ORIGINAL ARTICLE
The oral metagenome in health and disease
Pedro Belda-Ferre1, Luis David Alcaraz1, Rau´l Cabrera-Rubio1, He´ctor Romero2,
Aurea Simo´n-Soro1, Miguel Pignatelli1 and Alex Mira1
1Department of Genomics and Health, Center for Advanced Research in Public Health, Valencia, Spain and
2Laboratorio de Organizacio´n y Evolucio´n del Genoma, Facultad de Ciencias/C.U.R.E., Universidad de la
Repu´blica, Montevideo, Uruguay
The oral cavity of humans is inhabited by hundreds of bacterial species and some of them have a
key role in the development of oral diseases, mainly dental caries and periodontitis. We describe for
the first time the metagenome of the human oral cavity under health and diseased conditions, with a
focus on supragingival dental plaque and cavities. Direct pyrosequencing of eight samples with
different oral-health status produced 1Gbp of sequence without the biases imposed by PCR or
cloning. These data show that cavities are not dominated by Streptococcus mutans (the species
originally identified as the ethiological agent of dental caries) but are in fact a complex community
formed by tens of bacterial species, in agreement with the view that caries is a polymicrobial
disease. The analysis of the reads indicated that the oral cavity is functionally a different
environment from the gut, with many functional categories enriched in one of the two environments
and depleted in the other. Individuals who had never suffered from dental caries showed an over-
representation of several functional categories, like genes for antimicrobial peptides and quorum
sensing. In addition, they did not have mutans streptococci but displayed high recruitment of other
species. Several isolates belonging to these dominant bacteria in healthy individuals were cultured
and shown to inhibit the growth of cariogenic bacteria, suggesting the use of these commensal
bacterial strains as probiotics to promote oral health and prevent dental caries.
The ISME Journal advance online publication, 30 June 2011; doi:10.1038/ismej.2011.85
Subject Category: microbe–microbe and microbe–host interactions
Keywords: metagenomics; human microbiome; dental caries; Streptococcus mutans; pyrosequencing;
probiotics
Introduction
The oral cavity of humans is inhabited by hundreds
of bacterial species, most of which are commensal
and required to keep equilibrium in the mouth
ecosystem. However, some of them have a key role
in the development of oral diseases, mainly dental
caries and periodontal disease (Marsh, 2010). Oral
diseases initiate with the growth of the dental
plaque, a biofilm formed by the accumulation of
bacteria in a timely manner together with the human
salivary glycoproteins and polysaccharides secreted
by the microbes (Marsh, 2006). The subgingival
plaque, located within the neutral or alkaline
subgingival sulcus, is typically inhabited by anae-
robic Gram negatives and is responsible for the
development of gingivitis and periodontitis. The
supragingival dental plaque is formed on the teeth
surfaces by acidogenic and acidophilic bacteria,
which are responsible for dental caries. This is
considered the most extended infectious disease in
the world, affecting over 80% of the human
population (Petersen, 2004). A poor oral health has
also been related to the stomach ulcers, gastric
cancer or cardiovascular disease, among others
(Watabe et al., 1998; Wu et al., 2000). It is therefore
surprising that no efficient strategies to combat oral
diseases have been developed, despite their dra-
matic impact on human health. Some of the main
reasons that oral pathogens have not been eradicated
are related to the difficulty of studying the microbial
communities inhabiting the oral cavity: First, the
complexity of the ecosystem (several hundreds of
species have been reported with multiple interac-
tion levels) makes the potential pathogenical species
difficult to target (Socransky et al., 1998); second,
not a single ethiological agent can be identified as in
classical, Koch’s postulates diseases. This has been
clearly shown in periodontal disease, where at least
three bacterial species that belong to very different
taxonomic groups (the so-called ‘red complex’ of
periodontal pathogens) are known to be involved in
the illness (Darveau, 2010); and third, a large
proportion of oral bacteria cannot be cultured
(Paster et al., 2001), and therefore traditional
microbiological approaches give an incomplete
picture of the natural communities inhabiting the
Received 17 March 2011; revised 10 May 2011; accepted 12 May
2011
Correspondence: A Mira, Department of Genomics and Health,
Center for Advanced Research in Public Health (CSISP), Avda.
Catalun˜a 21, Valencia 46020, Spain.
