microRNA-based signatures obtained from endometrial fluid identify implantative endometrium

microRNA-based signatures obtained from endometrial fluid identify implantative endometrium Jone Iba~ nez-Perez 1,2,3,4 , Mar ıa D ıaz-Nu~ nez 1,2 , Marc Clos-Garc ıa 5 , Luc ıa Lainz 1,2 , Mar ıa Iglesias 1,2 , Miren D ıez-Zapirain 1,2 , Aintzane Rabanal 1,2 , Laura Ba´rcena 6 , Monika Gonza´lez 6 , Juan J. Lozano 7 , Urko M. Marigorta 8,9 , Esperanza Gonza´lez 4 , Fe´lix Royo 4,10 , Ana M. Aransay 6,10 , Nerea Subiran 2,11 , Roberto Matorras 1,2,3,12, *, and Juan Manuel Falco´n-Pe´rez 4,9,10,13, * 1 Human Reproduction Unit, Cruces University Hospital, University of the Basque Country (UPV/EHU), Barakaldo, Spain 2 Innovation in Assisted Reproduction Group, Biocruces Bizkaia Health Research Institute, Cruces University Hospital, Barakaldo, Spain 3 Department of Obstetrics and Gynecology, University of the Basque Country (UPV/EHU), Leioa, Spain 4 Exosomes Laboratory, CIC bioGUNE-BRTA, Derio, Spain 5 Novo Nordisk Foundation Center for Basic Metabolic Research (CBMR), Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark 6 Genome Analysis Platform, CIC bioGUNE-BRTA, Derio, Spain 7 Bioinformatics Platform, Centro de Investigacio´n Biome´dica en Red de Enfermedades Hepa´ticas y Digestivas (CIBERehd), Madrid, Spain 8 Integrative Genomics Lab, CIC bioGUNE-BRTA, Derio, Spain 9 IKERBASQUE, Basque Foundation for Science, Bilbao, Spain 10 Centro de Investigacio´n Biome´dica en Red en el A ´rea tema´tica de Enfermedades Hepa´ticas (CIBEReh), Madrid, Spain 11 Department of Physiology, Faculty of Medicine and Dentistry, University of the Basque Country (UPV/EHU), Leioa, Spain 12 Instituto Valenciano de Infertilidad (IVI) Bilbao/IVIRMA, Leioa, Spain 13 Metabolomics Platform, CIC bioGUNE-BRTA, Derio, Spain *Correspondence address. Human Reproduction Unit, Cruces University Hospital, University of the Basque Country (UPV/EHU), Barakaldo, Spain; E-mail: josero[email protected] (R.M.) https://orcid.org/0000-0002-4279-6823; Exosomes Laboratory, CIC bioGUNE-BRTA, Derio, Spain; E-mail: [email protected] (J.M.F.-P.) https://orcid.org/0000-0003-3133-0670 Submitted on September 30, 2021; resubmitted on August 2, 2022; editorial decision on August 9, 2022 STUDY QUESTION: Is it possible to use free and extracellular vesicle-associated microRNAs (miRNAs) from human endometrial fluid (EF) samples as non-invasive biomarkers for implantative endometrium? SUMMARY ANSWER: The free and extracellular vesicle-associated miRNAs can be used to detect implantative endometrium in a noninvasive manner. WHAT IS KNOWN ALREADY: miRNAs and extracellular vesicles (EVs) from EF have been described as mediators of the embryo–endometrium crosstalk. Therefore, the analysis of miRNA from this fluid could become a non-invasive technique for recognizing implantative endometrium. This analysis could potentially help improve the implantation rates in ART. STUDY DESIGN, SIZE, DURATION: In this prospective study, we first optimized different protocols for EVs and miRNA analyses using the EF of a setup cohort (n ¼72). Then, we examined differentially expressed miRNAs in the EF of women with successful embryo implantation (discovery cohort n ¼15/validation cohort n ¼30) in comparison with those for whom the implantation had failed (discovery cohort n ¼15/validation cohort n ¼30). Successful embryo implantation was considered when pregnancy was confirmed by vaginal ultrasound showing a gestational sac 4 weeks after embryo transfer (ET). PARTICIPANTS/MATERIALS, SETTING, METHODS: The EF of the setup cohort was obtained before starting fertility treatment during the natural cycle, 16–21 days after the beginning of menstruation. For the discovery and validation cohorts, the EF was collected from women undergoing frozen ET on Day 5, and the samples were collected immediately before ET. In this study, we compared five different methods; two of them based on direct extraction of RNA and the other three with an EV enrichment step before the RNA extraction. Small RNA sequencing was performed to determine the most efficient method and find a predictive model differentiating between implantative and non-implantative endometrium. The models were confirmed using quantitative PCR in two sets of samples (discovery and validation cohorts) with different implantation outcomes. V CThe Author(s) 2022. Published by Oxford University Press on behalf of European Society of Human Reproduction and Embryology. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact [email protected] Human Reproduction, Vol.37, No.10, pp. 2375–2391, 2022 Advance Access Publication on August 27, 2022 https://doi.org/10.1093/humrep/deac184 ORIGINAL ARTICLE Infertility Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . MAIN RESULTS AND THE ROLE OF CHANCE: The protocols using EV enrichment detected more miRNAs than the methods based on direct RNA extraction. The two most efficient protocols (using polymer-based precipitation (PBP): PBP-M and PBP-N) were used to obtain two predictive models (based on three miRNAs) allowing us to distinguish between an implantative and non-implantative endometrium. The first Model 1 (PBP-M) (discovery: AUC ¼0.93; P-value ¼0.003; validation: AUC ¼0.69; P-value ¼0.019) used hsa-miR-200b3p, hsa-miR-24-3p and hsa-miR-148b-3p. Model 2 (PBP-N) (discovery: AUC ¼0.92; P-value ¼0.0002; validation: AUC ¼0.78; P-value ¼0.0002) used hsa-miR-200b-3p, hsa-miR-24-3p and hsa-miR-99b-5p. Functional analysis of these miRNAs showed strong association with key implantation processes such as in utero embryonic development or transforming growth factor-beta