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Molecular characterization
of exosomes and their microRNA
cargo in human follicular fluid:
bioinformatic analysis reveals that
exosomal microRNAs control
pathways involved in
follicular maturation
Manuela Santonocito, Ph.D.,
a
Marilena Vento, Ph.D.,
b
Maria Rosa Guglielmino, Ph.D.,
a
Rosalia Battaglia, M.Sc.,
a
Jessica Wahlgren, Ph.D.,
c
Marco Ragusa, Ph.D.,
a
Davide Barbagallo, Ph.D.,
a
Placido Borzì, M.D.,
b
Simona Rizzari, M.Sc.,
b
Marco Maugeri, Ph.D.,
a
Paolo Scollo, M.D.,
b
Carla Tatone, Ph.D.,
d
Hadi Valadi, Ph.D.,
c
Michele Purrello, M.D., Ph.D.,
a
and Cinzia Di Pietro, Ph.D.
a
a
Department Gian Filippo Ingrassia, Biologia Cellulare e Molecolare, Genetica, Genomica Giovanni Sichel, Universit
adi
Catania;
b
Servizio di PMA/Azienda Ospedaliera Cannizzaro, Catania, Italy;
c
Department of Rheumatology and
Inflammation Research, University of Gothenburg, Gothenburg, Sweden; and
d
Department of Life, Health and
Environmental Sciences, University of L'Aquila, L'Aquila, Italy
Objective: To characterize well-represented microRNAs in human follicular fluid (FF) and to ascertain whether they are cargo of FF
exosomes and whether they are involved in the regulation of follicle maturation.
Design: FF exosomes were characterized by nanosight, flow cytometry, and exosome-specific surface markers. Expression microRNA
profiles from total and exosomal FF were compared with those from plasma of the same women.
Setting: University laboratory and an IVF center.
Patient(s): Fifteen healthy women who had undergone intracytoplasmic sperm injection.
Intervention(s): None.
Main Outcome Measure(s): TaqMan low-density array to investigate the expression profile of 384 microRNAs; DataAssist and
geNorm for endogenous control identification; significance analysis of microarrays to identify differentially expressed microRNAs;
nanosight, flow-cytometry, and bioanalyzer for exosome characterization; bioinformatic tools for microRNAs target prediction,
gene ontology, and pathway analysis.
Result(s): We identified 37 microRNAs upregulated in FF as compared with plasma from the same women. Thirty-two were
carried by microvesicles that showed the well-characterized exosomal markers CD63 and CD81. These FF microRNAs are
involved in critically important pathways for follicle growth and oocyte maturation. Specifically, nine of them target and
negatively regulate mRNAs expressed in the follicular microenvironment encoding inhibitors of follicle maturation and meiosis
resumption.
Received February 25, 2014; revised August 4, 2014; accepted August 5, 2014.
M.S. has nothing to disclose. M.V. has nothing to disclose. M.R.G. has nothing to disclose. R.B. has nothing to disclose. J.W. has nothing to disclose. M.R. has
nothing to disclose. D.B. has nothing to disclose. P.B. has nothing to disclose. S.R. has nothing to disclose. M.M. has nothing to disclose. P.S. has nothing
to disclose. C.T. has nothing to disclose. H.V. has nothing to disclose. M.P. has nothing to disclose. C.D.P. has nothing to disclose.
This work was supported by Ministero dell’Universit
a e della Ricerca Scientifica e Tecnologica (to C.D.P) and by Farmitalia SRL and LJ Pharma SRL. M. San-
tonocito acknowledges the support of the EMBO-European Molecular Biology Organization Germany and Ente Regionale per il diritto allo Studio Uni-
versitario for the assignment of a fellowship that allowed her to perform the experiments on exosome isolation and characterization with Dr. Hadi
Valadi's group at the University of Gothenburg, Sweden.
Reprint requests: Cinzia Di Pietro, Ph.D., Department Gian Filippo Ingrassia, Biologia Cellulare e Molecolare, Genetica, Genomica Giovanni Sichel, Universit
a
di Catania, Via Santa Sofia 87, Comparto 10, Edificio C, 95123 Catania, Italy (E-mail: dipietro@unict.it).
Fertility and Sterility® Vol. -, No. -,-2014 0015-0282/$36.00
Copyright ©2014 American Society for Reproductive Medicine, Published by Elsevier Inc.
http://dx.doi.org/10.1016/j.fertnstert.2014.08.005
VOL. -NO. -/-2014 1
ORIGINAL ARTICLE: REPRODUCTIVE BIOLOGY
Conclusion(s): This study identified a series of exosomal microRNAs that are highly repre-
sented in human FF and are involved in follicular maturation. They could represent noninvasive
biomarkers of oocyte quality in assisted reproductive technology. (Fertil Steril
Ò
2014;-:-–-.
Ó2014 by American Society for Reproductive Medicine.)
