Material and methods
The study was conducted between 2016 and 2017 at the Gynecology and Endometriosis Clinics of Koç University
Hospital in Istanbul, Turkey. The protocol of this prospective observational cohort study was approved by the
Koç University Clinical Research Ethics Committee (2016.220.IRB1.027). All study related procedures were per-
formed in accordance with relevant guidelines and regulations. All participants provided written signed informed
consent.
participants. Reproductive aged women who had a histologic diagnosis of endometriosis comprised the
study group, whereas asymptomatic reproductive aged women who presented for a routine well woman visit or
preconceptional counselling were included in the control group.
Exclusion criteria were:
• 45 years of age on the day of sample collection.
• Being ever pregnant including the day of sample collection.
• Postmenopausal status.
• Having clinical signs and symptoms suggestive of endometriosis, i.e. dysmenorrhea, dyspareunia, dyschesia
and/or infertility precluded recruitment to the control group. These symptoms were assessed with the Bibero-
glu-Behrmann (B&B) scale and women with a score >0 were not included in the control group
31.
• Having taken antibiotics or probiotics within the last 8 weeks.
• Inflammatory bowel disease, functional bowel disease, history of gastrointestinal cancer or surgery, acute
or severe gastrointestinal symptoms that require medical treatment, gastrointestinal infection or morbidity.
• An abnormal pap smear result within the last three years.
• Body mass index >30 kg/m2.
In addition, women who failed to achieve a pregnancy despite 12 months of regular unprotected intercourse
were considered infertile and were not recruited to the control group.
s ample collection. All participants provided stool samples at the clinic. Endometriosis patients, who would
undergo surgery, provided the samples on the evening before surgery.
A minimum of 5 mL fresh stool sample was collected in a 15 mL Falcon tube and rapidly transferred to −80 °C
to be stored in an upright position until DNA extraction.
Vaginal and endocervical swabs were collected following the insertion of a sterile vaginal speculum by one of
the two gynecologists (SY , ET) with eNATTM kits (606CS01L, Copan Group, Copan Italia). Two separate swabs
and collection tubes were used for vaginal and cervical samples. The swabs used to collect endocervical samples
were not touched to the vaginal walls during sample collection. Both samples were immediately transferred to
−80 °C to be stored in an upright position until DNA extraction.
DNA Extraction. Following the completion of sample collection, they were all transferred on dry ice to
Diagen laboratory located in, Ankara, Turkey for DNA extraction. Fecal samples were weighed to extract total
DNA using the QIAamp DNA Stool Mini Kit (Qiagen
®, Hilden, Germany), in accordance with the manufactur-
er’s instructions. Kurabo QuickGene DNA tissue kit S (DT-S) (Japan) was used for cervical and vaginal samples,
according to the manufacturer’s instructions.
Microbiome analysis. Extracted DNA samples were shipped on dry ice to FISABIO, Valencia, Spain for
further analysis.
16S rRNA gene amplification, library construction, and sequencing. The V3 and V4 regions of the
16S rRNA gene were amplified following the 16S Metagenomic Sequencing Library Preparation Illumina protocol
(Part # 15044223 Rev. A, Illumina, CA, USA). Extraction controls were amplified and sequenced in parallel with
the samples.
The primers targeting this region used were 16S Amplicon PCR Forward Primer = 5′-TCGTCGGCA
GCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG-3′ and 16S Amplicon PCR Reverse
Primer = 5′-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC-3′.
A total of 12.5 ng of genomic DNA per sample was used for amplification under the following PCR conditions:
5 min of initial denaturation at 94 °C followed by 25 cycles of denaturation (30 s at 94 °C), annealing (30 s at 52 °C)
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and elongation (1 min at 72 °C). After amplification, the products were visualized in 1.4% agarose gels and quan-
tified using a Qubit® 3.0 Fluorometer (Thermo Fisher Scientific, Carlsbad, CA, USA). Next, the multiplexing step
was performed with Nextera XT Index Kit (Illumina) by attaching dual indices to both ends of the PCR products.
The samples were pooled in equimolar amounts and sequenced in the Sequencing Service facilities of FISABIO
using a 2 × 300 bp paired-end run using the MiSeq
® Reagent kit v3, (Illumina), on a MiSeq Sequencer according
to manufacturer’s instructions (Illumina).
We used internal controls during extraction, PCR (there is a negative control for PCR) and sequencing.