signaling. LARGE SCALE DATA: The FASTQ data are available in the GEO database (access number GSE178917). LIMITATIONS, REASONS FOR CAUTION: One important factor to consider is the inherent variability among the women involved in the trial and among the transferred embryos. The embryos were pre-selected based on morphology, but neither genetic nor molecular studies were conducted, which would have improved the accuracy of our tests. In addition, a limitation in miRNA library construction is the low amount of input RNA. WIDER IMPLICATIONS OF THE FINDINGS: We describe new non-invasive protocols to analyze miRNAs from small volumes of EF. These protocols could be implemented in clinical practice to assess the status of the endometrium before attempting ET. Such evaluation could help to avoid the loss of embryos transferred to a non-implantative endometrium. STUDY FUNDING/COMPETING INTEREST(S): J.I.-P. was supported by a predoctoral grant from the Basque Government (PRE_2017_0204). This study was partially funded by the Grant for Fertility Innovation (GFI, 2011) from Merck (Darmstadt, Germany). It was also supported by the Spanish Ministry of Economy and Competitiveness MINECO within the National Plan RTI2018-094969-B-I00, the European Union’s Horizon 2020 research and innovation program (860303), the Severo Ochoa Centre of Excellence Innovative Research Grant (SEV-2016-0644) and the Instituto de Salud Carlos III (PI20/01131). The funding entities did not play any role in the study design, collection, analysis and interpretation of data, writing of the report or the decision to submit the article for publication. The authors declare no competing interests. Key words: embryo implantation / endometrial fluid / non-invasive biomarkers / extracellular vesicles / microRNAs / implantative endometrium / non-implantative endometrium / implantative IVF cycles / non-implantative IVF cycle / IVF Introduction Increasing embryo implantation rates is one of the greatest challenges in ART, as only 35% of embryo transfers (ETs) result in a clinical pregnancy (Matorras et al., 2002;De Geyter et al., 2020). Despite numerous studies focused on improving implantation rates, a reliable method of determining the competence of the endometrium, fundamental for successful implantation, is still lacking (Strowitzki et al., 2006;Craciunas et al.,2019). Currently, the endometrial biopsy is used to establish whether the endometrium is ready for ET (Casper, 2020). This is an invasive methodology, and the ET is not performed in the same cycle in which the sample is taken as it can have detrimental effects on implantation (van der Gaast et al.,2009). If the biopsy shows that the endometrium is receptive, the results will be extrapolated to the next cycle. This assumption is not realistic, since the endometrial cycle is a dynamic process involving many factors affecting the receptivity of the endometrium. The analysis of endometrial fluid (EF) obtained in a noninvasive manner, without biopsy, is a promising alternative (van der Gaast et al., 2003). It has been demonstrated that the aspiration of EF immediately before the ET does not affect the implantation. Moreover, the prompt analysis of EF composition might allow the ET in the same cycle (van der Gaast et al.,2003;Azkargorta et al.,2018; Matorras et al., 2018,2020). The EF can be obtained several times during the cycle and its analysis could reveal whether the endometrium is ready for implantation or therapeutic intervention is necessary for a successful procedure. The EF is a complex biological fluid that can modulate endometrial homeostasis and receptivity, it can sustain the preimplantation embryo and initiate the implantation process and it plays an important role in the embryo–endometrium communication (Ng et al.,2013;Vilella et al., 2015;Bhusane et al.,2016;Nguyen et al., 2016). microRNAs (miRNAs) are small non-coding RNA sequences (18–22 nucleotides) that are important regulators of genes at the post-transcriptional level (Bhaskaran and Mohan, 2014). They are essential during early embryonic development since they regulate cell proliferation and differentiation (Bhaskaran and Mohan, 2014). Some of these miRNAs have been associated with the extracellular vesicles (EVs), also present in the fluid obtained from the uterine cavity (Vilella et al.,2015). EVs are widely known mediators of intercellular communication, transmitting information from one cell to a multitude of other cells and locations (Han et al., 2020). Moreover, analyses of miRNA content of endometriumderived EVs show that they are taken up by the embryos, modifying their transcriptomic and adhesive phenotypes (Ng et al.,2013;Vilella et al., 2015;Greening et al., 2016;Balaguer et al., 2018;Marinaro et al., 2019). For example, the EV-associated hsa-miR-30d is internalized by mouse trophoectoderm and increases the embryo adhesion via upregulation of adhesive molecules (Vilella et al., 2015). One of the main challenges in ART is finding non-invasive tools for detecting the best time to perform the ET. Here, we developed a reproducible, sensitive, low-invasive method to comprehensively examine the miRNA landscape of the EF. First, we optimized the EF sample collection technique. Then, we established a robust method for analyzing vesicular and non-vesicular miRNAs from EF obtained in clinical settings, where sample size is limited and no sophisticated equipment is available. Finally, we applied these methods to a set of EF samples from women with different implantation outcomes. Our aim was to define a miRNA signature to identify the competence of the endometrium. If we could determine the state of the endometrium, it would 2376 Iba~ nez-Perez et al. Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . then be possible to change the ET strategy when the results show an unfavorable implantative pattern. Thus, the implantation rates could potentially be improved and the loss of embryos minimized by avoiding their transfer to non-implantative endometrium. Materials and methods Ethical approval Ethical approval for the study was obtained from the Cruces University Hospital Ethics Committee and Institutional Review Board (CEIC 11/45) and all the participants gave written consent for their participation. Study population The population under study consisted of a cohort of 162 women who attended the Human Reproduction Unit of Cruces University Hospital (Basque Country, Spain) from January 2018 to February 2021. For the setup and optimization of the techniques, the samples were collected before starting the fertility treatment. The samples were collected during the natural cycle, 16–21 days after the beginning of menstruation. To test the selected method, the samples were collected just before Day-5 frozen ETs, a practice which is performed increasingly often (Matorras et al., 2021). Out of 162 women (Supplementary Fig. S1), 72 participated in the setup, 30 in the discovery of the predicted models and 60 in the validation of the models. Forty-five women became pregnant and were included in the implantative endometrium group. The other 45, who did not achieve pregnancy, were included in the non-implantative endometrium group. The endometrium was considered implantative when pregnancy was confirmed by vaginal ultrasound showing a gestational sac 4 weeks after ET. Cases with a positive bhCG test where a gestational sac was not seen on vaginal ultrasound (biochemical miscarriages) were not included in the study. The inclusion criteria in the setup study were: age between 18 and 37 years; cycle duration between 27 and 29 days; absence of ovulatory disorders, myomas, endometriosis, polyps, uterine scars or hydrosalpinges; normal uterine and ovarian ultrasound; serum anti-Mu¨llerian hormone >0.4 ng/ml; and no history of gynecological infections, immune disorders or gynecological surgery. The inclusion criteria for the discovery and validation cohorts also included: frozen ET on Day 5 (good quality embryos; Types A and B of the Spanish Society for the Study of Reproductive Biology (ASEBIR) classification (ASEBIR, 2015) and transfer of 1–2 embryos derived from the oocytes of the same subject. The management of endometrial preparation was always carried out using the same protocol. A vaginal ultrasound was performed on Day 1 or 2 to confirm ovarian quiescence (absence of follicles >10 mm). An artificial cycle was started on Day 2 by administering 6 mg of estradiol daily (Progynova, Bayer, Barcelona, Spain). The development of the endometrium was monitored using serial vaginal ultrasounds. When the endometrium became 7-mm thick, the transfer day was scheduled. Vaginal progesterone at a dose of 400mg/12 hr (Utrogestan, SEID, Barcelona, Spain) was started the next morning, and the ET was performed on the 5th day of progesterone administration. If pregnancy was achieved, the estradiol and progesterone treatment was maintained until the 12th week of gestation. Embryo vitrification was performed on Day 4 or 5 using a Cryotop device (Kitazato BioPharma Co., Shizuoka, Japan). The embryos were cryopreserved and warmed using the Kitazato vitrification/warming kit (Kitazato BioPharma Co.), according to the manufacturer’s instructions. Frozen Day-4 embryos were thawed and cultured for 24 hr before the ET and Day-5 blastocysts for 2 hr before the ET. Sample collection and storage The EF was aspirated with a catheter used for ET (Frydman, Instrumentos Me´dicos Este´riles SA, Spain) connected to a 10-ml syringe under abdominal ultrasound guidance. Sample extraction was performed by gently applying a negative pressure with the syringe. The aspiration was interrupted at the internal cervical os to prevent contamination with cervical mucus. Special care was taken to avoid touching the uterine fundus or injuring the cervix and minimize sample contamination with blood and endometrial tissue. In cases with excessive vaginal secretions, the vagina was cleaned with saline solution before aspiration. Aspirate volumes ranged from 5 to 50ml. After aspiration, the 10-ml syringe was replaced with a 2-ml syringe containing 1.5 ml of 1Dulbecco’s PBS (DPBS) (Gibco, Thermo Fisher Scientific, # 14190250, MA, USA) to expel the EF. The aspirates were mixed with the 1DPBS and expelled into a cryogenic tube (5–50 ml of EF þ1500 mlof1DPBS). The mixed samples were centrifuged to remove contaminants at 2500gfor 5 min at room temperature, and the supernatants were then kept frozen at 80C until processed. The dilution of the supernatants was 1:30, with a final volume between 400 and 1300 ml. EV enrichment methods Size-exclusion chromatography A Poly-Prep chromatography column (BioRad, # 731-1550, Hercules, USA) was filled with 2.5 ml of Sepharose CL-2B cross-linked resin (Sigma, # CL2B300-100ML) and left packing overnight at 4C. The column was then washed twice with 2.5 ml of 1DPBS. Three aliquots of 400 ml from the setup cohort sample pool were used. Each aliquot was applied to the column, and then 4 ml of 1DPBS was added. The size-exclusion chromatography (SEC) separated the sample into 12 fractions (F1–F12); the EVs were eluted mainly in F3 but also in F4 and F5 fractions, as described by Prieto-Ferna´ndez et al. (2019). F1 to F10 had a final volume of 200 ml, and F11 and F12 of 1 ml. The 12 fractions