Bacterial biogeography of the human digestive tract.
ABSTRACT We present bacterial biogeography as sampled from the human gastrointestinal tract of four healthy subjects. This study generated >32 million paired-end sequences of bacterial 16S rRNA genes (V3 region) representing >95,000 unique operational taxonomic units (OTUs; 97% similarity clusters), with >99% Good's coverage for all samples. The highest OTU richness and phylogenetic diversity was found in the mouth samples. The microbial communities of multiple biopsy sites within the colon were highly similar within individuals and largely distinct from those in stool. Within an individual, OTU overlap among broad site definitions (mouth, stomach/duodenum, colon and stool) ranged from 32-110 OTUs, 25 of which were common to all individuals and included OTUs affiliated with Faecalibacterium prasnitzii and the TM7 phylum. This first comprehensive characterization of the abundant and rare microflora found along the healthy human digestive tract represents essential groundwork to investigate further how the human microbiome relates to health and disease.
- SourceAvailable from: Dilani B Senadheera[Show abstract] [Hide abstract]
ABSTRACT: Background: Periodontitis is an infectious and inflammatory disease of polymicrobial etiology that can lead to the destruction of bones and tissues that support the teeth. The management of chronic periodontitis (CP) relies heavily on elimination or at least control of known pathogenic consortia associated with the disease. Until now, microbial plaque obtained from the subgingival (SubG) sites has been the primary focus for bacterial community analysis using deep sequencing. In addition to the use of SubG plaque, here, we investigated whether plaque obtained from supragingival (SupG) and tongue dorsum sites can serve as alternatives for monitoring CP-associated bacterial biomarkers. Results: Using SubG, SupG, and tongue plaque DNA from 11 healthy and 13 diseased subjects, we sequenced V3 regions (approximately 200 bases) of the 16S rRNA gene using Illumina sequencing. After quality filtering, approximately 4.1 million sequences were collapsed into operational taxonomic units (OTUs; sequence identity cutoff of >97%) that were classified to a total of 19 phyla spanning 114 genera. Bacterial community diversity and overall composition was not affected by health or disease, and multiresponse permutation procedure (MRPP) on Bray-Curtis distance measures only supported weakly distinct bacterial communities in SubG and tongue plaque depending on health or disease status (P?<?0.05). Nonetheless, in SubG and tongue sites, the relative abundance of Firmicutes was increased significantly from health to disease and members of Synergistetes were found in higher abundance across all sites in disease. Taxa indicative of CP were identified in all three locations (for example, Treponema denticola, Porphyromonas gingivalis, Synergistes oral taxa 362 and 363). Conclusions: For the first time, this study demonstrates that SupG and tongue dorsum plaque can serve as alternative sources for detecting and enumerating known and novel bacterial biomarkers of CP. This finding is clinically important because, in contrast with SubG sampling that requires trained professionals, obtaining plaque from SupG and tongue sites is convenient and minimally-invasive and offers a novel means to track CP-biomarker organisms during treatment outcome monitoring.journal of micr. 08/2014; 2(32).
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ABSTRACT: The application of high-throughput next-generation sequencing to the analysis of the human microbiome has led to a shift in our understanding of the etiology of complex diseases. In consequence, a great deal of literature can now be found exploring this complex system, and reviewing recent findings. Observations of alterations in the intestinal microbiome associating with inflammatory bowel disease and other chronic conditions are well supported and have been widely accepted by the research community. Yet, it can be difficult to objectively evaluate the importance of these results, given the wide variety of methodologies applied by different groups in the field. The aim of this review is to focus attention on the basic principles involved in microbiome analyses, and to describe factors that may have an impact on the accurate interpretation of results.Am J Gastroenterol advance online publication, 22 April 2014; doi:10.1038/ajg.2014.73.The American Journal of Gastroenterology 04/2014; · 7.55 Impact Factor
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ABSTRACT: During the past decade, studies on the composition of human microbiota and its relation to the host became one of the most explored subjects of the medical literature. The development of high-throughput molecular technologies allowed a deeper characterization of human microbiota and a better understanding of its relationship with health and disease. Changes in human habits including wide use of antimicrobials can result in dysregulation of host-microbiome homeostasis, with multiple consequences. The purpose of this review is to highlight the most important evidence in the literature of host-microbiome interactions and illustrate how these intriguing relations may lead to new treatment and prevention strategies.The Brazilian journal of infectious diseases: an official publication of the Brazilian Society of Infectious Diseases 05/2014; · 1.04 Impact Factor
Bacterial biogeography of the human
Jennifer C. Stearns1*, Michael D. J. Lynch1,2, Dilani B. Senadheera3, Howard C. Tenenbaum3,
Michael B. Goldberg3, Dennis G. Cvitkovitch3, Kenneth Croitoru4, Gabriel Moreno-Hagelsieb2
& Josh D. Neufeld1
1Department of Biology, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada,2Department of Biology, Wilfrid Laurier
University, Waterloo, Ontario, N2L 3C5, Canada,3Faculty of Dentistry, University of Toronto, Toronto, Ontario, M5G 1G6,
Ontario, M5G 1X5, Canada.