E-mail: mira_ale@gva.es
The ISME Journal (2011), 1–11
& 2011 International Society for Microbial Ecology All rights reserved 1751-7362/11
www.nature.com/ismej

dental plaque. However, the development of meta-
genomic techniques and next-generation sequencing
technology now allows the study of whole bacterial
communities by analysing the total DNA pool from
complex microbial samples.
Pioneering metagenomic studies in the human
microbiome centred in the gut ecosystem, initially
through a shot-gun approach, in which DNA was
cloned in small-size plasmids followed by tradi-
tional Sanger sequencing method (Gill et al., 2006;
Kurokawa et al., 2007), obtaining reads of about
800–1000-bp long. Recent approaches include the
end sequencing of large-size fosmids (Vaishampayan
et al., 2010) and the use of Illumina sequencing
technology to deliver vast amounts of small-size
reads that could be later assembled (Qin et al.,
2010). Studies of the oral cavity microbiota, as well
as other body habitats within the human micro-
biome such as the skin, the vagina or the respiratory
tract, have mainly focused on the sequencing of
PCR-amplified rRNA genes (Aas et al., 2005; Grice
et al., 2008). These PCR-based studies have pro-
vided a substantial improvement of our knowledge
of oral bacterial communities compared with past
culture-based research, but the estimates of micro-
bial diversity are hampered by biases in PCR
amplification (de Lillo et al., 2006), cloning bias
(Ghai et al., 2010) and when short pyrosequencing
reads of the 16S rRNA gene were used, uncertainties
in taxonomic assignment (Keijser et al., 2008;
Lazarevic et al., 2009) and inflated diversity due to
pyrosequencing errors (Quince et al., 2009).
Recently, the first study of the oral metagenome
has been carried out by directly applying next-
generation sequencing to a single sample from a
healthy individual (Xie et al., 2010), thus removing
potential biases imposed by cloning and PCR. We
have applied a similar approach to several samples
varying in health status, directly sequencing the
metagenomic DNA by 454 pyrosequencing, which
has allowed us to compare the total genetic
repertoire of the bacterial community under differ-
ent health conditions.
Materials and methods
Sample collection
Supragingival dental plaque was obtained from 25
volunteers after signing an informed consent. The
sampling procedure was approved by the Ethical
Committee for Clinical Research from the DGSP-
CSISP (Valencian Health Authority, Spain). The oral
health status of each individual was evaluated by a
dentist following recommendations and nomencla-
ture from the Oral Health Surveys from the WHO,
taking samples with sterile curettes. Plaque material
from all teeth surfaces from each individual was
pooled. In volunteers with active caries, the dental
plaque samples were taken without touching
cavities. In those cases, material from individual
cavities was also extracted and kept separately. The
volunteers were asked not to brush their teeth 24 h
before the sampling. Information was obtained
regarding oral hygiene, diet and signs of periodontal
disease. DNA was extracted using the MasterPure
Complete DNA and RNA Purification Kit (Epicentre
Biotechnologies, Madison, WI, USA), following the
manufacturer’s instructions, adding a lysozyme
treatment (5 mg ml1, at 37 1C for 30 min). For this
study, eight samples were used for subsequent
pyrosequencing, selected on the basis of homogene-
ity in their clinical features, including similar age,
periodontal status, smoking habits and mucosal
health. Supragingival dental plaque samples were
taken from six individuals that were divided in
three groups according to the number of caries they
had suffered and that represented different degrees
of oral health: two individuals had never developed
caries in their lives (healthy controls), another two
individuals had been regularly treated for caries in
the past and had a low number of active caries at the
moment of sampling (one and four cavities, respec-
tively); and the last two individuals had a high
number of active caries (8 and 15) and poor oral
hygiene. In addition, samples from individual
cavities were collected, and for two of them enough
DNA for pyrosequencing was obtained: one at an
intermediate stage and the other one at an advanced
stage of caries development (dentin lesion), corre-
sponding to teeth 1.6 and 4.6 following WHO
nomenclature. The sequencing was performed at
Macrogen Inc. (Seoul, South Korea) using the
GS-FLX sequencer (Roche, Basel, Switzerland) with
Titanium chemistry. After quality checking, average
read length was 425±117 bp. Sequences were
deposited, and are publicly available in the
MG-RAST server with the following accesions:
4447192.3, 4447102.3, 4447103.3, 4447101.3,
4447943.3, 4447903.3, 4447971.3 and 4447970.3.
