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Microbial Genomics logo Microbial Genomics

Volume 9, Issue 11

Profiling of vaginal isolated from preterm and full-term pregnancies reveals strain-specific factors relating to host interaction Open Access

Abstract

Each year, 15 million infants are born preterm (<37 weeks gestation), representing the leading cause of mortality for children under the age of five. Whilst there is no single cause, factors such as maternal genetics, environmental interactions, and the vaginal microbiome have been associated with an increased risk of preterm birth. Previous studies show that a vaginal microbiota dominated by is, in contrast to communities containing a mixture of genera, associated with full-term birth. However, this binary principle does not fully consider more nuanced interactions between bacterial strains and the host. Here, through a combination of analyses involving genome-sequenced isolates and strain-resolved metagenomics, we identify that strains from preterm pregnancies are phylogenetically distinct from strains from full-term pregnancies. Detailed analysis reveals several genetic signatures that distinguish preterm birth strains, including genes predicted to be involved in cell wall synthesis, and lactate and acetate metabolism. Notably, we identify a distinct gene cluster involved in cell surface protein synthesis in our preterm strains, and profiling the prevalence of this gene cluster in publicly available genomes revealed it to be predominantly present in the preterm-associated clade. This study contributes to the ongoing search for molecular biomarkers linked to preterm birth and opens up new avenues for exploring strain-level variations and mechanisms that may contribute to preterm birth.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): genomics , Lactobacillus jensenii , microbe-host interactions , preterm birth and vaginal microbiome
Funding
This study was supported by the:
  • Horizon 2020 (Award H2020-MSCA-COFUND-2019-945385)
    • Principle Award Recipient: SaiRavi Chandra Nori
  • Science Foundation Ireland (Award 18/CRT/6214)
    • Principle Award Recipient: SaiRavi Chandra Nori
  • Irish Research Council (Award EPSPD/2016/25)
    • Principle Award Recipient: ConorFeehily
  • Science Foundation Ireland (Award 12/RC/2273_P2)
    • Principle Award Recipient: FionnualaM. McAuliffe
  • Science Foundation Ireland (Award 12/RC/2273_P2 and 16/SP/3827)
    • Principle Award Recipient: PaulD. Cotter
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2023-11-27
2025-04-22
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References

  1. The Human Microbiome Project Consortium Structure, function and diversity of the healthy human microbiome. Nature 2012; 486:207–214 [View Article]
     [Google Scholar]
  2. Ravel J, Gajer P, Abdo Z, Schneider GM, Koenig SSK et al. Vaginal microbiome of reproductive-age women. Proc Natl Acad Sci USA 2011; 108:4680–4687 [View Article]
     [Google Scholar]
  3. Zhou X, Bent SJ, Schneider MG, Davis CC, Islam MR et al. Characterization of vaginal microbial communities in adult healthy women using cultivation-independent methods. Microbiology 2004; 150:2565–2573 [View Article] [PubMed]
     [Google Scholar]
  4. Gong Z, Luna Y, Yu P, Fan H. Lactobacilli inactivate Chlamydia trachomatis through lactic acid but not H2O2. PLoS One 2014; 9:e107758 [View Article] [PubMed]
     [Google Scholar]
  5. O’Hanlon DE, Moench TR, Cone RA. In vaginal fluid, bacteria associated with bacterial vaginosis can be suppressed with lactic acid but not hydrogen peroxide. BMC Infect Dis 2011; 11:200 [View Article] [PubMed]
