proteolytic taxa like Leptotrichia and Prevotella, were found to be more diverse. Dysbiotic dental plaque
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microbiome had a better discriminatory power compared to salivary microbiome to distinguish
caries- active and caries- free children.
Another case- control study by Blostein etal. (2022) examined the salivary microbiome of 189
children followed from 2months to 5 years[28]. Interestingly, it was found that salivary microbiome analysis was able to predict future ECC status before detection of S. mutans in dental plaque.
The network of certain protective bacteria species, including Haemophilus parainfluenzae,
Neisseria, and Fusobacterium periodonticum was found to be correlated with salivary pH and
inversely related to the future detection of S. mutans. Hence, mean relative abundance of these
bacterial species was lower in future ECC cases than in controls. It is suggested that microbial successions in early life, in addition to etiologic risk factors such as diet and oral hygiene, may predispose children to ECC.
18.3.6 Multi- OMICS Studies in Dental Caries
Dental caries is a multifactorial disease. Therefore, it is not possible to obtain a holistic view using
few biomarkers or specific technical approaches. Therefore, more recently, researchers have sought
to employ a multi- omics approach to model network analysis of various microbial aspects including metagenomics, proteomics, transcriptomics and metabolomics[29]. There are only a few studies in the dental caries literature. Espinoza etal. (2022) used multi- omics approach involving
metagenomics and metatranscriptomics to analyse the microbiome of supragingival plaque in 91
Australian children[30]. Owing to this innovative approach, researchers were able to map the core
bacterial microbiome and viral microbiome which demonstrate the active transcriptions in the
supra- gingival plaque biofilm. Hence, the study characterised 658 bacterial and 189 viral
metagenome- assembled genomes (MAGs) from the supragingival plaque. Neisseria was identified
as a significant contributor with high connectivity in the supragingival plaque oral microbiome,
irrespective of the caries phenotype.
Furthermore, C. hominis was identified as one of the microbes with the highest enrichment in
connectivity, depending on the metabolic interactions, in both caries- free and caries- active states.
Therefore, C. hominis seemed to act as a bridge between caries- free and caries- dysbiotic states by
switching from pentose phosphate to TCA cycle carbohydrate metabolism. The network analysis
performed suggested that C. hominis promotes caries- free microbiome in connection with S. san-
guinis lysine metabolism, Abiotrophia. sp001815873 ATP synthesis and Neisseria cofactor when it
mediates pentose phosphate pathway metabolism. In contrast, in the caries- active states, C. hominis-
mediated TCA cycle is associated with the dysbiotic microbiome in the caries- active state.
The findings of the network analysis derived from this study highlight that the cariogenic process is more associated with a metabolic shift of the microbial community rather than extensive
gain or loss of taxa. A panel of transcripts and their associations, rather than specific abundances
of taxa or transcripts alone, can distinguish between caries- free and caries- active microbiomes.
The authors proposed probiotics that revert community association could be powerful therapeutics for dental caries. Hence, future research should evaluate the modulation of community network by probiotic bacteria for the prevention and control of cariogenic microbiome.
18.3.7 Oral Microbiome Associated withPeriodontitis
Periodontal disease begins with periodontal pathogens triggering an inflammatory condition,
which is then followed by an immune response. Exploring the microbiome in the periodontitis
context holds significant importance as it provides crucial insights into the complex interactions
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between oral bacteria and the host environment. Characterising the composition and dynamics of
the microbiome allows for exploring microbial shifts during disease progression, aiding in the
comprehension of periodontitis development and its targeted interventions.
Traditionally, periodontal microbiology centred on culture- based studies linking periodontitis to
a limited set of primarily anaerobic species like Porphyromonas gingivalis, Treponema denticola
and Bacteroides forsythia[31]. Recent sequencing advances, however, have transformed our under-
standing, revealing a more diverse oral microbial ecology with numerous uncharacterised species[32]. About half of the species associated with periodontitis are presently uncultivated, in
contrast to approximately one- third of species associated with health.[33]. This shift in perspective
underscores the complexity and richness of the oral microbiome, emphasising the need to consider
uncultivated species for a comprehensive understanding of periodontal diseases.
18.3.8 Dynamics ofSubgingival Microbial Diversity inPeriodontitis
While classical bacterial infections typically lead to a reduction in microbial diversity[34], periodontitis, in contrast, is often characterised by a diverse microbial community than that of a healthy
state in the majority of studies[33, 35–41]. Nevertheless, a few studies have presented opposing
findings, demonstrating either no change or a decline in microbial diversity in the context of
periodontitis[42–45].