We present bacterial biogeography as sampled from the human gastrointestinal tract of four healthy
subjects. This study generated .32 million paired-end sequences of bacterial 16S rRNA genes (V3 region)
representing .95,000 unique operational taxonomic units (OTUs; 97% similarity clusters), with .99%
Good’s coverage for all samples. The highest OTU richness and phylogenetic diversity was found in the
mouth samples. The microbial communities of multiple biopsy sites within the colon were highly similar
site definitions (mouth,stomach/duodenum,colon andstool) rangedfrom32–110 OTUs,25ofwhichwere
common to all individuals and included OTUs affiliated with Faecalibacterium prasnitzii and the TM7
phylum. This first comprehensive characterization of the abundant and rare microflora found along the
healthy human digestive tract represents essential groundwork to investigate further how the human
microbiome relates to health and disease.
inhabiting the mouth8,9and the distal colon, with emphasis on studies of gut colonization10,11, and populations
that are present in both health12,13and disease14,15. Despite the impact of the oral and gastrointestinal (GI)
microbiome on human health, a taxonomic baseline, consisting of a comprehensive survey of the diversity
and distribution of microbial communities within healthy human beings, is lacking. This is due to several issues
including difficulties in cultivating host-associated microorganisms, lack of suitable molecular methods for
comprehensive characterization of complex microbial communities, and the relative difficulty in obtaining
internal human mucosal samples for analysis. Although culturing microorganisms sampled from human body
sites continues to provide valuable insight into the bacterial populations present, knowledge of the human
microbiome has been expanded greatly by culture-independent techniques such as fluorescence microscopy,
bacterial phylogenetic microarrays, 16S rRNA gene sequencing and metagenomics.
Culture-independent methods have revealed unexpected microbial diversity at sites such as the mouth8and
stomach16. Preliminary next-generation sequencing studies have achieved greater coverage of the microbial
populations associated with multiple human body sites. In particular, global surveys of feces and external body
sites17–20, the oral cavity13and selective sampling of the human digestive tract21reveal high diversity, site-specific
clustering ofcommunitycomposition andtaxonomicuniquenessbetween individuals. However,untilnowthere
system in healthy individuals. The comprehensive characterization of normal microbial communities associated
with the human GI tract is acritical prerequisite to understanding and predicting alterations in these communit-
the human digestive system using next-generation 16S rRNA gene sequencing, leveraging Illumina sequencing
technology22. Using this approach, we address as-yet unanswered questions such as: How do microbial com-
munities change along the length of the GI tract? Which bacterial assemblages inhabit each GI location? Are
bacterial profiles in feces the same as those associated with intestinal mucosa? Do abundant bacteria differ
fundamentally from those found at relatively low abundance (i.e. the ‘‘rare biosphere’’)?
he diverse microbial communities that dwell in the human body are linked intimately with aspects of host
metabolism, physiology and function including maturation of the immune system1, energy balance2, sus-
ceptibility to disease3–5, and behavior6,7. Recent research has begun to enumerate the microbial species
14 June 2011
7 November 2011
25 November 2011
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Faculty of Health
University, 1280 Main
Street West, Hamilton,
Ontario, L8S 4K1,
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
In this study, the ,150-base long V3 region (,200 base PCR
tract of four healthy individuals (two females and two males). The
samples included mouth plaque (left and right supra-gingival and
sub-gingival, tongue), stomach (antrum and body), duodenum,
colon (transverse and descending), rectum and stool. The results
show that bacterial communities cluster by sample site and that
specific bacterial populations are characteristic of different human
tract, exhibiting clear differences even between colon mucosal and
fecal profiles. Despite the depth of sampling, most accumulation
curves did not plateau. The abundant and rare organisms within
each library belonged to similar taxonomic groups, although there
was an increase in the proportion of unclassified OTUs among rare
of the complete human digestive system, and therefore it represents
an essential baseline to support further studies linking microbial
communities with aspects of human health and disease.