of one aliquot were each used for RNA extraction with mirVana TM PARIS TM Kit (Thermo Fisher Scientific, # AM1556). The RNA obtained from fractions F3 and F4 was further analyzed by small RNA-sequencing (RNA-Seq). The 12 fractions of the other two aliquots were characterized using western blot (WB). Polymer-based precipitation method Since there was no published protocol for using the Invitrogen Total Exosome Isolation Reagent with the EF, we compared the Total Exosome Isolation Reagent for the cell culture media (Invitrogen by Thermo Fisher Scientific, # 4478359) with Total Exosome Isolation Reagent for other body fluids (Invitrogen by Thermo Fisher Scientific, # 4484453). Although both worked well with the EF, we used the # 4478359 because of its better cost-effectiveness ratio. The miRNAs as biomarkers of implantative endometrium 2377 Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . optimized protocol was as follows: centrifuge the EF supernatants at 3000gfor 30 min at 4C; transfer the supernatants to a fresh tube and add an equal volume of the Total Exosome Isolation Reagent (1:1); stir the mixture by vortexing until there is a homogeneous solution and incubate the sample for 30 min at room temperature; after the incubation, centrifuge the samples at 10 000gfor 1 hr at 4C; aspirate the supernatant by pipetting and discard it; the EVs are contained in the pellet, which may not be visible at the bottom of the tube; and finally, add 100 mlof1DPBS to resuspend the pellet. Ultracentrifugation Ultracentrifugation (UC) was carried out in a single step (100 000gfor 75 min at 4C) using a Beckman-Coulter TLA 120.2 rotor. The EV pellets were resuspended in 100 mlof1DPBS. RNA extraction methods We used two RNA isolation methods; we followed the manufacturer’s instructions for the mirVana TM PARIS TM Kit (Thermo Fisher Scientific, # AM1556) (DCT-M) and Norgen Plasma/Serum RNA Purification kit (DCT-N). Two different Norgen kits were used as needed; the midi kit (Norgen Biotek Corp., # 56100, Ontario, Canada) or the mini kit (Norgen Biotek Corp., # 55000). The RNA was eluted in nucleasefree water (Ambion, # AM9930 by Thermo Fisher Scientific). cDNA synthesis and TaqMan miRNA assay Following the manufacturer’s recommendations, cDNA was synthesized from 2 ml of RNA using the TaqMan Advanced miRNA cDNA Synthesis kit (Applied Biosystems, # A28007, by Thermo Fisher Scientific). The TaqMan reactions used were the TaqMan Fast Advanced Master Mix (Thermo Fisher Scientific, # 4444557) and TaqMan Advance miRNA assays (Thermo Fisher Scientific, # A25576). The quantitative PCR was performed using a Viia7 or QS6 system, and the data were analyzed using the QuantStudio RealTime PCR System version 1.3 (Applied Biosystems, by Thermo Fisher Scientific). The expression profiles of seven EV-associated miRNAs were used as reference (Thermo Fisher Scientific): hsa-let-7-5p (478579_mir), hsa-miR-17-5p (478447_mir), hsa-miR-200c-3p (478351_mir), hsa-miR-30c-5p (478008_mir), hsa-miR-30d-5p (478606_mir), hsa-miR-451a (478107_mir) and hsa-miR-92a-3p (477827_mir) (Supplementary Table SI). These miRNAs have been reported as secreted by endometrial epithelial cell lines (Ng et al., 2013), found in the EF aspirates (Vilella et al.,2015;Campoy et al., 2016) and secreted in endometrial exosomes associated with early embryo implantation (Vilella et al., 2015;Balaguer et al., 2018). Two other miRNAs were selected after the small RNA-Seq analysis using the setup pool cohort sample. These were the hsa-miR-21-5p (477975_mir) and hsa-miR-155-5p (483064_mir) miRNAs, which were among the most and least abundant miRNAs in the pool, respectively (Supplementary Table SI). In addition, two exogenous miRNAs were used as internal controls. To examine the efficiency of the RNA extraction, 4 ml of cel-miR-39 (478293_mir, Thermo Fisher Scientific) of a 0.1 nM stock were added to the sample before each RNA extraction procedure. To test the differences between the cDNA synthesis reactions, 0.2 ml of ath-miR-159a (478411_mir, Thermo Fisher Scientific) of a 0.001nM stock was added at the beginning of each cDNA synthesis reaction. Comparing the miRNA extraction methods Five different methods were compared to define a simple and effective strategy for detecting vesicular and non-vesicular miRNAs in small volumes of EF (Fig. 1). Two of these involved direct extraction using different RNA extraction kits, DCT-N (Norgen kit, # 56100) and DCT-M (mirVana PARIS kit, # AM1556). The other three required enrichment of EVs before RNA extraction. In one case, the enrichment was carried out by UC followed by RNA extraction with mirVana PARIS kit (UC-M). In the remaining two cases, the enrichment was carried out using the polymer-based precipitation (PBP) method and the RNA was extracted using the Norgen (# 55000) (PBP-N) or mirVana PARIS kit (PBP-M). In parallel, SEC was performed to characterize the protein and miRNA content of the EF (Fig. 1). The volumes of recovered EF samples varied depending on many factors, such as the operator collecting the sample and the EF volume or viscosity. In general, the volumes ranged from 400 ml to 1.3 ml. Therefore, we optimized the protocols to be used with the minimum volume available (400 ml) in all cases. All the tests were performed in triplicate. Technical reproducibility experiment A technical reproducibility experiment was conducted using the PBP-M and PBP-N protocols. Two operators (J.I.-P. and M.C.