High Diversity of the Saliva Microbiome in Batwa
Ivan Nasidze1*., Jing Li1., Roland Schroeder1, Jean L. Creasey2, Mingkun Li1, Mark Stoneking1
1Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany, 2D.D.S., Nevada City, California, United States of America
We describe the saliva microbiome diversity in Batwa Pygmies, a former hunter-gatherer group from Uganda, using next-
generation sequencing of partial 16S rRNA sequences. Microbial community diversity in the Batwa is significantly higher
than in agricultural groups from Sierra Leone and the Democratic Republic of Congo. We found 40 microbial genera in the
Batwa, which have previously not been described in the human oral cavity. The distinctive composition of the salvia
microbiome of the Batwa may have been influenced by their recent different lifestyle and diet.
Citation: Nasidze I, Li J, Schroeder R, Creasey JL, Li M, et al. (2011) High Diversity of the Saliva Microbiome in Batwa Pygmies. PLoS ONE 6(8): e23352. doi:10.1371/
Editor: Francisco Rodrı´guez-Valera, Universidad Miguel Hernandez, Spain
Received May 24, 2011; Accepted July 13, 2011; Published August 16, 2011
Copyright: ? 2011 Nasidze et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This research was funded by the Max Planck Society, Germany. The funders had no role in study design, data collection and analysis, decision to
publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: firstname.lastname@example.org
. These authors contributed equally to this work.
The Batwa Pygmies, also known as Twa, are believed to be the
original inhabitants of the equatorial forests of the Great Lakes
region of Central Africa . They live in southwestern Uganda,
northern and southern Rwanda and in many areas of the Kivu
province of the Democratic Republic of the Congo (DRC).
Traditionally, the Batwa have been semi-nomadic hunter-
gatherers. However, relatively recent human activities, such as
clearing of the forests for agriculture and creation of conservation
areas, have pushed the Batwa from their traditional homeland and as
a consequence their lifstyle has changed dramatically. Most Batwa
forest on a daily basis. Batwa groups are small, rarely exceeding 50
people, and are often based around members of a particular clan.
An interersting feature of the Batwa is that they differ
significantly from neighboring Bantu agriculturalists in having
fewer caries lesions and reduced tooth loss . Differences in diet
and lifestyle provide the most likely explanation for the greater
prevalence of caries lesions and tooth loss among the Bantu than
among the Batwa. The Batwa have less access to highly cariogenic,
refined carbohydrates than do the Bantu. In addition, because of
their hunter-gatherer lifestyle, the diet of the Batwa tends to be
higher in animal protein than that of the Bantu, and this would
also contribute to a lower caries rate .
It is also possible that the oral microbiome of the Batwa may
either influence, or be influenced by, the lower prevalence of
caries.To investigate this further, we analyze here the saliva
microbiome diversity of the Batwa in comparison with agricultural
groups from similar enviroments in Africa, in order to address the
following questions: 1) how different is the Batwa saliva
microbiome from that of African agriculturalists; and 2) is the
low level of dental caries in the Batwa associated with particular
Materials and Methods
All participants gave written informed consent. The protocol
was in accordance with the Helsinki Declaration, and was
approved by the Ethics Commission of the University of Leipzig
Samples and DNA extraction
Saliva samples were collected from: 39 Batwa from the
Mpungo, Mukongoro, Kitariro, Nyakatare, Bikuto commuinities
of Buhoma, Uganda: 20 individuals from Kinshasa, Democratic
Republic of Congo (DRC); and 13 individuals from Freetown,
Sierra Leone (SL). (Figure 1). DNA was extracted as described
PCR amplification of the microbial 16S rRNA gene
We amplified a region of the microbial 16S rRNA gene
containing variable segments V1 and V2, which were previously
shown to be more informative than other parts of the 16S rRNA
gene in terms of the number of phylotypes detected . We used
the forward primer for V1 and the reverse primer for V2 ,
which together amplify a ,350 bp PCR product containing V1
Sequencing on the Genome SequencerFLX platform
The PCR products were processed for parallel-tagged sequenc-
ing on the Genome Sequencer FLX platform, as described
previously [5,6]. Briefly, sample-specific barcode sequences were
ligated to the PCR products, and DNA concentrations were
assessed on a Mx3005PTM(Stratagene). Samples were then pooled
in equimolar ratios to a total DNA amount of 440 ng. The pooled
library was subsequently amplified in PCR-mixture-in-oil emul-
sions and sequenced on one lane of a 4-lane PicoTiterPlate on a
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Genome Sequencer FLX/454 Life Sciences sequencer (Branford
CT), according to the manufacturer’s protocol. The negative
control was sequenced on an individual lane.
