Bacterial Communities of the Coronal Sulcus and Distal Urethra of Adolescent Males

Department of Biology, Indiana University, Bloomington, Indiana, United States of America.
PLoS ONE (Impact Factor: 3.23). 05/2012; 7(5):e36298. DOI: 10.1371/journal.pone.0036298
Source: PubMed
Lactobacillus-dominated vaginal microbiotas are associated with reproductive health and STI resistance in women, whereas altered microbiotas are associated with bacterial vaginosis (BV), STI risk and poor reproductive outcomes. Putative vaginal taxa have been observed in male first-catch urine, urethral swab and coronal sulcus (CS) specimens but the significance of these observations is unclear. We used 16 S rRNA sequencing to characterize the microbiota of the CS and urine collected from 18 adolescent men over three consecutive months. CS microbiotas of most participants were more stable than their urine microbiotas and the composition of CS microbiotas were strongly influenced by circumcision. BV-associated taxa, including Atopobium, Megasphaera, Mobiluncus, Prevotella and Gemella, were detected in CS specimens from sexually experienced and inexperienced participants. In contrast, urine primarily contained taxa that were not abundant in CS specimens. Lactobacilllus and Streptococcus were major urine taxa but their abundance was inversely correlated. In contrast, Sneathia, Mycoplasma and Ureaplasma were only found in urine from sexually active participants. Thus, the CS and urine support stable and distinct bacterial communities. Finally, our results suggest that the penis and the urethra can be colonized by a variety of BV-associated taxa and that some of these colonizations result from partnered sexual activity.


Available from: George Weinstock
Bacterial Communities of the Coronal Sulcus and Distal
Urethra of Adolescent Males
David E. Nelson
*, Qunfeng Dong
, Barbara Van Der Pol
, Evelyn Toh
, Baochang Fan
, Barry P. Katz
Deming Mi
, Ruichen Rong
, George M. Weinstock
, Erica Sodergren
, J. Dennis Fortenberry
1 Department of Biology, Indiana University, Bloomington, Indiana, United States of America, 2 Department of Biological Sciences, Department of Computer Science &
Engineering, University of North Texas, Denton, Texas, United States of America, 3 School of Public Health, Indiana University, Bloomington, Indiana, United States of
America, 4 Department of Biostatistics, Indiana University School of Medicine, Indianapolis, Indiana, United States of America, 5 Department of Pediatrics, Indiana
University School of Medicine, Indianapolis, Indiana, United States of America, 6 Department of Genetics, Washington University St. Louis School of Medicine, St. Louis,
Missouri, United States of America
Lactobacillus-dominated vaginal microbiotas are associated with reproductive health and STI resistance in women, whereas
altered microbiotas are associated with bacterial vaginosis (BV), STI risk and poor reproductive outcomes. Putative vaginal
taxa have been observed in male first-catch urine, urethral swab and coronal sulcus (CS) specimens but the significance of
these observations is unclear. We used 16 S rRNA sequencing to characterize the microbiota of the CS and urine collected
from 18 adolescent men over three consecutive months. CS microbiotas of most participants were more stable than their
urine microbiotas and the composition of CS microbiotas were strongly influenced by circumcision. BV-associated taxa,
including Atopobium, Megasphaera, Mobiluncus, Prevotella and Gemella, were detected in CS specimens from sexually
experienced and inexperienced participants. In contrast, urine primarily contained taxa that were not abundant in CS
specimens. Lactobacilllus and Streptococcus were major urine taxa but their abundance was inversely correlated. In contrast,
Sneathia, Mycoplasma and Ureaplasma were only found in urine from sexually active participants. Thus, the CS and urine
support stable and distinct bacterial communities. Finally, our results suggest that the penis and the urethra can be
colonized by a variety of BV-associated taxa and that some of these colonizations result from partnered sexual activity.
