The Impact Of The Vaginal And Endometrial Microbiome Pattern On Assisted Reproduction Outcomes

The vaginal microbiome plays an important role in maintaining health, and there is evidence that microbial colonization of the upper genital tract can also influence successful embryo transfer. The aim of this study is to determine whether the vaginal and endometrial microbiome in people undergoing assisted reproduction techniques could affect the pregnancy rate. Regarding the microbiome dynamics during the cycle, we observed a decrease in alpha diversity from the follicular to luteal phase in the control group, in contrast to a stable pattern in the repetitive implantation failure group. As for endometrial and vaginal microbiome, alpha diversity was higher in the endometrium (Shannon p = 0.0139, Simpson p = 0.046); differences were also observed in beta diversity (p = 0.001). Compared to the endometrium, the vagina showed a greater relative abundance of Lactobacillus spp. (83.17% vs 84.82%, p < 0.0001), Streptococcus spp. (1.59% vs 7.74%, p = 0.014) and Ureaplasma spp. (0% vs. 0.89%, p = 0.006), and a lower abundance of Delftia spp. (0.95% vs 0%, p = 0.0003), Anaerobacillus spp. (1.59% vs 0%, p = 0.0004), and Ralstonia spp . (3.17% vs 0%, p = 0.0006). We also observed differences in both alpha diversity (Shannon p = 0.0206, Simpson p = 0.0206) and beta diversity between groups, along with differences for Ralstonia spp. (0.09% study group and 0.73% control, p = 0.0012). Finally, the relative abundance of Lactobacillus spp. differed between patients that did not versus did achieve pregnancy (91% vs 99%, p = 0.0445 visit 1, 94.63% vs. 97.69%, p = 0.0268 visit 2, 97.73% vs 99.74%, p = 0.0492 visit 3). The relative and prebiotic/probiotic supplements in an infertile Japanese population. Ninety-two patients undergoing IVF were recruited, and endometrial fluid samples were collected for sequencing using an intrauterine insemination (IUI) catheter. The bacterial composition of the endometrium and pregnancy outcomes were analyzed. For cases with NLDM, antibiotics and prebiotics/probiotics were administered according to their individual microbial conditions. Forty-seven cases (51.1%) presented LDM, and 45 cases (48.9%) NLDM, in the initial analysis. Nine patients with NLDM were treated with antibiotics and prebiotics/probiotics and successfully converted to LDM. The

impaired adaptation to endometrial changes. A greater relative abundance of Lactobacillus spp. and L. reuteri is correlated with higher chances of pregnancy. *MC Díaz Martínez and A Bernabeu García share equal responsibility for authorship.

