Skip to main content

Advertisement

SpringerLink
Log in

Vaginal microbiome and metabolome highlight specific signatures of bacterial vaginosis

  • Original Article
  • Published:
European Journal of Clinical Microbiology & Infectious Diseases Aims and scope Submit manuscript

Abstract

In this study, we sought to find novel bacterial and metabolic hallmarks for bacterial vaginosis (BV). We studied the vaginal microbiome and metabolome of vaginal fluids from BV-affected patients (n = 43) and healthy controls (n = 37) by means of an integrated approach based on quantitative polymerase chain reaction (qPCR) and proton nuclear magnetic resonance (1H-NMR). The correlations between the clinical condition and vaginal bacterial communities were investigated by principal component analysis (PCA). To define the metabolomics signatures of BV, 100 discriminant analysis by projection on latent structure (PLS-DA) models were calculated. Bacterial signatures distinguishing the health condition and BV were identified by qPCR. Lactobacillus crispatus strongly featured the healthy vagina, while increased concentrations of Prevotella, Atopobium and Mycoplasma hominis specifically marked the infection. 1H-NMR analysis has led to the identification and quantification of 17 previously unreported molecules. BV was associated with changes in the concentration of metabolites belonging to the families of amines, organic acids, short chain fatty acids, amino acids, nitrogenous bases and monosaccharides. In particular, maltose, kynurenine and NAD+ primarily characterised the healthy status, while nicotinate, malonate and acetate were the best metabolic hallmarks of BV. This study helps to better understand the role of the vaginal microbiota and metabolome in the development of BV infection. We propose a molecular approach for the diagnosis of BV based on quantitative detection in the vaginal fluids of Atopobium, Prevotella and M. hominis, and nicotinate, malonate and acetate by combining qPCR and 1H-NMR.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Hillier SL, Krohn MA, Cassen E, Easterling TR, Rabe LK, Eschenbach DA (1995) The role of bacterial vaginosis and vaginal bacteria in amniotic fluid infection in women in preterm labor with intact fetal membranes. Clin Infect Dis 20(Suppl 2):S276–S278

    Article  PubMed  Google Scholar 

  2. Drell T, Lillsaar T, Tummeleht L, Simm J, Aaspõllu A, Väin E, Saarma I, Salumets A, Donders GG, Metsis M (2013) Characterization of the vaginal micro- and mycobiome in asymptomatic reproductive-age Estonian women. PLoS One 8(1):e54379

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  3. 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 (2011) Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A 108(Suppl 1):4680–4687

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  4. Kaewsrichan J, Peeyananjarassri K, Kongprasertkit J (2006) Selection and identification of anaerobic lactobacilli producing inhibitory compounds against vaginal pathogens. FEMS Immunol Med Microbiol 48:75–83

    Article  CAS  PubMed  Google Scholar 

  5. Klebanoff SJ, Hillier SL, Eschenbach DA, Waltersdorph AM (1991) Control of the microbial flora of the vagina by H2O2-generating lactobacilli. J Infect Dis 164:94–100

    Article  CAS  PubMed  Google Scholar 

  6. Reid G, Younes JA, Van der Mei HC, Gloor GB, Knight R, Busscher HJ (2011) Microbiota restoration: natural and supplemented recovery of human microbial communities. Nat Rev Microbiol 9:27–38

    Article  CAS  PubMed  Google Scholar 

  7. Fredricks DN, Fiedler TL, Marrazzo JM (2005) Molecular identification of bacteria associated with bacterial vaginosis. N Engl J Med 353:1899–1911

    Article  CAS  PubMed  Google Scholar 

  8. Sobel JD (2000) Bacterial vaginosis. Annu Rev Med 51:349–356

    Article  CAS  PubMed  Google Scholar 

  9. Atashili J, Poole C, Ndumbe PM, Adimora AA, Smith JS (2008) Bacterial vaginosis and HIV acquisition: a meta-analysis of published studies. AIDS 22:1493–1501

    Article  PubMed Central  PubMed  Google Scholar 

  10. Brotman RM, Klebanoff MA, Nansel TR, Yu KF, Andrews WW, Zhang J, Schwebke JR (2010) Bacterial vaginosis assessed by gram stain and diminished colonization resistance to incident gonococcal, chlamydial, and trichomonal genital infection. J Infect Dis 202:1907–1915

    Article  PubMed Central  PubMed  Google Scholar 

  11. Donders GG, Van Bulck B, Caudron J, Londers L, Vereecken A, Spitz B (2000) Relationship of bacterial vaginosis and mycoplasmas to the risk of spontaneous abortion. Am J Obstet Gynecol 183:431–437

    Article  CAS  PubMed  Google Scholar 

  12. Hillier SL, Martius J, Krohn M, Kiviat N, Holmes KK, Eschenbach DA (1988) A case–control study of chorioamnionic infection and histologic chorioamnionitis in prematurity. N Engl J Med 319:972–978