During sequencing, we used internal control for 16S and it contained 1007 reads.
s equence Bioinformatics analysis. Primary processing of sequencing reads was carried out on the
raw reads starting by a quality assessment performed by the use of prinseq-lite program applying the following
parameters: min_length: 50, trim_qual_right: 30, trim_qual_type: mean and trim_qual_window: 20
32. We used
Prinseq-lite (v0.20.4) (webpage: http://prinseq.sourceforge.net). Forward and reverse reads passing the quality
check were joined using FLASH program applying default parameters
33. Next, joined, unjoined reads and single-
tons were concatenated and mapped against the human genome (GRCh38.p11, reference human genome, Dec
2013) by using Bowtie2
34 with end-to-end and very sensitive options (–very-sensitive: -D 20 -R 3 -N 0 -L 20 -i
S,1,0.50).
Human-unaligned files were taxonomically analyzed by aligning the reads to the Ribosomal Database Project
(RDP) database, using the naïve Bayesian rdp_classifier 2.12 tool that provides taxonomic assignments from
domain to genus
35. The resulting files were parsed to get the counts for each taxon in each sample, and finally
a unique contingency table was generated. The contingency table was converted into Biom format, using the
QIIME pipeline version 1.9.0 for composition and abundance analyses, as well as for ecological diversity
36. For
diversity within samples, or alpha diversity, 1,000 rarefactions of 9,500 random reads per sample, with replace-
ment, were carried out and the alpha diversity was calculated with Shannon diversity index (SI). Boxplots were
created using the free statistical package R 3.1.0
37. Diversity between samples, or beta diversity, was assessed with
Principal Coordinates Analysis (PCoA) using Bray-Curtis dissimilarity index matrices, implemented by QIIME
pipeline, to create linear combinations (multidimensional scaling) that explain the data better. Statistical signifi-
cance of sample groupings was calculated by using the resulting distance matrices and the Adonis nonparametric
analysis of variance
38. Additional analyses, such as non-parametric unpaired two-samples Wilcoxon tests for
groups, sample types, and both, were carried out with R scripts. Our nucleotide sequence data for 16S rRNA
gene was deposited in EBI Short Read Archive (https://www.ebi.ac.uk/ena) under the study accession number
PRJEB26800 with accession numbers ERS2487953 to ERS2488036.
Results
participant characteristics. Fourteen Caucasian women with endometriosis and 14 Caucasian healthy
controls were included in the study. Median (25th–75th percentile) age, (28.5 (26–31.3) vs 27.5 (25.8–30) years;
p = 0.54) and median (25th–75th percentile) body mass index, (23 (21–24.3) vs 21 (20.1–24.2) kg/m 2; p = 0.25),
were similar in the endometriosis and control groups, respectively. None of the participants were on oral contra-
ceptives or had an intrauterine device. None reported vaginal intercourse during the three days before sample
collection. Similar numbers of women in each group provided the samples during the follicular (7/14 in both
groups) or luteal phase (7/14 in both groups) of the menstrual cycle (p>0.99).
All women in the endometriosis group had moderate to severe (stage 3–4) endometriosis according to
American Fertility Society Revised Classification
39. All patients had endometriomas and widespread lesions in
the pelvis, all had deep infiltrating endometriotic nodules on one or both of the sacrouterine ligaments, and par-
tially or completely obliterated pouch of Douglas. While all women had superficial bowel involvement effecting
serosal surface only, two of the 14 women were considered to have bowel involvement affecting muscular and/or
mucosal layer of the sigmoid colon.
Cervical, vaginal and stool samples were obtained from each participant. In a set of 84 samples, we identified
327 different bacterial genera, a total of 6,160,862 reads, with an average of 73,344 ± 24,482 reads per sample
(ranging from 142 to 110,467). Our cut-point analyses were 9500 reads, and that excluded one sample (XS1_3H5
142 reads), while having a high number of reads for consistent analysis.
Diversity Analyses. Overall, PCoA analysis shows that vaginal, cervical and gut microbiota composition
was similar between the endometriosis group and controls (Fig. 1). Non-parametric adonis tests showed no sig-
nificant differences according to the condition status in all niches (Fig. 1). Bacterial diversity measured by SI was
similar for vaginal, cervical, and gut samples between from the endometriosis and the control groups (Fig. 2). The
fecal samples had higher diversity than both the cervical and vaginal samples (Fig. 2).
