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Vaginal Microbiota Is Stable throughout the Estrous Cycle in Arabian Mares
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Lactic acid bacteria (LAB) dominate human vaginal microbiota and inhibit pathogen proliferation. In other mammals, LAB do not dominate vaginal microbiota, however shifts of dominant microorganisms occur during ovarian cycle. The study objectives were to characterize equine vaginal microbiota in mares by culture-dependent and independent methods and to describe its variation in estrus and diestrus. Vaginal swabs from 8 healthy adult Arabian mares were obtained in estrus and diestrus. For culture-dependent processing, bacteria were isolated on Columbia blood agar (BA) and Man Rogosa Sharpe (MRS) agar. LAB comprised only 2% of total bacterial isolates and were not related to ovarian phases. For culture-independent processing, V3/V4 variable regions of the 16S ribosomal RNA gene were amplified and sequenced using Illumina Miseq. The diversity and composition of the vaginal microbiota did not change during the estrous cycle. Core equine vaginal microbiome consisted of Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria at the phylum level. At the genus level it was defined by Porphyromonas, Campylobacter, Arcanobacterium, Corynebacterium, Streptococcus, Fusobacterium, uncultured Kiritimatiaellae and Akkermansia. Lactobacillus comprised only 0.18% of the taxonomic composition in estrus and 0.37% in diestrus. No differences in the relative abundance of the most abundant phylum or genera were observed between estrus and diestrus samples.
Phylum taxonomic relative abundance in individual mares in estrus and diestrus (only taxa with a mean relative abundance >1.5% at estrus or diestrus are represented). The letters in the x axis correspond to each individual mare.
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V aginal Microbiota Is Stable throughout the Estrous
Marta Barba 1 , Rebeca Mart í nez-Bov í 1 , Juan Jos é Quereda 1 , Mar í a Lorena Moc é 1 ,
Mar í a Plaza-D á vila 1 , Estrella Jim é nez-T rigos 1 , Á ngel G ó mez-Mart í n 1 ,
Pedro Gonz á lez-T orres 2 , Bel é n Carbonetto 2 and Empar Garc í a-Rosell ó 1, *
1 Research Group-Microbiological Agents Associated with Animal Reproduction (Pr oVaginBio),
Department of Animal Production and Health, V eterinary Public Health and Food Science and
T echnology (PASAPT A), Faculty of V eterinary Medicine, Cardenal Herrera-CEU University ,
CEU Universities, 46115 Alfara del Patriarca, Spain; marta.barba@uchceu.es (M.B.);
rebeca.martinez@uchceu.es (R.M.-B.); juan.quereda@uchceu.es (J.J.Q.); mmoce@uchceu.es (M.L.M.);
maria.plaza@uchceu.es (M.P .-D.); estrella.jimenez@uchceu.es (E.J.-T .);
angel.gomezmartin@uchceu.es ( Á .G.-M.)
2 Microomics Systems S.L, 08003 Barcelona, Spain; pedro.gonzalez@microomics.eu (P .G.-T.);
belen.carbonetto@microomics.eu (B.C.)
* Correspondence: empar@uchceu.es; Tel.: + 34-9613-69000 (ext. 66020)
Received: 16 September 2020; Accepted: 28 October 2020; Published: 3 November 2020
Knowing which bacteria dominate vaginal microbiota and its variation throughout
the cycle is important to study how to prevent reproductive diseases. In women, vaginal microbiota
is dominated by Lactobacillus but this does not happen in other animals. Little is known about equine
vaginal microbiota. The aim of this study was to describe the dynamics of equine vaginal microbiota
during the ovarian cycle. Eight healthy adult Arabian mares were used to characterize vaginal
microbiota by standard microbiologic and metagenomic procedur es. The abundance of Lactobacillus
was < 2% by both methods, meaning that equine vaginal microbiota was not dominated by these
bacteria. Dominant bacteria included other genera such as Porphyromonas and Campylobacter among
others. No changes in vaginal microbiota composition were found, suggesting that equine vaginal
microbiota was stable throughout the ovarian cycle.