Key Words: Follicular fluid, exosomes, microRNA profile, intrafollicle molecular
communication
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MicroRNAs (miRNAs) are small, noncoding RNAs
that repress gene expression by targeting specific
mRNAs, most commonly in their 30untranslated
region. Accordingly, they play a very important role in
post-transcriptional gene regulation (1). miRNAs regulate
the activity of most protein-coding genes; a single miRNA
may target hundreds of mRNAs, while a specific mRNA mole-
cule may be regulated by several different miRNAs (1, 2).
Many miRNAs have been conserved throughout evolution
and perform important roles in cell differentiation and the
development of invertebrates, plants, and animals,
including humans (1, 2). Over the past few years it has
become evident that alterations of their expression are
important in the pathogenesis of human diseases such as
cancers and degenerative diseases (2, 3). Another avenue of
current research is the study of circulating miRNAs in body
fluids. It has been demonstrated that miRNAs are present in
most (if not all) biological fluids, such as serum, plasma,
saliva, urine, and breast milk (2, 4). In these fluids, miRNAs
display remarkable stability and resistance to degradation,
possibly because of their association with protein
complexes (e.g., argonaute RISC catalytic component 2,
nucleophosmin [nucleolar phosphoprotein B23, numatrin])
or because they are enclosed within membrane-bound nano-
vesicles, termed exosomes (5). Exosomes are vesicles of endo-
cytic origin between 30 and 100 nm in diameter; they are
formed through inward budding of endosomal membranes,
which gives rise to intracellular multivesicular bodies. These
later fuse with the plasma membrane and release the intralu-
menal vesicles into the extracellular environment as exo-
somes (5). Their unique chemical composition enables
exosome identification; specifically, tetraspanins such as
CD9, CD63, CD81, and CD82 are defined exosomal marker
proteins (6, 7). Recent studies have demonstrated that
exosomes are bioactive vesicles that promote intercellular
communication by shuttling proteins, mRNAs, and miRNAs
among cells (5, 8). The discovery that miRNAs might act
not only within cells but also may be involved in
intercellular communication led to the hypothesis that
miRNAs could represent the oldest hormones (2). Similar to
cellular miRNAs, the profiles of circulating miRNAs may be
associated with specific diseases. Accordingly, their role as
noninvasive biomarkers of pathologies and also as
potential targets of therapy has been investigated in
different neoplastic and degenerative diseases (e.g., colon
cancer, diabetes mellitus) (9, 10). Follicular fluid (FF)
consists of a complex mixture of nucleic acids, proteins,
metabolites, and ions, which are secreted by the oocyte,
granulose, and thecal cells; it also comprises plasma
components that cross the blood-follicle barrier via thecal
capillaries (11, 12). It represents a critically important
microenvironment for the development of oocytes: its
biochemical composition, related to the metabolic activity
of ovarian cells, reflects the physiological status of the
follicle. It is common opinion that the analysis of FF
components may provide useful information on oocyte
quality and the pathways involved in follicle differentiation
and development (11). The discovery of FF miRNAs could
open up the possibility to use these molecules as
biomarkers of oocyte quality. Some recent papers
demonstrated the presence of miRNA in FF in human and
in animal models, but they did not show their exact origin
and the role that they could perform inside ovarian follicles
(13–15). The aims of this paper were [1] to find well-
represented miRNAs in human FF whose detection was not
affected by plasma or cellular contamination; and [2] to
ascertain whether these miRNAs could regulate biologically
important pathways inside follicular cells. To identify upre-
gulated miRNAs in FF, we compared by real-time reverse
transcriptase–polymerase chain reaction (PCR) the expres-
sion profile of 384 miRNAs from FF and plasma collected
from the same women. We then isolated nanosized vesicles
and their miRNA cargo from FF and confirmed that [1] they
showed surface exosomal markers; [2] they carried miRNAs
upregulated in total FF. By using a computational approach,
we verified that nine FF miRNAs are able to regulate path-
ways involved in follicular maturation. We propose that the
identified miRNAs perform an important role inside ovarian
follicles and that their altered expression could be associated
with reproductive disorders, as has been demonstrated for
intracellular ovarian miRNAs (16). Accordingly, we propose
that these miRNAs represent useful new molecular markers
of oocyte quality.
MATERIALS AND METHODS
Patients
FF and plasma samples were collected from 15 healthy
women selected by an IVF center (Servizio di PMA, Azienda
Ospedaliera Cannizzaro, Catania) who had undergone intra-
cytoplasmic sperm injection. We selected women younger
than 35 years whose primary infertility was due to a male
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ORIGINAL ARTICLE: REPRODUCTIVE BIOLOGY
factor; this excluded pathologies that could influence oocyte
quality (e.g., endometriosis, polycystic ovaries, and ovarian
insufficiency). Moreover, we excluded from the study heavy
smokers and overweight women. Among the 15 enrolled
women, there were six pregnancies: two miscarriages and
five live births (one twin birth). The patients signed an
informed consent to participate in the research project, which
included the use of collected FF and plasma. The study was
exempted from Institutional Review Board approval because
patients were included in the IVF program. Accordingly,
there were no identifiers linking individuals to the samples
and no additional treatment or use of personal data was
necessary.