    Article  CAS  PubMed  Google Scholar 

  13. Nugent RP, Krohn MA, Hillier SL (1991) Reliability of diagnosing bacterial vaginosis is improved by a standardized method of gram stain interpretation. J Clin Microbiol 29:297–301

    PubMed Central  CAS  PubMed  Google Scholar 

  14. Amsel R, Totten PA, Spiegel CA, Chen KC, Eschenbach D, Holmes KK (1983) Nonspecific vaginitis. Diagnostic criteria and microbial and epidemiologic associations. Am J Med 74:14–22

    Article  CAS  PubMed  Google Scholar 

  15. Lamont RF, Sobel JD, Akins RA, Hassan SS, Chaiworapongsa T, Kusanovic JP, Romero R (2011) The vaginal microbiome: new information about genital tract flora using molecular based techniques. BJOG 118:533–549

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Coen M, O’Sullivan M, Bubb WA, Kuchel PW, Sorrell T (2005) Proton nuclear magnetic resonance-based metabonomics for rapid diagnosis of meningitis and ventriculitis. Clin Infect Dis 41:1582–1590

    Article  CAS  PubMed  Google Scholar 

  17. Laghi L, Picone G, Cruciani F, Brigidi P, Calanni F, Donders G, Capozzi F, Vitali B (2014) Rifaximin modulates the vaginal microbiome and metabolome in women affected by bacterial vaginosis. Antimicrob Agents Chemother 58:3411–3420

    Article  PubMed Central  PubMed  Google Scholar 

  18. Urbanczyk-Wochniak E, Luedemann A, Kopka J, Selbig J, Roessner-Tunali U, Willmitzer L, Fernie AR (2003) Parallel analysis of transcript and metabolic profiles: a new approach in systems biology. EMBO Rep 4:989–993

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Yeoman CJ, Thomas SM, Miller ME, Ulanov AV, Torralba M, Lucas S, Gillis M, Cregger M, Gomez A, Ho M, Leigh SR, Stumpf R, Creedon DJ, Smith MA, Weisbaum JS, Nelson KE, Wilson BA, White BA (2013) A multi-omic systems-based approach reveals metabolic markers of bacterial vaginosis and insight into the disease. PLoS One 8(2):e56111

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  20. Vitali B, Pugliese C, Biagi E, Candela M, Turroni S, Bellen G, Donders GG, Brigidi P (2007) Dynamics of vaginal bacterial communities in women developing bacterial vaginosis, candidiasis, or no infection, analyzed by PCR-denaturing gradient gel electrophoresis and real-time PCR. Appl Environ Microbiol 73:5731–5741

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Vitali B, Biagi E, Brigidi P (2012) Protocol for the use of PCR-denaturing gradient gel electrophoresis and quantitative PCR to determine vaginal microflora constitution and pathogens in bacterial vaginosis. In: MacKenzie CR, Henrich B (eds) Diagnosis of sexually transmitted diseases, vol 903. Springer, New York, pp 177–193

    Chapter  Google Scholar 

  22. Cruciani F, Brigidi P, Calanni F, Lauro V, Tacchi R, Donders G, Peters K, Guaschino S, Vitali B (2012) Efficacy of rifaximin vaginal tablets in treatment of bacterial vaginosis: a molecular characterization of the vaginal microbiota. Antimicrob Agents Chemother 56:4062–4070

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  23. Zozaya-Hinchliffe M, Lillis R, Martin DH, Ferris MJ (2010) Quantitative PCR assessments of bacterial species in women with and without bacterial vaginosis. J Clin Microbiol 48:1812–1819

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. De Backer E, Verhelst R, Verstraelen H, Alqumber MA, Burton JP, Tagg JR, Temmerman M, Vaneechoutte M (2007) Quantitative determination by real-time PCR of four vaginal Lactobacillus species, Gardnerella vaginalis and Atopobium vaginae indicates an inverse relationship between L. gasseri and L. iners. BMC Microbiol 7:115

    Article  PubMed Central  PubMed  Google Scholar 

  25. Byun R, Nadkarni MA, Chhour KL, Martin FE, Jacques NA, Hunter N (2004) Quantitative analysis of diverse Lactobacillus species present in advanced dental caries. J Clin Microbiol 42:3128–3136

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. Zariffard MR, Saifuddin M, Sha BE, Spear GT (2002) Detection of bacterial vaginosis-related organisms by real-time PCR for Lactobacilli, Gardnerella vaginalis and Mycoplasma hominis. FEMS Immunol Med Microbiol 34:277–281