Patient samples and Illumina libraries. For each healthy individual
(two males, two females), the samples included dental plaque (left
and body), duodenum, colon (transverse and descending), rectum
and stool. The stool was collected within 24 hours of GI sampling
and prior to Klean Prep of the colon whereas all other GI and oral
samples were collected on the same day for each individual at the
time of gastroscopy and colonoscopy. Libraries were constructed for
all samples by amplification of the V3 region of the bacterial 16S
rRNA gene. A unique index was used to label each sample and
multiplex Illumina sequencing resulted in 46,960,900 paired-end
reads. Removal of low-quality and short (,100 nucleotide) se-
quences followed by perfect-match assembly reduced the total to
32,770,833 assembled sequences with an average length of 149.3 6
10.9 bases (sequenced primer regions removed). Clustering at 97%
identity produced 97,252 unique operational taxonomic units (OTUs)
of which 56,910 (0.17% of sequences) were singletons (occurring once
in only one sample; Table S2). Good’s coverage was high with an
average of 0.996 across all samples.
In parallel to human samples, we conducted a validation of the
Illumina sequencing approach. This validation consisted of pro-
bacterial cultures, with both Sanger-based sequencing of a single
clone library (96 clones), and Illumina sequencing of two technical
replicates (.500,000 sequences for each replicate). The Illumina
method recovered 16S rRNA gene sequences from all 12 organisms
with a reproducible abundance distribution (Fig. S1), confirming
the reproducibility of this analytical approach. Fewer Pseudomonas
sequences were recovered in the replicate Illumina libraries than
expected based on the initial mix ratio. However, no Pseudomonas
sequences were detected within the Sanger-sequenced library. These
results demonstrate the importance of increased sequencing coverage
to offset the loss of detected OTUs by possible methodological biases.
Note that additional assessments of alpha diversity were not possible
with these data due to low-level sequence contamination likely assoc-
iated with bacterial growth media, as observed previously22,23.
Sequence clustering and quality. Because of the large number of
singleton sequences, as well as the use of the highly variable V3
region, we tested sequence clustering at different identity thresholds
using the CD-HIT algorithm24(Table S1). The observed pattern of
cluster richness indicated that existing clusters were not diffuse and
therefore the selected 97% threshold was appropriate for CD-HIT
clustering of true sequences with their derivatives containing se-
quencing and/or PCR errors.
Using default parameters and a de novo analysis, UCHIME iden-
tified a non-trivial number of potential chimeric sequences, ranging
the majority of these sequences did not appear to be legitimate chi-
meras were almost exclusively low-scoring sequences, indicating
lower confidence in their identification as chimeras. Modifying
UCHIME parameters to decrease false positives in short read
of putative chimeras to , 2% of all sequences at a site, and typically
, 0.5%. Because the majority of these sequences corresponded to
singletons or low-abundance clusters and alpha diversity measures
were notthe primary focus of this study, the potential chimeras were
not removed from the data for subsequent analyses.
Microbial community diversity estimates. Shannon diversity
estimates were highest in samples from the mouth (Fig. 1A). Sto-
mach samples were the least diverse and colon and stool samples
were highly variable. Phylogenetic diversity in the mouth was signifi-
cantly higher and much more consistent across individuals than in
any of the other locations tested (Fig. 1B). Despite collecting an
average of ,700,000 sequences per sample, the accumulation and
Chao1 curves did not level off for most samples (Fig. S2).
Taxonomic characteristics. Of the nearly 33 million sequences
collected in this study, 0.63% and 10.83% could not be assigned to
aphylum or genus, respectively (counts for phyla and genera in each
sample presented in Tables S3 and S4, respectively). This indicates
that the 16S rRNA gene dataset found potentially novel lineages in
the human microbiome. This study found 19 known phyla to be
present in the oral samples of all individuals, with a predominance
of five or six major phyla: Actinobacteria, Bacteroidetes, Firmicutes,
Fusobacteria, Proteobacteria and either of Spirochaetes, TM7 or SR1
gingival plaque samples as would be expected in healthy subjects.
Figure 1 | Alpha diversity of each sample. (a) Shannon diversity and
(b) phylogenetic diversity (PD) at each body site for all four subjects,
where points represent a sample. Five iterations of rarefied subsets of
200,000 sequences from each sample were used to calculate the values
for both metrics and the average was plotted. Asterisks indicate
statistical significance (Kruskal-Wallis test, p , 0.05).