Background
For over a century, conventional wisdom held that the cervical plug maintained the sterility of the uterine cavity. Nevertheless, technological advances in mass sequencing over the last decade have begun to uncover different microbial communities, including in the vagina and the endometrial cavity.
These microbiota have proven to be involved in reproductive health and disease, interacting with host cells along the female reproductive tract and generating the physical, chemical and biological environment that the embryo encounters during the peri-implantation period and throughout the pregnancy (1).
Endometrial implantation is the single most important event determining the success of embryo transfer in assisted reproductive therapy (ART) (2). Other factors include the presence of microbial colonization of the upper genital tract (3) and possibly utero-cervical microbial colonization (4), which has been shown to be an independent and significant factor determining the success of assisted reproductive treatments (5).
The main bacteria at vaginal and endometrial level belong to the genus Lactobacillus, producers of lactic acid that maintain the acidic pH of the vagina, which acts as a barrier against pathogens (6).
The association between vaginal flora and fertility has been widely studied for years. The normal flora of the reproductive tract includes a variety of Lactobacillus spp., which provides a healthy environment for the embryo during the pre-implantation period and also promotes successful implantation. The livebirth rate is correlated with the production of H 2 O 2 by Lactobacillus spp. and inversely correlated with the existence of bacterial vaginosis. Thus, alterations of the vaginal flora such as bacterial vaginosis (provoked by Gardnerella vaginalis) are associated with an increased risk of miscarriage (7,8). Other pathogenic microorganisms such as Chlamydia trachomatis, Neisseria gonorrhoeae and Mycoplasma tuberculosis have also been associated with a lower gestation rate, causing subclinical alterations related to risk factors for subfertility (9).
Studies on the vaginal microbiome and female infertility are scarce and recent. The first longitudinal study analyzing the microbiome of healthy pregnant women with on-term delivery versus healthy non-pregnant women showed differences between the two groups, with the microbiome of pregnant women showing greater stability (10).
At the moment, the microbiome can be studied by analyzing samples taken either from the endometrium or vagina, but all up-to-date studies have collected their specimens from different locations. Indeed, the best sample site for providing a prognosis of ART success has yet be determined. A recent paper published by Moreno et al. concluded that the uterine microbiota appears to be a continuum of the vaginal one. By contrast, other authors have reported significant differences between the vaginal and endometrial microbiota, highlighting the importance of evaluating the upper genital tract in order to understand the role of its microbiota in the physiological and pathological processes that take place in the uterine cavity, including embryo implantation, pregnancy maintenance and gynecological diseases. With regard to the endometrial microbiota, however, there are several significant obstacles. As in the case of any other low biomass microbiota, the small amount of the initial sample makes it vulnerable to contamination with exogenous bacterial DNA. For this reason, careful and appropriate investigation of the endometrial microbiota is exceptionally important in detecting uterine dysbiosis, which may affect reproductive function (11).
Within the framework of this study, we assumed that alterations in the vaginal microbiome reduce women's fertility through their negative impact on embryo implantation. Determining what makes a microbiome normal or which microorganisms can further limit female fertility may be the key to improving the prognosis of fertility treatments.
Our primary aim was to identify the vaginal and endometrial microbiome patterns associated with the rate of gestation in women undergoing assisted reproduction treatments.

Description Of The Studied Variables
The study included 48 participants, who provided 273 samples, of which 264 were analyzed. Figure 1 details the number of patients and samples initially included in the study, losses and net inclusion data and analysis. Sociodemographic characteristics and clinical outcomes of the patients included in the study were recorded for the whole sample and according to achievement of an evolutionary pregnancy (Table 1), as well as patients with and without repeated implantation failures (RIF and NO RIF). At the level of the graph analysis, the "NO RIF" group is labeled as a control group for methodological issues, though it was not treated as such. Specifically, these patients showed a decrease in alpha diversity from the follicular to the luteal phase. In contrast, the RIF group showed a stable microbiome pattern across different timepoints.
This lack of dynamism in the pattern of the vaginal microbiome in RIF patients could entail a lack of adaptation to endometrial physiology and preparation, and therefore a worse prognosis for embryo implantation (Fig. 2).

Vaginal And Endometrial Microbial Patterns At Visit 1
We observed statistically significant differences alpha diversity between endometrial and vaginal samples (p = 0.0139 for Shannon index and p = 0.046 for Simpson index), with higher values in endometrial samples (Fig. 3a).
Using PERMANOVA, the matrices with beta diversity measures showed statistical differences in    In relation to beta diversity, no statistically significant differences were observed between the two groups ( Fig. 4b). Likewise, the univariate analysis showed no statistically significant results. In relation to the taxonomic allocation, the RIF group had a lower relative abundance of the genus Streptococcus, and a higher abundance of Prevotella spp., Ureaplasma spp., and Dialister spp. The NO RIF group presented a higher relative abundance of Streptococcus spp., Veionella spp., and Aerocuoccus spp. As for the genus Lactobacillus, no differences were observed between groups ( Fig. 4c). At the species level, we observed a higher relative abundance of L. helveticus in the RIF patients, and of L. iners, L. jensenii, L. gasseri and L. agalactiae in the NO RIF group patients (Fig. 4d).