Sequence analysis
Artificially replicated sequences (accounting for
1.2–4.54% of the raw reads) were removed from
the data set using the ‘454 replicate filter’ (Gomez-
Alvarez et al., 2009). The human sequences were
identified by MegaBlast (Altschul et al., 1990)
against the human genome (e-value cutoff 1e10)
and were removed from the final data set. They
accounted for 2.23–74.99% of the replicate-filtered
reads (Supplementary Table 1). The metagenomic
reads were mapped against 1117 sequenced refer-
ence genomes using the Nucmer and Promer v3.06
alignment algorithms, with the default parameters
(Kurtz et al., 2004). The nucleotide identity values
of each read against its hit in the genome were used
to generate frequency histograms. If the mode was
94% or higher the plot was considered to represent
sequence identity against the same species
(Konstantinidis and Tiedje, 2005). Stand-alone
RPSBlast was used to align reads (translated into
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all six possible reading frames) to protein profiles
(represented by position-specific scoring matrices).
Queries were performed against the complete con-
served domains database (Marchler-Bauer et al.,
2009) and against the COGs (Tatusov et al., 2003)
and Tigrfams (Selengut et al., 2007) databases.
Fractions of sequences assigned in each case are
shown in Supplementary Table 2. TFams classi-
fication assignments were integrated into higher
hierarchical levels, according to the Tigrfam classi-
fication scheme, in subroles and main roles. COGs
assignments were also integrated into the higher
level of COG’s functional categories. In addition,
samples were uploaded to the MGRAST server
(Meyer et al., 2008) and the functional assignment
based on SEED subsystems was retrieved for the
three hierarchical levels used: Subsystem, subsys-
tem hierarchy 2 and subsystem hierarchy 1 (bottom
up). In all cases, a table containing the counts of
functional categories per sample was generated and
used for subsequent analysis. All statistical analyses
were conducted on R (2.6.2). Heat maps of taxo-
nomic composition were generated using the gplots
library of R (Warnes et al., 2009) with relative
frequencies per sample, as well as Euclidean distance,
or normal medians. The relative rates of over-repre-
sented features present in the people without caries
were estimated using a control of the false discovery
rate, for testing the amount of false positive predictions
(q-values) for a given P-value of significance, with the
algorithm described by White et al. (2009).
Taxonomic assignment
16S rRNA sequences were extracted from the reads
of each metagenome by similarity search using
BLASTn (Altschul et al., 1990) against the RDP
database, with an e-value cutoff of 1e–10. Sequences
o200 bp were removed. Phylogenetic assignment of
the sequences was made using the RDP Classifier
(Wang et al., 2007), using an 80% confidence
threshold. New operational taxonomic units were
proposed if the reads were over 400 bp in length and
had a nucleotide identity between 80–95% to
known 16S sequences. Taxonomic assignments of
all open reading frames were carried out based on a
lowest common ancestor (LCA) algorithm (Alstrup
et al., 2004) with the characteristics described in the
MEGAN software (Huson et al., 2007). We imple-
mented the algorithm in a multi-threaded com-
mand-line oriented in-house software in order to
obtain faster analysis and simplify its integration in
pipelines and downstream analysis. To obtain the
LCA of each sequence, we carried out BLASTx
homology searches against a custom database com-
prising the non-eukaryotic sequences of the NCBI’s
non-redundant database. For each query sequence
(read), only hits with a bit score at least 90% of the
best matches were considered in the LCA computa-
tion. We also made use of the script phymmBL
(Brady and Salzberg, 2009) that combines the
assignment of sequences both by homology and
by nucleotide composition using hidden Markov
Models. All the available complete and WGS genomes
were retrieved from the human oral microbiome
database (Chen et al., 2010), as well as the RefSeq of
NCBI containing all bacterial and archaea genomes
(june 2010), and were used to build a local database to
perform taxonomic model constructions and homol-
ogy searches, using sequences larger than 200 bp to
predict taxonomic affiliation. At this read length,
phymmBL’s performance at the class level has been
estimated to be over 75%. All the taxonomic and
functional results were parsed into a MySQL database
for further analysis.