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
Although stomach and duodenum samples showed fewer OTUs
than other sites, they harbored representatives of most phyla
observed throughout the study with the exception of a population
of unclassified Cyanobacteria not seen elsewhere. Because a colon
prep was applied prior to sampling and Cyanobacteria-related
sequences have previously been reported in the colon of humans
and the guts of other mammals26,27, Cyanobacteria may be resident
organisms within the duodenum and not simply DNA sequences
transiently present there at the time of collection. Interestingly,
three of the four duodenum samples contained larger proportions
ofAcidobacteria (mainlyunclassified Acidobacteria Gp22; Table S4)
than any other sampled site. The results of this study reveal sub-
stantial OTU diversity in the stomach and duodenum, although, as
reflected in their low Shannon indices (Fig. 1), most communities
were dominated by only a few genera.
Bacteroidetes and Firmicutes predominated in colon mucosal sites,
followed by lower proportions of Proteobacteria and Fusobacteria
(Fig. 2). Firmicutes, with a small proportion of Actinobacteria, pre-
dominated in three of the four stool samples.
Sample clustering. Samples clustered strongly by gastrointestinal
site using either weighted or unweighted UniFrac distances (Fig. S3
A and B). Samples clustered first by major body site then by sample
sub-site (mainly with unweighted UniFrac), then by subject at colon
sites, which were similar to one another and distinct from stool
in most cases. Principal coordinate analysis (PCoA) plots using
UniFrac distances (Figs. 3 and S4) clustered samples mainly by
location (Fig. 3B and S4B), whereas we did not observe clustering
due to other variables such as gender (Fig. 3C and S4C) or subject
(Fig. 3D and S4D).
The taxonomic information overlaid onto the PCoA plot illu-
even those occurring at low abundances (phyla such as Verrucomi-
crobia, TM7 and Spirochaetes, genera such as Faecalibacterium and
Figure 2 | Genera represented in the digestive tracts of four subjects (S1–S4). Bars delineate unique genera and are coloured with the phylum level
4, respectively. Low abundance phyla comprising the ‘‘Other’’ category include Acidobacteria, Chloroflexi, Deinococcus-Thermus, Euryarchaeota,
Lentisphaerae, Planctomycetes, Synergistetes and Tenericutes.
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
Haemophilus) (Figs. 3A and S4A). The dataset contained represen-
tatives of 19 known phyla and 436 known genera (Tables S2 and S3,
respectively). Colon mucosal communities were largely comprised
of known anaerobic microorganisms and the predominant genera
at these sites were Bacteroides, Coprococcus, and Faecalibacterium. A
species of the latter genus, Faecalibacterium prausnitzii has been
implicated in colonic health due to itsanti-inflammatory properties4.
Bacteroides are thought to be the key anaerobes in health and
disease28and were the most abundant genera identified (occurring
mainly in colon mucosal sites), making up the bulk of the Bac-
teroidetes sequences obtained in the study. However, several other
genera such as Prevotella and Capnocytophaga were particularly
abundant and important in clustering of oral sample sites.
Within-subject OTU overlap across sites. The overlap of OTU
clusters among broad sampling regions (mouth, stomach/duodenum,
colon, stool) were calculated with singleton sequences removed. The
resulting Venn diagrams demonstrated consistent overlap patterns
for each subject (Figure 4). Stool and colon sites had the largest OTU
overlap within an individual, with both sites also sharing a large
number of OTUs with the mouth. The stomach and duodenum
set of OTUs typically shared the fewest clusters with other body
sites. A subset of 32–110 OTUs were present in every sampling
region of each individual, with 25 of these OTUs being present in
all subjects (Table S5). The abundances of these 25 shared OTUs
varied among individuals and sites, but were generally high, ranging
from ca. 50,000– 2,800,000sequences.Included in this shared subset
were Faecalibacterium, TM7 and Streptococcus (Table S5).
Tracking species of interest. The taxonomic composition and
dynamics of low-abundance microorganisms in ecosystems are
poorly understood. In this study, bacterial OTUs ranked by abun-
dance generally had consistent taxonomic assignments between
abundant and rare groups in oral and digestive tract sites (Figs. 5
and S5). Nonetheless, in all subjects and GI sites, the proportion of
unclassified sequences increased in low abundance ranks, compared
to predominant OTUs.