Endometrial microbiome pattern
The alpha diversity of the endometrial microbiome at visit 1 was significantly higher in the NO RIF group ( Fig. 4e; p = 0.0206 for both Shannon and Simpson indices). There were also statistically signficant differences in beta diversity, as seen in the PCoA graph (Fig. 4f Prevotella is observed in the RIF group (Fig. 4g). In the univariate analysis we found statistically significant differences for the genus Ralstonia, observing a much higher relative abundance in the NO RIF group compared to the RIF group (0.73% versus 0.09%; p = 0.0012). There are no statistically significant differences in alpha or beta diversity between the samples over the different visits.

Taxonomic characterization
We did not observe any statistically significant difference between the visits for either the composition of genera or species (Fig. 5). There were some apparent changes in abundance of the genera Lactobacillus, Streptococcus and Prevotella: both Lactobacillus and Streptococcus were more abundant on visits 1 and 2, showing a decrease on visit 3. Prevotella shows a higher abundance on visit 1 and 3, especially on the latter timepoint. In the univariate analysis there were no statistically significant differences.
At the species level, the bar chart shows some differences in relative abundance for the following species: L. helveticus, L. iners, L. gasseri and L. jensenii (Fig. 5). L. helveticus was most abundant on visit 2; L.iners, on visit 1; and L. gasseri, on visit 3. At that timepoint, results showed a smaller proportion of L. jensenii. However, these differences were not statistically significant.
Association of the vaginal sample taken at different visits with the gestation rate Diversity analysis Analyzing diversity as a function of the gestation rate, we observed a greater alpha diversity in patients who do not achieve pregnancy, obtaining a trend without reaching statistically significant values (Shannon p = 0.0748 and Simpson p = 0.0856). Regarding the beta diversity, no statistically significant differences were found at visit 1 according to gestation rate. For the samples collected at visit 2, the differences in alpha diversity were not statistically significant; however, there is a trend suggestive of a negative correlation between the gestation rate and alpha diversity (p = 0.1518). For beta diversity, we found no difference in relation to visit 2 and the pregnancy rate. The samples taken at visit 3 show no difference in alpha or beta diversity.

Taxonomic characterization
At visit 1, participants who achieved pregnancy presented a significantly greater abundance of Lactobacillus spp. than those who did not, while Streptococcus spp. and Prevotella spp. were more abundant in the latter group (Fig. 6a). Streptococcus and Prevotella may thus be associated with a poor prognosis with regard to gestation. On the other hand, an abundance of Lactobacillus spp. could be indicative of more favorable conditions. The differences were observed at the genus level for Lactobacillus spp. (91% with no gestation vs 99% with gestation; p = 0.0445) and at the species level for L. reuteri (0.39% vs 0.17%; p = 0.0397; Fig. 6b).
Similar results were obtained at visit 2. Those who achieved pregnancy presented a greater relative abundance of Lactobacillus spp.than those who did not (97.69% versus 94.63%; p = 0.0268; Fig. 6c-6d). The opposite was true for the case of Streptococcus spp. (Fig. 6c).

