Vaginal Microbiota in Pregnancy: Evaluation Based on Vaginal Flora, Birth Outcome, and Race

Abstract

Objective This study aims to evaluate vaginal microbiota differences by bacterial vaginosis (BV), birth timing, and race, and to estimate parameters to power future vaginal microbiome studies.

Methods Previously, vaginal swabs were collected at 21 to 25 weeks (stored at −80°C), and vaginal smears evaluated for BV (Nugent criteria). In a blinded fashion, 40 samples were selected, creating 8 equal-sized groups stratified by race (black/white), BV (present/absent), and birth timing (preterm/term). Samples were thawed, DNA extracted, and prepared. Polymerase chain reaction (PCR) with primers targeting the 16S rDNA V4 region was used to prepare an amplicon library. PCR products were sequenced and analyzed using quantitative insight into microbial ecology; taxonomy was assigned using ribosomal database program classifier (threshold 0.8) against the modified Greengenes database.

Results After quality control, 97,720 sequences (mean) per sample, single-end 250 base-reads, were analyzed. BV samples had greater microbiota diversity (p < 0.05)—with BVAB1, Prevotella, and unclassified genus, Bifidobacteriaceae family (all p < 0.001) more abundant; there was minimal content of Gardnerella or Mobiluncus. Microbiota did not differ by race or birth timing, but there was an association between certain microbial clusters and preterm birth (p = 0.07). To evaluate this difference, 159 patients per group are needed.

Conclusions There are differences in the vaginal microbiota between patients with and without BV. Larger studies should assess the relationship between microbiota composition and preterm birth.

Keywords

bacterial vaginosis - birth timing - pregnancy - race - vaginal microbiome

Note

The authors report no conflicts of interest. This study was presented in part at the 34rd Annual Meeting of the Society for Maternal-Fetal Medicine; February 6–10, 2014; New Orleans, LA and the Annual Meeting of the Infectious Diseases Society for Obstetrics and Gynecology; August 7–9, 2014; Stowe, VT.

• References

• 1 Costello EK, Lauber CL, Hamady M, Fierer N, Gordon JI, Knight R. Bacterial community variation in human body habitats across space and time. Science 2009; 326 (5960) 1694-1697
• 2 Gupta K, Stapleton AE, Hooton TM, Roberts PL, Fennell CL, Stamm WE. Inverse association of H2O2-producing lactobacilli and vaginal Escherichia coli colonization in women with recurrent urinary tract infections. J Infect Dis 1998; 178 (2) 446-450
• 3 Sobel JD. Is there a protective role for vaginal flora?. Curr Infect Dis Rep 1999; 1 (4) 379-383
• 4 Klebanoff SJ, Hillier SL, Eschenbach DA, Waltersdorph AM. Control of the microbial flora of the vagina by H2O2-generating lactobacilli. J Infect Dis 1991; 164 (1) 94-100
• 5 Voravuthikunchai SP, Bilasoi S, Supamala O. Antagonistic activity against pathogenic bacteria by human vaginal lactobacilli. Anaerobe 2006; 12 (5–6) 221-226
• 6 Srinivasan S, Fredricks DN. The human vaginal bacterial biota and bacterial vaginosis. Interdiscip Perspect Infect Dis 2008; 2008: 750479
• 7 Fredricks DN, Fiedler TL, Marrazzo JM. Molecular identification of bacteria associated with bacterial vaginosis. N Engl J Med 2005; 353 (18) 1899-1911
• 8 Ravel J, Gajer P, Abdo Z , et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A 2011; 108 (1) (Suppl. 01) 4680-4687
• 9 Nugent RP, Krohn MA, Hillier SL. Reliability of diagnosing bacterial vaginosis is improved by a standardized method of gram stain interpretation. J Clin Microbiol 1991; 29 (2) 297-301
• 10 Neggers Y, Goldenberg R, Cliver S, Hauth J. Effects of domestic violence on preterm birth and low birth weight. Acta Obstet Gynecol Scand 2004; 83 (5) 455-460
• 11 Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 2013; 79 (17) 5112-5120
• 12 Kumar R, Eipers P, Little RB , et al. Getting started with microbiome analysis: sample acquisition to bioinformatics. Curr Protoc Hum Genet 2014; 82: 1 , 29
• 13 Caporaso JG, Lauber CL, Walters WA , et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A 2011; 108 (Suppl. 01) 4516-4522
• 14 Liu Z, Lozupone C, Hamady M, Bushman FD, Knight R. Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic Acids Res 2007; 35 (18) e120
• 15 Caporaso JG, Lauber CL, Walters WA , et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 2012; 6 (8) 1621-1624
• 16 Kuczynski J, Lauber CL, Walters WA , et al. Experimental and analytical tools for studying the human microbiome. Nat Rev Genet 2012; 13 (1) 47-58
• 17 Liu Z, DeSantis TZ, Andersen GL, Knight R. Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers. Nucleic Acids Res 2008; 36 (18) e120
• 18 Mizrahi-Man O, Davenport ER, Gilad Y. Taxonomic classification of bacterial 16S rRNA genes using short sequencing reads: evaluation of effective study designs. PLoS ONE 2013; 8 (1) e53608
• 19 Nelson MC, Morrison HG, Benjamino J, Grim SL, Graf J. Analysis, optimization and verification of Illumina-generated 16S rRNA gene amplicon surveys. PLoS ONE 2014; 9 (4) e94249
• 20 Navas-Molina JA, Peralta-Sánchez JM, González A , et al. Advancing our understanding of the human microbiome using QIIME. Methods Enzymol 2013; 531 (531) 371-444
• 21 Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 2010; 26 (2) 266-267
• 22 Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010; 26 (19) 2460-2461
• 23 Lozupone C, Hamady M, Knight R. UniFrac—an online tool for comparing microbial community diversity in a phylogenetic context. BMC Bioinformatics 2006; 7 (7) 371
• 24 Lozupone CA, Hamady M, Kelley ST, Knight R. Quantitative and qualitative beta diversity measures lead to different insights into factors that structure microbial communities. Appl Environ Microbiol 2007; 73 (5) 1576-1585
• 25 McDonald D, Price MN, Goodrich J , et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 2012; 6 (3) 610-618
• 26 Caporaso JG, Kuczynski J, Stombaugh J , et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 2010; 7 (5) 335-336
• 27 Vázquez-Baeza Y, Pirrung M, Gonzalez A, Knight R. EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience 2013; 2 (1) 16
• 28 Thies FL, König W, König B. Rapid characterization of the normal and disturbed vaginal microbiota by application of 16S rRNA gene terminal RFLP fingerprinting. J Med Microbiol 2007; 56 (Pt 6): 755-761
• 29 Romero R, Hassan SS, Gajer P , 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
• 30 Aagaard K, Riehle K, Ma J , et al. A metagenomic approach to characterization of the vaginal microbiome signature in pregnancy. PLoS ONE 2012; 7 (6) e36466
• 31 Hyman RW, Fukushima M, Jiang H , et al. Diversity of the vaginal microbiome correlates with preterm birth. Reprod Sci 2014; 21 (1) 32-40