Citation: Nelson DE, Dong Q, Van Der Pol B, Toh E, Fan B, et al. (2012) Bacterial Communities of the Coronal Sulcus and Distal Urethra of Adolescent Males. PLoS
ONE 7(5): e36298. doi:10.1371/journal.pone.0036298
Editor: Jacques Ravel, Institute for Genome Sciences, University of Maryland School of Medicine, United States of America
Received December 14, 2011; Accepted March 30, 2012; Published May 11, 2012
Copyright: ß 2012 Nelson 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 work was supported by National Institutes of Health Grants NIH UH2 DK083980 to JDF and NIH RC2 HG005806 to DN and QD. 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: (DEN); (JDF)
. These authors contributed equally to this work.
The bacterial communities (microbiotas) associated with differ-
ent body surfaces can impact pathogen colonization resistance and
autoimmune disease [1]. For example, dysbioses of the gastroin-
testinal tract microbiota can trigger overgrowth of pathogens [1]
such as C. difficile [2], which are linked to chronic inflammatory
conditions including Crohn’s disease and ulcerative colitis [3,4],
and can increase risk of colonization by enteropathogens including
Clostridia, Salmonella, Vibrio, Escherichia and Shigella spp. [5,6].
Probiotic activities of Lactobacillus spp. that colonize the vagina
illustrate mechanisms by which the microbiota can influence
susceptibility to infectious disease [7]. Lactobacillus spp. regulate the
balance of pro-inflammatory cytokines in vaginal secretions
[8,9,10], block colonization and invasion of some pathogens [11]
and produce lactic acid, hydrogen peroxide [12] and bacteriocins
[13] that inhibit other vaginal microorganisms. Reduction of
vaginal Lactobacillus spp. is associated with the overgrowth of
anaerobic bacteria that occurs in bacterial vaginosis (BV) [14], and
increased susceptibility to bacterial and viral sexually transmitted
infection (STI) [15,16]. Thus there is strong evidence that the
composition of the female reproductive tract microbiota is linked
to reproductive health and resistance to STI in women.
In comparison, the microbiota of the male reproductive tract is
poorly described. The penis itself provides distinct anatomical
environments in the urethra and the coronal sulcus (CS). Both sites
are exposed to similar foreign microbial communities during
sexual activity. Some bacteria transferred during sexual activity
(e.g., Neisseria gonorrhoeae and Chlamydia trachomatis) cause substantial
world-wide morbidity [17]. In addition, the CS and distal urethras
of healthy men at least episodically support bacterial communities
[18,19,20,21]. Lactobacillus spp. have been identified in urine and
urethral swabs [19], and BV-associated taxa including Prevotella,
Gardnerella and Sneathia are found in CS [20] and urethral
specimens from adult men [18,19]. Although the role of bacteria
in the male urethra is unknown, the CS microbiota has been
hypothesized to mediate effects of circumcision on risk of HIV and
other STI [20].
A limitation in understanding the microbiota of the penis is the
lack of data from healthy young men who have and or have not
had partnered sexual experiences. These data would allow more
thorough description of the microbiota of the urethra and CS, and
could provide insight into changes associated with sexual
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Page 1
exposures. To fill this gap, we collected urine and CS specimens
from eighteen healthy 14–17 year old men with varied circum-
cision status and sexual histories. Sampling was repeated at
monthly intervals to investigate stability of the microbiota over a
three-month period. Bacteria were identified using multiple 16 S
rRNA sequencing methods. Urine and corresponding CS speci-
mens supported stable, but dissimilar microbiotas. Major urine
taxa in most of the sexually experienced and inexperienced
participants were members of the order Lactobacillialles. Finally,
some bacteria were detected only in participants with histories of
partnered sexual activity.