-G.) performed the tests independently. The samples used in these experiments came from the setup pool cohort, and each of the operators tested 10 aliquots using each method. Quantitative PCR (qPCR) was used to examine reproducibility; nine miRNAs were analyzed (seven reference miRNAs and two miRNAs obtained from the small RNA-Seq analysis) (Supplementary Table SI). Dithiothreitol treatment assay Two aliquots from the setup pool cohort were used to perform the experiment. One of the aliquots was treated with a 1.4% dithiothreitol (DTT) solution in a 1:1 ratio (Miller et al.,2012;Wang et al., 2017) and the other served as control; 1DPBS (1:1) was added. The samples were mixed by vortexing and incubated at room temperature for 15 min. Then, 1DPBS was added until the EF samples were diluted to the ratio of 1:8, and the samples were centrifuged at 3000gfor 15minat4 C. The supernatants were recovered, and 400-ml aliquots were taken. The EV enrichment was conducted using 400-ml aliquots, following the PBP method, and the pellet was resuspended in 100 ml of 1DPBS. From this volume, 15 ml was reserved for WB, 5 mlfor cryo-electron microscopy, 5 ml for nanoparticle-tracking analysis (NTA), and the rest of the suspension was used for RNA analysis with Norgen (# 55000). The isolated RNA was eluted in 100 mlof nuclease-free water. Two microliters of the eluate was used for the subsequent cDNA synthesis, and the rest was stored at 80C. RNase protection assay The samples used in this step came from the setup pool cohort, and each aliquot tested had a final volume of 400 ml. All the samples were first EV-enriched using the PBP method (described above) and the EVs were resuspended in 200 ml of DPBS. In the RNase protection assay, four different procedures were compared. Samples were treated according to following protocols: RNase A (Sigma-Aldrich, # 10109142001, MA, USA) (RNase); Proteinase K (Sigma-Aldrich, 2378 Iba~ nez-Perez et al. Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . # 03115879001) þRNase (PRT-K); Triton X-100 (Sigma-Aldrich, # T8787) þRNase (TX-100); and TX-100 þProteinase K þRNase (TX þPRT). An untreated sample was used as a control. Samples were treated with TX-100 to a final concentration of 0.1%. Proteinase K (0.05 mg/ml concentration) was added and the mixture was incubated for 10 min at 37C. The reaction was stopped by adding 5 mM of phenylmethylsulfonyl fluoride (Sigma-Aldrich, # 10837091001) and heating at 90C for 5 min. The samples were finally treated with 0.1 mg/ml RNase A (RNase) for 20 min at 37C. The control samples were kept at 4C until RNA extraction. Before extraction, b-mercaptoethanol was used to inhibit RNases, as described by Norgen (# 55000). The RNA was eluted in 50 ml of nuclease-free water. Two microliters were used for the subsequent cDNA synthesis, and the rest was stored at 80C. All the analyses were performed in triplicate with two technical duplicates, ending with six TaqMan qPCR replicates. Analysis and quantification of the EF protein content WB analysis Asampleof15ml was mixed with 5 ml of NuPAGE LDS Sample Buffer 4(Invitrogen # NP0007, by Thermo Fisher Scientific). The fractions obtained by SEC were concentrated using 99.5% acetone (Panreac Applichem, # 161007, Darmstadt, Germany) and resuspended in 20 mlof1LDS sample buffer. They were heated for 5 min at 37C, 10 min at 65C and 15 min at 95C and centrifuged for 10 min at 13 000g. Each protein preparation was loaded and separated under non-reducing conditions in 4–12% Bis–Tris precast gels (Invitrogen, # NP0336BOX, by Thermo Fisher Scientific) in MOPS SDS Running Buffer 1(Invitrogen, # NP0001, by Thermo Fisher Scientific). Precision Plus Protein Dual Color Standard (BioRad, # 161-0374) was used as a marker for protein molecular weights. The proteins were transferred to an Immobilon-P Transfer membrane (Merck Millipore, # IPVH00010, MA, USA) in NuPAGE Transfer Buffer 1(Invitrogen, # NP0006-1 by Thermo Fisher Scientific) for 1 hr at 100 V. The blocking was performed using 5% Blotting-Grade Blocker (BioRad, # 1706404) and 0.2% Tween-20 (Sigma-Aldrich, # P2287, MA, USA) diluted in 1DPBS, for 1 hr. Primary antibodies were incubated overnight and the membranes were washed three times for 10 min with 1 DPBS. Incubation with the secondary horse-radish peroxidase-conjugated antibody (1:6000) was performed at room temperature for 30 min. The chemiluminescence was detected using Pierce ECL Plus Western Blotting Substrate (Thermo Fisher Scientific, # 32132). The bands were visualized on high-performance films (GE Healthcare, Figure 1. Workflow summarizing the different methods used to analyze microRNAs from the endometrial fluid of patients undergoing ART. We compared five different methods, two of which used the direct extraction of RNA from the endometrial fluid (EF) (DCT-N and DCT-M). The other three included the extracellular vesicle (EV) enrichment (UC-M, PBP-N and PBP-M) before RNA extraction. In parallel, we carried out a size-exclusion chromatography (SEC-M) to characterize the proteins and miRNAs in the EF. The samples came from the setup pool cohort, and each experiment was performed in triplicate, using sample aliquots of 400 ml. DCT-N: direct RNA extraction with Norgen Plasma/Serum RNA purification kit. DCT-M: direct extraction of RNA with mirVana PARIS kit. UC-M: EV enrichment by ultracentrifugation and RNA extraction using mirVana PARIS kit. PBP-N: EV enrichment with a polymer-based precipitation method and RNA extraction with Norgen Plasma/Serum RNA purification kit. PBP-M: EV enrichment using the polymer-based precipitation method and RNA extraction with mirVana PARIS kit. SEC-M: EV enrichment with SEC and RNA extraction with mirVana PARIS kit. miRNAs, microRNAs; PBP, polymer-based precipitation. miRNAs as biomarkers of implantative endometrium 2379 Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . # 28906844, IL, USA) employing the AGFA Curix-60 automatic processor (Agfa, Cologne, Germany). The primary antibodies used in this study were mouse anti-CD63 (1:500; clone H5C6 from Developmental Studies Hybridoma Bank, IA, USA), mouse anti-CD9 (1:500; clone 209306, R&D Systems, Minneapolis, MN, USA), mouse anti-CD81 (1:500, Clone JS-81, 555675, BD, NJ, USA), mouse antiCD133 (1:500 clone W6B3C1, Miltenyi Biotec, North RhineWestphalia, Germany), mouse anti-Rab8 (1:1000; Clone 4, 610844, BD, NJ, USA), mouse anti-Flotillin-1 (1:500; Clone 18 610820, BD, NJ, USA), mouse anti-HSP90 (1:500; 610418, BD, NJ, USA) and rabbit anti-Limp II (1:500; ab16522, Abcam, Cambridge, UK). The intensity of the bands was quantified by densitometry using ImageJ software v. 1.52a (ImageJ software, MD, USA). Coomassie blue staining SimplyBlue TM SafeStain from Invitrogen (Cat. # LC6060, Thermo Fisher Scientific) was used following the manufacturer’s recommendations. The intensity of the bands was quantified by densitometry using ImageJ software (v. 1.52a). Spectrophotometer Spectrophotometric measurements were performed using a NanoDrop TM One Microvolume UV–Vis Spectrophotometer (Thermo Fisher Scientific) in the wavelength range of 230–576 nm. Concentrations of RNA and proteins were obtained after measuring the absorbance of 1 mlofthesample. Nanoparticle-tracking analysis The size distribution of the EV preparations was analyzed by measuring the rate of Brownian motion using a NanoSight LM10 system (NanoSight, Amesbury, UK), equipped with fast video capture and particle-tracking software. NTA acquisition settings were the same for all samples, and each video was analyzed to obtain the mean and mode of vesicle size and estimate the particle concentration (Dragovic et al., 2011). Cryo-electron microscopy EV preparations were directly adsorbed onto glow-discharged holey carbon grids (Quantifoil, Großlo¨bichau, Germany). The grids were blotted at 95% humidity and rapidly plunged into liquid ethane with the aid of Vitrobot (Maastricht Instruments BV, Maastricht, The Netherlands). Vitrified samples were imaged at liquid-nitrogen temperature using a JEM-2200FS/CR transmission cryo-electron microscope (JEOL, Tokyio, Japan) equipped with a field emission gun and operated at an acceleration voltage of 200 kV. Real-time qPCR assay The relative expression levels of the miRNAs obtained for the setup pool cohort were normalized to ath-miR-159 expression and calculated using the 2 DCt (Ct miRNACt ath-miR-159a) method. The relative expression levels of the discovered and validated miRNAs were normalized to internal controls; the differences between the groups were calculated employing the 2 DCt (Ct miRNACt mean internal controls) equation. Subsequently, the fold changes were obtained using the 2 DDCt method (Rao et al., 2013). Endogenous controls were selected from the reference miRNAs (Supplementary Table SI) using the NormFinder software (MOMA, Aarhus, Denmark). The NormFinder is an algorithm using a model-based approach to calculate the stability of a reference transcript; the calculation is based on the intergroup and intragroup variations. The stability score is a weighted measure of these two parameters, and the most stable reference transcript is the one with the smallest stability value (Andersen et al., 2004). Only the samples for which we could find the internal controls with fewer than 30 Ct cycles (in qPCR) were used in the regression study of the discovery cohort (Supplementary Table SII) and to validate the models in the validation cohort (Supplementary Table SIII). Correlation analysis The corrplot package (Wei et al.,2017) of the R 3.6.2 program was used to analyze the correlations between the proteins (2019-12-12, R Foundation for Statistical Computing, Vienna, Austria). Statistical analysis GraphPad Prism v.8.0 (GraphPad Software, California, USA) was employed to analyze the data. The statistical significance of the experiments carried out with the setup pool cohort was determined using paired Student’s t-tests. For the results obtained for the discovery and validation cohorts, unpaired Student’s t-tests with Welch’s correction were employed. Statistical differences were considered significant at a P-value smaller than 0.05 (two-sided). Sample sizes and P-values are all shown in the figures and figure captions. Small RNA-Seq The quantity and quality of the RNA were evaluated using Agilent RNA 6000 Pico Chips (Agilent Technologies, Cat. # 5067-1513, CA, USA). Sequencing libraries were prepared following the protocol included with the NEXTflex TM Small RNA-Seq Kit v3 (V CBioo Scientific Corp., Cat. # 5132-06, protocol V19.01, Austin, TX, USA). Briefly, the total RNA from each sample was incubated for 2 min at 70C. Then, a 304 N adenylated adapter (adapter dilution 1/4) and ligase enzyme were added, and ligation was carried out by incubation overnight at 20C. After removing the excessive 30adapter, 5’ adapter was added with the ligase enzyme and the mixture was incubated at 20C for 1 hr. The ligation product was used for reverse transcription with the M-MuLV reverse transcriptase in a thermocycler for 30 min at 42C and 10 min at 90C. Next, the enrichment of the cDNA was performed using PCR cycling: 2 min at 95C; 20–27 cycles of 20 s at 95C, 30 s at 60Cand15sat72 C, with the final elongation of 2 min at 72C and a pause at 4C. The PCR products were resolved on 8% Novex TBE polyacrylamide gels (Cat. # EC6215BOX, Thermo Fisher Scientific), and a band between 150 and 400 bp was cut out. Small RNAs were extracted from the polyacrylamide gel using an adapted protocol in which the DNA from gel slices was dissolved in ddH 2 O overnight at room temperature. Afterwards, the libraries were visualized employing an Agilent 2100 Bioanalyzer with an Agilent High Sensitivity DNA kit (Agilent Technologies, Cat. # 5067-4626) and quantified using a Qubit dsDNA HS DNA Kit (Thermo Fisher Scientific, Cat. # Q32854). The amount of cDNA in each library that was sent for sequencing was 10 nM. Sequencing was carried out in pools of isomolar libraries and all of them were sequenced in a 2380 Iba~ nez-Perez et al. Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . HiSeq2500 (Illumina Inc) to achieve at least 10 million 50-nt singlereads per sample. Alignment The FASTQs were trimmed for the adapters following the recommendations of the NEXTflex TM Small RNA-Seq Kit manufacturers. We used the Bowtie program (Langmead et al., 2009)toalignthereads against the human genome (GRCh38), with a mismatch of 0 to avoid false positives. We chose miRBase v22 to quantify the mature miRNAs, employing the Partek Flow application (version 7.0). Small RNA-Seq data analysis We performed differential abundance analyses to identify miRNAs associated with different implantation outcomes. To avoid rare molecules, following the Trimmed Mean of M-values (TMM) normalization, we retained miRNAs with counts per million >1, non-zero counts in at least 15 individuals, and at most 10 zero counts in each of the two subgroups, i.e., the successful (n ¼15) and unsuccessful implantations (n ¼15). Differential expression was then assessed employing the edgeR (Robinson et al.,2010) using the SARTools R package (Varet et al., 2016). The program fits a log-linear model for each miRNA that uses a group (implantative versus non-implantative) as the factor of contrast. Applying the edgeR default parameters for normalization and shrinkage, this gives a fold change estimate that corresponds to the mean expression level in the implantative samples divided by the mean expression level in the non-implantative group. For further analysis, we selected the miRNAs with logFC >1.5 or logFC <1.5 and the adjusted P-value <0.05. The Benjamini–Hochberg procedure was used to calculate the false discovery rate for each comparison and obtain the adjusted P-values (Supplementary Tables SIV and SV). Regression study A subset of miRNAs was used to generate two linear regression models with k-fold cross-validations, one for each miRNA extraction protocol assessed. Samples were randomly divided into training and testing datasets (80–20%). Three miRNAs were used per modeling process. The hsa-miR-24-3p, hsa-miR-200b-3p and hsa-miR-148b-3p were selected for PBP-M and hsa-miR-24-3p, hsa-miR-200b-3p and hsa-miR-99b-5p for PBP-N. The resulting model reproducibility was further tested by bootstrap correction with 500 replications. The analysis was performed using R v4.0.0 software (R Development Core Team; http://cran.r-project.org) with ROCR (Sing et al.,2005)and caTools packages. Functional analysis of the miRNAs The target genes of the validated miRNAs were obtained from the TarBase database, v7.0. The biological processes in which these miRNAs are involved were analyzed using the Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) in terms of biological process categories employing Diana-miRPath tools v3.0 (Vlachos et al., 2015). The Fisher’s exact test and false discovery rate correction were performed to select enriched KEGG pathways and GO processes. We selected only the pathways and processes with Pvalues <0.05. The results for the KEGG were merged by ‘pathway union’ and the results for GO by ‘category union’. Results Optimization of EF sample preparation The treatment of the samples with 1.4% DTT (Miller et al., 2012; Wang et al.,2017) was useful for degrading the mucus pellet formed after centrifugation; most mucus disappeared, as shown in Supplementary Fig. S2A. The NTA and cryo-electron microscopy analyses (Supplementary Fig. S2B and C) revealed heterogeneous EV populations with diameters between 100 and 800nm under both experimental conditions (with and without DTT). In the untreated samples, the average concentration was 1.9 10 9 §7.8 10 7 particles/ml, with a mean size of 291.5 §0.1 nm and mode 196.4 §3.2 nm. In the DTT-treated samples, we detected more particles (mean 2.7 10 9 §5.9 10 7 particles/ml), with larger mean size (mean 313.6 §2.5 nm and mode 248.5 §8.1 nm). The WB showed different patterns of vesicular markers in the two conditions (Supplementary Fig. S2D). The intensity of the Rab8 marker in the DTT-treated samples was stronger than in the untreated samples, in agreement with the number of particles detected in the NTA. In contrast, the intensities of the Limp II, CD133 and CD63 markers were stronger in the untreated samples. The seven reference miRNAs (Supplementary Table SI) were detected in all the samples for both conditions. In the DTT-treated group, the levels of the following miRNAs were significantly reduced compared to the untreated group: hsa-let-7e-5p, hsa-miR-17-5p, hsa-miR-200c-3p, hsa-miR-30c-5p and hsa-miR-451a (Supplementary Fig. S2E). Characterization of the miRNAs in EF The SEC method separated the EF into several fractions. The results of WB analysis of the fractions demonstrate that it was possible to detect exosomal markers in small-volume EF samples (Fig. 2A). The CD63 and CD81 markers were detected in the F3 and to a lesser extent in F4 and F5 fractions. Rab8 was also mainly detectable in F3–F5 fractions. Immunoglobulins were also found in fractions F6 to F11. The study of the distribution of the seven reference miRNAs (Supplementary Table