The potential diagnostic value of large 16S rRNA gene datasets
such as those generated in this study is apparent when mining for
sequences from species of clinical interest (Fig. 6; Table S6). In
Figure 3 | Contribution ofdifferenttaxonomic groupstoseparation ofsamplesbased onphylogeneticinformation. The contribution ofeachgroup is
represented by the size of the circles (grey) overlayed onto a PCoA of unweighted UniFrac distances for all samples within the oral and digestive tract.
Panels (a–d) represent variations in sample colouration to highlight potential relationships between sample clustering and metadata.
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
particular, high levels of sequences matching the beneficial species
F. prausnitzii were present in all the distal gut samples, though they
were much more abundant in two of the four individuals. Whenever
this species was abundant in the mucosa, it was also abundant in
the corresponding stool. On the other hand, the ability to detect
sequences of potentially harmful organisms such as Streptococcus
mutans, Treponema denticola or Clostridium difficile at very low
relative abundances has potential diagnostic value and possible
prophylactic applications. In this study, the observation of C.
difficile-like sequences at low-relative abundance in all subjects pro-
vides useful insight into the prevalence of this potential bacterial
This study generated .32 million sequences representing .95,000
unique OTUs with .99% Good’s coverage for all samples. Inter-
individual variability is a hallmark of human microbiome studies.
Accordingly, there was more phylogenetic variability between sub-
jects than there was between sample sites from within each GI loca-
tion (e.g. mouth, large intestine), likely due to the similarity in redox
conditions and availability of nutrients at sites compared with the
variabilityof host-specific factors such asdiet ororalhygiene. This is
not surprising if the gastrointestinal tract is thought of as a changing
ecosystem where adaptable microbial communities are replaced
continually by functionally similar representatives in each host20.
Nonetheless, although the types of organisms present within each
person are distinct at the OTU level, they are very similar at higher
The mouth samples contained the most phylogenetically similar
microbiomes across subjects. This observation concurs with those
made from shallower sequence sampling coverage by Costello and
the oral sites here were also observed in previous 16S rRNA gene
surveys8,29, whereas some of the low-abundance groups seen in this
study, such as Alphaproteobacteria, Coriobacteridae, Acidobacteria,
Deltaproteobacteria and Deinococci, were found in a recent PCR-
independent metagenomic study of oral communities30. This suggests
that our method not only reproduces the results of previous 16S
rRNA gene screens but can identify low abundance organisms not
usually detected with less sequence coverage. These results reinforce
the notion of the mouth as the entry point for GI bacteria (highest
diversity) with selectionfor asubsetofthetotaldiversityoccurring as
these organisms pass through the gastrointestinal tract. The micro-
bial diversity associated with mouth samples was similar to that
observed in a previous pyrosequencing study of oral microflora31.
Our study found greater OTU numbers in the stomach than pre-
vious studies16, likely due to the greater sequencing depth achieved
here. Recent evidence for diverse microbial populations within the
stomach has challenged the traditional notionthat the upper GI tract
which these findings reflect genuine diversity, or whether alpha
diversity measures (e.g. Fig S2) continue to be inflated by artifacts
of next-generation sequencing approaches33. As in the murine gut12,
diversity along the GI track increased from stomach to stool.
Bacterial density and growth rates are also known to change along
the GI track34. In agreement with previous reports including those
using metagenomes sequences35, the abundant organisms in colon
and stool samples were similar between individuals, with inter-indi-
vidual variation occurring in the least abundant groups.
The taxonomic groups represented within the GI tract were sim-
ilar overall to previous findings13,21, where these sites were investi-
the same individual within a short timeframe, gradients of microbial
community composition as well as distinct differences at different
body sites along the digestive tract were apparent (Fig. 4). Bacterial
communities in the oral cavity were made up of different taxonomic
groups and were phylogenetically distinct from those at colon sites
(based on UniFrac), whereas there was an observable representation
of bacterial taxonomic groups in both the mouth and colon but not
3; Fig. 2). These results point to a seeding of mucosal (colonic)
communities with organisms from higher up in the digestive tract.
Within multi-site shared OTUs (Fig. 4), those related to both
Figure 4 | Venn diagrams demonstrating 97% OTU cluster overlap within broad sampling regions. Numbers correspond to unique OTU clusters
within a subset. To highlight shared OTUs, singleton clusters were removed before analysis.
