Skip to main content

Advertisement

SpringerLink
Log in

The dynamics of the vaginal microbiome during infertility therapy with in vitro fertilization-embryo transfer

  • ASSISTED REPRODUCTION TECHNOLOGIES
  • Published:
Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

Purpose

To determine the vaginal microbiome in women undergoing IVF-ET and investigate correlations with clinical outcomes.

Methods

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.

Results

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.

Conclusions

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.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

Abbreviations

AP:

Antagonist Protocol

B:

At baseline

DH:

Demi-Halt Protocol

E2 :

Estradiol

GE:

After 6-to-8 weeks of gestation

GnRH:

Gonadotropin-releasing hormone

hCG:

Human chorionic gonadotropin

IRB:

Institutional Review Board

IVF-ET:

In vitro fertilization-embryo transfer

LF:

At late follicular stage

LLP:

Long Luteal Protocol

MFP:

Microflare Protocol

P4 :

Progesterone

PCA:

Principal Component Analysis

RDP:

Ribosomal Database Project

rDNA:

The 16S ribosomal RNA gene

SDI:

Shannon Diversity Index

SGTC:

Stanford Genome Technology Center

TR:

At embryo transfer

UCSF:

University of California San Francisco

VLDL:

Very Low Dose leuprolide acetate Protocol

References

  1. Bezirtzoglou E, Voidarou Ch, Papadaki A, Tsiotsias A, Kotsovolou O, et al. Hormone therapy alters the composition of the vaginal flora in ovariectomized rats. Microb Ecol. 2008;55:751–9.

    Article  PubMed  CAS  Google Scholar 

  2. Schloss PD, Handelsman J. Status of the microbial census. Microbiol Mol Biol Rev. 2004;68:686–91.

    Article  PubMed  Google Scholar 

  3. Hyman RW, Fukushima M, Diamond L, Kumm J, Giudice LC, Davis RW. Microbes on the Human Vaginal Epithelium. Proc Natl Acad Sci USA. 2005;102:7952–7.

    Article  PubMed  CAS  Google Scholar 

  4. Selman H, Mariani M, Barnocchi N, Mencacci A, Bistoni F, 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;24:395–9.

    Article  PubMed  Google Scholar 

  5. Hyman RW, Jiang H, Fukushima M, Davis RW. A direct comparison of the KB Basecaller and phred for identifying the bases from DNA sequencing using chain termination chemistry. BMC Research Notes. 2010;3:257.

    Article  PubMed  Google Scholar 

  6. Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, Kulam-Syed-Mohideen AS, McGarrell DM, Marsh T, Garrity GM, Tiedje JM. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 2009;37:D141–5. Database issue.

    Article  PubMed  CAS  Google Scholar 

  7. Wayne LG, Brenner DJ, Colwell RR, Grimont PAD, Kandler O, et al. Report of the ad-hoc-committee on reconciliation of approaches to bacterial systematics. Int J Syst Bacteriol. 1987;37:463–4.

    Article  Google Scholar 

  8. Pace NR. A molecular view of microbial diversity and the biosphere. Science. 1997;276:734–40.

    Article  PubMed  CAS  Google Scholar 

  9. Stackebrandt E, Frederiksen W, Garrity GM, Grimont PA, Kämpfer P. Report of the ad hoc committee for the re-evaluation of the species definition in bacteriology. Int J Syst Evol Microbiol. 2002;52(3):1043–7.

    Article  PubMed  CAS  Google Scholar 

  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.

    Article  PubMed  CAS  Google Scholar 

  11. Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R. UniFrac: an effective distance metric for microbial community comparison. ISME J. 2011;5:169–72.

    Article  PubMed  Google 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.

    PubMed  CAS  Google Scholar 

  13. Shannon CE. A mathematical theory of communication. Bell System Technical Journal. 1948;27:379–423. 623–656.

    Google Scholar 

  14. Hughes JB, Hellmann JJ, Ricketts TH, Bohannan BJM. Counting the Uncountable: Statistical Approaches to Estimating Microbial Diversity. Appl Environ Micro. 2001;67:4399–406.

    Article  CAS  Google Scholar 

  15. Fredricks DN, Fiedler TL, Marrazzo JM. Molecular identification of bacteria associated with bacterial vaginosis. N Engl J Med. 2005;353:1899–911.

    Article  PubMed  CAS  Google Scholar 

  16. Oakley BB, Fiedler TL, Marrazzo JM, Fredricks DN. Diversity of human vaginal bacterial communities and associations with clinically defined bacterial vaginosis. Appl Environ Microbiol. 2008;74:4898–909.

    Article  PubMed  CAS  Google Scholar 

  17. Ravel J, Gajer P, Abdo Z, Schneider GM, Koenig SS, McCulle SL, Karlebach S, Gorle R, Russell J, Tacket CO, Brotman RM, Davis CC, Ault K, Peralta L, Forney LJ. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A. 2011;108 Suppl 1:4680–7.