Genus Analysis. We performed Wilcoxon tests for the comparison of pairs of groups and only for bacteria,
which were present in at least half of the samples of at least one of the two groups. For vaginal samples, at genus
level, the complete absence of Gemella and Atopobium in the endometriosis group was noteworthy. In cervical
samples, at genus level, Atopobium and Sneathia were completely absent, while Alloprevotella was significantly
increased in the endometriosis group (p < 0.01 for both). For stool samples, genera Sneathia , Barnesella and
Gardnerella were significantly decreased in the endometriosis group (p < 0.01 for all). (Figs 3–6 and Table 1)
There were 25 different observed genera, the majority being Lactobacillus (80–84%), in the cervical micro-
biota of the endometriosis group and controls. In patients with endometriosis, 84.6% were Lactobacillus and
10.5% Gardnerella, making 95.1% of the total bacteria. In the control group, Lactobacillus comprised 80.2% and
Gardnerella 7.3% of total bacteria.
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Two patients in the endometriosis group, had more Escherichia/Shigella in stool, and further follow-up of
these patients showed severe bowel involvement by endometriosis requiring segmental colon resection (Fig. 7).
Sensitivity Analyses Excluding Lactobacillus. Sensitivity analyses of vaginal microbiota after exclusion
of Lactobacillus species, showed that Gardnerella comprised a significantly higher proportion of the remaining
microbiota in endometriosis group than in controls (72.9% vs 36.8%, p < 0.05). Escherichia/Shigella was also more
abundant in the endometriosis group; Prevotella and Dialister were decreased in patients with endometriosis
compared to the controls, without statistical difference.
Sensitivity analysis excluding Lactobacillus species showed that Gardnerella comprised a significantly
higher proportion of the remaining microbiota in the cervix of endometriosis group than in controls (67.7%
vs 36.8%, p < 0.05). Streptococcus, Escherichia/Shigella and Ureaplasma were also more abundant in the endo-
metriosis group. However, Prevotella, Dialister, and Megasphaera were significantly decreased in patients with
v
VAGINAL SAMPLES CERVICAL SAMPLES
STOOL SAMPLES
CONTROL
ENDOMETRIOSIS
adonis p-value: 0.504 adonis p-value: 0.776
adonis p-value: 0.635
Figure 1. Principal Coordinates analysis showing the distribution of the vaginal, cervical and stool samples,
based on Bray-Curtis dissimilarity matrices. Blue dots indicate control group (n = 14), red dots, stage 3–4
endometriosis group (n = 14).
Figure 2. Boxplots depicting the Shannon diversity index of the cervical (Cx), gut (G) and vaginal (V)
microbiota in control (C) (n = 14) and endometriosis (E) (n = 14) groups. Boxes indicate the first and third
quartiles, dash lines the upper and lower whiskers, crosses indicate the mean, and horizontal bold lines the
median.
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Figure 3. Sample graphs showing some of the genera which had different abundance between stage 3–4
endometriosis (n = 14) and controls (n = 14).
Figure 4. Most abundant taxa (at genus level) among healthy controls (n = 14) and women with stage 3–4
endometriosis (n = 14) in vaginal samples.
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endometriosis compared to the controls. The complete absence of particular genus, Atopobium in the endometri-
osis group was noteworthy (Figs 4 and 5).
Discussion
Overall, vaginal, cervical and gut microbiota composition was similar between women with stage 3–4 endome-
triosis and controls. However, there were some differences between bacteria groups. Noteworthy are, the absence
of a particular genus, Atopobium in vaginal and cervical microbiota, increased Gardnerella presence in cervical
microbiota, and more women having Escherichia and Shigella dominant gut microbiota in the endometriosis
group.
Even though SI is a good tool to assess microbiota diversity in anatomical sites where there are many gen-
era, e.g. stool, it can have limitations in sites where there are only a few genera like the vagina and the cervix
40.
In our sample, there were 230 genera in the stool and 182, 183 in the vagina and cervix, respectively. Thus, the
observed differences in some bacteria could be still relevant. In addition, the lower genital tract of reproductive
aged females is unique as it is predominantly populated by a single genus, i.e. Lactobacillus , which is also the
most abundant genus in endometrial microbiota, a fact that could limit the value of SI as an assessment tool41–43.
Therefore, we undertook sensitivity analyses by excluding Lactobacillus, and the following bacteria were found
to be significantly increased; Sneathia, Gardnerella, Streptococcus, Escherichia/Shigella and Ureaplasma, while
Alloprevotella was significantly decreased in the cervix.
If confirmed in other studies, the complete absence of Atopobium in the vagina and cervix, together with the
increased presence of Gardnerella, Escherichia/Shigella and Ureoplasma in cervical microbiome of patients with
endometriosis could be a relevant finding of this study. Atopobium is recently implicated as a gynecological
pathogen associated with bacterial vaginosis, obstetric bacteremia, and, possibly, with endometrial cancer
44–47.