     [Google Scholar]
  6. O’Hanlon DE, Moench TR, Cone RA. Vaginal pH and microbicidal lactic acid when lactobacilli dominate the microbiota. PLoS One 2013; 8:e80074 [View Article] [PubMed]
     [Google Scholar]
  7. Aroutcheva A, Gariti D, Simon M, Shott S, Faro J et al. Defense factors of vaginal lactobacilli. Am J Obstet Gynecol 2001; 185:375–379 [View Article] [PubMed]
     [Google Scholar]
  8. Delgado-Diaz DJ, Tyssen D, Hayward JA, Gugasyan R, Hearps AC et al. Distinct immune responses elicited from cervicovaginal epithelial cells by lactic acid and short chain fatty acids associated with optimal and non-optimal vaginal microbiota. Front Cell Infect Microbiol 2019; 9:446 [View Article] [PubMed]
     [Google Scholar]
  9. Witkin SS, Mendes-Soares H, Linhares IM, Jayaram A, Ledger WJ et al. Influence of vaginal bacteria and D- and L-lactic acid isomers on vaginal extracellular matrix metalloproteinase inducer: implications for protection against upper genital tract infections. mBio 2013; 4:e00460-13 [View Article] [PubMed]
     [Google Scholar]
  10. Alonzo Martínez MC, Cazorla E, Cánovas E, Martínez-Blanch JF, Chenoll E et al. Study of the Vaginal Microbiota in Healthy Women of Reproductive Age. Microorganisms 2021; 9:1069 [View Article]
     [Google Scholar]
  11. Tsementzi D, Pena-Gonzalez A, Bai J, Hu Y-J, Patel P et al. Comparison of vaginal microbiota in gynecologic cancer patients pre- and post-radiation therapy and healthy women. Cancer Med 2020; 9:3714–3724 [View Article] [PubMed]
     [Google Scholar]
  12. Srinivasan S, Fredricks DN. The human vaginal bacterial biota and bacterial vaginosis. Interdiscip Perspect Infect Dis 2008750479 [View Article] [PubMed]
     [Google Scholar]
  13. Carter KA, Balkus JE, Anzala O, Kimani J, Hoffman NG et al. Associations between vaginal bacteria and bacterial vaginosis signs and symptoms: A comparative study of Kenyan and American Women. Front Cell Infect Microbiol 2022; 12:801770 [View Article] [PubMed]
     [Google Scholar]
  14. Gosmann C, Anahtar MN, Handley SA, Farcasanu M, Abu-Ali G et al. Lactobacillus-deficient cervicovaginal bacterial communities are Associated with increased HIV Acquisition in Young South African Women. Immunity 2017; 46:29–37 [View Article] [PubMed]
     [Google Scholar]
  15. Brotman RM, Bradford LL, Conrad M, Gajer P, Ault K et al. Association between Trichomonas vaginalis and vaginal bacterial community composition among reproductive-age women. Sex Transm Dis 2012; 39:807–812 [View Article] [PubMed]
     [Google Scholar]
  16. Leitich H, Kiss H. Asymptomatic bacterial vaginosis and intermediate flora as risk factors for adverse pregnancy outcome. Best Pract Res Clin Obstet Gynaecol 2007; 21:375–390 [View Article] [PubMed]
     [Google Scholar]
  17. Leitich H, Bodner-Adler B, Brunbauer M, Kaider A, Egarter C et al. Bacterial vaginosis as a risk factor for preterm delivery: A meta-analysis. Am J Obstet Gynecol 2003; 189:139–147 [View Article] [PubMed]
     [Google Scholar]
  18. Perin J, Mulick A, Yeung D, Villavicencio F, Lopez G et al. Global, regional, and national causes of under-5 mortality in 2000–19: an updated systematic analysis with implications for the Sustainable Development Goals. The Lancet Child Adolescent Health 2022; 6:106–115 [View Article]
     [Google Scholar]
  19. Fettweis JM, Serrano MG, Brooks JP, Edwards DJ, Girerd PH et al. The vaginal microbiome and preterm birth. Nat Med 2019; 25:1012–1021 [View Article] [PubMed]
     [Google Scholar]