SI) showed that the relative quantity of miRNAs increased in fractions F3 to F11 (Fig. 2B). In F3, which corresponds to the vesicular fraction, the most abundant miRNAs were hsa-miR-451a and hsa-miR-92a-3p, and the least abundant were hsa-miR-30d-5p and hsa-miR-200c-3p. This trend was maintained in the rest of the fractions, except for F7, where hsa-miR-200c-3p was the second most abundant miRNA. The protective effect of the EVs on the miRNAs was confirmed by the RNase assay. In the samples treated with RNase or Triton X-100 (TX-100) with RNase, only the hsa-miR-30c-5p was significantly degraded compared to the control (Fig. 2C). In the samples treated with proteinase K (PRT-K) and RNase, there was a significant decrease in the levels of all the analyzed miRNAs (although all the miRNAs were detectable in all the replicates). The miRNAs were further degraded when the samples were treated with TX-100, PRT-K and RNase (TX þPRT). In this case, we could only detect hsa-miR-200c-3p and hsamiR-92a-3p in all the replicates. Under these conditions, hsa-miR-451a, hsa-miR-17-5p and hsa-miR-30d-5p were detected in four of six replicas, hsa-let-7-5p in two of six replicas and hsa-miR-30c-5p was undetectable. In the TX þPRT treatment, the detection of all miRNAs was significantly reduced compared to the previous combinations. miRNAs as biomarkers of implantative endometrium 2381 Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . Identification of an efficient method to perform a comprehensive analysis of miRNAs from EF Although we detected all the reference miRNAs (Supplementary Table SI) in all the extraction replicates obtained using the DCT-M, DCT-N, PBP-M, PBP-N and UC-M protocols, differences in the abundance of each miRNA were found among them (Fig. 3A). The miRNA analysis showed that the methods employing the EV enrichment step with PBP (PBP-N and PBP-M) performed better than the others, with PBP-N being the most efficient method. The protocols using direct Figure 2. Characterization of the microRNAs (miRNAs) in the endometrial fluid of patients undergoing ART. (A) Western blot shows different EV markers (CD63, CD81 and RAB8) and soluble proteins (Igs) in the fractions of size-exclusion chromatography (SEC). The fractions obtained by SEC were numbered from F1 to F12. (B) Distribution of the seven reference miRNAs among the fractions of the SEC. Normalized relative quantification was used to detect the miRNAs in the fractions. To perform experiments A and B, a 400-ml sample aliquot from the setup pool cohort was added onto the column. The number of replicates for each fraction was six and the data show the mean with SEM. (C) RNase protection assay. Sample analysis to examine the association of miRNAs with proteins and EVs. The graphs show the Ct values of the reference miRNAs evaluated using the qPCR. The number of replicates for each condition was six and the data show the mean with SEM. The number of replicates in which each miRNA was detected is shown at the bottom of each column. Each aliquot (400 ml) came from the setup pool cohort. Statistical significance was determined using the paired Student’s t-test analysis. * ,$,&,# P<0.05; ** ,$$,&&,## P<0.01; *** ,$$$,&&&,### P<0.001. * versus Control, $ versus RNase, & versus TX-100, # versus PRT-K. Control: control sample without treatment. RNase: samples treated with RNase. TX-100: samples treated first with Triton-X 100 (TX-100) followed by RNase treatment. PRT-K: samples treated first with proteinase K and then with RNase. TXPRT: samples treated first with TX-100, then with proteinase K and finally with RNase. EVs, extracellular vesicles; qPCR, quantitative PCR. 2382 Iba~ nez-Perez et al. Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 Figure 3. Optimization of different methods for analyzing the miRNAs in endometrial fluid of patients undergoing ART. (A) Results for the seven reference miRNAs analyzed by quantitative PCR for each of the compared techniques. Normalized relative quantification revealed that the most efficient method was the PBP-N, while the UC-M method was the least efficient. Statistical significance was determined using paired t-test analysis. The number of replicates for each case was 12 and the data show the mean with SEM. * versus PBP-N; $ versus PBP-M; & versus DCT-N; # versus DCT-M. (B) The Venn diagram shows the number of unique miRNAs detected using small RNA-Seq for each method and the number of miRNAs common among them. The number of unique miRNAs detected by each technique was 251 for PBP-M, 151 for PBP-N, 204 for SEC F3 and 149 for SEC F4. The samples (400 ml) for experiments A and B came from the setup pool cohort, and each experiment was performed in triplicate. (C) A technical reproducibility experiment was conducted to compare the performance of PBP-M and PBP-N methods. The graphs show Ct values for each miRNA, each operator (a, JIP; b, MCG) and method (PBP-M or PBP-N). Box plots show the median, maximum and minimum values and all the points. The 400-ml samples came from the setup pool cohort. Each operator analyzed 20 aliquots, 10 by employing the PBP-M and 10 miRNAs as biomarkers of implantative endometrium 2383 (continued) Downloaded from https://academic.oup.com/humrep/article/37/10/2375/6678065 by Universidad del Pais Vasco user on 08 November 2022 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Instituto de Salud Carlos III (PI20/01131). The funding entities did not have any role in study design, sample collection, analysis and interpretation of data, report writing or decision to submit the article for publication. 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