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Effect of the vaginal microbiome on the pregnancy rate in women receiving assisted reproductive treatment

Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

Purpose

To investigate if the vaginal microbiome influences the IVF outcome.

Methods

Thirty-one patients undergoing assisted reproductive treatment (ART) with own or donated gametes and with cryotransfer of a single euploid blastocyst were recruited for this cohort study. Two vaginal samples were taken during the embryo transfer procedure, just before transferring the embryo. The V3 V4 region of 16S rRNA was used to analyze the vaginal microbiome, and the bioinformatic analysis was performed using QIIME2, Bioconductor Phyloseq, and MicrobiomeAnalyst packages. Alpha diversity was compared between groups according to the result of the pregnancy test.

Results

Fourteen (45.2%) patients did not and seventeen (54.8 %) did achieve pregnancy under ART. A greater index of alpha diversity was found in patients who did not achieve pregnancy comparing to those who did, although this difference was not significant (p = 0.088). In the analysis of beta diversity, no statistically significant differences were observed between groups established as per the pregnancy status. Samples from women who achieved pregnancy showed a greater presence of Lactobacillus spp. The cluster analysis identified two main clusters: the first encompassed the genera Lactobacillus, Gardnerella, Clostridium, Staphylococcus, and Dialister, and the second included all other genera. Women who achieved pregnancy were mainly detected microorganisms from the first cluster.

Conclusions

The vaginal microbiome can influence the results of ART. The profiles dominated by Lactobacillus were associated with the achievement of pregnancy, and there was a relationship between the stability of the vaginal microbiome and the achievement of pregnancy.

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References

  1. Peñalver Bernabé B, Cralle L, Gilbert JA. Systems biology of the human microbiome. Curr Opin Biotechnol. 2018;51:146–53.

    Article  PubMed  Google Scholar 

  2. Witkin SS, Linhares IM, Giraldo P. Bacterial flora of the female genital tract: function and immune regulation. Best Pract Res Clin Obstet Gynaecol. 2007;21(3):347–54.

    Article  PubMed  Google Scholar 

  3. Mascarenhas MN, Flaxman SR, Boerma T, Vanderpoel S, Stevens GA. National, regional, and global trends in infertility prevalence since 1990: a systematic analysis of 277 health surveys. PLoS Med. 2012;9:e1001356.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Lambert JA, John S, Sobel JD, Akins RA. Longitudinal analysis of vaginal microbiome dynamics in women with recurrent bacterial vaginosis: recognition of the conversion process. PLoS One. 2013;8(12):e82599.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Ralph SG, Rutherford AJ, Wilson JD. Influence of bacterial vaginosis on conception and miscarriage in the first trimester: cohort study. BMJ. 1999;319(7204):220–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Haahr T, Zacho J, Bräuner M, Shathmigha K, Skov Jensen J, Humaidan P. Reproductive outcome of patients undergoing in vitro fertilization treatment and diagnosed with bacterial vaginosis or abnormal vaginal microbiota: a systematic PRISMA review and meta-analysis. BJOG. 2018.

  7. van Oostrum N, De Sutter P, Meys J, Verstraelen H. Risks associated with bacterial vaginosis in infertility patients: a systematic review and meta-analysis. Hum Reprod. 2013a;28(7):1809–15.

    Article  PubMed  Google Scholar 

  8. Romero R, Hassan SS, Gajer P, Tarca AL, Fadrosh DW, Nikita L, et al. The composition and stability of the vaginal microbiota of normal pregnant women is different from that of non-pregnant women. Microbiome. 2014;2(1):4.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Graspeuntner S, Bohlmann MK, Gillmann K, Speer R, Kuenzel S, Mark H, et al. Microbiota-based analysis reveals specific bacterial traits and a novel strategy for the diagnosis of infectious infertility. PLoS One. 2018;13(1):e0191047.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Kyono K, Hashimoto T, Nagai Y, Sakuraba Y. Analysis of endometrial microbiota by 16S ribosomal RNA gene sequencing among infertile patients: a single-center pilot study. Reprod Med Biol. 2018;17:297–306.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Singer M, Borg M, Ouburg S, Morré SA. The relation of the vaginal microbiota to early pregnancy development during in vitro fertilization treatment—a meta-analysis. J Gynecol Obstet Hum Reprod. 2019a;48(4):223–9. https://doi.org/10.1016/j.jogoh.2019.01.007 Review.

    Article  CAS  PubMed  Google Scholar 

  12. Bracewell-Milnes T, Saso S, Nikolaou D, Norman-Taylor J, Johnson M, Thum MY. Investigating the effect of an abnormal cervico-vaginal and endometrial microbiome on assisted reproductive technologies: a systematic review. Am J Reprod Immunol. 2018;80(5):e13037. https://doi.org/10.1111/aji.13037 Review.

    Article  PubMed  Google Scholar 

  13. Kroon SJ, Ravel J, Huston WM. Cervicovaginal microbiota, women’s health, and reproductive outcomes. Fertil Steril. 2018;110(3):327–36. https://doi.org/10.1016/j.fertnstert.2018.06.036 Review.

