1887

Abstract

Vaginal dysbiosis-induced by an overgrowth of anaerobic bacteria is referred to as bacterial vaginosis (BV). The dysbiosis is associated with an increased risk for acquisition of sexually transmitted infections. Women with symptomatic BV are treated with oral metronidazole (MET), but its effectiveness remains to be elucidated. This study used whole-genome sequencing (WGS) to determine the changes in the microbiota among women treated with MET. WGS was conducted on DNA obtained from 20 vaginal swabs collected at four time points over 12 months from five randomly selected African American (AA) women. The baseline visit included all women who were diagnosed with asymptomatic BV and were untreated. All subjects were tested subsequently once every 2 months and received a course of MET for each BV episode during the 12 months. The BV status was classified according to Nugent scores (NSs) of vaginal smears. The microbial and resistome profiles were analysed along with the sociodemographic metadata. Despite treatment, none of the five participants reverted to normal vaginal flora — two were consistently positive for BV, and the rest experienced episodic cases of BV. WGS analyses showed spp. as the most abundant organism. After treatment with MET, there was an observed decline of and species. One participant had a healthy vaginal microbiota based on NS at one follow-up time point. Resistance genes including and were detected. Though limited in subjects, this study shows specific microbiota changes with treatment, presence of many resistant genes in their microbiota, and recurrence and persistence of BV despite MET treatment. Thus, MET may not be an effective treatment option for asymptomatic BV, and whole metagenome sequence would better inform the choice of antibiotics.

Funding
This study was supported by the:
  • National Institutes of Health (Award 1R15AI128714-01)
    • Principle Award Recipient: KalaiMathee
  • Florida International University
    • Principle Award Recipient: MakellaS Coudray
  • Florida International University Dissertation Year Fellowship
    • Principle Award Recipient: DanielRuiz-Perez
  • National Institutes of Health (Award 1R15AI128714-01)
    • Principle Award Recipient: GiriNarasimhan
  • National Institutes of Health (Award 1R15AI128714-01)
    • Principle Award Recipient: PurnimaMadhivanan
Loading

Article metrics loading...

/content/journal/acmi/10.1099/acmi.0.000226
2021-05-04
2021-05-15
Loading full text...

Full text loading...

/deliver/fulltext/acmi/3/5/acmi000226.html?itemId=/content/journal/acmi/10.1099/acmi.0.000226&mimeType=html&fmt=ahah

