Skip to main content
Log in

Intrauterine Growth Restriction Is Associated with Unique Features of the Reproductive Microbiome

  • Maternal Fetal Medicine/Biology: Original Article
  • Published:
Reproductive Sciences Aims and scope Submit manuscript

Abstract

Intrauterine growth restriction (IUGR) is an obstetrical complication with an increased risk of perinatal mortality and morbidity. The uterus, once considered to be a sterile environment, has now been described in recent microbiome studies to harbor diverse commensal placenta microbiota, as well as potentially pathogenic flora known to cause infection. Therefore, in this pilot study, we tested whether IUGR was associated with changes to the reproductive microbiome. The reproductive microbiome was surveyed using 16S sequencing (20 IUGR, 20 controls). Alpha and beta diversity were compared, and differential taxa features associated with IUGR were identified. Microbial screening of the placenta demonstrated a diverse range of flora predominantly including Proteobacteria, Fusobacteria, Firmicutes, and Bacteroidetes. Neither alpha- nor beta-diversity was significantly different by IUGR status. However, at the taxa level, IUGR patients had significantly higher prevalence of Neisseriaceae, mucosal β-hemolytic bacteria known to uptake iron-bound host proteins including hemoglobin. Moreover, the increase in anaerobic bacteria such as Desulfovibrio reflects the emergence of a hypoxic environment in the IUGR placenta. Further analysis of the reproductive microbiome of IUGR samples showed lower levels of H202-producing Bifidobacterium and Lactobacillus that switch from respiration to fermentation, a less energetic metabolic process, when oxygen levels decrease. Source tracking analysis showed that the placental microbial contents were predominantly contributed from an oral source, as compared to a gut or vaginal source. Our results suggest that the reproductive microbiome profiles may, in the future, constitute potential biomarkers for fetal health during pregnancy, while Neisseriaceae may constitute promising therapeutic targets for IUGR treatment.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Data Availability

16S rRNA gene sequencing data has been deposited into the EMBL Nucleotide Sequence Database (ENA) with Project ID PRJEB25504.

References

  1. Mandruzzato G, Antsaklis A, Botet F, Chervenak FA, Figueras F, Grunebaum A, et al. Intrauterine restriction (IUGR). J Perinat Med. 2008;36(4):277–81. https://doi.org/10.1515/JPM.2008.050.

    Article  PubMed  Google Scholar 

  2. Lausman A, On T, Kingdom J, et al. Intrauterine growth restriction: screening, diagnosis, and management Maternal Fetal Medicine Committee. J Obstet Gynaecol Can. 2013;74135(2958):741–8.

    Article  Google Scholar 

  3. Lawn JE, Cousens S, Zupan J. 4 Million neonatal deaths: when? Where? Why? Lancet. 2005;365(9462):891–900. https://doi.org/10.1016/S0140-6736(05)71048-5.

    Article  PubMed  Google Scholar 

  4. Romo A, Carceller R, Tobajas J. Intrauterine growth retardation (IUGR): epidemiology and etiology. Pediatr Endocrinol Rev. 2009;6(Suppl 3):332–6.

    PubMed  Google Scholar 

  5. Sharma D, Shastri S, Sharma P. Intrauterine growth restriction: antenatal and postnatal aspects. Clin Med Insights Pediatr. 2016;10:67–83. https://doi.org/10.4137/CMPed.S40070.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Aditya I, Tat V, Sawana A, Mohamed A, Tuffner R, Mondal T. Use of Doppler velocimetry in diagnosis and prognosis of intrauterine growth restriction (IUGR): a review. J Neonatal-Perinatal Med. 2016;9(2):117–26. https://doi.org/10.3233/NPM-16915132.

    Article  CAS  PubMed  Google Scholar 

  7. Griffiths SK, Campbell JP. Placental structure, function and drug transfer. Contin Educ Anaesth Crit Care Pain. 2015;15(2):84–9. https://doi.org/10.1093/bjaceaccp/mku013.

    Article  Google Scholar 

  8. Jiménez E, Marín ML, Martín R, Odriozola JM, Olivares M, Xaus J, et al. Is meconium from healthy newborns actually sterile? Res Microbiol. 2008;159(3):187–93. https://doi.org/10.1016/j.resmic.2007.12.007.

    Article  CAS  PubMed  Google Scholar 

  9. Stout MJ, Conlon B, Landeau M, Lee I, Bower C, Zhao Q, et al. Identification of intracellular bacteria in the basal plate of the human placenta in term and preterm gestations. Am J Obstet Gynecol. 2013;208(3):226.e1–7. https://doi.org/10.1016/j.ajog.2013.01.018.