Discussion
The role of the vaginal microbiota in reproduction and assisted reproductive technology procedures is an active field of research, and while there is a growing body of evidence supporting its relevance, crispatus (12). In this sense, we intended to assess the correlation between the vaginal and endometrial microbiome in order to simplify the study of the female reproductive tract. We found that In terms of which sample type would be preferable for studying the microbial composition at a given point in treatment, our results suggest that vaginal samples can provide sufficient evidence to correlate the diversity and taxonomic composition of endometrial samples both with pregnancy rates and for patients with RIF (in fact, both are equally valid because of their association with pregnancy).
Vaginal samples are also more convenient, less invasive, less risky in terms of complications like endometrial tearing, and easier to collect. In addition, processing the samples coming from the endometrium using NGS technique presents greater difficulties in the analysis, especially in terms of DNA extraction and the quality of the sequences obtained, so a single endometrial sample could be insufficient. As both types of samples are similarly predictive of the result for IVF, as far as the pattern of the microbiome is concerned, the vaginal sample is preferable.
Another important aspect of the present study is the assessment of both diversity and taxonomic characterization according to participants' history of repeated implantation failures. Previously, was characterized the microbiota in endometrial fluid (EF) and vaginal secretions (VS) in 28 infertile women with a history of RIF and 18 infertile controls without, who underwent their first attempt at embryo transfer and IVF. The microbiota in the EF presented a higher alpha diversity and higher quantity of bacterial species than the microbiota in the VS in both the RIF and the control group. The analysis of the UniFrac distance matrices between EF and VS also revealed a significantly different grouping. Moreover, the microbiota detected in the EF showed significant variation in the composition of the bacterial community between the RIF group and the control group, which was not observed in the VS. Burkholderia spp. were not detected in the microbiota of the EF in any sample in the control group, but they were in a quarter of the RIF patients (14).
In our study, alpha diversity was higher at the endometrial level in the NO RIF patients. This did not occur in vaginal samples, where no differences were observed. In the above-mentioned study they did find differences in EF in both groups. When we analyzed the taxonomic characterization, we also observed clear differences in the relative abundances of the different genera and species in the different groups. For the RIF group at the vaginal level, the genus Streptococcus presented lower relative abundance, whereas Prevotella, Ureaplasma and Dialister were more prominent. In contrast, the genera Streptococcus, Veionella and Aerocuoccus showed a higher abundance in the NO RIF group. As for Lactobacillus spp., we did not observe differences in the relative abundance between groups.
At the endometrial level, we found a higher abundance of the genus Prevotella and the species L. relative abundance of lactobacilli of less than 90% in endometrial fluid was predictive of adverse pregnancy outcomes. In this study, patients classified as NLDM and showing a relative abundance of more than 80% Lactobacillus spp. in the endometrium showed good pregnancy outcomes, suggesting that this threshold could be considered sufficient for embryo implantation (17). In addition, even if classified as NLDM, the endometrium with a dominant quantity of Bifidobacteria could also be an acceptable environment for implantation (18 Lactobacillus spp.) in their endometrium. They also aimed to report cases that were treated for NLDM simultaneously with antibiotics and prebiotic/probiotic supplements in an infertile Japanese population. Ninety-two patients undergoing IVF were recruited, and endometrial fluid samples were collected for sequencing using an intrauterine insemination (IUI) catheter. The bacterial composition of the endometrium and pregnancy outcomes were analyzed. For cases with NLDM, antibiotics and prebiotics/probiotics were administered according to their individual microbial conditions. Forty-seven cases (51.1%) presented LDM, and 45 cases (48.9%) NLDM, in the initial analysis. Nine patients with NLDM were treated with antibiotics and prebiotics/probiotics and successfully converted to LDM. The results of this study did not demonstrate a clear benefit for establishing a Lactobacillus-dominant endometrium in terms of pregnancy outcomes, but knowledge of the endometrial microbial status of infertile patients is important since recovery of the Lactobacillus-dominant endometrium could benefit implantation (18). In this preliminary study, the predominance of Lactobacillus was favorable in terms of the pregnancy rate; however, the results were not as significant as in the previous pilot study (17); the reasons for this may be due to the limited number of cases, short follow-up period, or ethnic differences. In an other study also concluded that women with an abnormal vaginal microbiota are approximately 1.4 times less likely to become pregnant after in vitro fertilization treatment, compared to women with a normal microbiota pattern (19).
With reference to the taxonomic characterization in our study, we found that the relative abundance of bacteria of the genus Lactobacillus spp. is higher in patients who achieve pregnancy after ART.
Likewise, the greater presence of this genus was detected in the first and third visit (secretory phase of the previous cycle and day of the negative HCG test). Since no statistically significant differences were obtained when analyzing the differences in relative abundance between samples taken in the three consecutive visits during the treatment, we could opt for any of the three options (secretory phase of the previous cycle, proliferative phase of the cycle of the cryotransfer or the day of the embryo transfer). We concluded that they are comparable in terms of the results of the microbiome pattern, and their extrapolation is justified. Samples can thus be taken when considered most appropriate during the fertility treatment.