Ovarian Stimulation and Sample Collection
Hormone stimulation was performed by treatment with
GnRH agonists (triptorelin or buserelin), followed by ovarian
stimulation with recombinant FSH and hMG. Stimulation
was monitored using both serum and E
2
concentrations as
well as ultrasound measurements of follicle numbers and di-
ameters. When follicles had reached a diameter >18 mm and
serum E
2
concentration per follicle reached 150–200 ng/L,
ovulation was induced with 10,000 IU of hCG. Transvaginal
ultrasound–guided aspiration of ovarian follicles was per-
formed 34–36 hours after hCG injection. FF samples were
centrifuged for 200at 2,800 rpm at 4C to remove follicular
cell residues and any blood traces; the supernatant was
immediately transferred into a clean polypropylene tube
and stored at 20C for further analysis. Samples with
massive blood contamination were excluded from further
analysis. Blood samples were collected in commercially
available EDTA-containing tubes. Cells were removed from
plasma by centrifugation for 100at 1,800 rpm at 4C. The
resulting supernatant was immediately transferred into a
clean polypropylene tube using a Pasteur pipette and stored
at 20C. We recovered about 20 mL of FF from each
woman. FF of individual follicles was kept separated until
decumulation of the oocytes to collect only the FF in which
nuclear mature oocytes (metaphase II) had been identified. To
obtain a homogenous pool of samples, 18 mL of FF from
each woman was mixed and 270 mL of pooled FF was
obtained. We used three aliquots of 400 mL for miRNA puri-
fication from total FF, while two aliquots of 120 mL for exo-
some characterization and exosomal miRNA purification.
From the same cohort of 15 women, 5 mL of blood from
each woman was collected, 2 mL of plasma was obtained,
and 1 mL was used to make a pool of 15 mL. We used three
aliquots of 400 mL for miRNA purification.
Exosome Purification and Characterization
FF exosomes were isolated and characterized according to a
previously published protocol with minor modifications
(17). Two different isolations were performed: the first for
exosome molecular characterization and the second for
miRNA extraction. For each, a volume of 120 mL of pooled
samples from the 15 women was aliquoted in 50-mL tubes
and centrifuged at 3,000 rpm for 15 minutes at 4C to pellet
debris. The supernatant was transferred to ultracentrifuge
tubes and ultracentrifuged at 16,500 gfor 30 minutes at
4C, followed by filtration through a 0.2-mm syringe filter.
Finally, exosomes were pelleted by ultracentrifugation at
120,000 gfor 70 minutes at 4C in a Beckman Optima
L-100 XP ultracentrifuge using a Ti70 rotor (Beckman
Coulter). Exosome pellets were resuspended in Trizol (Invitro-
gen) for RNA isolation or in phosphate-buffered saline (PBS)
for nanosight and fluorescence-activated cell sorter analysis.
For the nanoparticle tracking analysis (NTA), samples were
diluted with sterile PBS following the manufacturer's instruc-
tions. Samples (approximately 300 mL) were injected into the
LM10 unit with a 1-mL sterile syringe. Capturing and
analyzing settings were manually set according to the proto-
col. Using the NanoSight LM10 instrument, vesicles were
visualized by laser light scattering, and Brownian motion of
these vesicles was captured on video. The number of tracks al-
ways exceeded 200, and five size distribution measurements
were taken for each sample. Recorded videos were then
analyzed with NTA software, which provided high-
resolution particle size distribution profiles and concentration
measurements of the vesicles in solution. Flow cytometry
analysis was performed according to a previously published
protocol (18). Aldehyde/sulfate latex beads of 4 mm (Invitro-
gen) were serially diluted with PBS to reach a final concentra-
tion of 2,900 beads/mL. Vesicles from FF samples were
incubated with 25 mL of diluted latex beads at 37C for 30 mi-
nutes and then overnight at 4C with gentle agitation. After
one wash in PBS, exosome-coated beads were incubated
with 20 mL 1 M glycine (Sigma-Aldrich) for 30 minutes at
20C to block any remaining available binding sites. After
two washes in PBS with 1% fetal bovine serum (FBS),
exosome-coated beads were stained with phycoerythrin-
(PE-) conjugated CD63, CD81, or CD9 antibodies or isotype
control (BD Biosciences Pharmingen) and incubated for
1 hour at 4C with gentle agitation. After the third wash in
PBS/FBS 1% solution, samples were resuspended in PBS
and analyzed on FACSCantoII (Becton Dickinson) with
FlowJo software (TreeStar, Inc.).
miRNA Isolation
All experiments were performed in triplicate. Three aliquots of
400 mL of FF and plasma samples were thawed completely on
ice. miRNA isolation was performed by using a Qiagen miR-
Neasy Mini Kit (Qiagen GmbH), according to the Qiagen Sup-
plementary Protocol for the purification of small RNAs from
serum and plasma and finally eluted in a 30-mL volume of
elution buffer. Total RNA was isolated from three aliquots
of FF exosomes using Trizol reagent (Invitrogen), according
to the manufacturer's instructions. Before precipitating the
RNA with isopropyl alcohol, 20 mg RNase-free glycogen (In-
vitrogen) as carrier was added to the aqueous phase and the
samples were stored for 16 hours at 80C. RNA pellets
were dissolved in RNase-free water. Detection and quality
control of RNA were performed using an Agilent 2100 Bio-
analyzer (Agilent Technologies Sweden AB) and 2100 Expert
software.