    Article  CAS  PubMed  Google Scholar 

  27. Matsuki T, Watanabe K, Fujimoto J, Takada T, Tanaka R (2004) Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in human feces. Appl Environ Microbiol 70:7220–7228

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  28. Matsuki T, Watanabe K, Fujimoto J, Miyamoto Y, Takada T, Matsumoto K, Oyaizu H, Tanaka R (2002) Development of 16S rRNA-gene-targeted group-specific primers for the detection and identification of predominant bacteria in human feces. Appl Environ Microbiol 68:5445–5451

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  29. Rinttilä T, Kassinen A, Malinen E, Krogius L, Palva A (2004) Development of an extensive set of 16S rDNA-targeted primers for quantification of pathogenic and indigenous bacteria in faecal samples by real-time PCR. J Appl Microbiol 97:1166–1177

    Article  PubMed  Google Scholar 

  30. Tiveljung A, Forsum U, Monstein HJ (1996) Classification of the genus Mobiluncus based on comparative partial 16S rRNA gene analysis. Int J Syst Bacteriol 46:332–336

    Article  CAS  PubMed  Google Scholar 

  31. Coombes KR, Fritsche HA Jr, Clarke C, Chen J-N, Baggerly KA, Morris JS, Xiao LC, Hung MC, Kuerer HM (2003) Quality control and peak finding for proteomics data collected from nipple aspirate fluid by surface-enhanced laser desorption and ionization. Clin Chem 49:1615–1623

    Article  CAS  PubMed  Google Scholar 

  32. Liland KH, Almøy T, Mevik BH (2010) Optimal choice of baseline correction for multivariate calibration of spectra. Appl Spectrosc 64:1007–1016

    Article  CAS  PubMed  Google Scholar 

  33. Savorani F, Tomasi G, Engelsen SB (2010) icoshift: A versatile tool for the rapid alignment of 1D NMR spectra. J Magn Reson 202:190–202

    Article  CAS  PubMed  Google Scholar 

  34. Dieterle F, Ross A, Schlotterbeck G, Senn H (2006) Probabilistic quotient normalization as robust method to account for dilution of complex biological mixtures. Application in 1H NMR metabonomics. Anal Chem 78:4281–4290

    Article  CAS  PubMed  Google Scholar 

  35. Ihaka R, Gentleman R (1996) R: a language for data analysis and graphics. J Comput Graph Stat 5:299–314

    Google Scholar 

  36. Hothorn T, Bretz F, Westfall P (2008) Simultaneous inference in general parametric models. Biom J 50:346–363

    Article  PubMed  Google Scholar 

  37. Yao F, Coquery J, Lê Cao KA (2012) Independent Principal Component Analysis for biologically meaningful dimension reduction of large biological data sets. BMC Bioinformatics 13:24

    Article  PubMed Central  PubMed  Google Scholar 

  38. Shipitsyna E, Roos A, Datcu R, Hallén A, Fredlund H, Jensen JS, Engstrand L, Unemo M (2013) Composition of the vaginal microbiota in women of reproductive age—sensitive and specific molecular diagnosis of bacterial vaginosis is possible? PLoS One 8(4):e60670

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. Spraul M, Schütz B, Humpfer E, Mörtter M, Schäfer H, Koswig S, Rinke P (2009) Mixture analysis by NMR as applied to fruit juice quality control. Magn Reson Chem 47(Suppl 1):S130–S137

    Article  CAS  PubMed  Google Scholar 

  40. Biagi E, Vitali B, Pugliese C, Candela M, Donders GG, Brigidi P (2009) Quantitative variations in the vaginal bacterial population associated with asymptomatic infections: a real-time polymerase chain reaction study. Eur J Clin Microbiol Infect Dis 28:281–285

    Article  CAS  PubMed  Google Scholar 

  41. Turovskiy Y, Sutyak Noll K, Chikindas ML (2011) The aetiology of bacterial vaginosis. J Appl Microbiol 110:1105–1128

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  42. Ling Z, Kong J, Liu F, Zhu H, Chen X, Wang Y, Li L, Nelson KE, Xia Y, Xiang C (2010) Molecular analysis of the diversity of vaginal microbiota associated with bacterial vaginosis. BMC Genomics 11:488

    Article  PubMed Central  PubMed  Google Scholar 

  43. Macklaim JM, Gloor GB, Anukam KC, Cribby S, Reid G (2011) At the crossroads of vaginal health and disease, the genome sequence of Lactobacillus iners AB-1. Proc Natl Acad Sci U S A 108(Suppl 1):4688–4695

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  44. Gardner HL, Dukes CD (1955) Haemophilus vaginalis vaginitis: a newly defined specific infection previously classified non-specific vaginitis. Am J Obstet Gynecol 69:962–976