The initial sequence reads were filtered to remove artifactual
sequence reads (i.e., reads containing two or more different tags, no
tags, primers in the middle of sequence reads, or without a primer
sequence). The filtered sequences were then searched against the
Ribosomal Database Project II (RDPII) database , using the online
seqmatch_intro.jsp) and a threshold setting of 90%, to assign a
genus to each sequence. Diversity statistics and apportionment of
variation based on the frequency distribution of genera within and
between individuals were calculated with Arlequin 3.1 , while
pairwise correlation analysis and principal component analysis
(PCA) were carried out using STATISTICA 6.1 (StatSoft, Inc.) .
Mann-Whitney U tests  were used to compare distributions of
correlation coefficients. Rarefaction analysis was carried out using
the Resampling Rarefaction 1.3 software (http://www.uga.edu/
,strata/software/index.html ). UniFrac analysis  was used to
compare microbial community diversity in a phylogenetic context.
Comparative data on the salivia microbiome diversity in two
agricultural groups, from the Democratic Republic of Congo
(DRC) and Sierra Leone (SL), came from another study (J. Li, I.
Nasidze, and M. Stoneking, unpublished data).
A total of 29728 sequence reads were obtained from the
Genome Sequencer FLX. After filtering and removing sequence
reads less than 200 bp, 24358 sequences remained (Table 1).
Sequences shorter than 200 bp give potentially unreliable results
when compared to the RDPII database and were therefore
excluded from further analysis; more than 81.9% of the sequence
reads were at least 200 bp (Figure S1).
The results of comparing these sequences to the RDPII
database are provided in Table S1 and illustrated in the heat
plot in Figure 2. Altogether, 99.8% of the sequences matched a
previously-identified genus, while 0.2% were unknown (did not
match any sequence in the database above the 90% threshold
value). In the following analyses we focus only on those sequences
that matched a known genus in the RDPII database. A total of
127genera were detected in the 39 Batwa, compared to 71 genera
in the SL group and 54 genera in the DRC group (Table 1);
overall, 143 microbial genera were detected (Table S2). Although
many more genera were detected in the Batwa than in the other
two groups, there were also many more sequence reads obtained
from the Batwa than from the other two groups, as well as more
reads obtained for the SL group than the DRC group (Table 1). In
order to test whether or not the differences in the number of
detected genera are due to the diffferences in number of sequence
reads, we carried out a rarefaction analysis (Figure 3). The
rarefaction curves for the SL and DRC groups overlap, indicating
Figure 1. A map of sampling locations and piecharts showing the frequencies of the 15 most common microbial genera in these
Table 1. Number of sequence reads, detected genera and AMOVA.
No. ofUnknownTotal no. ofNo. of genera per individualVariance betweenVariance within
sequences%genera min - mean - maxindividuals (%)individuals (%)
Batwa Pygmy24358 0.0212711 - 30 - 6116.2783.73
DRC*53530.7548 - 13 - 2232.12 67.88
SL*178200.77112 - 23 - 3730.5769.43
*data from J. Li, I. Nasidze and M. Stoneking (unpublished data).
Saliva Microbiome Diversity in Batwa Pygmies
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Figure 2. Heat plot of the abundance of each bacterial genus in each individual, based on the partial 16S rRNA sequences. Each
numbered column corresponds to a genus, with the genus name for each number indicated in Table S1. Each row is an individual saliva sample. The
abundance of each genus is indicated by the grayscale value, according to the scale at the bottom of the plot. BP – Batwa Pygmy; DRC – group from
the Democratic Republic of the Congo; SL – group from Sierra Leone.
Figure 3. Rarefaction analysis of the number of bacterial genera detected in the three human groups as a function of the number of
reads. The data points represent averages of 1000 randomized resamplings without replacement.
Saliva Microbiome Diversity in Batwa Pygmies
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that the different numbers of genera detected for these two groups
can be explained by the difference in number of sequence reads.
However, the curve for the Batwa increases much more rapidly
compared with the other two groups, indicating that for similar
numbers of sequence reads, many more genera are detected in the
Batwa than in the other two groups. Thus, the Batwa are
distinguised from the other two groups in having many more
genera in their saliva microbiome.
A list of the top fifteen most frequent microbial genera found in
these groups and their distribution is shown in Figure 1. These
genera account for 81.9–89.4% of the total number of reads
obtained for each group.