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Reverse Transcription, Preamplification and
MicroRNA Profiling
Expression profiles of 384 miRNAs were investigated by using
TaqMan low-density array technology (Applied Biosystems)
in a 7900HT fast real time PCR system (Applied Biosystems).
This technology is highly specific, and it allows the amplifica-
tion of only mature miRNAs (19).
RNA (3 mL of each sample) was reverse-transcribed (RT)
by using the TaqMan MicroRNA Reverse Transcription Kit
and Megaplex RT Primer Pool A (Applied Biosystems). Four
microliters of RT products were preamplified with TaqMan
PreAmp Master Mix 2and Megaplex PreAmp Primers
Pool A (Applied Biosystems). Preamplification products
were subsequently diluted in 75 mL of RNase free purified wa-
ter. Nine microliters of each amplified product was mixed
with Universal Master Mix II, no uracil-N glycoslyase
(Applied Biosystems), and loaded into TaqMan Human Micro-
RNA Array A cards (Applied Biosystems), according to the
manufacturer's instructions.
Expression Data Analysis
Housekeeping gene detection. No data are available on reli-
able reference genes to be used for miRNA normalization in
FF. Accordingly, we used DataAssist version 3 software
(Applied Biosystems) and the geNorm algorithm (http://
medgen.ugent.be/jvdesomp/genorm/) to identify appro-
priate endogenous controls. GeNorm is based on the geomet-
ric average of multiple internal control genes, and it is
especially useful for normalization of data from a large and
unbiased set of genes (e.g., miRNA expression profiling) (20,
21). DataAssist is a data analysis tool that is useful to
compare samples when using the comparative CT (DDCT)
method for calculating relative quantitation of gene
expression. In a first step, three miRNAs common to two
programs and having a low score in both (the lower the
score, the better the normalization) were selected as
housekeeping genes. The miRNAs miR-25, miR-28-3p, and
miR-145 were identified for comparison between FF and
plasma, and miR-126, miR-28-3p, and miR-145 were identi-
fied for exosomes versus plasma. The DCt values were
independently calculated by using the three selected house-
keeping genes, for each sample.
Identification of differentially expressed miRNAs. To iden-
tify differentially expressed (DE) miRNAs, three different
significance analysis of microarrays (SAM; http://www.
tm4.org) tests (Tusher, 5th percentile and minimum S value)
were used, applying a two-class unpaired test among DCt
and using a Pvalue based on all possible permutations:
imputation engine, K-nearest neighbors (10 neighbors); false
discovery rate, <.05. We considered as DE miRNAs only
those with three housekeeping genes in common after at least
two SAM tests.
Relative quantification and selection of upregulated
miRNAs. The DCt values of DE miRNAs were used to calcu-
late relative quantity (RQ) values as a natural logarithm of
2
DDCt
and the average of DCt of each plasma sample as cali-
brator. miRNAs with a natural logarithm of RQ values R2.5
were considered as upregulated (highly expressed) in FF or
exosomes compared with plasma. For each DE miRNA, nine
RQ values (three for each housekeeping gene) were obtained
that were reciprocally comparable, and RQ values obtained
with the housekeeping miR145 were used to perform addi-
tional statistical analysis according to Livak and Schmittgen
(22). The mean fold change was calculated as a natural loga-
rithm of RQ values, and the error was estimated by evaluating
the 2
DDCt
equation using DDCt plus SD and DDCt minus
SD (22).
miRNA Target Prediction
Targets of upregulated miRNAs were explored by using a
combination of different approaches. By interpolation among
the highest numbers of 11 prediction tools, the first series of
experimentally validated and predicted targets were extracted
from miRecords (http://mirecords.biolead.org)(23).To
improve prediction, TarBase, version 5.0 (http://www.dia
na.pcbi.upenn.edu/tarbase), and miRTarBase, version 3.5
(http://mirtarbase.mbc.nctu.edu.tw), were also used. These
are two databases that have accumulated more than 50,000
experimentally supported targets. An additional filtering
was performed by using starBase, version 2.0, a database
for predicted miRNA-target interactions that are overlapped
with data from Argonaute cross-linked immunoprecipita-
tion-sequencing (CLIP-Seq; http://starbase.sysu.edu.cn).
CLIP-Seq experiments are based on cross-linking between
RNA and proteins, followed by immunoprecipitation coupled
with high-throughput sequencing. The application of this
technique is useful for the identification of miRNA binding
sites. Finally, our list was enriched by retrieving from the
literature specific information on validated miRNA targets.
Gene Ontology (GO) and Pathway Analysis
The analysis was independently performed on miRNAs upre-
gulated in total FF and miRNAs upregulated in exosomes. The
GO functional classification of miRNA targets was focused
on the biological processes, in which target mRNAs are
involved. For this analysis, the g:GOSt (GO statistics) tool
of g:Profiler (http://biit.cs.ut.ee/gprofiler/) was used and
Bonferroni correction for a Pvalue of .05 was applied.
