The dynamics of the vaginal microbiome during infertility therapy with in vitro fertilization-embryo transfer
- 661 Downloads
To determine the vaginal microbiome in women undergoing IVF-ET and investigate correlations with clinical outcomes.
Thirty patients had blood drawn for estradiol (E2) and progesterone (P4) at four time points during the IVF-ET cycle and at 4–6 weeks of gestation, if pregnant. Vaginal swabs were obtained in different hormonal milieu, and the vaginal microbiome determined by deep sequencing of the 16S ribosomal RNA gene.
The vaginal microbiome underwent a transition during therapy in some but not all patients. Novel bacteria were found in 33% of women tested during the treatment cycle, but not at 6–8 weeks of gestation. Diversity of species varied across different hormonal milieu, and on the day of embryo transfer correlated with outcome (live birth/no live birth). The species diversity index distinguished women who had a live birth from those who did not.
This metagenomics approach has enabled discovery of novel, previously unidentified bacterial species in the human vagina in different hormonal milieu and supports a shift in the vaginal microbiome during IVF-ET therapy using standard protocols. Furthermore, the data suggest that the vaginal microbiome on the day of embryo transfer affects pregnancy outcome.
KeywordsMetagenomics Vagina Microbiome Infertility IVF Pregnancy
After 6-to-8 weeks of gestation
Human chorionic gonadotropin
Institutional Review Board
In vitro fertilization-embryo transfer
At late follicular stage
Long Luteal Protocol
Principal Component Analysis
Ribosomal Database Project
The 16S ribosomal RNA gene
Shannon Diversity Index
Stanford Genome Technology Center
At embryo transfer
University of California San Francisco
Very Low Dose leuprolide acetate Protocol
- 10.Caporaso JG, Kucynski J, Stombaugh J, Bittner K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widman J, Yatsunenko T, Zaneveld J, Knight R. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.PubMedCrossRefGoogle Scholar
- 12.Roseboom TJ, Vermeiden JPW, Schoute E, Lens JW, Schats R. The probability of pregnancy after embryo transfer is affected by the age of the patient, cause of infertility, number of embryos transferred and the average morphology score, as revealed by multiple logistic regression analysis. Hum Reprod. 1995;10:3035–41.PubMedGoogle Scholar
- 13.Shannon CE. A mathematical theory of communication. Bell System Technical Journal. 1948;27:379–423. 623–656.Google Scholar
- 22.Egbase PE, Al-Sharhan M, Al-Othman S, Al-Mutawa M, Udo EE, et al. Incidence of microbial growth from the tip of the embryo transfer catheter after embryo transfer in relation to the clinical pregnancy rate following in vitro fertilization and embryo transfer. Hum Reprod. 1996;11:1687–9.PubMedGoogle Scholar
- 26.Kim YJ, Ku SY, Jee BC, Suh CS, Kim SH, Choi YM, Kim JG, Moon SY. Dynamics of early estradiol production may be associated with outcomes of in vitro fertilization. Fertil Steril. 2010;94:2866–70.Google Scholar
- 27.Var T, Tonguc E, Dogan M, Mollamahmutoglu L. Relationship between the oestradiol/oocyte ratio and the outcome of assisted reproductive technology cycles with gonadotropin releasing hormone agonist. Gynecol Endocrinol. 2011;27(8):558–61. Epub 2010 Jul 20. PubMed PMID: 20642381.PubMedCrossRefGoogle Scholar