Lactic acid bacteria (LAB) dominate human vaginal microbiota and inhibit pathogen
proliferation. In other mammals, LAB do not dominate vaginal microbiota, however shifts of
dominant microorganisms occur during ovarian cycle. The study objectives were to characterize
equine vaginal microbiota in mares by culture-dependent and independent methods and to describe
its variation in estrus and diestrus. Vaginal swabs fr om 8 healthy adult Arabian mares were obtained
in estrus and diestrus. For culture-dependent processing, bacteria were isolated on Columbia blood
agar (BA) and Man Rogosa Sharpe (MRS) agar. LAB comprised only 2% of total bacterial isolates and
were not related to ovarian phases. For culture-independent processing, V3 / V4 variable regions of
the 16S ribosomal RNA gene were amplified and sequenced using Illumina Miseq. The diversity
and composition of the vaginal microbiota did not change during the estrous cycle. Core equine
vaginal microbiome consisted of Firmicutes, Bacteroidetes, Proteobacteria and Actinobacteria at the
phylum level. At the genus level it was defined by Porphyromonas, Campylobacter, Arcanobacterium,
Corynebacterium, Streptococcus, Fusobacterium , uncultured Kiritimatiaellae and Akkermansia . Lactobacillus
comprised only 0.18% of the taxonomic composition in estrus and 0.37% in diestrus. No di ff erences
in the relative abundance of the most abundant phylum or genera were observed between estrus and
Keywords: horses; equine; microbiome; metagenomic; estrus; diestrus; reproductive; vagina
Animals 2020 , 10 , 2020; doi:10.3390 / ani10112020 www.mdpi.com / journal / animals
Endometritis is considered as one of the most frequent causes of subfertility in mares [
most important physical barriers of uterine defense are the vulva, the vaginal vestibule (caudal vagina)
and the cervix. Although curr ent reproductive protocols include vulvar washing with water and
neutral soap, it is essential to pass through the vaginal vestibule, and manipulation of the cervix to
carry out reproductive procedures. This would allow bacterial pathogens present in the vaginal tract
to reach the uterus during artificial insemination or other manipulations [
microbiota in human medicine has led to the prevention and treatment of vaginal and repr oductive
Culture-dependent and culture-independent methods are complementary in describing vaginal
microbiota in women, although culture-independent methods are mor e precise in detecting clinically
relevant vaginal non- Lactobacillus species (e.g., Atopobium vaginae, Sneathia sanguinegens or Prevotella spp.)
known to be associated with bacterial vaginosis in women [
miss the great diversity present in both diseased and healthy reproductive tracts. On the other
hand, culture-independent studies based on metagenomics have changed the understanding of the
role of the microbiome in health, including the reproductive tract. Metagenomics have allowed
one to study the link between dysbiosis (i.e., microbiota imbalance) and certain diseases [
Moreover , an increased comprehension of the reproductive micr obiota may lead to novel antibiotic-free
therapeutic approaches to improve reproduction pr ocedures, such as the use of probiotics to promote
It is known th at lactic acid ba cteria (LAB) do minate human va ginal micro biota and inhib it
opportun istic pathoge n prolifera tion [
]. The estrog en peak in women is a ssociated wit h a higher
abundanc e of Lactobacil lus spp. [
]. In ot her mammals, LAB do not d ominate vagin al microbio ta,
however sh ifts of dominan t microor ganisms occur d uring the ovari an cycle [
abundant genera in the vaginal microbiota of ewes and cows were shown to be Aggregatibacter spp.
and Streptobacillus spp. in one study [
] or Ureaplasma spp. and Histophilus spp. in another study [
in contrast to human samples [ 13 ].
There is scarce information regarding equine vaginal or uterine micr obiota. One culture-based
approach study described the presence of LAB in vaginal equine samples such as Lactobacillus spp.
], however the relative abundance of these bacteria in mares remains
unknown. A recent study using metagenomics has revealed that a moderate diverse microbiome is
present in equine uterine samples where no significant growth was obtained by aerobic cultur e [
Furthermore, the uterine microbiome composition was found to be very similar to populations found
on the external cervical os, meaning that communication between the uterine lumen and cranial vagina
Further studies to describe the vaginal microbiome in healthy mares are needed before investigating
how bacterial populations change in diseases such as endometritis or can be modulated for its treatment
or prevention. The aim of this study was to describe autochthonous caudal vaginal microbiota in
healthy mares. Our first objective was to characterize the vaginal microbiota by culture-dependent and
culture-independent methods. Our second objective was to compare the vaginal microbiota in estrus
2.1. Animals and Experimental Design
Eight healthy adult Arabian cyclic mares aged 5–23 years old and weighing between 350 and
450 kg were studied during estrus and diestrus, between June and July 2018. Mares were kept
in several paddocks with access to ad libitum water and fed alfalfa and grass hay . Three mares
were maiden and five mares were multiparous. No history of previous reproductive or fertility
problems was reported in any mare. The genital tract was examined transrectally using a B-mode
ultrasound scanner (Sonosite NanoMaxx) with an 8 MHz linear array probe. All mares had
ovulated at least once before the start of the study , which was confirmed by the presence of a
corpus luteum (CL). T ransrectal palpation, ultrasound examination and teasing were performed
to determine estrus and diestrus, once a week (every 7 days), and each mare showed regular
cycles. Each mare was sampled (vaginal samples and blood) twice, once in estrus and once in
diestrus. Furthermore, plasma progesterone concentration was determined to confirm the ovarian
phase. Diestrus was considered when progesterone concentration was > 1 ng / mL, and estrus when
]. Inclusion criteria for estrus consideration (follicular phase) included: follicle diameter
30 mm, endometrial edema (score of 1–3), positive teasing and progesterone concentration < 1 ng / mL.