Conclusions
When analyzing the pattern of the vaginal and endometrial microbiome, we observed differences between the two types of samples. Our analysis of the vaginal samples taken at different visits, in contrast, indicated no differences in the microbiome pattern according to assessment timepoint. A greater relative abundance of Lactobacillus spp. and L. reuteri correlated with a higher pregnancy rate.
When comparing changes in the microbiome pattern between the RIF and NO RIF group, we found a lack of adaptability and variation in the RIF group compared to the NO RIF group. In the RIF group, we found lower alpha diversity at the endometrial level along with a lower relative abundance of Streptococcus spp., Aerocuoccus spp. and Ralstonia spp. This group presented a higher abundance of Prevotella spp., Ureaplasma spp., and Dialister spp. Further studies are needed to confirm our findings and to clarify the role of antibiotic and/or probiotic treatment in the normalization of the microbiome pattern and its consequences on clinical outcomes.

Materials And Methods Design And Study Population
We designed a longitudinal, descriptive, observational cohort study. People presenting to the Instituto The PCR products were visualized using agarose electrophoresis, verifying that the amplified DNA band was the correct size (449 base pairs). All products of amplification were stored at − 20ºC for subsequent sequencing.
Sequencing of region V3V4 of 16S rRNA gene Once the V3V4 amplicon was obtained and purified, we generated the library with the identifying indexes of each sample using the Nextera XT sequencing kit (Illumina). After the purification of the libraries, the samples were quantified using Qubit 2.0 (ThermoFisher), which were previously diluted to a concentration of 4 nM before being mixed and prepared for sequencing. The final concentration of the library was 15 pM. The library was sequenced using Miseq Reagent kit v3 (Illumina) reagents.
We used Miseq (Illumina) as the sequencing equipment and metagenomics for the workflow.

Bioinformatic Analysis Of The Sequences
Once the sequencing was finished, the primary analysis of the obtained sequences consisted of demultiplexing, using MiSeqReporter software (Illumina). The unindexed paired-end sequences of each sample were exported from MiSeq for their analysis in fastq format.
The bioinformatic analysis of the sequences was carried out using the QIIME2 package. In addition, for further data analysis we worked with the MicrobiomeAnalyst program. Deblur was used to filter and denoise the sequences with QIIME2. The sequences were grouped in OTUs with a similarity percentage of 97%.
In order to estimate alpha diversity, a rarefraction analysis was performed at 1000 sequences per sample, followed by an alpha diversity analysis. Different indexes were used: Shannon, Simpson and Faith. Since these indices did not follow a normal distribution, the non-parametric Mann-Whitney U method was used.
The results for beta diversity were visualized with QIIME2 using the graphics generated by principle coordinate analysis (PCoA), obtained with EMPeror. We carried out the analysis of beta diversity using the unweighted UniFrac index. UniFrac is a measure of beta diversity that uses phylogenetic information to compare samples belonging to the interest groups, in this case four. The unweighted version is qualitative. Therefore, UniFrac measures concordance based on the abundance of OTUs in each sample, including also phylogenetic distances. The matrices with beta diversity measurements were analysed for differences in composition according the group they belong to (type of sample) by • Consent for publication: All included patients signed informed consent prior to participating in the study.
• Availability of data and material: The datasets generated and/or analysed during the current study are not publicly available because they contain patients' personal data and the results of their microbioma pattern analysis in addition to sociodemographical parameters, but they are available from the corresponding author on reasonable request.
• Competing interests: The authors declare they have no competing interests.
• Funding: Figure 1 Description of the patients and total samples included in the study Figure 2 Linear mixed effects models test (a) for the gestation rate (b) for the study group