References

  1. Ferreira CST, Donders GG, Parada CMGdeL, Tristão AdaR, Fernandes T et al. Treatment failure of bacterial vaginosis is not associated with higher loads of Atopobium vaginae and Gardnerella vaginalis . J Med Microbiol 2017; 66:1217–1224 [CrossRef][PubMed]
    [Google Scholar]
  2. Xiao B, Niu X, Han N, Wang B, Du P et al. Predictive value of the composition of the vaginal microbiota in bacterial vaginosis, a dynamic study to identify recurrence-related flora. Sci Rep 2016; 6:26674 [CrossRef][PubMed]
    [Google Scholar]
  3. Ravel J, Brotman RM, Gajer P, Ma B, Nandy M et al. Daily temporal dynamics of vaginal microbiota before, during and after episodes of bacterial vaginosis. Microbiome 2013; 1:29 [CrossRef][PubMed]
    [Google Scholar]
  4. Smith WL, Hedges SR, Mordechai E, Adelson ME, Trama JP et al. Cervical and vaginal flora specimens are highly concordant with respect to bacterial vaginosis-associated organisms and commensal Lactobacillus species in women of reproductive age. J Clin Microbiol 2014; 52:3078–3081 [CrossRef][PubMed]
    [Google Scholar]
  5. Koumans EH, Sternberg M, Bruce C, McQuillan G, Kendrick J et al. The prevalence of bacterial vaginosis in the United States, 2001-2004; associations with symptoms, sexual behaviors, and reproductive health. Sex Transm Dis 2007; 34:864–869 [CrossRef][PubMed]
    [Google Scholar]
  6. Brotman RM. Vaginal microbiome and sexually transmitted infections: an epidemiologic perspective. J Clin Invest 2011; 121:4610–4617 [CrossRef][PubMed]
    [Google Scholar]
  7. Allsworth JE, Lewis VA, Peipert JF. Viral sexually transmitted infections and bacterial vaginosis: 2001-2004 National health and nutrition examination survey data. Sex Transm Dis 2008; 35:791–796 [CrossRef][PubMed]
    [Google Scholar]
  8. Brotman RM, Shardell MD, Gajer P, Tracy JK, Zenilman JM et al. Interplay between the temporal dynamics of the vaginal microbiota and human papillomavirus detection. J Infect Dis 2014; 210:1723–1733 [CrossRef][PubMed]
    [Google Scholar]
  9. Bautista CT, Wurapa E, Sateren WB, Morris S, Hollingsworth B et al. Bacterial vaginosis: a synthesis of the literature on etiology, prevalence, risk factors, and relationship with Chlamydia and gonorrhea infections. Mil Med Res 2016; 3:4 [CrossRef][PubMed]
    [Google Scholar]
  10. Coudray MS, Madhivanan P. Bacterial vaginosis-A brief synopsis of the literature. Eur J Obstet Gynecol Reprod Biol 2020; 245:143–148 [CrossRef][PubMed]
    [Google Scholar]
  11. Muzny CA, Sunesara IR, Kumar R, Mena LA, Griswold ME et al. Characterization of the vaginal microbiota among sexual risk behavior groups of women with bacterial vaginosis. PLoS One 2013; 8:e80254 [CrossRef][PubMed]
    [Google Scholar]
  12. Balkus JE, Srinivasan S, Anzala O, Kimani J, Andac C et al. Impact of periodic presumptive treatment for bacterial vaginosis on the vaginal microbiome among women participating in the preventing vaginal infections trial. J Infect Dis 2017; 215:723–731 [CrossRef][PubMed]
    [Google Scholar]
  13. Vitali B, Cruciani F, Picone G, Parolin C, Donders G et al. Vaginal microbiome and metabolome highlight specific signatures of bacterial vaginosis. Eur J Clin Microbiol Infect Dis 2015; 34:2367–2376 [CrossRef][PubMed]
    [Google Scholar]
  14. Crucitti T, Hardy L, van de Wijgert J, Agaba S, Buyze J et al. Contraceptive rings promote vaginal lactobacilli in a high bacterial vaginosis prevalence population: a randomised, open-label longitudinal study in Rwandan women. PLoS One 2018; 13:e0201003 [CrossRef][PubMed]
    [Google Scholar]
  15. Lambert JA, John S, Sobel JD, Akins RA. Longitudinal analysis of vaginal microbiome dynamics in women with recurrent bacterial vaginosis: recognition of the conversion process. PLoS One 2013; 8:e82599 [CrossRef][PubMed]
    [Google Scholar]
  16. Ravel J, Gajer P, Abdo Z, Schneider GM, Koenig SSK et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci U S A 2011; 108 Suppl 1:4680–4687 [CrossRef][PubMed]
    [Google Scholar]
  17. Mohammadzadeh F, Dolatian M, Jorjani M, Alavi Majd H. Diagnostic value of Amsel's clinical criteria for diagnosis of bacterial vaginosis. Glob J Health Sci 2014; 7:8–14 [CrossRef][PubMed]
    [Google Scholar]
  18. Amegashie CP, Gilbert NM, Peipert JF, Allsworth JE, Lewis WG et al. Relationship between Nugent score and vaginal epithelial exfoliation. PLoS One 2017; 12:e0177797 [CrossRef][PubMed]
    [Google Scholar]
  19. Gajer P, Brotman RM, Bai G, Sakamoto J, Schütte UME et al. Temporal dynamics of the human vaginal microbiota. Sci Transl Med 2012; 4:132ra52 [CrossRef][PubMed]
    [Google Scholar]
  20. Schwebke JR, Lee JY, Lensing S, Philip SS, Wiesenfeld HC et al. Home screening for bacterial vaginosis to prevent sexually transmitted diseases. Clin Infect Dis 2016; 62:531–536 [CrossRef][PubMed]
    [Google Scholar]