Results and discussion
The oral microbiome by pyrosequencing
Supragingival dental plaque samples were taken from
six individuals that were divided in three groups
according to the number of caries they had suffered
and that represented different degrees of oral health:
two individuals had never developed caries in their
lives (healthy controls), another two individuals had
been regularly treated for caries in the past and had a
low number of active caries at the moment of
sampling; and the last two individuals had a high
number of active caries and poor oral hygiene. In
addition, samples from individual cavities were
collected, and for two of them enough DNA for
pyrosequencing was obtained. A total of 1 Gbp of
DNA sequence was obtained from the eight samples
selected. The amount of human DNA in the metagen-
omes varied from 0.5–40% in supragingival dental
plaque samples (Supplementary Table 1), thus the
total size of the studied metagenome was reduced to
842 Mbp of sequence. We obtained an average read
length of 425±117 bp, which allowed a functional
assignment in a significant fraction of the metagen-
ome (Supplementary Table 2). In addition, assembly
of those reads produced 1103 contigs larger than 5 Kb
and 354 longer than 10 Kb. Success in the assembly of
large contigs was dependent on sequencing effort. We
obtained an average of 129.5 Mbp of filtered, high-
quality sequences for each of the six oral samples. In
the two cavity samples, around 70% of the reads
corresponded to human DNA, and an average of
32.5 Mbp of filtered, high-quality reads were obtained.
Estimating diversity in the oral metagenome
We estimated microbial diversity in all samples by
three different methods. First, we selected the reads
matching 16S rRNA genes, assigning them to different
taxonomic levels. A total of 4254 16S rRNA sequences
were obtained (Supplementary Table 1), giving a
similar picture of diversity to that obtained through
16S rRNA PCR-dependent procedures (Bik et al.,
2010), although the relative proportions of each
taxonomic group were different (Figure 1). These
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Figure 1 Bacterial diversity in the oral cavity. The graph on the left shows the relative frequency of different bacterial taxa, based on the
assignment of the DNA reads by the PhymmBL software and by 16S rRNA reads extracted from the metagenome, and compared with the PCR
results obtained by Bik et al. (2010). The graph on the right indicates the relative contribution of each taxonomic group to the coding potential of
the ecosystem, based on the COGs functional classification system. It can be observed that the functional contribution is not equal among taxa.
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16S rRNA reads identified 186 sequences represent-
ing novel operational taxonomic units previously
undetected by PCR amplification (Supplementary
Table 3). Rarefaction curves and different diversity
indexes based on the rRNA sequences obtained from
the metagenomic reads indicate an estimate of
73–120 genera for dental plaque samples (Supple-
mentary Table 1 and Supplementary Figure 2). A
second approach to estimate diversity was the use of
a LCA algorithm to classify all reads giving a hit in
public databases at the taxonomic level for which
the assignment was unambiguous (Huson et al.,
2007). Over 1.5 million reads were assigned by this
procedure, confirming the presence of bacterial
groups detected by 16S rRNA genes, but suggesting
that a wider range of taxonomic groups was present
(Supplementary Figure 1). Finally, the recently
developed phymmBL binning procedure (Brady
and Salzberg, 2009) was used to taxonomically
assign 1.94 million reads from our data set. The
results agreed again with the taxonomic distribution
described by the 16S rRNA and the LCA approaches,
but with further implication of other bacterial taxa.
The results from these three methods show that the
relatively small numbers of 16S genes in directly
sequenced metagenomes are enough to describe the
main taxonomic groups present without cloning or
PCR-based biases, although at the expense of lower
sequence depth. Some of the taxa found at low
proportions in our data set were also detected by
large-scale 16S rRNA cloning studies (Paster et al.,
2001; Bik et al., 2010) but others were not (Figure 1).
This could be not only due to lower amplification
efficiency of these bacteria by universal primers, but
also due to the detection of false positive hits by the
LCA and phymmBL approaches.