Pathway analysis was performed by using the prediction soft-
ware DIANA-microT-4.0 (beta version; http://diana.cslab.
ece.ntua.gr/pathways/). DIANA-miRPath uses miRNA targets
that have been predicted with high accuracy based on
DIANA-microT-CDS. In our analysis, we input upregulated
miRNAs, and the software performs an enrichment analysis
of multiple miRNA targets genes comparing the set of miRNA
targets to all known KEGG pathways. It retrieved signaling
pathways enriched with gene targets of the miRNAs sorting
them by Pvalues (P-value threshold .05 and microthreshold
0.8) (24).
RESULTS
Exosome Characterization and miRNA Isolation
The nanovesicles isolated from human FF had an average
size of 40 nm in diameter, which is consistent with the
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ORIGINAL ARTICLE: REPRODUCTIVE BIOLOGY
characteristic size range of exosomes (25) (Fig. 1A). More-
over, our samples were positive for the tetraspanin proteins
CD63 and CD81, which are known to be enriched in exo-
somes (25) (Fig. 1B). RNAs isolated from exosomes were
small-sized RNAs and lacked bands corresponding to
cellular 18S and 28S ribosomal RNAs (Fig. 1C).
Expression Profile of mRNAs
We identified 37 miRNAs upregulated in human FF compared
with in plasma (Fig. 2). Specifically, 15 miRNAs were found to
be upregulated in total FF compared with in plasma; 10 miR-
NAs were carried by exosomes, while five were not (Fig. 2).
Twenty-two miRNAs were present exclusively in exosomes.
FIGURE 1
Characterization of exosomes. (A) Nanoparticle tracking measurement of particle size and concentration. Pelleted fractions from FF are vesicles
whose diameter size ranged from 10 to 100 nm, with a peak size between 30 and 50 nm. Average vesicle size was 40 nm. Particle size is
consistent with exosome size range. Error bars represent SDs obtained from five measurements of the same sample. (B) Flow cytometry
detection of surface molecules on exosomes from FF. Exosomes, bound to latex beads, were immunostained by using monoclonal antibodies
against the tetraspanins CD9, CD63, and CD81 and analyzed by flow cytometry. The antibodies were compared with their appropriate isotype
control IgG1. FF exosomes were positive for CD63 and CD81. (C) Exosomal RNA analyzed using a Bioanalyzer. RNA pattern, isolated from FF
exosomes, is visualized in Bioanalyzer as electrophoretic data and a gel-like image. The results show that exosomes are enriched in small RNAs
and contain no 18S and 28S ribosomal RNAs. Abbreviations: SSC-H ¼side scatter height; FU ¼fluorescence; nt ¼nucleotides.
Santonocito. Exosomal microRNAs in human follicular fluid. Fertil Steril 2014.
VOL. -NO. -/-2014 5
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FIGURE 2
MicroRNA expression in total FF and exosomes compared with plasma. Black bars show the 10 upregulated miRNAs in total FF and in exosomes.
Gray bars represent five upregulated miRNAs exclusively in the total FF, and light gray bars represent 22 upregulated miRNAs in exosomes only. Fold
change is shown as the natural logarithm of RQ values, which were calculated through the 2
DDCt
method (by using miR-145 as an endogenous
control and plasma as the calibrator sample) and respective SD values.
Santonocito. Exosomal microRNAs in human follicular fluid. Fertil Steril 2014.
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They were undetectable in total FF because their relative con-
centration was higher in purified exosomes compared with
total FF (Fig. 2). The five miRNAs detected only in total FF
and absent in exosomes could be free circulating miRNAs
associated with protein complexes (Fig. 2). Interestingly,
miR-508-3p, whose fold change value was among the high-
est, seems to be follicle specific, since we could not detect it
in plasma (Fig. 2). Among the 37 miRNAs previously cited,
we found miR-10b, miR-29a, miR-99a, miR-125b, miR-132,
miR-202, miR-212, and miR-874, which had been reported
to be highly expressed in granulose or in cumulus cells in hu-
mans and in mice (26–28).
Genomic Analysis
Genomic analysis showed that 22 miRNAs (miR-29a, miR-99a,
miR-100, miR-125b, miR-132, miR-134, miR-193b,miR-203,
miR-212, miR-214, miR-323-3p, miR-337-5p, miR-365,
miR-370, miR-410, miR-449a, miR-489, miR-493, miR-503,
miR-508-3p, miR-542-5p, and miR-654-3p) are localized in
13 different clusters; a number of the upregulated miRNAs
were part of the same cluster (Supplemental Table 1). Interest-
ingly, miR-134, miR-323-3p, miR-410, and miR-654-3p were
localized within the large miR-379/miR-656 cluster, which is
exclusively present in placental mammals and involvedin em-
bryonic development (29). We found that genes encoding 13
miRNAs were located inside genes encoding proteins, while
those for the other 24 miRNAs were located in extragenic re-
gions or inside noncoding genes (Supplemental Table 1).