    Article  Google Scholar 

  10. DiGiulio DB. Diversity of microbes in amniotic fluid. Semin Fetal Neonatal Med. 2012;17(1):2–11. https://doi.org/10.1016/j.siny.2011.10.001.

    Article  PubMed  Google Scholar 

  11. Collado MC, Rautava S, Aakko J, Isolauri E, Salminen S. Human gut colonisation may be initiated in utero by distinct microbial communities in the placenta and amniotic fluid. Sci Rep. 2016;6:23129. https://doi.org/10.1038/srep23129.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Urushiyama D, Suda W, Ohnishi E, Araki R, Kiyoshima C, Kurakazu M, et al. Microbiome profile of the amniotic fluid as a predictive biomarker of perinatal outcome. Sci Rep. 2017;7(1):12171. https://doi.org/10.1038/s41598-017-11699-8.

  13. Zheng J, Xiao X, Zhang Q, Mao L, Yu M, Xu J. The placental microbiome varies in association with low birth weight in full-term neonates. Nutrients. 2015;7(8):6924–37. https://doi.org/10.3390/nu7085315.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Aagaard K, Ma J, Antony KM, Ganu R, Petrosino J, Versalovic J. The placenta harbors a unique microbiome. Sci Transl Med. 2014;6(237):237ra65. https://doi.org/10.1126/scitranslmed.3008599.

  15. Antony KM, Ma J, Mitchell KB, Racusin DA, Versalovic J, Aagaard K. The preterm placental microbiome varies in association with excess maternal gestational weight gain. Am J Obstet Gynecol. 2015;212(5):653.e1–653.e16. https://doi.org/10.1016/j.ajog.2014.12.041.

    Article  Google Scholar 

  16. Prince A, Ma J, Kannan P, Alvarez M, Gisslen T, Antony K, et al. 122: the microbiome of the placenta is altered among subjects with severe chorioamnionitis & spontaneous preterm birth. Am J Obstet Gynecol. 2015;212(1):S78–9. https://doi.org/10.1016/j.ajog.2014.10.168.

    Article  Google Scholar 

  17. Cao B, Stout MJ, Lee I, Mysorekar IU. Placental microbiome and its role in preterm birth. Neoreviews. 2014;15(12):e537–45. https://doi.org/10.1542/neo.15-12-e537.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Human Microbiome Project C. A framework for human microbiome research. Nature. 2012;486(7402):215–21. https://doi.org/10.1038/nature11209.

    Article  CAS  Google Scholar 

  19. Huttenhower C. Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486(7402):207–14. https://doi.org/10.1038/nature11234.

    Article  CAS  Google Scholar 

  20. Hewitt KM, Mannino FL, Gonzalez A, et al. Bacterial diversity in two neonatal intensive care units (NICUs). PLoS One. 2013;8(1). doi:https://doi.org/10.1371/journal.pone.0054703.

  21. Kang M, Mischel RA, Bhave S, Komla E, Cho A, Huang C, et al. The effect of gut microbiome on tolerance to morphine mediated antinociception in mice. Sci Rep. 2017;7. https://doi.org/10.1038/srep42658.

  22. Nossa CW, Oberdorf WE, Yang L, Aas JA, Paster BJ, Desantis TZ, et al. Design of 16S rRNA gene primers for 454 pyrosequencing of the human foregut microbiome. World J Gastroenterol. 2010;16(33):4135–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Hu J, Raikhel V, Gopalakrishnan K, Fernandez-Hernandez H, Lambertini L, Manservisi F, et al. Effect of postnatal low-dose exposure to environmental chemicals on the gut microbiome in a rodent model. Microbiome. 2016;4:26. https://doi.org/10.1186/s40168-016-0173-2.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Torres J, Bao X, Goel A, Colombel JF, Pekow J, Jabri B, et al. The features of mucosa-associated microbiota in primary sclerosing cholangitis. Aliment Pharmacol Ther. 2016;43(7):790–801. https://doi.org/10.1111/apt.13552.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Masella AP, Bartram AK, Truszkowski JM, Brown DG, Neufeld JD. PANDAseq: paired-end assembler for illumina sequences. BMC Bioinf. 2012;13(1):31. https://doi.org/10.1186/1471-2105-13-31.

    Article  CAS  Google Scholar 

  26. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6. https://doi.org/10.1038/nmeth.f.303.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Bray JR, Curtis JT. An ordination of the upland forest communities of Southern Wisconsin. Ecol Monogr. 1957;27(4):325–49. https://doi.org/10.2307/1942268.