    CAS  PubMed  Google Scholar 

  45. Al-Mushrif S, Eley A, Jones BM (2000) Inhibition of chemotaxis by organic acids from anaerobes may prevent a purulent response in bacterial vaginosis. J Med Microbiol 49:1023–1030

    Article  CAS  PubMed  Google Scholar 

  46. Chaudry AN, Travers PJ, Yuenger J, Colletta L, Evans P, Zenilman JM, Tummon A (2004) Analysis of vaginal acetic acid in patients undergoing treatment for bacterial vaginosis. J Clin Microbiol 42:5170–5175

    Article  PubMed Central  PubMed  Google Scholar 

  47. Mirmonsef P, Gilbert D, Zariffard MR, Hamaker BR, Kaur A, Landay AL, Spear GT (2011) The effects of commensal bacteria on innate immune responses in the female genital tract. Am J Reprod Immunol 65:190–195

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  48. Sobel JD, Karpas Z, Lorber A (2012) Diagnosing vaginal infections through measurement of biogenic amines by ion mobility spectrometry. Eur J Obstet Gynecol Reprod Biol 163:81–84

    Article  CAS  PubMed  Google Scholar 

  49. Wolrath H, Forsum U, Larsson PG, Borén H (2001) Analysis of bacterial vaginosis-related amines in vaginal fluid by gas chromatography and mass spectrometry. J Clin Microbiol 39:4026–4031

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  50. Cruciani F, Wasinger V, Turroni S, Calanni F, Donders G, Brigidi P, Vitali B (2013) Proteome profiles of vaginal fluids from women affected by bacterial vaginosis and healthy controls: outcomes of rifaximin treatment. J Antimicrob Chemother 68:2648–2659

    Article  CAS  PubMed  Google Scholar 

  51. Spear GT, French AL, Gilbert D, Zariffard MR, Mirmonsef P, Sullivan TH, Spear WW, Landay A, Micci S, Lee BH, Hamaker BR (2014) Human α-amylase present in lower-genital-tract mucosal fluid processes glycogen to support vaginal colonization by Lactobacillus. J Infect Dis 210:1019–1028

    Article  PubMed Central  PubMed  Google Scholar 

  52. Thoma ME, Klebanoff MA, Rovner AJ, Nansel TR, Neggers Y, Andrews WW, Schwebke JR (2011) Bacterial vaginosis is associated with variation in dietary indices. J Nutr 141:1698–1704

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This study was supported by the Ministry of Instruction, University and Research (MIUR), Italy.

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Author information

Author notes

  1. F. Cruciani

    Present address: Consiglio per la Ricerca e la Sperimentazione in Agricoltura (CRA)—Cereal Research Centre (CER), S.S. 673 Km 25 + 200, 71122, Foggia, Italy

Authors and Affiliations

  1. Department of Pharmacy and Biotechnology, University of Bologna, Via San Donato 19/2, 40127, Bologna, Italy

    B. Vitali, F. Cruciani & C. Parolin

  2. Department of Agro-Food Science and Technology, University of Bologna, P.zza Goidanich 60, 47522, Cesena, Italy

    G. Picone & L. Laghi

  3. Department of Obstetrics and Gynecology, General Hospital Heilig Hart, Kliniekstraat 45, 3300, Tienen, Belgium

    G. Donders

  4. University Hospital Antwerp, Wilrijkstraat 10, 2650, Edegem, Belgium

    G. Donders

Authors
  1. B. Vitali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. F. Cruciani
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. G. Picone
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. C. Parolin
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. G. Donders
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. L. Laghi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to B. Vitali.

Electronic supplementary material

Below are the links to the electronic supplementary material.

ESM 1

(PDF 568 kb)

Fig. S1

Biplot of a PCA performed on the autoscaled qPCR data. Median values of the sample groups corresponding to healthy and BV-affected women are indicated as H and BV, respectively. The open circles and filled squares indicate samples from healthy and BV women, respectively. Expl. Var, explained variance (PDF 568 kb) (PDF 155 kb)

Fig. S2

Biplot of a PCA performed on the autoscaled qPCR data related to BV-associated bacteria (a) and metabolites selected by the sPLS-DA model (b). Median values of the sample groups corresponding to healthy women dominated by L. crispatus, L. iners, L. gasseri, L. jensenii and BV-affected women dominated by L. iners, L. gasseri or none of the four considered species are indicated as Hc, Hi, Hg, Hj, BVi, BVg and BVn, respectively. The open circles and filled squares indicate samples from healthy and BV women, respectively. Expl. Var, explained variance (PDF 384 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Vitali, B., Cruciani, F., Picone, G. et al. Vaginal microbiome and metabolome highlight specific signatures of bacterial vaginosis. Eur J Clin Microbiol Infect Dis 34, 2367–2376 (2015). https://doi.org/10.1007/s10096-015-2490-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10096-015-2490-y

Keywords

Search

Navigation