    Article  PubMed  Google Scholar 

  14. Lawley B, Tannock GW. Analysis of 16S rRNA gene amplicon sequences using the QIIME software package. Methods Mol Biol. 2017;1537:153–63.

    Article  CAS  PubMed  Google Scholar 

  15. Kuczynski J, Stombaugh J, Walters WA, González A, Caporaso JG, Knight R. Using QIIME to analyze 16S rRNA gene sequences from microbial communities. Curr Protoc Microbiol. 2012; Chapter 1:Unit 1E.5.

  16. McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE. 2013;8(4):e61217.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Dhariwal A, Chong J, Habib S, King I, Agellon LB, Xia J. MicrobiomeAnalyst - a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data. Nucleic Acids Res. 2017;45:W180–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. MacIntyre DA, Chandiramani M, Lee YS, Kindinger L, Smith A, Angelopoulos N, et al. The vaginal microbiome during pregnancy and the postpartum period in a European population. Sci Rep. 2015;5:8988.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Subramaniam A, Kumar R, Cliver SP, Zhi D, Szychowski JM, Abramovici A, et al. Vaginal microbiota in pregnancy: evaluation based on vaginal flora, birth outcome, and race. Am J Perinatol. 2016;33(4):401–8.

    PubMed  Google Scholar 

  20. Aagaard K, Riehle K, Ma J, Segata N, Mistretta TA, Coarfa C, et al. A metagenomic approach to characterization of the vaginal microbiome signature in pregnancy. PLoS One. 2012;7(6):e36466.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Ravel J, Gajer P, Abdo Z, Schneider GM, Koenig SS, McCulle SL, et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A. 2011;108(Suppl 1):4680–7.

    Article  CAS  PubMed  Google Scholar 

  22. Moreno I, Codoñer FM, Vilella F, Valbuena D, Martinez-Blanch JF, Jimenez-Almazán J, et al. Evidence that the endometrial microbiota has an effect on implantation success or failure. Am J Obstet Gynecol. 2016;215(6):684–703.

    Article  PubMed  Google Scholar 

  23. Walther-António MR, Jeraldo P, Berg Miller ME, Yeoman CJ, Nelson KE, Wilson BA, et al. Pregnancy's stronghold on the vaginal microbiome. PLoS One. 2014;9(6):e98514.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Miller EA, Beasley DAE, Dunn RR, Archie EA. Lactobacilli dominance and vaginal pH: why is the human vaginal microbiome unique? Front Microbiol. 2016;7:1936.

    PubMed  PubMed Central  Google Scholar 

  25. Kyono K, Hashimoto T, Kikuchi S, Nagai Y, Sakuraba Y. A pilot study and case reports on endometrial microbiota and pregnancy outcome: an analysis using 16S rRNA gene sequencing among IVF patients, and trial therapeutic intervention for dysbiotic endometrium. Reprod Med Biol. 2019;18:72–82.

    Article  CAS  PubMed  Google Scholar 

  26. Maduka RN, Osaikhuwuomwan JA, Aziken ME. The effect of bacterial colonization of the embryo transfer catheter on outcome of in vitro fertilization–embryo transfer treatment. Afr J Med Health Sci. 2018;17(1):7–13.

    Article  Google Scholar 

  27. Selman H, Mariani M, Barnocchi N, Mencacci A, Bistoni F, Arena S, et al. Examination of bacterial contamination at the time of embryo transfer, and its impact on the IVF/pregnancy outcome. J Assist Reprod Genet. 2007;24(9):395–9. https://doi.org/10.1007/s10815-007-9146-5.

    Article  PubMed  PubMed Central  Google Scholar 

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Authors and Affiliations

  1. Reproductive Unit, Instituto Bernabeu, 03016, Alicante, Spain

    Andrea Bernabeu, Ana Fuentes, Belen Moliner, Juan Carlos Castillo, Joaquin Llacer & Rafael Bernabeu

  2. Molecular Biology and Genetics Unit, Instituto Bernabeu Biotech, Avda. Albufereta, 31, 03016, Alicante, Spain

    Belén Lledo, Francisca M. Lozano & Jose Antonio Ortiz

  3. Biology of Reproduction Unit, Instituto Bernabeu, 03016, Alicante, Spain

    Ma. Carmen Díaz & Jorge Ten

  4. Nursing Department, Instituto Bernabeu, 03016, Alicante, Spain

    Vicente Ruiz

  5. Chair of Reproductive and Community Medicine, Miguel Hernández University, 03550, San Juan de Alicante, Spain

    Adriana Lopez-Pineda, Concepcion Carratala-Munuera, Domingo Orozco-Beltran & Jose A. Quesada

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  1. Andrea Bernabeu
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  2. Belén Lledo
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  3. Ma. Carmen Díaz
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  6. Ana Fuentes
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  16. Rafael Bernabeu
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Correspondence to Belén Lledo.

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Bernabeu, A., Lledo, B., Díaz, M.C. et al. Effect of the vaginal microbiome on the pregnancy rate in women receiving assisted reproductive treatment. J Assist Reprod Genet 36, 2111–2119 (2019). https://doi.org/10.1007/s10815-019-01564-0

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  • DOI: https://doi.org/10.1007/s10815-019-01564-0

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