Differing observations regarding species diversity and richness across studies may be linked to
the depth of the pocket being sampled, which varies across the spectrum of periodontal disease. In
the early stages of the disease, there is a gradual transition in the microbiome with pathogenic
bacteria invading the healthy community, resulting in a mixed community with heightened diversity and richness. Once periodontitis is established, the subgingival community typically exhibits a
preference for the proliferation of periodontal pathogens, while still maintaining some healthassociated species, although their proportions are diminished. The increased prevalence of pathogenic taxa may then contribute to a more uniform community structure, potentially resulting in a
decline in overall diversity as the disease progresses.
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18.3.9 Subgingival Microbial Shifts During Periodontitis
In periodontitis, the subgingival microbiota is characterised by the prevalence of the Bacteroidetes,
Spirochaetes, Synergistetes and Firmicutes phyla, while health is closely associated with
Proteobacteria, Actinobacteria, Fusobacteria and Firmicutes[33, 36, 40, 44–46]. Within these phyla,
Bacteroidetes, Synergistetes and Spirochaetes exhibit significantly higher relative abundance in per-
iodontitis, whereas Proteobacteria is notably abundant in a healthy state.
At the genus level, periodontitis is marked by a notably higher presence of genera Porphyromonas,
Tannerella, Treponema, Filifactor and Peptostreptococcus as observed in various studies[33, 35, 36, 38,
40, 44, 46]. On the contrary, within a healthy community, genera like Streptococcus, Corynebacterium,
Haemophilus, Capnocytophaga, Gemella and Actinomyces exhibit notably higher abundance compared to instances of disease[35, 36, 40, 46]. Prevotella, Fusobacteria, Porphyromonas, Streptococcus
and Leptotrichia dominate both periodontitis and health, though the relative abundance in periodontitis was higher than in health[36, 40, 43, 46]. This indicates a microbial succession during periodontitis, characterised by an increase in periodontitis- associated bacteria and a decline in health- associated
bacteria, although the latter continues to persist, albeit in reduced numbers[33, 35]. The transition
from health to disease is marked by the establishment of low- abundance species as dominating community members rather than a complete substitution of health- associated species.
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While there is a reorganisation of microbial taxa from a state of health to disease, the periodontitisassociated and health- associated taxa ultimately differentiate at the species level. The presence of
red- complex species such as P. gingivalis, Tannerella forsythia, T. denticola, Fusobacterium nuclea-
tum subsp vincentii and Treponema Socranskii in periodontitis is well established across multiple
studies[33, 39, 45, 46]. Recently, advanced high- throughput techniques have brought to light previously undiscovered species implicated in periodontitis, including Filifactor alocis, Porphyromonas
endodontalis, Desulfobulbous oral taxon 041 and Bacteroidales sp OT 274. The fact that F. alocis is
Gram- positive challenges the simplistic idea that bacteria associated with periodontitis are mostly
Gram- negative, while those linked to healthy communities are Gram- positive. The presence of
F. alocis alongside other important periodontal bacteria, and its current role in causing periodontal
disease, likely involves multiple factors and necessitates thorough investigation for a complete
understanding[47].
18.3.10 Periodontal Microbial Complexes
In 1998, Socransky introduced the concept of bacterial complexes in periodontitis, grouping
cultivable species based on their associations and interactions[48]. While Socransky’s classification offered a useful model for comprehending the intricate dynamics of the oral microbiome in periodontitis, this concept has progressed with the advancements in molecular
techniques. These advancements have enabled a deeper understanding of the non- cultivable
microbial components implicated in periodontal health and disease. For instance, Szafranski
etal. utilised hierarchical cluster analysis at the species level to identify two clusters representing the shift of microbiota from healthy to dysbiotic communities.[39]. The periodontitisassociated module identified the presence of red- complex bacteria (P. gingivalis and T. forsythia)
along with a few orange complex species (F. nucleatum vicentii, F. nucleatum nucleatum,
E. nodatum and S. constellatus). Moreover, species that had not been previously linked with
any modules were discovered within the red- complex cluster, such as Selenomonas sputigena
HOT151, Fretibacterium sp. HOT 360, Desulfobulbus sp. HOT 41 and TM7 [G- 5 sp.] thereby
broadening the comprehension of Socransky’s bacterial complexes. The observed co- occurring
ecological symbiosis among pathogens indicates their coexistence in a mutually beneficial
manner. In vitro studies conducted in controlled environments have revealed that S. sanguinis
hinders the P. gingivalis growth by producing hydrogen peroxide [49]. Additionally, it was
observed to impede the activation of IL- 6, IL- 8 and TNF- α expression triggered by lipopolysac-
charide (LPS) from periodontal bacteria. In contrast, Duran–Pinedo et al. discovered that
P. gingivalis led to the death of Streptococcus mitis within a biofilm model. A recent study
using scanning electrochemical microscopy revealed a mutually beneficial relationship
between S. mitis and Capnocytophaga matruchotii, characterised by metabolic synergy.[50].