Despite the low number of samples examined,
interesting differences in diversity can be seen
between healthy and diseased individuals. All three
methods showed a tendency for Bacilli and Gamma-
Proteobacteria to be more common in healthy
individuals, whereas typically anaerobic taxa like
Clostridiales and Bacteroidetes are more frequent
in diseased samples (Figure 1, Supplementary
Figure 1). Bacilli are particularly depleted in the
two samples from within cavities, and one of them
showed a high proportion of Actinobacteria. Reads
assigned to beta-Proteobacteria (mainly Neisseriales)
and TM7 were at very low proportions in diseased
samples, and studies based on a larger number of
individuals should test whether their presence
could be associated to healthy conditions. Corre-
spondence analysis between the metagenomes
based on the taxonomic assignation by 16S rRNA
reads showed that samples with poor oral health
tended to cluster together, whereas different con-
sortia of bacteria can be found in healthy indivi-
duals (Figure 2). Some genera, like Rothia or
Aggregatibacter appear to be specifically associated
to healthy samples, in agreement with PCR-based
studies that compared bacterial diversity in healthy
controls and diseased volunteers (Aas et al., 2005,
2008; Corby et al., 2005). The metagenomic recruit-
ments also showed Aggregatibacter as one of
the prevalent species in individuals without caries
(see below).
Sequence similarity searches against 18S rRNA
databases revealed very few significant hits against
eukaryotic species. No rRNA reads were identified
from Candida or other fungi that are regular
inhabitants of the oral cavity, indicating that
although these organisms are frequently detected
by PCR amplification (Ghannoum et al., 2010), they
are probably present at low proportions. In sample
CA-04, significant hits to the rRNA ITS region
of the protozoan Trichomonas tenax were found.
Trichomonas tenax is found particularly in the oral
cavity of patients with poor oral hygiene and
advanced periodontal disease (Kleinberg, 2002),
and it has been shown to be involved in broncho-
pulmonary infections.
An effective tool to quantify the presence of
selected species in metagenomes is provided by
sequence recruitments (Rodriguez-Valera et al.,
2009). Individual metagenomic reads that give a
hit over a certain identity threshold against a
Figure 2 Correspondence analysis (CoA) of the bacterial diver-
sity in oral samples based on 16S rRNA reads extracted from the
metagenomes. The first axis successfully separates healthy from
diseased individuals. The graph suggests bacterial genera which
are potentially associated with absence of caries.
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reference bacterial genome are ‘recruited’ to plot a
graph, which will vary in density depending on the
abundance of that organism in the sample. If the
average nucleotide identity displayed is above 94%,
the recruitment is very likely made against reads of
the same species (Konstantinidis and Tiedje, 2005).
By comparing our metagenomes against the genomes
of 1117 fully sequenced genomes available in
databases, we were able to estimate the abundance
of close relatives of these reference species in our
samples (Supplementary Figure 3A). Interestingly,
bacteria closely related to Aggregatibacter and
Streptococcus sanguis were among the three with
the highest level of recruitment in individuals
without caries, in agreement with these species
being more frequently amplified from the oral cavity
of healthy individuals (Aas et al., 2005; Corby et al.,
2005). On the other hand, Streptococcus gordonii
and Leptotrichia buccalis were abundant in indivi-
duals with caries. Strains of Veillonella parvula
were the most abundant in all individuals with
caries and appeared to be common to all samples,
but interestingly the recruitment plots show differ-
ences between strains (Supplementary Figure 4). For
instance, the Veillonella present in the two healthy
individuals shows a genomic island without recruit-
ment, even at the protein level, between positions
2066–2094 Kb of the reference genome. Individuals
with caries CA-04 and CA1-01 do contain this
region, which includes CRISPR-associated genes,
hypothetical proteins, a protein involved in DNA
uptake and an amidophosphoribosyltransferase.
This way, differences between strains of the same
species can be identified which would pass
unnoticed by 16S rRNA studies, and future work
should identify whether those differential genes
might be involved in pathogenesis. In addition,
recruitment plots indicate that few taxa are normally
dominant in each metagenome (Supplementary
Figure 3B). This suggests that although bacterial
diversity is indeed very large in the oral cavity, very
few taxa account for most of the bacterial cells, and a
big portion of the identified species are present at
very low densities.