Intriguingly, a recent study comparing uterine microbiome between women with endometrial cancer and with
benign pathologies, reported the presence of Atopobium vaginae in 14/15 women with endometrial cancer, as
opposed to 4/10 women with benign pathologies
46. The authors suggest that Atopobium can facilitate infection
by Porphyromonas species, which can be present intracellularly and disrupt cell regulatory functions eventually
leading to a carcinogenic trigger
46. Whether the association is causal is unclear, but from a different perspective,
maybe the absence of Atopobium can be related to occurrence of endometriosis, which is also a benign gyneco-
logic pathology, through a different downstream effect.
Niche Decreased Increased
Vagina Gemella* Atopobium* —
Vagina excluding Lactobacillus — Gardnerella Escherichia/Shigella
Cervix Atopobium* Snethia Alloprevotella
Cervix excluding Lactobacillus Prevotella Dialister Megasphaera Gardnerella Streptococcus Escherichia/Shigella Ureaplasma
Stool Gardnerella Snethia Barnesella
Table 1. Differences between microbiota in women with endometriosis and healthy controls. *Completely
absent.
Figure 5. Most abundant taxa (at genus level) among healthy controls (n = 14) and women with stage 3–4
endometriosis (n = 14) in cervical samples.
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If there is indeed an association between endometriosis and female microbiota composition, what would
be the direction of causation; altered immune response leading to both endometriosis and different microbiota
composition or different microbiota, including the mere presence or absence of a single species, leading to altered
immune function and the disease? While microbiome could be a useful screening/diagnostic tool for endome-
triosis in both scenarios, it could become a therapeutic target in the latter. Indeed, a former study including
95 women who underwent surgery for benign gynecologic conditions, not known to be related to infectious
etiology, reported subtle differences between uterovaginal microbiomes of patients with adenomyosis, infertility
due to endometriosis, and fibroids
41. However, the study cohort lacked healthy controls and comparators for
Figure 7. Bacterial abundance in stool samples from controls (n = 14) and stage 3–4 endometriosis (n = 14)
group. Increased Escherichia/Shigella abundance is observed in E2 and E4 who later required segmental colon
resection due to bowel involvement.
Figure 6. Most abundant taxa (at genus level) among healthy controls (n = 14) and women with stage 3–4
endometriosis (n = 14) in stool samples.
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endometriosis associated infertility included fertile women whose microbiome could have changed due to past
pregnancy48,49. Our study is unique in the sense that microbiome between nulligravid healthy controls and endo-
metriosis patients were compared.
It is intriguing that two women in the endometriosis group had Escherichia/Shigella dominant gut microbiome,
while none of the controls showed a similar composition. It is even more interesting that these two women underwent
segmental colon resection as part of surgical treatment of deep infiltrating endometriosis during the period between
sample collection and the microbiome analyses, i.e. the surgeons were not aware of microbiome composition. It is not
always possible to assess the depth of bowel involvement preoperatively with imaging, and if confirmed, gut microbi-
ome analysis could be an additional tool to predict the possibility of bowel resection and to counsel the patients.
The advantages of this study are strict selection criteria reflected by stability of microbiota, exclusion of ever
pregnant women, and women with other conditions/medications that could affect the microbiome. All partic -
ipants belonged to the same ethnicity. Whether vaginal and/or cervical microbiota varies across the menstrual
cycle is controversial
41,50. Y et, similar numbers of women provided samples during the follicular and luteal phases
in both groups, and observed differences and similarities between the two groups are unlikely to be altered by
menstrual cycle. Importantly, inclusion of women with histology proven endometriosis is an advantage. The lack
of laparoscopic confirmation of the absence of endometriosis in the control group could be regarded as a short-
coming of our study. However, women in the control group were asymptomatic and did not have any ultrasound
findings of the condition with B&B scores of zero, rendering them very unlikely to have endometriosis. Moreover,
even if some women in the control group had mild endometriosis that could not be diagnosed with history and
pelvic examination, this would have made the study groups more similar leading to underestimation of any dif-
ferences between them. Thus, the observed differences in the present study are unlikely to be overestimates. The
absence of whole genome and metagenomic analyses and endometrial samples are other limitations, however,
collection of endometrial samples without contaminating with cervical microbiome is not feasible.
In conclusion, while overall microbiome composition in the cervix, vagina and gut seems similar between
women with stage 3–4 endometriosis and healthy controls, there seems to be some differences at the genus level.
Further studies are needed to analyze an association between endometriosis and microbiota.
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