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
with all general site locations (e.g. mouth, stomach/duodenum,
colon, stool) in all individuals. It is interesting to note the all-subject
and all-site distribution for sequences of Faecalibacterium-like bac-
teria (Table S5), which have been associated with anti-inflammatory
widespread exposure and continuous seeding of this beneficial bac-
terium in humans. TM7-related bacteria represents a largely uncul-
tivated phylum36, with corresponding sequences associated with a
iated with chronic periodontitis39, and other body sites such as the
will be useful to assess the widespread distribution of the core 25
OTUs shared between all sites in additional individuals.
Previous studies of luminal bacterial communities have reported
different ratios of Firmicuties, Bacteroidetes and Actinobacteria
in stool samples, with some samples entirely dominated by Fir-
micutes21. The ratio of Firmicutes to Bacteroidetes within stool has
recently been suggested to fluctuate with the body mass index (BMI)
of the individuals sampled12. Although we sampled only four indivi-
duals, we noted that the ratios of Firmicutes to Bacteroidetes within
the intestinal mucosal and stool samples were not the same (Fig. 2).
This difference in ratio suggests that the specific relationships
with BMI that were found previously may differ for luminal (stool)
and mucosa-associated bacterial communities. Additional research
consistent across individuals although a previous study has also
shown stool microbial profiles that are distinct from fecal profiles27.
The number of sequences obtained and the low cost of Illumina
sequencing were especially helpful in the detection of sequences
occurring below traditional detection levels. The analyses of low-
abundance sequences (Fig. 5, Fig. S5) indicate that only relatively
still with a small proportion of unclassified organisms, at all sites
within the human GI tract. This observation contrasts with the pat-
OTUs belonged to different taxonomic groups from those of high-
abundance OTUs. However, in agreement with previous observa-
tions22,44, we observed an increasing proportion of unknown or
unclassified organisms among rare OTUs. Because phylogenetic
and taxonomic diversity is expected to correlate with functional
of rare organisms indicates a possible functionally redundant role of
the rare biosphere in the oral and GI tract. Further research will
continue to explore the identities and roles of rare uncharacterized
taxa in human and environmental samples. Notably, the Illumina
sequencing method applied here resulted in a relatively low propor-
tion of chimeric sequences within the data, consistent with previous
observations25. This is not surprising considering the short length of
the PCR amplicons and the absence of long stretches of highly con-
served nucleotides. This finding emphasizes the usefulness of this
method for deep-sequencing of 16S rRNA genes and removes the
The analysis of sequences across all samples demonstrates the
quantitative strengths of large 16S rRNA gene datasets to character-
ize complex microbial communities (Fig. 6). However, although
variable regions have high taxonomic resolution45, caution should
accompany the interpretation of such targeted analyses because V3-
region sequences can represent closely related species, and thus will
not, in some cases, be able to distinguish pathogenic from com-
mensal members or, potentially, even closely related species within
the same genus45. Similar concerns apply not only to our data, but
also to any single-gene (or even phenotype-based) analyses of host-
associated microorganisms. Sequencing variable regions of the 16S
Figure 5 | Rank abundance plots and proportional taxonomic bar plots
for sequences from Subject 1 pooled within various body sites and
assigned to order. To demonstrate taxonomic distribution at decreasing
ranks, the data were split according to different logarithmic abundance
ranges as appropriate. The low abundance orders comprising the ‘‘Other’’
category included Synergistales, Halanaerobiales, Mycoplasmatales,
Xanthomonadales, Sphingobacteriales, Caulobacterales,
Desulfobacterales, Legionellales, Oceanospirillales, Deinococcales,
Methanobacteriales, Myxococcales, Anaerolineales, Methylophilales,
Chromatiales, Thermales, Bdellovibrionales, Desulfuromonadales,
Solirubrobacterales, Methanomicrobiales, Planctomycetales,
Methylococcales, Anaeroplasmatales, Coriobacteriales,
Desulfovibrionales, Rhizobiales, Rhodocyclales, Sphingomonadales,
Victivallales. Plots for subjects 2–4 are available in Figures S5.
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
rRNA gene is one of many investigative techniquesand thus requires
additional complementary approaches to confirm observations.
We have generated a first baseline that improves our understand-
ing of how human-associated bacteria change along the digestive
system. This initial investigation into our internal biogeography is
of particular importance because the oral cavity and GI tract consti-
tute areas of intimate interactions between bacterial communities
and human cells.