Results and Discussion
Compositions of CS and urine microbiotas are similarly
measured by different 16 S rRNA sequencing approaches
There were no data concerning optimal methods for cultivation-
independent characterization of CS or urine microbiotas; thus we
analyzed total genomic DNA from 72 CS and urine specimens
using four different 16 S rRNA sequencing approaches. Near full-
length 16 S rRNA alleles were assembled from individual Sanger
sequence reads [18], while the V1–V3, V3–V5 and V6–V9 sub-
regions of 16 S rRNA alleles were analyzed by multiplex PCR and
pyrosequencing using a protocol developed by human microbiome
demonstration projects ( [22]. Only 8 urine
and 3 CS specimens yielded poor quality or no PCR amplicons
using the Sanger approach and these same specimens tended to
yield poor pyrosequencing results. This indicated that some
specimens either had low bacterial loads or contained inhibitors
that blocked 16 S PCR amplification. Taxonomy was assigned
using RDP classifier. In total, 56,406; 756,640; 759,914 and
1,212,918 sequences from full-length, V1–V3, V3–V5 and V6–V9
16 S rRNA regions were assigned to the genus level with 90%
confidence, respectively (Tables S1, S2, S3, S4, S5).
PCR-based 16 S rRNA identification can introduce biases
during priming, amplification, cloning and sequencing [23]. Types
and proportions of taxa identified in urine and CS specimens by
each sequencing approach were compared. Major taxa and their
relative proportions were similar in all the datasets (Figures 1a and
1b; Tables S1, S2, S3, S4, S5) with the following exceptions: V6–
V9 under-represented Prevotella, Gardnerella was not captured by the
V1–V3 approach, and Corynebacteria were over-represented in both
V1–V3 and V3–V5. These results indicated that sub-region
sequencing provided reasonable coverage of both urethral and CS
bacterial communities, with the caveat that validation against
other methods is warranted to reveal taxa missed by any single
method. Since a large number of near full-length Sanger 16 S
sequences were obtained and pyrosequencing failed to reveal
additional major taxa our subsequent analyses were based on the
Sanger data and cross-checked against the sub-region data sets.
The CS Supports a Complex and Stable Microbiota
In the 17/18 enrollment specimens that yielded 16 S rRNA
amplicons, 58 high confidence taxa were predicted from 9,070
16 S rRNA sequences (Figure 2A). Three genera were in most
specimens; Corynebacteria (16/17), Staphylococcus (16/17) and Anaero-
coccus (15/17), and these accounted for more than 58.9% of the
sequences. Other abundant genera, in order of relative abun-
dance, included Peptoniphilus (13/17), Prevotella (4/17), Finegoldia
(14/17), Porphyromonas (8/17), Propionibacterium (11/17) and Delftia
(8/17). All of these genera, along with high quality sequences that
could not be classified to the genus-level with 90% confidence
(11.2%), accounted for an additional 30.5% of the sequences
(Figure 2A and Table S1). Pseudomonas were notably less abundant
(,0.01%) in CS specimens in this cohort than they were in a
group of adult African men described in a previous study [20].
Comparison of major taxa in enrollment and subsequent
monthly CS specimens indicated no dramatic differences in
composition during the study interval. To assess stability of the CS
microbiota, weighted and unweighted Unifrac PCA [24], the
Sørenson similarity index and Spearman correlation coefficient
were used to compare longitudinal CS specimens. All of these
measures confirmed that longitudinal CS specimens from the same
participant were significantly more similar to one another than to
CS specimens from other participants (Figure 3A). Lin’s concor-
dance correlation coefficents were calculated to measure stability
of individual taxa (Figure 4A). Staphyloccoccus, Mobiluncus, Prevotella,
Dialister and Anaerococcus yielded mean values of . 0.5, indicating
that these taxa were stable members of CS communites. In
contrast, major urine taxa including Veillonella and Streptococcus
were detected in some CS specimens but yielded values between 0
and 0.25. This indicates that although some urine taxa periodically
colonize or reside in the CS, they are not stable members of the
CS microbiota.