Inclusion criteria for diestrus consideration (luteal phase) included detection of a CL, negative teasing
and progesterone concentration > 1 ng / mL. All mares had to fulfill all inclusion criteria for both cycle
phases to be included in the study . Animal procedures were handled in accordance with the Spanish
Department of Agriculture Guide for Care and Use of Animals in Research and were appr oved by the
local animal welfare committee at the Universidad CEU Cardenal Herrera (ref: 2017 / VSC / PEA / 00245).
Blood samples were taken from the jugular vein in heparinized tubes and were immediately
placed on ice for transportation. Samples were centrifuged at 3500 rpm (2000
plasma was separated. Plasma samples were frozen at
C until progesterone quantification using a
by solid-phase, competitive chemiluminescent enzyme immunoassay (Immunlite
System, Siemens Healthineers, Madrid, Spain). Mean and SD progesterone concentration in estrus was
0.30 ± 0.24 ng / mL and in diestrus, 4.27 ± 1.53 ng / mL.
V aginal sampling was performed with animals restrained in the stocks. Contamination was
prevented by vulvar cleaning with neutral soap and water before sampling and by avoiding contact
with the vulva. Samples were obtained by gentle swabbing of the vaginal wall at the level of the
vestibule (caudal vagina) for 30 s in sterile conditions, as previously described [
were obtained for each sampling point (i.e., in estrus and in diestrus) and immediately placed in
transport tubes. One swab was used for culture-independent processing, the second swab was used
for culture-dependent bacterial isolation and the third swab was used for cytological analysis.
For cytological examination, each cotton swab was moistened with 0.2 mL of 0.9% saline solution
and gently rolled onto a clean glass microscope slide and air-fixed. The smears were fixed with methanol
for hematoxylin and eosin staining (Tinci
pida Grifols, Diagnostic Grifols, S.A., Barcelona, Spain)
and were examined by a photomicroscope (Leica DM2000). Ten microscopic fields from each sample
400 magnification to identify and count the number of epithelial cells (superficial or
basal cells) and inflammatory cells (neutrophil and macrophages) per microscopic field and at
× 1000 magnification to identify and count bacteria as previously described [ 17 – 19 ].
Each vaginal swab was homogenized in 1 mL of brain heart infusion broth (Scharlab, Barcelona,
Spain) and vortexed for 1 min at maximum speed to suspend attached bacteria. Then, decimal dilutions
in phosphate-bu ff ered saline (PBS) were plated in 13.5 cm diameter Petri dishes containing the following
media: Man Rogosa and Sharpe (MRS) agar (Scharlab, Barcelona, Spain) for the selective growth of
lactic acid bacteria (LAB) and Columbia blood agar (BA; Dismalab, V aldemorrillo, Madrid, Spain)
as a general bacterial growth medium. Plates were incubated for 48 h at 37
aerobically , respectively. The number of colony forming units (CFU / mL) was counted.
2.6. Culture-Independent Processing
For culture-independent processing, the third swab was frozen at
for high-throughput sequencing [ 4 ].
2.6.1. Library Preparation and Sequencing
DNA ex tracti on was do ne using t he DNeas y Power Lyz er Power Soil Ki t (Qiage n, Hild en,
Germ any) fol lowin g the manu factur er’s instr uctio ns. Agit ation us ing T issue l yser II
(Qia gen, Hil den, German y) at 30 Hz / s for 10 mi n at 4
C was pe rforme d. Mock c ommuni ty
DNA wa s includ ed as a con trol of l ibrary p repa ration ( Zymobi omics M icrob ial
Comm unity DN A, Zymo Resear ch, Irvi ne, CA, USA ). The amp lifica tion wa s done
usin g primer s speci fic to the V 3-V4 re gions o f the 16S rR NA DNA (V 3-V4-F orwar d
-TCG TCGGCA GCGTC AGA TGTGT AT AAGAGAC AGCCT ACGGGN GGCWGC AG-3
5 0 GTC TCGTGG GCTCG GAGA TGTG TA TA AGAGAC AGGAC TA CHVGGG TA TCT AA TCC-3 0 ).