    Article  Google Scholar 

  28. Anderson MJ. A new method for non parametric multivariate analysis of variance. Austral Ecol. 2001;26(2001):32–46. https://doi.org/10.1111/j.1442-9993.2001.01070.pp.x.

    Article  Google Scholar 

  29. Oksanen J. Multivariate analysis of ecological communities in R: vegan tutorial. R Doc 2015:43. doi:https://doi.org/10.1016/0169-5347(88)90124-3.

  30. Shannon CE. A mathematical theory of communication. Bell Syst Tech J. 1948;27(July 1928):379–423. https://doi.org/10.1145/584091.584093.

    Article  Google Scholar 

  31. Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12(6):R60. https://doi.org/10.1186/gb-2011-12-6-r60.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Caporaso JG, Lauber CL, Walters WA, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. PNAS. 2010. https://doi.org/10.1073/pnas.1000080107/-/DCSupplemental.www.pnas.org/cgi/doi/10.1073/pnas.1000080107.

  33. Bassols J, Serino M, Carreras-Badosa G, Burcelin R, Blasco-Baque V, Lopez-Bermejo A, et al. Gestational diabetes is associated with changes in placental microbiota and microbiome. Pediatr Res. 2016;80(6):777–84. https://doi.org/10.1038/pr.2016.155.

    Article  CAS  PubMed  Google Scholar 

  34. Doyle RM, Harris K, Kamiza S, et al. Bacterial communities found in placental tissues are associated with severe chorioamnionitis and adverse birth outcomes. PLoS One. 2017;12(7). doi:https://doi.org/10.1371/journal.pone.0180167.

  35. Amarasekara R, Jayasekara RW, Senanayake H, Dissanayake VH. Microbiome of the placenta in pre-eclampsia supports the role of bacteria in the multifactorial cause of pre-eclampsia. J Obstet Gynaecol Res. 2015;41(5):662–9. https://doi.org/10.1111/jog.12619.

    Article  CAS  PubMed  Google Scholar 

  36. Koliada A, Syzenko G, Moseiko V, Budovska L, Puchkov K, Perederiy V, et al. Association between body mass index and Firmicutes/Bacteroidetes ratio in an adult Ukrainian population. BMC Microbiol. 2017;17:120. https://doi.org/10.1186/s12866-017-1027-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, et al. Bayesian community-wide culture-independent microbial source tracking. Nat Methods. 2011;8(9):761–5. https://doi.org/10.1038/nmeth.1650.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Ley RE, Bäckhed F, Turnbaugh P, Lozupone CA, Knight RD, Gordon JI. Obesity alters gut microbial ecology. Proc Natl Acad Sci U S A. 2005;102(31):11070–5. https://doi.org/10.1073/pnas.0504978102.

    Article  CAS  Google Scholar 

  39. Ley R, Turnbaugh P, Klein S, Gordon J. Microbial ecology: human gut microbes associated with obesity. Nature. 2006;444(7122):1022–3. https://doi.org/10.1038/nature4441021a.

    Article  CAS  PubMed  Google Scholar 

  40. Saini R, Saini S, Saini S. Periodontitis: a risk for delivery of premature labor and low-birth-weight infants. J Nat Sci Biol Med. 2010;1(1):40–2. https://doi.org/10.4103/0976-9668.71672.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Gomes-Filho IS, Pereira EC, Cruz SS, Adan LFF, Vianna MIP, Passos-Soares JS, et al. Relationship among mothers’ glycemic level, periodontitis, and birth weight. J Periodontol. 2016;87(3):238–47. https://doi.org/10.1902/jop.2015.150423.

    Article  PubMed  Google Scholar 

  42. Dasanayake AP, Li Y, Wiener H, Ruby JD, Lee M-J. Salivary Actinomyces naeslundii Genospecies 2 and Lactobacillus casei levels predict pregnancy outcomes. J Chem Inf Model. 2005;76(2):171–7. https://doi.org/10.1017/CBO9781107415324.004.

    Article  Google Scholar 

  43. Satokari R, Grönroos T, Laitinen K, Salminen S, Isolauri E. Bifidobacterium and Lactobacillus DNA in the human placenta. Lett Appl Microbiol. 2009;48(1):8–12. https://doi.org/10.1111/j.1472-765X.2008.02475.x.