Circumcision alters the CS microbiota
Price and colleagues reported that circumcision alters the adult
CS microbiota and that anaerobic and putative vaginal taxa are
most abundant prior to circumcision, whereas aerobes and skin
taxa increase following circumcision [20]. Taxa in enrollment
specimens from participants who had (12/17) and who had not (5/
17) been circumcised were compared to test if similar relationships
could be detected in young men (Figure 5A). Consistent with the
Price study, Corynebacteria and Anaerococcus were dominant in both
groups and were present in similar proportions. Staphylococcus was
significantly enriched (26.6% vs. 5.5%) in enrollment specimens
from circumcised participants (Wilcoxon signed-rank test, p-
value = 0.0048) while Porphyrmonas was enriched (6.4% vs. 0.3%)
in uncircumcised participants (Wilcoxon signed-rank test, p-
value = 0.026). Prevotella was exclusively identified in uncircumcised
participants (4/6) (Fisher’s exact test p-value = 0.006) and was
abundant in this sub-group (12.9%).
Weighted Unifrac analysis robustly separated CS and urine
specimens (Figure 6A). This analysis also clearly differentiated
circumcised and uncircumcised CS specimens (Figure 6B). In
contrast, groups of circumcised and uncircumcised urines were not
as clearly differentiated (Figure 6C). Clustering of CS and urine
CS specimens from each sampling point based upon Bray-Curtis
and Sørenson’s similarity coefficients as a measure of distance also
indicated that CS and urine specimens from the same subject
rarely grouped together (Figure S1 and data not shown).
Collectively, these results indicated that circumcision most strongly
impacted the CS and that the microbiotas in corresponding CS
and urine specimens were dissimilar.
Circumcised and uncircumcised CS contained taxa that have
been associated with the superficial skin [25] and especially moist
skin sites, such as the inguinal crease [26]. CS contained high
proportions of Corynebacteria or Staphyloccocus and lower proportions
of Propionibacteria and Betaproteobacteria; patterns associated with
sebaceous and dry skin sites, respectively [26]. Some taxa
including Prevotella and Porphyromonas were more abundant in
uncircumcised CS, but were not predominant components of the
CS microbiota. Interestingly, multiple taxa common in urine were
rare or absent from CS specimens.
Microbiotas of Urine and CS are Dissimilar
18/18 enrollment urines yielded specific PCR amplicons and 51
high confidence taxa were predicted from a total of 10,144 16 S
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Figure 1. Comparison of CS and urine microbiotas measured by different 16 S rRNA sequencing methods. Distribution of RDP taxa
(90% confidence) in enrollment (A) CS and (B) urine specimens. Proportions of normalized sequences are on the Y-axis. (black) Sanger, (white) V1–V3,
(dark gray) V3–V5 and (light gray) V6–V9 sequence data sets.
Figure 2. Distribution of major taxa in enrollment CS and urine specimens. Sanger data-set. (A) CS specimens. (B) urine specimens.
Penis Microbiomes of Adolescent Males
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rRNA sequences. Some abundant CS taxa were detected in urine
but microbiotas of these specimen types were dissimilar (Figure 2).
Urine contained high proportions of genera whose members are
obligate and/or facultative anaerobes (Figure 2B). Streptococcus (11/
18), Lactobacillus (4/18), Gardnerella (5/18) and Veillonella (4/18),
accounted for 59.1% of enrollment urine sequences. Closest RDP
matches of almost all of the enrollment Lactobacillus and Gardnerella
sequences corresponded to L. iners and G. vaginalis, while more
diverse species of Streptococcus (agalactiae, mitis, anginosus and
uncultured taxa) and Veillonella (dispar, atypica, montpellierensis, parvula
and uncultured taxa) were represented. In contrast, only 1.3% of
CS sequences corresponded to these taxa and .99% of these were
The urine Microbiota is Less stable than is the Microbiota
of the CS
Similar to CS, independent measures confirmed urine speci-
mens from the same participants were significantly more similar to
one another than urine specimens from other participants
(Figure 3B). To compare relative stability of the CS and urine
microbiotas, Sørensen’s similarity coefficients were computed for
pairwise specimens from different sampling points for each subject
swab and urine specimen. The analysis incorporated a linear
mixed-effect model to account for clustering due to multiple
specimens from each subject (Figure 7). Sørensen’s similarity
coefficient of CS (0.60) was significantly higher than urine (0.52)
(p-value = 0.0001) indicating that the CS microbiota was more
Some urine taxa were stable during the study period (Figures 4B
and 5B). Average lengths of continuous colonization with
Propionibacterium and Lactobacillus were 2.33 and 2.75 months
respectively, and Lin’s concordance correlation coefficent for these
taxa were .0.5. Outside these ‘‘core’’ taxa, the urine microbiota
was less stable than CS. Corynebacteria, Anaerococcus, Staphylococcus
and Prevotella accounted for only 22.1% of enrollment urine
sequences as opposed to 63.5% of CS sequences (Figure 2).