Functional diversity in the oral ecosystem
One of the powerful applications of LCA and
phymmBL approaches is that each read with a
significant hit can be assigned a taxonomic origin,
and at the same time can also be related in many
cases to a putative function. By relating taxonomy to
function we have been able to predict what
ecological or metabolic role each bacterial group
can have. An example of this ‘who can do what’
approach can be seen in Figure 1 by using the COGs
function classification system. It shows that cate-
gories are not equally distributed, and that some
taxonomic groups are especially endowed for per-
forming concrete functions. For example, a large
portion of genes involved in defence mechanisms
(that is, restriction endonucleases and drug efflux
pumps) appear to be encoded by Bacilli. Other
functions unequally distributed were cell motility
genes in Clostridiales (mainly flagellar proteins) or
signal transduction and carbohydrate metabolism in
Bacilli (Figure 1, right). A more detailed functional
analysis of the metagenome was performed using
several systems for gene classification at different
hierarchical levels. All pyrosequencing reads were
compared against the conserved domains database,
the Subsystems annotation environment (SEED) and
the Tigrfams profiles (see Materials and methods
section). Correspondence analysis (CoA) of the eight
samples according to the functional assignment of
the reads gave similar clustering patterns for the
three function classification systems (Supplemen-
tary Figure 5). Samples from diseased individuals
tended to cluster together, indicating that a similar
set of functions were encoded in their metagenomes,
and the two samples from individuals that had
never suffered from caries, together with sample
CA1-01 (with only one cavity at the moment of
sampling), could be separated from the rest by the
principal component. When the functional assign-
ment of the oral microbiome was compared with
that of the adult gut microbiome (Kurokawa et al.,
2007) a w2-test of independence revealed that the
overall gut and oral functional roles depicted in the
RAST subsystems are significantly different
(w2(df¼158)¼ 17 057.42, Po2.2e16, f¼ 0.123), and
this was supported also by clustering analysis where
the oral samples clustered together (Figure 3),
indicating that the gut and the mouth are two
different ecosystems in terms of the relative fre-
quencies of functions encoded in their metagen-
omes. It had previously been shown that the
taxonomic diversity of the gut and oral ecosystems
is clearly distinct (Bik et al., 2010), despite the fact
that clear examples of horizontal gene transfer have
been shown between these two interconnected
niches (Mira, 2007). Our data show large blocks of
over-represented functions in the gut microbiome,
while others appear over-represented in the oral
samples (a detailed list of these functional categories
is represented in Supplementary Figure 6). It is
interesting to note that metabolic genes, like those
involved in sugar uptake and assimilation, are
enriched in gut bacteria together with adhesion
proteins and prophage genes, whereas gene families
related to oxidative and osmotic stress or iron
scavenging are more frequent in the oral microbiome
(Figure 3). Thus, the relative proportion of these
functional categories provides important insights
into the ecology of each ecosystem and the potential
role of the corresponding microbiotas for human
health.
Within the oral samples, individuals are clustered
according to their health status (Figure 3). From an
applied viewpoint, it is interesting that several
functional categories are over-represented in sam-
ples from individuals without caries. Remarkable
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uprepresented genes in healthy individuals are
involved in antibacterial peptides like bacteriocins
(P-value¼ 2.95 e7; q-value¼ 4.63 e8), periplas-
mic stress response genes like degS, degQ (P¼ 2.46
e46; q¼ 3.22 e46), capsular and extracellular
polysaccharides (P¼ 7.04 e5; q¼ 8.5 e6) and
bacitracin stress response genes (P¼ 3.4 e3;
q¼ 3.24 e4). Other functional categories were also
over-represented but the difference was not statisti-
cally significant, like genes involved in quorum
sensing and phospholipid metabolism. The higher
presence of bacteriocin-related genes points at these
bioactive compounds as promising potential anti-
caries agents. Some gene features over-represented
in individuals with active caries are involved in
mixed-acid fermentation (P¼ 2.85 e260; q¼ 2.65
e259) and DNA uptake and competence (P¼ 6.29
e8; q¼ 1.13 e8). Finally, it must be underlined
that some over-represented genes in healthy indivi-
duals have an unknown function, and future studies
should elucidate whether they are involved in the
protection of the teeth against cariogenic conditions.
Cavities are complex ecosystems
We were able to extract sufficient DNA for 454
pyrosequencig in two samples from individual
teeth, one at an intermediate stage and the other
one at an advanced stage of caries development
(dentin lesion). Given that mutans streptococci
initially were considered to be the main ethiological
agents of dental caries (Loesche, 1986), it is not
surprising that most strategies against this disease
have aimed at targeting Streptococcus mutans.