  20. Romero R, Dey SK, Fisher SJ. Preterm labor: one syndrome, many causes. Science 2014; 345:760–765 [View Article] [PubMed]
     [Google Scholar]
  21. Jeffcoat MK, Geurs NC, Reddy MS, Cliver SP, Goldenberg RL et al. Periodontal infection and preterm birth. J Am Dent Assoc 2001; 132:875–880 [View Article]
     [Google Scholar]
  22. Hyman RW, Fukushima M, Jiang H, Fung E, Rand L et al. Diversity of the vaginal microbiome correlates with preterm birth. Reprod Sci 2014; 21:32–40 [View Article] [PubMed]
     [Google Scholar]
  23. Subramaniam A, Kumar R, Cliver SP, Zhi D, Szychowski JM et al. Vaginal microbiota in Pregnancy: Evaluation based on vaginal flora, birth outcome, and race. Am J Perinatol 2016; 33:401–408 [View Article] [PubMed]
     [Google Scholar]
  24. Haque MM, Merchant M, Kumar PN, Dutta A, Mande SS. First-trimester vaginal microbiome diversity: a potential indicator of preterm delivery risk. Sci Rep 2017; 7:16145 [View Article] [PubMed]
     [Google Scholar]
  25. Witkin SS. Vaginal microbiome studies in pregnancy must also analyse host factors. BJOG 2019; 126:359 [View Article] [PubMed]
     [Google Scholar]
  26. Feehily C, Crosby D, Walsh CJ, Lawton EM, Higgins S et al. Shotgun sequencing of the vaginal microbiome reveals both a species and functional potential signature of preterm birth. NPJ Biofilms Microbiomes 2020; 6:50 [View Article] [PubMed]
     [Google Scholar]
  27. Callahan BJ, DiGiulio DB, Goltsman DSA, Sun CL, Costello EK et al. Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women. Proc Natl Acad Sci USA 2017; 114:9966–9971 [View Article]
     [Google Scholar]
  28. Romero R, Hassan SS, Gajer P, Tarca AL, Fadrosh DW et al. The vaginal microbiota of pregnant women who subsequently have spontaneous preterm labor and delivery and those with a normal delivery at term. Microbiome 2014; 2:18 [View Article] [PubMed]
     [Google Scholar]
  29. Gudnadottir U, Debelius JW, Du J, Hugerth LW, Danielsson H et al. The vaginal microbiome and the risk of preterm birth: a systematic review and network meta-analysis. Sci Rep 2022; 12:7926 [View Article] [PubMed]
     [Google Scholar]
  30. Stafford GP, Parker JL, Amabebe E, Kistler J, Reynolds S et al. Spontaneous preterm birth is associated with differential expression of vaginal metabolites by Lactobacilli-dominated microflora. Front Physiol 2017; 8:615 [View Article] [PubMed]
     [Google Scholar]
  31. Amabebe E, Reynolds S, Anumba DOC. Spectral binning of cervicovaginal fluid metabolites improves prediction of spontaneous preterm birth and Lactobacillus species dominance. Reprod Fertil 2021; 2:L4–L6 [View Article] [PubMed]
     [Google Scholar]
  32. de Freitas AS, Dobbler PCT, Mai V, Procianoy RS, Silveira RC et al. Defining microbial biomarkers for risk of preterm labor. Braz J Microbiol 2020; 51:151–159 [View Article]
     [Google Scholar]
  33. Pace RM, Chu DM, Prince AL, Ma J, Seferovic MD et al. Complex species and strain ecology of the vaginal microbiome from pregnancy to postpartum and association with preterm birth. Med 2021; 2:1027–1049 [View Article] [PubMed]
     [Google Scholar]
  34. Simpson PJ, Stanton C, Fitzgerald GF, Ross RP. Genomic diversity and relatedness of bifidobacteria isolated from a porcine cecum. J Bacteriol 2003; 185:2571–2581 [View Article] [PubMed]
     [Google Scholar]
  35. Krueger F et al. FelixKrueger/TrimGalore: v0.6.10 - add default decompression path; 2023
  36. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet j 2011; 17:10 [View Article]
     [Google Scholar]
  37. Prjibelski A, Antipov D, Meleshko D, Lapidus A, Korobeynikov A. Using SPAdes De Novo Assembler. Curr Protoc Bioinformatics 2020; 70:e102 [View Article] [PubMed]