  21. R Core Team R: A Language and Environment for Statistical Computing Vienna, Austria: R Foundation for Statistical Computing; 2014
    [Google Scholar]
  22. Wickham H. The Split-Apply-Combine strategy for data analysis. J Stat Softw 2011; 1:1–29
    [Google Scholar]
  23. Harrell Jr F 2018; Package ‘Hmisc’. https://hbiostat.org/R/Hmisc/
  24. Oksanen J, Blanchet F, Friendly M, Kindt R, Legendre P. Vegan: community ecology package. R package version 2.5-3. https://cran.rproject.org/web/packages/vegan/index.html2018 ; 2018
  25. Somerfield PJ, Clarke KR, Warwick RM. Simpson index. Encyclopedia Ecol 20083252–3255
    [Google Scholar]
  26. Schober P, Boer C, Schwarte LA. Correlation coefficients: appropriate use and interpretation. Anesth Analg 2018; 126:1763–1768 [CrossRef][PubMed]
    [Google Scholar]
  27. Fernandez M, Riveros JD, Campos M, Mathee K, Narasimhan G. Microbial "social networks". BMC Genomics 2015; 16 Suppl 11:S6–13 [CrossRef][PubMed]
    [Google Scholar]
  28. Mahalanobis PC. On the generalised distance in statistics. Proc Natl Inst Sci India 1936; 2:49–55
    [Google Scholar]
  29. Rohart F, Gautier B, Singh A, Lê Cao K-A. mixOmics: An R package for ‘omics feature selection and multiple data integration. PLoS Comput Biol 13:e10057522017 [CrossRef]
    [Google Scholar]
  30. Welch BL. The generalisation of student's problems when several different population variances are involved. Biometrika 1947; 34:28–35 [CrossRef][PubMed]
    [Google Scholar]
  31. Haynes W. Benjamini–hochberg method. In Dubitzky W, Wolkenhauer O, Cho K-H, Yokota H. (editors) Encyclopedia of Systems Biology New York: Springer; 2013 p 78
    [Google Scholar]
  32. Ruiz-Perez D, Guan H, Madhivanan P, Mathee K, Narasimhan G. So you think you can PLS-DA?. BMC Bioinformatics 2020; 21:207225 [CrossRef]
    [Google Scholar]
  33. Stebliankin V, Sazal M, Valdes C, Mathee K, Narasimhan G. Novel approach for microbiome analysis using bacterial replication rates and causal inference with applications. bioRxiv 2020
    [Google Scholar]
  34. Alcock BP, Raphenya AR, Lau TTY, Tsang KK, Bouchard M et al. Card 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res 2020; 48:D517–D25 [CrossRef][PubMed]
    [Google Scholar]
  35. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods 2012; 9:357–359 [CrossRef][PubMed]
    [Google Scholar]
  36. Warnes GR, Bolker B, Bonebakker L, Gentleman R, Huber W. gplots: various R programming tools for plotting data. R package version 3.0.1. https://CRAN.R-project.org/package=gplots2016 ; 2016
  37. Wickham H. ggplot2: Elegant Graphics for Data Analysis New York: 2016
    [Google Scholar]
  38. Sievert C plotly for R. https://plotly-book.cpsievert.me ; 2018
  39. Mayer BT, Srinivasan S, Fiedler TL, Marrazzo JM, Fredricks DN et al. Rapid and profound shifts in the vaginal microbiota following antibiotic treatment for bacterial vaginosis. J Infect Dis 2015; 212:793–802 [CrossRef][PubMed]
    [Google Scholar]
  40. Hummelen R, Fernandes AD, Macklaim JM, Dickson RJ, Changalucha J et al. Deep sequencing of the vaginal microbiota of women with HIV. PLoS One 2010; 5:e12078 [CrossRef][PubMed]
    [Google Scholar]
  41. Zhou X, Brown CJ, Abdo Z, Davis CC, Hansmann MA et al. Differences in the composition of vaginal microbial communities found in healthy Caucasian and black women. Isme J 2007; 1:121–133 [CrossRef][PubMed]
    [Google Scholar]
  42. Deng Z-L, Gottschick C, Bhuju S, Masur C, Abels C et al. Metatranscriptome analysis of the vaginal microbiota reveals potential mechanisms for protection against metronidazole in bacterial vaginosis. mSphere 2018; 3: 27 06 2018 [CrossRef][PubMed]
    [Google Scholar]
  43. Alauzet C, Lozniewski A, Marchandin H. Metronidazole resistance and nim genes in anaerobes: A review. Anaerobe 2019; 55:40–53 [CrossRef][PubMed]
    [Google Scholar]
  44. Freeman CD, Klutman NE, Metronidazole LKC. A therapeutic review and update. Drugs 1997; 54:679–708
    [Google Scholar]
  45. Brooks JP, Buck GA, Chen G, Diao L, Edwards DJ et al. Changes in vaginal community state types reflect major shifts in the microbiome. Microb Ecol Health Dis 2017; 28:1303265 [CrossRef][PubMed]
    [Google Scholar]
  46. Madden T, Grentzer JM, Secura GM, Allsworth JE, Peipert JF. Risk of bacterial vaginosis in users of the intrauterine device: a longitudinal study. Sex Transm Dis 2012; 39:217–222 [CrossRef][PubMed]
    [Google Scholar]
  47. Abdelmaksoud AA, Koparde VN, Sheth NU, Serrano MG, Glascock AL et al. Comparison of Lactobacillus crispatus isolates from Lactobacillus-dominated vaginal microbiomes with isolates from microbiomes containing bacterial vaginosis-associated bacteria. Microbiology 2016; 162:466–475 [CrossRef][PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/acmi/10.1099/acmi.0.000226
Loading
/content/journal/acmi/10.1099/acmi.0.000226
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Most cited this month Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error