These include the development of a vaccine using
known surface antigens, passive immunization
strategies that could neutralize the bacterium, the
co-aggregation of S. mutans to probiotic strains or
the use of specific inhibitors of S. mutans proteins,
among others (Russell et al., 2004). In addition, the
Figure 3 Functional profiles from oral and adult-gut metagenomic samples. Classification was based on Subsystem hierarchy 2 of
MG-RAST. Counts were normalized to the total number of reads per sample and then normalized by function. Blue to red gradient
indicates levels of under/over-representation. Large blocks of gene categories are over-represented in each of the two microbiotas,
indicating that the gut and the oral cavity are two functionally distinct ecosystems. Within the oral microbiome, some functional roles are
over-represented in individuals without caries. A full version of this figure indicating all 101 functional categories is included in
Supplementary Figure 6. Sequences from the healthy adult-gut metagenomes were taken from Kurokawa et al. (2007). The age and sex of
each individual are indicated below each label.
The oral metagenome
P Belda-Ferre et al
7
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presence of mutans streptococci in children is
typically associated to caries risk in oral-health
evaluation protocols (Ge et al., 2008). However,
pioneering molecular-based studies of cavities have
failed to amplify mutans streptococci by PCR or
hybridization in a significant proportion of cavities,
suggesting that other bacterial genera like Lactoba-
cillus, Actinomyces or Bifidobacterium could be
involved in the disease (Aas et al., 2008; Becker
et al., 2002). Recent molecular work has confirmed
this finding and expanded the list of potential
cariogenic bacteria to other species like Veillonella,
Propionibacterium and Atopobium (Aas et al.,
2008), most of them are poorly studied bacteria.
The metagenomes of cavities studied here showed
an almost complete absence of S. mutans. However,
they displayed a large taxonomic diversity, which
are included among the most common genera,
Veillonella, Corynebacterium or Leptotrichia (Sup-
plementary Table 4). Some of these bacteria, parti-
cularly Veillonella, have been shown to be
predominant at all stages of caries progression (Aas
et al., 2008) and under high-glucose conditions, and
appear to be implied in acid production (Bradshaw
and Marsh, 1998). Interestingly, consortia between
Veillonella alcalescens and S. mutans were shown
to produce more acid than any one of these species
separately (Noorda et al., 1988), suggesting that
synergistic effects probably take place, as it has been
demonstrated in other complex microbial commu-
nities. Thus, although these data are based on the
metagenomes from only two cavities, they favour a
nonspecific plaque hypothesis for the development
of dental caries (Marsh, 1994; Kleinberg, 2002).
Further work should elucidate the potential role
these bacteria had other than mutans streptococci in
the progression of caries, as well as their synergistic
and antagonistic interactions. The forecoming im-
provements in the amount of DNA required for next-
generation sequencing techniques will allow a
metagenomic study of cavities at different stages of
development, including initial, white-spot lessions.
This is important because mutans streptococci
could be instrumental at initial stages of caries,
after which other species could colonize the niche.
If caries is confirmed to be a polymicrobial disease,
this should be taken into account for future
therapeutic strategies. For instance, a potential
solution for immunization strategies could pass
through the selection of vaccine targets shared by
different pathogens involved in the process of tooth
decay (Mira et al., 2004; Mira, 2007).
a
S. australis
S. infantis
S. sp. 7747
S. peroris
S. pseudopneumoniae
S. pneumoniae
S. mitis
S. oralis
S. parasanguinis
S. sanguinis
S. alactolyticus
S. gallolyticus
S. hyointestinalis
S. suis
S. gallinaceus
S. cristatus
S. oligofermentans
S. sinensis
S. constellatus
S. intermedius
S. mutans UA159
S. sanguinis SK36
S. mutans UA159
S. sanguinis SK36
CA04P NOCA01
100
80
60
0.5 1 1.5
100
80
60
0.5 1 1.5
0.5 1 1.5
2 0.5 1 1.5 2
b
c
d
%
ID
%
ID
Mb Mb
Mb Mb
S. gordonii
Figure 4 Searching of bacterial strains with a potential antagonistic effect against cariogenic bacteria. Metagenomic recruitment plots
are used to detect the species (a), which are at low frequencies in individuals with caries but are among the most common in caries-free
subjects. These species are then selected based on culture conditions and microscopic examination (b). The isolates are grown in solid
media to provide an inhibition screening against caries-producing bacteria (c), selecting the strains that display inhibition rings (d), such
as the Streptococcus strain 7747. Sequencing the genome of these inhibitory strains and comparing it against the metagenome of caried
individuals must confirm that these strains are absent under diseased conditions.