Given the overall differences in the genera detected among the
three groups, how strongly correlated are the saliva microbiome
compositions of different individuals within and between groups?
To address this question, we calculated correlation coefficients for
the distribution of genera detected between each pair of
individuals, both within and between groups (Figure 4). In general,
with only a few exceptions, there are positive correlations within
each group. The average correlation coefficient within the Batwa
and within the SL group are similar (0.40 and 0.42, respectively),
while it is much lower within the DRC group (average correlation
coefficient=0.26). The average correlation is also higher between
the Batwa and the SL (0.42) than between the Batwa and DRC or
between the SL and DRC.
We also carried out an analysis of molecular variance
(AMOVA) in order to investigate how much of the total variation
in the saliva microbiome is due to differences within vs. among
individuals from each group. The results indicate that the SL and
DRC groups have very similar apportionments of variation, but
the Batwa have much less differentiation between individuals, with
16% of the variation between individuals, vs. 30–32% for the
other two groups (Table 1). Thus, the Batwa are characterized by
more overall diversity but more similarity among individuals in
their saliva microbiome, compared to the other two groups.
Pricipal component analysis (PCA; Figure 5) showed a quite
distinct position of most of the Batwa, separate from individuals
from SL and DRC. The latter two groups are not clearly separated
from each other.
In order to test whether the patterns observed in the PCA plot
are also seen at the sequence level, and not just from inferred
genera, we also carried out UniFrac analysis and multidimenional
scaling (MDS) based on UniFrac distances. The resulting MDS
plot is highly consistent with the patterns observed in the PCA plot
To gain further insights into the influence of lifestyle and diet on
the human saliva microbiome, we compared the saliva micro-
Figure 4. Pairwise correlation matrix between data sets, both within groups and between groups. The correlation coefficient values are
indicated by the grayscale value, according to the scale at the bottom of the matrix.
Saliva Microbiome Diversity in Batwa Pygmies
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biomes of Batwa Pygmies (who were, until recently, traditional
hunter-gatherers) with two farming groups, from Sierra Leone and
the Democratic Republic of the Congo.We found significantly
higher diversity in the saliva microbiome of the Batwa (127 different
genera) compared with the groups from DRC (54 different genera)
and SL (71 different genera). Rarefaction analysis (Figure 3)
indicated that this difference between the Batwa and the other
groups is not due to the higher number of sequence reads for the
Batwa, but instead reflects a true excess of the number of microbial
genera in the Batwa. One potential factor could be the protein-rich
diet of the Batwa, as more than 49% of their diet consists of hunted
animal meat . However, in the last two decades an agricultural
diet has become more prevalent in the Batwa.
We found 59 microbial genera that are unique to the Batwa
(Table S2). Although most of them are present in very low
frequency, some are present in higher numbers. For example,
Cloacibacterium, found at low frequency in several Batwa, was
discovered recently but in a different enviroment, namely in
municipal wastewater  and freshwater lake sediments .
We compared the list of microbial genera found in Batwa with
the Human Oral Microbiome Database  and with our
previous study of the saliva microbiome from worldwide
populations , and found that almost a third of the microbial
genera detected in the Batwa (40 genera) have not been described
in the human oral cavity before (Table S2). This finding suggests
that the human oral cavity harbors a much more diverse microbial
community than described so far, and illustrates the importance of
analyzing the oral microbiome in diverse human populations.
Although groups from SL and DRC are geographically distant
(figure 1), they show a higher degree of similarity to each other
than with the Batwa. The average genetic distance (Fst value)
between these groups is lower (0.183) than with the Batwa (0.226
and 0.242 respectively). This patterns are obvious also from MDS
and PC plots. This observation suggests that similar lifstyles and
diet can lead to more similar oral microbiomes, although larger
scale studies that include more groups from different parts of the
world are needed to further investigate this.
One ofthe interestingfeaturesofthe Batwaisa verylow incidence
of dental caries, compared with other neighboring groups. A key
environmental factor influencing pathogenicity of the oral biofilms
that colonize the hard tissues of the human mouth is pH . Alkali
generation, particularly through ammonia production from arginine
and urea, plays a major role in pH homeostasis in oral biofilms and
may protect from the initiation and progression of dental caries .
There are two major substrates for alkali production by oral biofilms
colonizing the teeth, urea and arginine; urea is present in saliva and
Figure 5. Principal coordinate plot based on genera frequencies showing relationships among the oral microbiome composition in
Batwa Pygmy and human groups from DRC and SL. Color coding for each group is shown at the bottom of the figure.
Saliva Microbiome Diversity in Batwa Pygmies
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