GO and Pathway Analysis
GO analysis of validated and predicted targets was indepen-
dently performed on miRNAs upregulated in total FF and
miRNAs upregulated in exosomes. GOs were used to func-
tionally categorize miRNA target genes that were identified
in a range of biological processes. The GO terms ranged
from one to three levels of detail, and only significant GO
terms are reported. The maximum Pvalue was .048.
Figure 3A shows the significant GOs, and in the x-axis the
negative log
10
(Pvalue) is reported. The most significant bio-
logical processes involving the targets of our upregulated
miRNAs are developmental, regulation of cellular process,
cell differentiation, and cell communication (Fig. 3A).
Pathway analysis showed that WNT, MAPK, ErbB, and
TGFbsignaling pathways, which are shared by total FF and
exosome miRNAs, are the most significant, with a negative
log
10
(Pvalue) between 11.04 and 4.12 (Fig. 3B). Figure 3C
specifically shows the miRNAs involved in the regulation of
the significant pathways presented in Figure 3B. It can be
observed that WNT and MAPK signaling pathways are clearly
targeted by most miRNAs with a very small Pvalue. On the
other hand, it can be seen that some miRNAs (e.g., miR-132,
miR-212, and miR-214) could regulate at least eight different
FIGURE 3
GO analysis based on highly expressed miRNA targets and heat-map representations of signaling pathways. (A) GO terms within the biological
process category for highly expressed miRNA targets in total FF (red bars) and in exosomes (blue bars) are shown. The x-axis represents the
log
10
(Pvalue); the significance was determined by the adjusted Bonferroni correction. (B) Signaling pathway heat map regulated by total FF
and exosomal miRNAs. Gray boxes indicate that the pathway is not significant. (C) miRNAs versus pathways. The probability values are reported
as log
10
(Pvalue) for both panels. Abbreviations: EXO ¼exosomes; P ¼plasma.
Santonocito. Exosomal microRNAs in human follicular fluid. Fertil Steril 2014.
VOL. -NO. -/-2014 7
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pathways (Fig. 3C). To perform a more accurate analysis, our
computational approach was validated using literature data.
Its application confirmed that miR-29a, miR-99a, miR-100,
miR-132, miR-212, miR-214, miR-218, miR-508-3p, and
miR-654-3p are particularly interesting. In fact, their expres-
sion inside granulose or cumulus cells and their regulatory
role were demonstrated by their targeting mRNAs involved
in ovarian physiology and pathology (14, 26–41).
DISCUSSION
In this paper, we describe the identification of 37 miRNAs up-
regulated in human FF compared with plasma; our data
demonstrate that 32 of them are carried by exosomes
(Fig. 2). In fact, the average size of isolated microvescicles
was 40 nm in diameter, and they were positive for the tetra-
spanin proteins CD63 and CD81, which are known to be en-
riched in exosomes (Fig. 1A and B). The absence of marker
CD9 could be due to the fact that exosomes may express
different surface markers, based on their cellular source of
origin and their specific physiological state (6, 17). The
presence of miRNAs within FF vesicles was recently
described in humans and in animal models, but no data
were presented to support their identification as exosomes;
furthermore, absence of miRNA target identification
precluded characterization of downstream networks and
corresponding biomolecular functions (13–15). We studied
miRNAs upregulated in FF compared with plasma; this
allowed us to hypothesize that they were not released by
blood cells but specifically by ovarian follicle cells. The
presence of exosome miRNAs means that an unexplored
communication tool could exist inside ovarian cells. By
applying many different computational tools, we performed
multiple searches in public databases and literature data to
confirm that identified miRNAs could carry out their
biological role inside ovarian follicles. This approach
allowed us to confirm that miR-29a, miR-99a, miR-100,
miR-132, miR-212, miR-214, miR-218, miR-508-3p, and
miR-654-3p are novel molecular regulators of ovarian follicle
pathways. In fact, as we will explain more in detail later, some
of these miRNAs or their host genes are expressed in granulose
or cumulus cells, and some of their validated targets per-
formed their role inside follicular cells (26–41). Genomic
analysis showed that some miRNAs belong to the same
cluster, supporting the fact that they are all highly
expressed in FF at the same time (Supplemental Table 1). In
fact, clustered miRNAs arise from a common primary
transcript and are expected to have similar expression
profiles. Interestingly, miR-132 and miR-212, located in a
cluster at 17p13.3, were found highly upregulated in mouse
mural granulose cells after LH/hCG induction (26). In addi-
tion, intronic miRNAs are usually expressed together with
the host gene: miR-218 is located within the slit homolog 2
(Drosophila, SLIT2) gene, which encodes the secreted SLIT
glycoprotein roundabout (ROBO) receptors ligand. SLIT and
ROBO have been proposed to be regulated by steroid hor-
mones and to modulate physiological cell functions in the
ovary (39). GO and pathway analysis demonstrated that the
targets of upregulated miRNAs could perform their role inside
ovarian follicles during follicular maturation. In fact, we iden-
tified biological processes involved in development, in cell
differentiation, and in cell communication (Fig. 3A). We
found that most of the upregulated miRNAs are involved in
the regulation of the WNT, MAPK, ErbB, and TGFbsignaling
pathways (Fig. 3B and C). These pathways have been described
inside the different cell compartments of the ovarian follicle
and perform a critically important role for follicular develop-
ment, meiotic resumption, and subsequent ovulation (42–45).