Average lengths of continuous colonization with these taxa were
all ,1.5 months and Lin’s concordance correlation coefficents
were all ,0.5 (Figure 4B). When present in sequential urine from
Figure 3. Comparison of intraperson and interperson similarity of CS and urine microbiotas. Black bars indicate comparison of
specimens from the same participant (4 specimens) and white bars indicate comparison of each specimen to all specimens from different
participants. A) CS specimens. B) Urine specimens. SO, Sørenson similarity index; SC, Spearman similarity coefficient; UU, unweighted Unifrac distance;
WU, weighted Unifrac distance. Wilcoxon P-values for all comparisons (same versus different participants) were all ,1E10
. Bars indicate 95%
confidence intervals.
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the same participant the relative abundance of these taxa also
varied widely (data not shown). Our interpretation is that some of
these taxa may not be true urethral residents but contaminants
from the urethral meatus or CS.
The Mic robiota of Urine is Simila r to that of other
Mucosal Surfaces
Additional results supported the hypothesis that microbial
communities of the urethra and CS are distinct. Lactobacillus,
Veillonella, Aerococcus, Ureaplasma, Gardnerella and Mycoplasma were
detected only, or almost exclusively, in urine. Bacteria in these
genera have been identified in mucosal samples of which
Ureaplasma, Gardnerella and Mycoplasma are urogenital pathogens
Partnered sexual exposures impact the penis microbiota
Comparison of the microbiotas of young men in this study with
older men from previous studies [18,19,20] suggested sexual
history could be a determinant of the penis microbiota compo-
sition. Known sexually transmitted organisms (N. gonorrhoeae, C.
trachomatis, U. parvum and M. genitalium) and other poorly
characterized taxa associated with the urogenital tract in other
studies (M. hominis and Sneathia spp.) were rare or not detected in
this study. Because different types of sexual activities expose the
CS and urethra to different microbiotas we reasoned that they
might also impact penis microbiotas differently.
Only one participant reported any history of insertive anal sex,
whereas 11/18 (61%) reported ever having had vaginal sex and
10/18 (56%) reported fellatio. Lactobacillus, Prevotella, Streptococcus,
Staphylococcus and Anaerococcus were detected at similar frequencies
in urine and CS from participants with and without sexual
experience. BV-associated taxa including Atopobium, Megasphaera,
Mobiluncus, Prevotella, Gemella, Veillonella, Gardnerella and Clostridium
[29] were each detected in one or more participants who reported
no partnered sexual experiences (Tables S1, S2, S3, S4). These
results indicate many putative vaginal taxa also colonize the male
urethra and CS, possibly from other body sites or environmental
reservoirs. Alternatively, urine from male infants frequently
contain Lactobacillus [30] so these could be vertically inherited
Figure 4. Temporal stability of CS and urine taxa. Lin’s concordance correlation coefficients (Y-axis) were calculated to assess agreement of
abundance of taxa, (X-axis), in sequential (A) CS, or (B) urine specimens from the same participants (three intervals: months 0–1, 1–2, 2–3), the red
trend line indicates mean of the three intervals. Bars indicate 95% confidence intervals.