The amplification reaction was performed in a 10-
concentration. The PCR program included: 3 min at 95
C (initial denaturation) followed by 25 cycles:
C and a final elongation step of 5 min at 72
of PCR products was done using AMPure XP beads (Beckman Coulter , Nyon, Switzerland) with a
ratio according to the manufacturer’s instructions. Final elution from the magnetic beads was done
L of the eluate were transferred to a fresh 96-well plate. The used
primers contained overhangs, which allowed the addition of full-length Nextera barcoded adapters for
Illumina MiSeq sequencing during a second PCR step (with only 8 cycles). S Sequencing ready libraries
had ~450-bp insert sizes. Second PCR products were purified with the SequalPrep normalization kit
(Invitrogen, ThermoFisher Scientific, W altham, MA, USA), according to the manufacturer’s protocol.
L final volume and pooled for sequencing. Quantification of the final pool
was done with the qPCR using Kapa library quantification kit for Illumina Platforms (Kapa Biosystems,
Sigma Aldrich, Saint Louis, MO, USA) on an ABI 7900HT real-time cycler (Applied Biosystems,
ThermoFisher Scientific, Waltham, MA, USA). Sequencing was performed using Illumina MiSeq
300 bp reads 15% of PhIX control libraries used to increase the diversity of the sequenced
sample. Negative controls were added from DNA extraction steps, including one control for the
sample collection bu ff er and one blank DNA extraction control using sterile water . Negative controls
for both PCR amplification steps were also included. Control PCR products were visualized in 1.5%
agarose gel electrophoresis stained with SYBR Safe (Applied Biosystems, ThermoFisher Scientific,
W altham, MA, USA). No visible bands were observed.
2.6.2. Amplicon Sequences Processing and Analysis
In brief, raw demultiplexed forward and reverse reads were processed using the following
methods and pipelines as implemented in QIIME2 version 2019.4 with default parameters unless
]. DADA2 was used for quality filtering, denoising, pair-end merging and amplicon sequence
variant calling (ASV , i.e., phylotypes or Operational Taxonomic Units, OTUs) using the qiime dada2
]. Q20 was used as quality threshold to define read sizes for trimming before
merging (parameters: –p-trunc-len-f and –p-trunc-len-r). Reads were truncated at the position when
the 75th percentile Phred score felt below Q20: 288 bp for forward reads and 226 bp for reverse reads.
After quality filtering steps, average sample size was 18,778 reads (min: 3547 reads, max: 46,269 reads).
ASVs were aligned using the qiime alignment ma ff t method [
]. The alignment was used to create a
tree and to calculate phylogenetic relations between ASVs using qiime2 phylogeny fasttree method [
ASV tables were subsampled without replacement in order to even sample sizes for diversity analysis
using qiime diversity core-metrics-phylogenetic pipeline. The smallest sample size was chosen for
]. Unweighted and weighted Unifrac distances were calculated to compare community
structure. Alpha diversity metrics: observed OTUs (i.e., richness), Pielou‘s evenness index and Shannon
index were calculated. Taxonomic assignment of ASVs was performed using a Bayesian classifier
trained with Silva database (i.e., 99% OTUs database) using the qiime feature-classifier classify-sklearn
]. Since the swab samples could contain vaginal tissue cells, phylotypes were filtered to
discard contaminant Eukariota DNA-derived amplicons using Blast against the mentioned database
2.7.1. Cytological and Culture-Dependent Data
Normality of the data was assessed based on examination of histograms plots and the Shapiro–W ilk
test. Normally distributed variables (basal and superficial cells) were expressed as mean and standard
deviation (SD) and non-normally distributed variables (BA and MRS counts) were expressed as
the median and interquartile range (ICR). Di ff erences between basal and superficial cells observed
in cytological examination in estrus and diestrus were compared by a paired t -test. BA and MRS
counts between estrus and diestrus were compared by the W ilcoxon-signed rank test. Values of
p < 0.05 were considered significant. Statistical analyses were performed using SPSS
(IBM Corporation, New Y ork, NY , USA).
Di ff erential abundance of taxa was tested using the Kruskal–W allis non-parametric test on the
relative abundance of taxa (total sum scale) [
]. After Kruskal–Wallis, Conover’s test with the false
discovery rate Benjamini–Hochberg correction was added for pairwise comparison. Alpha diversity
comparisons were performed using the Kruskal–W allis non-parametric test. Beta diversity distance
matrices were used to calculate principal coordinates analysis (PCoA) and to make ordination plots
using R software package version 3.6.0 (R Foundation for Statistical Computing, Vienna, Austria,
http: // www .R- project.org ). The significance of grouping based on composition and structure of the
microbial communities was tested using Permanova. Permdisp test was used to identify locati
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