WNT proteins are secreted extracellular signaling molecules
that activate the G protein–coupled receptors Frizzled (Fz). It
has been demonstrated that WNTs and Fz are expressed at
specific stages of follicular growth and luteinization, and
their role could be important for the growth and
development of ovarian follicles (42). The MAPK pathway,
activated by FSH and LH trigger, stimulates granulose cell
proliferation and cumulus expansion (43). Its activation in
cumulus cells appears to require the permissive effect of
TGFbfamily factors produced by the oocyte, such as growth
differentiation factor 9 and bone morphogenetic protein 15.
On the other hand, the MAPK pathway and the ErbB
pathway promote meiosis resumption in the oocyte by a
decrease of cAMP (44, 45). The outcome of the complex
interaction among the different molecules involved in these
pathways is the elimination of meiosis-inhibiting factors
and/or the accumulation or activation of oocyte maturation
signals (44). Interestingly, we found that miR-29a, miR-99a,
miR-100, miR-132, miR-212, miR-214, miR-218, miR-508-
3p, and miR-654-3p could trigger meiosis resumption by
negatively regulating genes encoding for follicle maturation
inhibiting factors (46, 47) (Fig. 4). We present a schematic
view of the pathways inside follicular cells and oocytes, and
we pinpoint where our miRNAs could perform their action
(Fig. 4).
miR-132, miR-212, and miR-214 have phosphatidylino-
sitol 3,4,5-trisphosphate 3-phosphatase (PTEN) as a validated
target (37, 38). PTEN performs an important role in the
regulation of primordial follicle survival and activation,
cyclic follicular recruitment, ovulation, and meiosis
resumption; nevertheless, the inhibitory mechanisms that
are involved in PTEN silencing remain unknown (47). Our
miRNAs represent the best candidates for its silencing and
the resulting MAPK activation mediated by v-akt murine
thymoma viral oncogene homolog 1 (AKT1). Intriguingly, in
ovarian cancer, miR-214 induces cell survival and cisplatin
resistance by targeting PTEN (38). Deregulation of PTEN in-
hibitors could be associated with reproductive disorders, as
it has been shown that PTEN knockout mice exhibit follicular
depletion in young adulthood and polycystic ovarian failure
(48). It was recently demonstrated that PTEN downregulation
may inhibit the formation of polycystic ovaries in a rat model
(49). Moreover, PTEN inhibition by miR-132, miR-212, and
miR-214 could be used as a potential tool to trigger the acti-
vation and enhance the survival rate of primordial follicles in
cultured ovarian cortical tissue in vitro (50).
Mechanistic target of rapamycin (MTOR) is a validated
target of miR-99a and miR-100, and tuberous sclerosis 1
(TSC1) is a predicted target of miR-508. The altered regulation
of miR-99a (in cluster with let-7c, which is highly expressed
8VOL. -NO. -/-2014
ORIGINAL ARTICLE: REPRODUCTIVE BIOLOGY
in cumulus cells [27]), and miR-100 is involved in ovarian
cancer through MTOR regulation (33, 34). MTOR inhibition,
one of the necessary steps for follicular maturation, could
be mediated by these miRNAs (47). miR-654-3p inhibits
cyclin-dependent kinase inhibitor 1 (P21), a negative regu-
lator of cell cycle progression (40). It has been demonstrated
that P21 inhibition induces oocyte maturation (41). Another
brake for cell cycle progression and meiosis resumption is
FIGURE 4
Ovarian follicle, signaling pathways, and FF miRNAs. Model summarizing crucial LH- and FSH-induced signaling pathways resulting in oocyte
meiosis resumption. Hormone-receptor binding activates the AKT,PKA, and MAPK pathways and then induces the EGF-like factors' expression
in granulosa cells. EGF-like factors act on EGFR to activate the RAS-MAPK pathway, contributing to phosphorylation of Cx-43 and the resulting
decrease in gap junction permeability. These events would reduce NPR2 activity, induce PDE1 activation, and decrease cGMP levels in oocytes.