Inclusion and exclusion criteria. Samples were collected from two men and two
women. All subjects were healthy adults undergoing a routine colonoscopy and
at Mount Sinai Hospital (Toronto, Canada) due to clinical criteria that justified
screening; i.e., age over 50, family history of cancer in first degree relatives or occult
blood positive fecal testing. Exclusion criteria included new onset diarrhea
gastrointestinal symptoms, any condition requiring the need for antibiotic
medication prior to dental procedures, self-reported pregnancy, severe periodontal
disease including but not limited to purulent exudates, generalized dental mobility
and/orseveregumrecession, activetreatmentofperiodontitiswithintheprevious six
months, disease conditions that could be expected to interfere with examination
procedures or the subject safely completing the study, presence of any dental caries
open lesions, and use of systemic antibiotics within the past three months. For
tooth sites, and no class III restorations prior to sampling. All sampling was
conducted in accordance with relevant guidelines and regulations and research
approved by the Research Ethics Boards of Mount Sinai Hospital and the University
of Waterloo (ORE# 15605).
Sample collection. Each subject provided a stool sample prior to, and within
220uC until the time of endoscopy and the sample was stored at 280uC until DNA
extraction. Prior to gastroscopy and colonoscopy, samples of the oral biofilm were
collected from supra-gingival plaque, sub-gingival plaque, and the surface of the
tongue. Plaque samples were collected using a sterile curette and placed into 1 ml of
sterile DNA-free Dulbecco’s Phosphate Buffered Saline (D-PBS; Invitrogen). Supra-
gingival samples were taken from caries-free interproximal sites between the
maxillary lateral incisor and the maxillary cuspid incisor or the maxillary cuspid
23/24) for each subject. Sub-gingival plaque was taken from periodontal pockets of
the above-mentioned teeth. Teeth were isolated to minimize salivary contamination
and two strokes of the curette were used per site in an attempt to standardize
collection. Sampling of the tongue was done with a sterile stainless steel spatula with
transverse colon, sigmoid colon, rectum, gastric antrum, gastric body and of the
duodenum were collected. Tissue samples were placed in 1 ml of sterile D-PBS as
above, then rapidly frozen at 280uC until used for DNA extraction.
DNA extraction. For each site an individual replicate sample was thawed, then
vortexed to disperse clumps (plaque samples) or dislodge mucosal attached cells
(biopsy samples). Stool samples were thawed and homogenized by mixing prior to
DNA extraction. Total genomic DNA was isolated from 500 ml of the sample storage
buffer (or from 0.25 g of feces) with the PowerSoil DNA isolation kit (Mo Bio, USA)
according to the manufacturer’s instructions with minor modifications, described
below. Only supernatants from vortexed tissue biopsies were included in the DNA
isolation in order to reduce the co-extraction of human DNA. Modifications to the
DNA isolation kit protocol included the addition of a 40 sec bead-beating step (at
speed 6.0in a FastPrep homogenizer; MPBiomedicals, USA) and heating to70uCfor
10 min prior to binding of contaminants with kit reagents. Purified DNA was
separated on a 1% agarose gel and quantified by densitometry of the gel image and
Figure 6 | Abundance of V3 regions of 16S rRNA genes of targeted organisms within all samples. The entire sequence dataset was queried for type
strains of Streptococcus mutans, Treponema denticola, Clostridium difficile and Faecalibacterium prausnitzii. For results from additional target organisms,
see Table S6.
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170
spectrophotometry (NanoDrop 1000; Thermo Scientific, USA) of the sample. Of the
sufficient DNA for subsequent PCR amplification.
PCR conditions and Illumina library construction. Due to the low biomass of
several samples, a nested PCR protocol was used to amplify the bacterial 16S rRNA
gene from all samples. For the first round of amplification, the near full-length 16S
rRNA gene was amplified using primers 27F and 1492R46. For Illumina library
preparation, amplification of the V3 region used modified 341F and 518R primers47
containing asix-base barcode, the Illumina adaptersequenceandregionsforbinding
20 cycles were used for the second round. One exception to this was the use of 30
amounts to be sequenced in two lanes of a Genome Analyzer IIx at the Plant
Defined bacterial community. A defined microbial community was prepared in
order to compare Illumina library sequencing to traditional Sanger sequencing. To
prepare this community, genomic DNA from the following 12 bacterial strains was
added in equivalent amounts with the exception of Staphylococcus, for which
threefold more DNA was added: Pseudomonas aeruginosa (ATCC 10145),
Escherichia coli (ATCC 11303), Klebsiella pneumoniae (Macdonald Campus of
McGillculturecollection), Alicaligenes faecalis (ATCC 8750), Enterobacter aerogenes
(ATCC 13048), Lactobacillus plantarum (ATCC 8014), Bacillus subtilis (ATCC
6633), Enterococcus faecalis (ATCC 19433), Citrobacter freundii (ATCC 8090),
Proteus vulgaris (ATCC 6380), Clostridia sporogenes (ATCC 19404), Staphylococcus
epidermidis (ATCC 12228). The V3 region of the 16S rRNA gene was amplified as
reproducibility. These additional two libraries were sequenced as part of a separate
Illumina run containing additional environmental samples. Near full-length 16S
rRNA genes from the same pool of DNA were amplified using 27F/1492R primers as
described above and inserted into the TOPO cloning system (Invitrogen, Canada)
then used to transform E. coli, as per kit instructions. Ninety-six positive clones were
chosen and sequenced with conventional Sanger sequencing. All sequences were
classified using the RDP classifier with the same conditions as below.