Figure 5. Impact of circumcision on the CS and urine microbiotas. Relative normalized abundance of major (A) CS and (B) urine taxa in
circumcised (red) and uncircumcised (blue) participants at all four sampling points (Z-axis). Bars indicate 95% confidence intervals.
Penis Microbiomes of Adolescent Males
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communities. In either scenario, the observation that the male and
female genital tracts support similar microbiotas suggests that
some of these organisms could survive sexual transfer.
Colonization rates in asymptomatic older men at high risk for
STI with various Ureaplasma, Mycoplasma and Sneathia spp. can
exceed 30% [18,19]. In this study, Ureaplasma, Mycoplasma, and
Figure 6. Similarity of CS and urine taxa. A-C) Weighted Unifrac comparison of the microbiotas in select groups of specimens (Sanger data-set).
A) All CS (red) and all urine (blue) specimens. B) Circumcised (red) and uncircumcised (blue) CS specimens. C) Circumcised (red) and uncircumcised
(blue) urine specimens.
Figure 7. The microbiota of the CS is more stable than that of urine. Sørenson’s similarity indices calculated between pairwise specimens
within each participant’s (month = 0, 1, 2, 3) CS and urine samples, separately. A linear mixed-effects model was used to test if the index differed
between CS and urine samples, taking into account multiple specimens from the same participants (clustered data). Participants are indicated at left,
Sørenson similarity values are on the Y-axis, and blue dots indicate unique specimens.
Penis Microbiomes of Adolescent Males
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Sneathia were each detected in two participants (considering all sets
of sequence data and excluding singlets in 454 data-sets that could
result from rare miscalls of primer bar codes [31]) and one
participant was co-colonized with all three organisms. All of these
participants reported sexual exposures. Interestingly, Sneathia was
detected in one participant co-incident with his first anal sexual
exposure. These observations support the hypothesis that sexual
exposures could alter the composition of the male urethral flora.
Similarities of urine and vaginal microbiota
Only 2 enrollment urines lacked Lactobacillus and/or Streptococcus
entirely. One contained a high proportion of unclassified (20.0%)
and Escherichia coli (36.9%) sequences, indicating possible urinary
tract infection. The other contained a mixture of Prevotella and
Staphylococcus. All other enrollment urine contained high proportions
of Streptococcus or Lactobacillus, but rarely both. Spearman’s rank
correlation coefficient was used to assess the co-occurrence of taxa in
urine specimens. The occurrences of Lactobacillus and Streptococcus in
urine specimens were negatively correlated (r = 20.40, p-val-
ue = 0.0012). Interestingly, similar Lactobacillus- and Streptococcus-
dominated communities can maintain the low pH of the vagina [32].
Our results show that the penis does not support a single
characteristic microbiota and that it is important to distinguish
between the urethra and CS in understanding the compositions
and possible interactions of these microbiotas with STI. Sexually
transmitted pathogens that colonize the penis can exclusively
colonize the urethra (C. trachomatis, N. gonorhoeae, M. genitalium and
U. urealyticum) or both the urethra and CS (human papilloma virus,
herpes simplex virus (HSV-2), human immunodeficiency virus
(HIV), H. ducreyi, T. pallidum). Whether the CS and urethral
microbiota contribute to STI colonization resistance is unclear but
reports that circumcision differentially impacts risk for HIV [33],
HSV-2, T. pallidum and H. ducreyi [34] and urethral pathogens (C.
trachomatis and N. gonorhoeae) [35] is in concordance with our
findings. A future direction would be to test if the urethral
microbiota is relevant to risk for urethral STI.