The oral metagenome
P Belda-Ferre et al
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Search for potential probiotics through metagenomics
The existence of a small proportion of the human
adult population that has never suffered from dental
caries has led some authors to suggest the presence
of some bacterial species with a potential antag-
onistic effect against cariogenic bacteria (Corby
et al., 2005). Bacterial replacement of pathogenic
strains by innocuous isolates obtained from healthy
individuals has been successfully shown to prevent
pharynx infections and is the basis for probioticts
preventing infectious disease in the gut and other
human niches (Tagg and Dierksen, 2003). Metage-
nomic recruitment of cariogenic bacteria against the
oral microbiome of healthy individuals shows a
complete absence of S. mutans and S. sobrinus.
Interestingly, the lack of detection of the cariogenic
bacteria is accompanied by an intense recruitment
of other streptococci (mainly those related to
S. sanguis) and Neisseria, which comprise the most
abundant genera in these individuals (Supplemen-
tary Figure 3B). Given the possibility that isolates
of these dominant genera could be involved in
antagonistic interactions with cariogenic bacteria,
fresh dental plaque samples from 10 healthy
individuals (including those from which the meta-
genomic sequences were obtained) were collected
and used for culturing under conditions optimal for
the growth of neisserial and streptococcal species.
After microscopic examination, diplococci and
streptococci were selected, providing a collection
of 249 isolates. Those that could be grown on the
same culture medium as S. mutans and S. sobrinus
were transferred to a loan culture of these cariogenic
bacteria. This simple screening identified 16 strains
that displayed inhibition rings (Figure 4). PCR
amplification of the 16S rRNA gene identified
most of them as streptococci, with a 96–99%
sequence identity to S. oralis, S. mitis and
S. sanguis. Thus, this metagenomic approach al-
lowed us to quantify the most abundant bacteria
and confirms the previously hypothesized presence
of bacteria with a protective effect against cariogenic
species. This effect appears to be direct (that is,
inhibitory), but other indirect effects such as
stimulation of the immune response or direct
competition for the same substrate or niche cannot
be ruled out. Future research on these isolates
should aim at identifying the secreted compounds
responsible for the inhibition of caries-producing
bacteria, and metagenomic libraries of dental
plaque DNA may prove useful in this respect
(Seville et al., 2009). Our own inhibition screenings
performed on metagenomic fosmid libraries from
dental plaque of healthy individuals against cario-
genic bacteria suggest that antimicrobial peptides
are among the products causing the inhibition. We
propose the probiotic use of these anti-cariogenic
bacteria or the utilization of the antibiotics they
encode as promising new therapies against dental
caries and other oral diseases (Devine and Marsh,
2009).
Conclusion
We have shown that the direct pyrosequencing of
human samples is a feasible approach to study the
human microbiome, which would obviate the biases
imposed by cloning and PCR and that would
provide a more complete view of human-related
bacterial communities beyond their composition
inferred from the 16S rRNA gene (Ghai et al.,
2010; Xie et al., 2010). Even in samples with a large
proportion of human DNA such as cavities, the large
throughput of next-generation sequencing has pro-
vided enough sequences to gain insights into the
microbiology of caries, suggesting that it is the
outcome of a complex bacterial community. Despite
the limited number of samples analyzed in this first
study, important differences between healthy and
diseased sites and individuals can be observed at
the taxonomic and functional level, suggesting that
the dental plaque of individuals that have never
suffered from caries can be a genetic reservoir of
new anticaries compounds and probiotics. Future
population-based studies must evaluate whether the
trends described in this study hold when higher
sample sizes are used. We hope that these results
stimulate further sequencing of the oral metagenome
and metatranscriptome in the future as a tool to
understand and combat the development of oral
diseases.
Acknowledgements
This work was funded by the following projects from the
Spanish MICINN: SAF2009-13032-C02-02 from the IþD
program, BIO2008-03419-E from the EXPLORA program
and MICROGEN CSD2009-00006 from the Consolider-
Ingenio program. We thank Professor F Rodriguez-Valera
and Professor Siv G Andersson for their advice and
comments, and three anonymous referees for their
constructive comments that significantly improved the
manuscript.
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