The Polymicrobial Synergy and Dysbiosis (PSD) model suggests that the initiation of periodontitis arises from a synergistic and imbalanced shift in the microbial community, which
includes both well- known periopathogens and recently discovered taxa, rather than solely
relying on specific ‘periopathogens’ such as the ‘red complex’[51]. In accordance with this
model, keystone pathogens, along with accessory pathogens, initially disrupt the host’s
immune system. This disruption of the immune system is subsequently aggravated by pathogens, eventually causing the homeostasis breakdown and the commencement of destructive
inflammation[52]. Many studies have recently reemphasised this model[38, 42, 43]. Additional
research is necessary to elucidate how the recently identified taxa build upon the traditional
complex concept.
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18.3.11 Functional Interactions Among Periodontal Microbiome
At a taxonomic level, the variability in microbial profiles among individuals in both health and
disease is widely recognised. However, the metagenome of the subgingival microbiota exhibits less
variability between individuals, indicating a more uniform distribution of functional categories or
metabolic pathways[45]. Functionally similar communities are noted in periodontitis, although
they exhibit less functional consistency compared to a healthy microbiome. For instance, within
the core microbiome of periodontitis, the flagellar genes originate from Treponema spp in certain
individuals, while in others, they are provided by Selenomonas spp or Campylobacter spp.
(Dabdoub etal. 2016). Thus, despite the taxonomic variabilities, there exist functional similarities.
The comparison of periodontitis and health- associated communities revealed shared genes primarily implicated in central functions such as carbohydrate and protein metabolism, protein, aerobic respiration, amino acid synthesis and virulence[53]. Although core functions remain consistent
between health and disease, the relative abundances of specific gene functions exhibit significant
differences between the two groups. Specifically, periodontal pathogens demonstrate a marked
elevation in genes associated with virulence, including flagellar mobility, adhesion, bacterial
chemotaxis, invasion, proteolysis, intracellular resistance, quorum sensing and iron acquisition
systems[36, 41, 45, 53–55]. The red- complex members, as well as Aggregatibacter actinomycetem-
comitans, demonstrate the overexpression of numerous putative virulence factors in periodontitis[55]. Additionally, there is a preferential increase in genes associated with Lipid- A synthesis in
periodontitis, with substantial contributions from genera Capnocytophaga, Fusobacterium,
Campylobacter, Porphyromonas, Tannerella, Prevotella and Treponema[53, 55].
Notably, the taxa associated with health exhibited a specialised genome primarily geared towards
energy acquisition via carbohydrate metabolism. Conversely, in periodontitis, energy acquisition
depended more on fermentation and methanogenesis[53]. Methanogens can indirectly influence
periodontitis progression by engaging in syntrophic interactions with other subgingival microbial
community members[49]. Since fermentation typically yields less energy than aerobic respiration,
a healthy microbial community was considered as an energy- efficient ecosystem, while community associated with periodontitis was perceived to engage in a more strenuous reciprocal effort for
survival. Additionally, the byproducts of fermentation, such as short- chain fatty acids like propionate, butyrate and isobutyrate, have been closely associated with periodontitis[56].
In addition to observed differences in energy acquisition, some periodontal microbiota is capable
of actively suppressing immune activation. This process could potentially enable microbes to evade
the immune system, resulting in an accumulation of microbes at levels that have the potential to
induce periodontal diseases[31]. An example is P. gingivalis produces a specific form of LPS that
reduces the response of Toll- like receptor 4. Additionally, it secretes a serine phosphatase that
inhibits the secretion of IL- 8, which is a pro- inflammatory cytokine. This mechanism is believed to
interfere with the normal host inflammatory process[31]. On the other hand, in health, it is plausible that the regulation of the immune response by native organisms could be vital in maintaining
balance, as evidenced by the presence of P. gingivalis albeit in low quantities.
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18.4 Future Directions inOral Microbiome Research
andClinical Implications
Research on the oral microbiome has only recently begun to unveil its true potential over last
few decades due to advancements in metagenomics sequencing coupled with other OMICS techniques. Until now, most studies have been of an observational nature. However, in clinical
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settings, it is more important to understand how the oral microbiome could be modulated for
health benefits. Personalised oral health care is anticipated to emerge, tailoring interventions
based on individual microbial profiles for more effective preventive and treatment strategies.
Microbial therapeutics, such as probiotics, will likely play a key role in modulating the oral
microbiome to promote a healthier balance. In this regard, future research projects should focus
on microbiome modulation therapy, which can be used as an adjunct therapy along with professional mechanical therapy for dental caries and periodontitis. More emphasis should be placed
on translational research, where bench work can be applied in clinical settings. While gut microbiome transplant has proven to be a possible therapy for some gut diseases, oral microbiome
transplant is still in its infancy[57, 58]. Utilising advances in metagenomic and metatranscriptomic technologies early disease detection can revolutionise diagnostics, offering insights into
oral conditions at their inception. These advancements collectively hold the potential to revolutionise oral healthcare, providing more tailored and effective approaches to maintain and
improve oral health.
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