It has long been appreciated that taxa that resemble those in the
female genital tract, colonize the male urethra, at least episodically
[21]. Our results are the first to show that some of these taxa
persist and colonize the penis prior to the onset of partnered sexual
activity. Colonization of the female and male genital tracts with
similar bacteria may reflect shared embryonic origins of these
tissues. It also suggests that these microbiotas might have common
ecological functions, such as lactic acid production and pathogen
resistance. A caveat is that 16 S rRNA sequencing does not yield
sufficient resolution to differentiate if the taxa in male and female
genital tract specimens are indeed the same organisms or tell us if
they have similar metabolic capacities.
Finally, our results suggest that partnered sexual behavior can
alter the composition of the urogenital microbiota. Although small
sample size limits the confidence of some conclusions, it is still
noteworthy that BV associated taxa including Mycoplasma,
Ureaplasma, and Sneathia were detected only in sexually experienced
participants [29]. Technologies that differentiate strain-level
polymorphisms, such as metagenomic sequencing, could be used
to test if these organisms are sexually transmitted and could yield
insights into the nature of idiopathic urogenital tract syndromes
that impact both men and women.
Study Design
Young men (ages 14–17 at enrollment; N = 18) were enrolled as
a single cohort during the week of January 2, 2010. The
participants were a non-clinical sample, recruited from diverse
community contacts, although not all are resident in a single
community. Additional enrollment criteria included no antibiotic
use in the past 60 days, absence of existing urinary tract infection
(including sexually transmitted infections), absence of immune
suppressing conditions, and overall good general health status.
Prior sexual activity was not considered. Self-reported race/
ethnicity was White (7/18), Black (7/18), and Latino (4/18).
Self-reported behavioral data was collected at enrollment using
a web-based, computer-assisted self-interview. Participants report-
ed circumcision status, lifetime and recent sexual activity (oral,
anal, vaginal), and presence or absence of genitourinary symp-
toms. All participants were asymptomatic at enrollment. All
participants and parents provided written, informed consent.
Ethics approval for this study was obtained from the Institu-
tional Review Board of Indiana University and all subjects were
recruited through the Indiana University Medical School. Written
informed consent to participate in the study was provided by next
of kin, caregivers or guardians on the behalf of the minors/
children participants in this study and this procedure was
approved by the Institutional Review Board of Indiana University.
Specimens were collected at enrollment, and at three subse-
quent one-month intervals. Specimens were collected in the
participant’s home. Voided urine sample and a CS swab sample
were collected at each time point. Urine was obtained by first-
catch void into a sterile collection cup. CS samples were obtained
following training on a flaccid penis model. Participants were
instructed to retract the foreskin (if present), and firmly trace the
groove of the coronal sulcus circumferentially (using a flocked
4 mm flexible handle elution swab). Samples were immediately
placed in a cooler, and transported to the laboratory within four
hours were they were stored at 280 C until DNA extraction.
Molecular Methods
CS samples were thawed and then suspended in 1 ml PBS then
were vortexed for 1 min. Urine (10 ml) were thawed and pelleted
by centrifugation for 15 min at 4,0006g at 4uC. In both cases,
DNA was harvested from specimens using a Qiagen DNeasy
(Qiagen Inc., Valencia CA) blood and tissue extraction kit.
Genomic DNA was eluted in nuclease-free water and stored at
4uC until sequencing. Reagent only controls were processed in
parallel to monitor for reagent contamination [18]. 16 S rRNA
PCR, Sanger sequencing and assembly of sequences were
performed as described previously [19]. Pyrosequencing of the
V1–V3, V3–V5 and V6–V9 sub-regions was performed according
a protocol developed by the Human Microbiome Project Data
Generation Working Group available at http://www.hmpdacc.
org [22].