    Article  CAS  PubMed  Google Scholar 

  44. Fardini Y, Chung P, Dumm R, Joshi N, Han YW. Transmission of diverse oral bacteria to murine placenta: evidence for the oral microbiome as a potential source of intrauterine infection. Infect Immun. 2010;78(4):1789–96. https://doi.org/10.1128/IAI.01395-09.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Gomez-Arango LF, Barrett HL, McIntyre HD, Callaway LK, Morrison M, Nitert MD. Contributions of the maternal oral and gut microbiome to placental microbial colonization in overweight and obese pregnant women. Sci Rep. 2017;7(1). doi:https://doi.org/10.1038/s41598-017-03066-4.

  46. Lauder AP, Roche AM, Sherrill-Mix S, Bailey A, Laughlin AL, Bittinger K, et al. Comparison of placenta samples with contamination controls does not provide evidence for a distinct placenta microbiota. Microbiome. 2016;4:29. https://doi.org/10.1186/s40168-016-0172-3.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Perez-Muñoz ME, Arrieta MC, Ramer-Tait AE, Walter J. A critical assessment of the “sterile womb” and “in utero colonization” hypotheses: implications for research on the pioneer infant microbiome. Microbiome. 2017;5(1). doi:https://doi.org/10.1186/s40168-017-0268-4.

  48. Borghi E, Massa V, Severgnini M, Fazio G, Avagliano L, Menegola E, et al. Antenatal microbial colonisation of mammalian gut. Reprod Sci. 2019;26(8):1045–53. https://doi.org/10.1101/236190.

    Article  CAS  PubMed  Google Scholar 

  49. De Agüero MG, Ganal-Vonarburg SC, Fuhrer T, et al. The maternal microbiota drives early postnatal innate immune development. Science (80- ). 2016;351(6279):1296–302. https://doi.org/10.1126/science.aad2571.

    Article  CAS  Google Scholar 

  50. Wong CT, Xu Y, Gupta A, Garnett JA, Matthews SJ, Hare SA. Structural analysis of haemoglobin binding by HpuA from the Neisseriaceae family. Nat Commun. 2015;6:10172. https://doi.org/10.1038/ncomms10172.

    Article  CAS  PubMed  Google Scholar 

  51. Jones R, Peña J, Mystal E, Marsit C, Lee M, Stone J, et al. Mitochondrial and glycolysis-regulatory gene expression profiles are associated with intrauterine growth restriction. J Matern Fetal Neonatal Med. 2020;33(8):1336–45.

    CAS  PubMed  Google Scholar 

Download references

Acknowledgments

We thank the OCS genome technology center of the New York University Langone Medical Center for the library preparation and sequencing services.

Funding

This work was funded by the MSSM seed fund (JZH), Henan provincial science and technology research and development special funds #182102410020 (YJX), and NICHD HD00849/RSDP/Wyeth (MJL).

Author information

Authors and Affiliations

Authors

Contributions

JZH supported this study, designed the study, performed sequencing analysis and bioinformatics, and drafted the manuscript. MW, YM, and LL collected and processed the samples and performed 16S PCR experiments. IP supported the study, participated in the design of the study, and helped to draft the manuscript. YJX supervised the design of the study and helped to draft the manuscript. MJL conceived the overall study, supervised all the experiments, collected clinical samples and clinical information, and coordinated and drafted the manuscript. PB wrote and revised the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Men-Jean Lee.

Ethics declarations

This study was approved by the Institutional Review Board at the Icahn School of Medicine at Mount Sinai.

Conflict of Interest

The authors declare that they have no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Figure S1

Measurement of bacterial loading and richness of bacterial community in placental samples. 1A. Measurement of bacterial loading. The relative bacterial loading was calculated using the base 2 with the exponent of the difference between the real-time PCR Cp values from the bacterial 16S rDNA gene and the human beta-actin gene. 1B. Measurement of richness of bacterial community in placental samples. Box plots compared the mean and variance of the microbial alpha-diversity measured by Shannon index and Inverse Simpson index between IUGR and AGA placental samples. (PDF 982 kb)

Table S1

Mean comparison of LEfSe selected genera. The mean abundance of LEfSe selected genera was compared between IUGR and normal placenta samples between C-section and vaginal deliveries. P-values were obtained from non-parametric Wilcoxon test. (XLSX 9 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hu, J., Benny, P., Wang, M. et al. Intrauterine Growth Restriction Is Associated with Unique Features of the Reproductive Microbiome. Reprod. Sci. 28, 828–837 (2021). https://doi.org/10.1007/s43032-020-00374-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s43032-020-00374-5

Keywords

Navigation