    Article  PubMed  CAS  Google Scholar 

  18. Forney LJ, Gajer P, Williams CJ, Schneider GM, Koenig SS, et al. Comparison of self-collected and physician-collected vaginal swabs for microbiome analysis. J Clin Microbiol. 2010;48:1741–8.

    Article  PubMed  CAS  Google Scholar 

  19. Jakobsson T, Forsum U. Changes in the predominant human Lactobacillus flora during in vitro fertilisation. Ann Clin Microbiol Antimicrob. 2008;7:14–21.

    Article  PubMed  Google Scholar 

  20. Witkin SS, Kligman II, Grifo JA, Rosenwaks Z. Chlamydia trachomatis detected by polymerase chain reaction in cervices of culture-negative women correlates with adverse in vitro fertilization outcome. J Infect Dis. 1995;17:1657–659.

    Article  Google Scholar 

  21. Liversedge NH, Turner A, Horner PJ, Keay SD, Jenkins JM, et al. The influence of bacterial vaginosis on in vitro fertilization and embryo implantation during assisted reproduction treatment. Hum Reprod. 1999;14:2411–5.

    Article  PubMed  CAS  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.

    PubMed  CAS  Google Scholar 

  23. Egbase PE, Udo EE, Al-Sharhan M, et al. Prophylactic antibiotics and endocervical microbial inoculation of the endometrium at embryo transfer. Lancet. 1999;354:651–2.

    Article  PubMed  CAS  Google Scholar 

  24. Fanchin R, Harmas A, Benaoudia F, Lundkvist U, Oliveness F, et al. (Microbials of the cervix assessed at the time of embryo transfer adversely affects in vitro fertilization outcome. Fertil Steril. 1998;70:866–70.

    Article  PubMed  CAS  Google Scholar 

  25. Moore DE, Soules MR, Klein NA, Fujimoto VY, Agnew KJ, et al. Bacteria in the transfer catheter tip influence the live-birth rate after in vitro fertilization. Fertil Steril. 2000;74:1118–24.

    Article  PubMed  CAS  Google 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.

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

We thank Liza Jalalian and Shehua Shen for assistance with the measurement of the serum hormone concentrations, and Monika Trebo for posting the CEL files on the Stanford Genome Technology Center website.

This work was supported by National Human Genome Research Institute grant P01 HG000205 (RWD, LCG).

Competing interests statement

The authors declare no competing financial interests.

Author information

Authors and Affiliations

  1. Department of Biochemistry, Stanford University, Stanford, CA, USA

    Richard W. Hyman, Curtis Palm & Ronald W. Davis

  2. Department of Stanford Genome Technology Center, Stanford University, Stanford, CA, USA

    Richard W. Hyman, Hui Jiang, Curtis Palm, Marilyn Fukushima & Ronald W. Davis

  3. Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, 505 Parnassus Avenue, Room M1496, San Francisco, CA, USA, 94143-0132

    Christopher N. Herndon, Denise Bernstein, Kim Chi Vo, Zara Zelenko & Linda C. Giudice

  4. Department of Statistics, Stanford University, Stanford, CA, USA

    Hui Jiang

  5. Department of Genetics, Stanford University, Stanford, CA, USA

    Ronald W. Davis

  6. Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA

    Hui Jiang

Authors
  1. Richard W. Hyman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christopher N. Herndon
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Hui Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Curtis Palm
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Marilyn Fukushima
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Denise Bernstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kim Chi Vo
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Zara Zelenko
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ronald W. Davis
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Linda C. Giudice
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Linda C. Giudice.

Additional information

Author contributions

RWH and LCG designed the experiments and wrote this manuscript. CNH developed the clinical database of IVF-ET patients and coordinated running the hormone assays. HJ performed several of the statistical analyses. CP applied UniFrac to the data and undertook the QIIME analyses. MF carried out the sequencing reactions, processed and assembled the sequence reads, and compared the consensus sequences to the data in the RDP. MF and RWH hand edited the contigs. KCV and DB identified appropriate patients, screened and enrolled patients, facilitated UCSF IRB compliance and sample collection, and transfer to the SGTC. ZZ measured the hormone concentrations. RWD provided the intellectual, physical, and financial milieu for the experiments at the SGTC.

Capsule

Metagenomics was used to determine the vaginal microbiome in IVF-ET cycles. Diversity of species varied in 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.

Electronic supplementary materials

Below is the link to the electronic supplementary material.

ESM 1

(DOC 159 kb)

ESM 2

(DOC 51 kb)

ESM 3

(DOC 85 kb)

ESM 4

(DOC 86 kb)

ESM 5

(DOC 683 kb)

ESM 6

(DOC 56 kb)

ESM 7

(DOC 570 kb)

ESM 8

(DOC 30 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hyman, R.W., Herndon, C.N., Jiang, H. et al. The dynamics of the vaginal microbiome during infertility therapy with in vitro fertilization-embryo transfer. J Assist Reprod Genet 29, 105–115 (2012). https://doi.org/10.1007/s10815-011-9694-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10815-011-9694-6

Keywords

Search

Navigation