Within the oocyte, activated PDE3A degrades cAMP and meiosis resumes. Identified miRNAs could act along these pathways and regulate the
processes of follicular development and meiotic resumption. Abbreviations: FSHR ¼FSH receptor; LHR ¼LH receptor; AC ¼adenylate cyclase;
cAMP ¼cyclic adenosine 30,50-monophosphate; PKA ¼cAMP-dependent protein kinase; CREB ¼cAMP responsive element binding protein;
MAPK ¼mitogen-activated protein kinase; EGF ¼epidermal growth factor; EGFR ¼EGF receptor; PI3K ¼phosphatidylinositol 3 kinase; PIP2 ¼
phosphatidylinositol 4, 5-bisphosphate; PIP3 ¼phosphatidylinositol-3,4,5-trisphosphate; AKT ¼v-akt murine thymoma viral oncogene
homolog (also known as PKB); CDK ¼cyclin-dependent kinase; E2F ¼E2F transcription factor; PLC ¼phospholipase C; IP3 ¼inositol 1,4,5-
trisphosphate; DAG ¼1,2-diacylglycerol; PKC ¼protein kinase C; Cx-43 ¼connexin 43; NPR2 ¼natriuretic peptide receptor B/guanylate
cyclase B; cGMP ¼cyclic guanosine 30,50-monophosphate; PDE3A ¼phosphodiesterase 3A, cGMP-inhibited.
Santonocito. Exosomal microRNAs in human follicular fluid. Fertil Steril 2014.
VOL. -NO. -/-2014 9
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represented by retinoblastoma protein (RB1). We found
that miR-132 and miR-212 have as a validated target this
tumor suppressor (36) (Fig. 4). We found that DNA
(cytosine-5-)-methyltransferase 3 alfa (DNMT3A) and DNA
(cytosine-5-)-methyltransferase 3 beta (DNMT3B) are regu-
lated by miR-29a and miR-132 (30, 37), both of which are
found highly expressed in granulose and cumulus cells (26,
27). It is known that DNA methylation establishment is
dynamically controlled during oocyte growth and that it
may contribute to gene regulation in the oocyte by marking
specific genes for activity in the embryo (51). DNMT3
silencing, mediated by miR-29a and miR-132, could explain
the hypomethylation found in preimplantation embryos and
also in the inner-cell mass (52). Recent studies have suggested
a link between the use of assisted reproductive technology
(ART) and the increased incidence of normally rare imprinting
disorders (52). In agreement with literature data about the
complexity of gene expression regulation mediated by miR-
NAs, we found that several miRNAs could act on the same
mRNA (e.g., miR-132, miR-212, and miR214 are able to regu-
late PTEN) and that a single miRNA may target different
mRNAs (miR-132 is able to regulate PTEN, RB1, and
DNMT3A; Fig. 4). We propose that identified miRNAs are syn-
thesized by ovarian follicle cells and that they could be trans-
ferred to recipient cells through FF exosomes. It is known that
exocytosis and endocytosis mechanisms have been described
in granulose cells and oocytes (53–56), but further studies are
necessary to identify specific exosome surface markers able to
discriminate the vesicles released by somatic follicular cells or
by the oocyte and to ascertain whether their cargo acts in an
autocrine or paracrine manner.
Conclusions
This study identified exosomal miRNAs highly represented in
human FF and involved in the regulation of ovarian follicular
pathways. We believe that, as it has been demonstrated for
intracellular ovarian miRNAs, their altered expression could
be associated with reproductive disorders. We propose that
these miRNAs could represent noninvasive molecular
markers of oocyte quality in ART.
Acknowledgments: The authors thank Professor Antony
Bridgewood for language revision of the manuscript.
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SUPPLEMENTAL TABLE 1
Upregulated FF miRNAs and their genomic localization.
Extragenic miRNAs
a
miRNAs located in protein encoding genes
miRNA Chromosomal position Clustered miRNAs miRNA Chromosomal position Clustered miRNAs Host gene
miR-886-5p 5q31.1 miR-214 1q24.3 miR-199a-2
miR-3120
DNM3
miR-339-3p 7p22.3 miR-135b 1q32.1 LEMD1
miR-29a 7q32.3 miR-29b-1 miR-10b 2q31.1 HOXD3
miR-31 9p21.3 miR-95 4 ABLIM2
miR-202 10q26.3 miR-218 4p15.31 SLIT2
miR-210 11p15.5 miR-449a 5q11.2 miR-449b
miR-449c
CDC20 B
miR-100 11q24.1 let-7a-2 miR-887 5p15.1 FBXL7
miR-125b 21q21.1 miR-99a
miR-125b
let-7c
miR-874 5q31.2 KLHL3
miR-99a miR-489 7q21.3 miR-653 CALCR
miR-134 14q32.31 Cluster
miR-379/miR-656
miR-204 9q21.12 TRPM3
miR-323-3p miR-455-5p 9q32 COL27A1
miR-410 miR-483-5p 11p15.5 IGF2
miR-654-3p miR-140-3p 16q22.1 WWP2
miR-203 14q32.33 miR-203b
miR-203a
miR-337-5p 14q32.2 miR-493
miR-665
miR-431
miR-433
miR-127
miR-432
miR-337
miR-370
miR-493
miR-193b 16p13.12 miR-365a
miR-193bmiR-365
miR-212 17p13.3 miR-132
miR-212miR-132
miR-503 Xq26.3 miR-450a-2
miR-542
miR-450a-1
miR-450b
miR-503
miR-424
miR-542-5p
miR-508-3p Xq27.3 miR-507
miR-506
a
Or located in noncoding genes.
Santonocito. Exosomal microRNAs in human follicular fluid. Fertil Steril 2014.
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