Data analysis. Illumina sequencing returned a total of 46,960,900 raw sequences
sequences were assembled and filtered, excluding those containing unknown (N)
characters or a nucleotide mismatch within the assembly overlap. After assembly
identical sequences within a treatment library were collapsed, maintaining sequence
corresponding to 23,709 100% identity groups, were deleted. A total of 8,344,920
groups of identical sequences, corresponding to 32,770,833 sequences were used in
clustering algorithm. A sequence identity cutoff of 97% was used to identify OTUs
and the results of the CD-HIT algorithm using this threshold wasused in subsequent
analysis. Clustered data were then evaluated for potential chimeric sequences using
the fast implementation of UCHIME within the USEARCH package v.4.2.6648using
default and modified parameters.
Taxonomy was assigned using the RDP-II classifier45and assignments were
bar charts were plotted using the ggplot2 package49implemented in the R statistical
Representative sequences from each cluster were aligned with the PyNAST aligner
to the greengenes core set51in QIIME v 1.2.052. A phylogeny was constructed within
QIIME using FastTree53. Rarefaction curves, alpha diversity and beta diversity cal-
culations were performed using QIIME and plotted independently. For rarefaction
curves of Chao1 species estimates, five sets of resampled data (without replacement)
were used. Calculations for Chao1, phylogenetic diversity and Shannon diversity
involved five rarefied subsets of 200,000 sequences from each sample. Supra-gingival
calculated based on the phylogenetic information within each sample with both the
unweighted and weighted UniFrac analysis. UPGMA trees of weighted and
unweighted UniFrac values were calculated with QIIME and plotted with FigTree v
1.3.154. Jackknife values were calculated with 100 sets of 200,000-sequence rarefied
tables (without replacement). Principal coordinate analysis (PCoA) of weighted and
unweighted UniFrac were also calculated and plotted with QIIME.
To characterize the overlap of OTUs present among broad sampling regions
(mouth, stomach/duodenum, colon and stool) and across subjects, Venn diagrams
this analysis because they made up the majority of OTU clusters and were not shared
between sites or subjects.
determining the presence of organisms of interest, a non-redundant blastn database
was constructed from our 16S rRNA sequences. Corresponding sequences from
medically significant species (see Table S6) were then queried against the custom
database. To ensure strict matches, a 99% identity threshold was used with no more
than a two-nucleotide deviation in length from the medically significant query
sequence (Fig. 6).
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We thank Rachel Caplan for assistance with sampling and Kevin Ow for assistance with
obtaining ethicsapproval for this study. Thisresearch was funded byaCatalyst Grant from
the Canadian Institutes of Health Research (CIHR).
JDN, DC, GMH, KC, HCT DBS and MBG contributed to the initial design of the research.
JCS and MDJL conducted the experimental and bioinformatics analyses with guidance
from GMH and JDN, HCT and MBG collected oral biofilm samples, KC conducted the
colonoscopies and gastroscopies. JCS prepared the first draft of this publication and all
authors contributed to the subsequent stages of manuscript preparation.
Supplementary information accompanies this paper at http://www.nature.com/
Competing financial interests: The authors declare no competing financial interests.
License: This work is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike 3.0 Unported License. To view a copy of this
license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/
How to cite this article: Stearns, J.C. et al. Bacterial biogeography of the human digestive
tract. Sci. Rep. 1, 170; DOI:10.1038/srep00170 (2011).
SCIENTIFIC REPORTS | 1 : 170 | DOI: 10.1038/srep00170