     [Google Scholar]
  38. Bosi E, Donati B, Galardini M, Brunetti S, Sagot M-F et al. MeDuSa: a multi-draft based scaffolder. Bioinformatics 2015; 31:2443–2451 [View Article] [PubMed]
     [Google Scholar]
  39. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 2013; 29:1072–1075 [View Article] [PubMed]
     [Google Scholar]
  40. Uritskiy GV, Diruggiero J, Taylor J. Metawrap - A flexible pipeline for genome-resolved Metagenomic data analysis 08 information and computing sciences 0803 computer software 08 information and computing sciences 0806 information systems. Microbiome 2018; 6:1–13 [View Article]
     [Google Scholar]
  41. Asnicar F, Thomas AM, Beghini F, Mengoni C, Manara S et al. Precise phylogenetic analysis of microbial isolates and genomes from metagenomes using PhyloPhlAn 3.0. Nat Commun 2020; 11:2500 [View Article] [PubMed]
     [Google Scholar]
  42. Page AJ, Cummins CA, Hunt M, Wong VK, Reuter S et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 2015; 31:3691–3693 [View Article] [PubMed]
     [Google Scholar]
  43. Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform. Nucleic Acids Res 2002; 30:3059–3066 [View Article] [PubMed]
     [Google Scholar]
  44. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD et al. Corrigendum to: IQ-TREE 2: New models and efficient methods for phylogenetic inference in the genomic Era. Mol Biol Evol 2020; 37:2461 [View Article] [PubMed]
     [Google Scholar]
  45. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article] [PubMed]
     [Google Scholar]
  46. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 2014; 30:2068–2069 [View Article] [PubMed]
     [Google Scholar]
  47. Cantalapiedra CP, Hernández-Plaza A, Letunic I, Bork P, Huerta-Cepas J. eggNOG-mapper v2: Functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol Biol Evol 2021; 38:5825–5829 [View Article] [PubMed]
     [Google Scholar]
  48. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990; 215:403–410 [View Article] [PubMed]
     [Google Scholar]
  49. Sullivan MJ, Petty NK, Beatson SA. Easyfig: a genome comparison visualizer. Bioinformatics 2011; 27:1009–1010 [View Article] [PubMed]
     [Google Scholar]
  50. Wattam AR, Davis JJ, Assaf R, Boisvert S, Brettin T et al. Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center. Nucleic Acids Res 2017; 45:D535–D542 [View Article] [PubMed]
     [Google Scholar]
  51. Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun 2018; 9:5114 [View Article] [PubMed]
     [Google Scholar]
  52. Sheydina A, Eberhardt RY, Rigden DJ, Chang Y, Li Z et al. Structural genomics analysis of uncharacterized protein families overrepresented in human gut bacteria identifies a novel glycoside hydrolase. BMC Bioinformatics 2014; 15:1–10 [View Article] [PubMed]
     [Google Scholar]
  53. Mehta SD, Zhao D, Green SJ, Agingu W, Otieno F et al. The microbiome composition of a Man’s penis predicts incident Bacterial vaginosis in his Female sex partner with High Accuracy. Front Cell Infect Microbiol 2020; 10:433 [View Article] [PubMed]
     [Google Scholar]
  54. Gilbert JA, Lynch SV. Community ecology as a framework for human microbiome research. Nat Med 2019; 25:884–889 [View Article] [PubMed]
     [Google Scholar]
  55. Kindschuh WF, Baldini F, Liu MC, Liao J, Meydan Y et al. Preterm birth is associated with xenobiotics and predicted by the vaginal metabolome. Nat Microbiol 2023; 8:246–259 [View Article] [PubMed]
     [Google Scholar]