Sequence Analysis and Statistics
16 S sequences were processed as described previously (18, 19).
Briefly, raw 16 S sequence reads were compared to human
genome sequences at NCBI using BLASTN [36]. Sequence reads
below the BLAST E-value cutoff 10
were considered putative
human DNA contaminants and were removed from the subse-
quent analyses. For 16 S rRNA contigs obtained from Sanger
sequence reads, we applied the GreenGenes criteria to define full-
length or near-full 16 S gene (i.e., the sequence length
. = 1250 bp). Only full length or near-full length contigs were
selected for subsequent analysis. These contigs were screened for
chimeras using Bellerophon [37] and default parameters at the
GreenGenes web server [38]. For sequence reads obtained from
454 sequencing technology, each read was sorted to specimens
only if a perfect barcode sequence was detected. Sequences that
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did not contain perfect matches to primer barcodes, were less than
200 bp in length, and or had average quality scores of less than 25
were discarded. The primer and barcode sequences were then
trimmed from the remaining sequences using customized Perl
scripts. Both the 16 S contigs from Sanger sequencing and 16 S
raw sequences were classified with RDP Classifier v2.2 [39] using
a series of confidence cutoffs ranging from 0.6 to 0.9. For selected
subset of genera member sequences were BLASTed against the
SILVA database [40]. Species-level assignments were decided
based on near perfect alignments to top database matches and
were manually examined for alignment quality (i.e., both
alignment length and percentage similarity). Multiple sequence
alignments were produced using ClustalW [41] with default
parameters, and neighbor-joining phylogenic trees were construct-
ed using PHYLIP [42]. Principal coordinate analyses of microbial
communities were performed using Unifrac [24]. The above
Unifrac analyses were also repeated by random sub-sampling from
each specimen. Briefly, sequence reads were randomly extracted
without replacement from each specimen (100 reads for Sanger
sequences and 200 reads for 454 sequences) and this procedure
was repeated 100 times. The averaged sequence counts were used
for Unifrac analyses. Microsoft EXCEL and customized scripts
developed in the R statistical package (
were used for statistical analyses. To correct for multiple tests, false
discovery rates were computed with the R package function
qvalue. Wilcoxon’s rank sum test was used to assess comparisons of
continuous variables between groups. The Wilcoxon’s signed rank
test for paired data was used for comparisons between swab and
urine samples from the same subject. Fisher’s exact test was used
for comparisons of categorical variables between groups. Sør-
ensen’s similarity index was calculated between either swab or
urine specimens from different time points within each subject to
assess intra-subject variability of microbiotas over time. Differenc-
es in the index between swab and urine samples were assessed
using linear mixed-effects models. Lin’s concordance correlation
coefficent was used to assess the agreement of measurements of
abundance of different taxa over time. A 95% confidence interval
was also calculated for Lin’s concordance correlation coefficient.
Spearman’s correlation coefficent was employed to assess whether
the abundances of two taxa were independent or associated. P
values less than 0.05 were considered significant. All sequences
from this study are available at
Supporting Information
Figure S1 Heirarchical clustering of enrollment urine
and CS swab microbiomes. Sanger sequences from enroll-
ment urine and swab specimens were heirarchically clustered
using A) Bray-Curtis and B) Spearman’s correlation coefficients as
a measure of distance. Urine and swab specimens are labeled U
and S, respectively.
Table S1 RDP classifier summary of 16 S rRNA se-
quences and select meta-data. Tables list 90% confidence
RDPII results for quality-checked sequences. Sanger data set.
Table S2 RDP classifier summary of 16 S rRNA se-
quences and select meta-data. Tables list 90% confidence
RDPII results for quality-checked sequences. V1–V3 data-set.
Table S3 RDP classifier summary of 16 S rRNA se-
quences and select meta-data. Tables list 90% confidence
RDPII results for quality-checked sequences. V3–V5 data-set.
Table S4 RDP classifier summary of 16 S rRNA se-
quences and select meta-data. Tables list 90% confidence
RDPII results for quality-checked sequences. V6–V9 data-set.
Table S5 Numbers and sizes of 16 S rRNA amplicons by
sample type and method.
Author Contributions
Conceived and designed the experiments: DEN BVDP QD GMW ES
BPK JDF. Performed the experiments: JDF BVDP BF ET GMW ES.
Analyzed the data: DEN BVDP BPK DM JDF RR QD. Wrote the paper:
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