  56. Lee J-Y, Seo S, Shin B, Hong SH, Kwon E et al. Development of a new biomarker model for predicting preterm Birth in cervicovaginal fluid. Metabolites 2022; 12:734 [View Article] [PubMed]
     [Google Scholar]
  57. Chan D, Bennett PR, Lee YS, Kundu S, Teoh TG et al. Microbial-driven preterm labour involves crosstalk between the innate and adaptive immune response. Nat Commun 2022; 13:975 [View Article] [PubMed]
     [Google Scholar]
  58. Sanozky-Dawes R, Barrangou R. Lactobacillus, Glycans and drivers of health in the vaginal Microbiome. Microbiome Research Reports 2022; 1:18 [View Article]
     [Google Scholar]
  59. van der Veer C, Hertzberger RY, Bruisten SM, Tytgat HLP, Swanenburg J et al. Comparative genomics of human Lactobacillus crispatus isolates reveals genes for glycosylation and glycogen degradation: implications for in vivo dominance of the vaginal microbiota. Microbiome 2019; 7:49 [View Article] [PubMed]
     [Google Scholar]
  60. Nunn KL, Clair GC, Adkins JN, Engbrecht K, Fillmore T et al. Amylases in the Human Vagina. mSphere 2020; 5:6 [View Article] [PubMed]
     [Google Scholar]
  61. Tester R, Al-Ghazzewi FH. Intrinsic and extrinsic carbohydrates in the vagina: A short review on vaginal glycogen. Int J Biol Macromol 2018; 112:203–206 [View Article] [PubMed]
     [Google Scholar]
  62. Spear GT, French AL, Gilbert D, Zariffard MR, Mirmonsef P et al. Human α-amylase present in lower-genital-tract mucosal fluid processes glycogen to support vaginal colonization by Lactobacillus. J Infect Dis 2014; 210:1019–1028 [View Article] [PubMed]
     [Google Scholar]
  63. France MT, Fu L, Rutt L, Yang H, Humphrys MS et al. Insight into the ecology of vaginal bacteria through integrative analyses of metagenomic and metatranscriptomic data. Genome Biol 2022; 23:66 [View Article] [PubMed]
     [Google Scholar]
  64. Odeblad E, Parade A. The discovery of different types of Cervical mucus and the billings ovulation method. WOOMB International ltd 1994
     [Google Scholar]
  65. Wiggins R, Hicks SJ, Soothill PW, Millar MR, Corfield AP. Mucinases and sialidases: their role in the pathogenesis of sexually transmitted infections in the female genital tract. Sex Transm Infect 2001; 77:402–408 [View Article] [PubMed]
     [Google Scholar]
  66. Critchfield AS, Yao G, Jaishankar A, Friedlander RS, Lieleg O et al. Cervical mucus properties stratify risk for preterm birth. PLoS One 2013; 8:e69528 [View Article] [PubMed]
     [Google Scholar]
  67. Canny GO, McCormick BA. Bacteria in the intestine, helpful residents or enemies from within?. Infect Immun 2008; 76:3360–3373 [View Article] [PubMed]
     [Google Scholar]
  68. Nierop Groot MN, Kleerebezem M. Mutational analysis of the Lactococcus lactis NIZO B40 exopolysaccharide (EPS) gene cluster: EPS biosynthesis correlates with unphosphorylated EpsB. J Appl Microbiol 2007; 103:2645–2656 [View Article]
     [Google Scholar]
  69. Mijakovic I, Musumeci L, Tautz L, Petranovic D, Edwards RA et al. In vitro characterization of the Bacillus subtilis protein tyrosine phosphatase YwqE. J Bacteriol 2005; 187:3384–3390 [View Article] [PubMed]
     [Google Scholar]
  70. Bae T, Schneewind O. The YSIRK-G/S motif of staphylococcal protein a and its role in efficiency of signal peptide processing. J Bacteriol 2003; 185:2910–2919 [View Article] [PubMed]
     [Google Scholar]
  71. Butler EK, Davis RM, Bari V, Nicholson PA, Ruiz N. Structure-function analysis of MurJ reveals a solvent-exposed cavity containing residues essential for peptidoglycan biogenesis in Escherichia coli. J Bacteriol 2013; 195:4639–4649 [View Article] [PubMed]
     [Google Scholar]
  72. Schütze A, Benndorf D, Püttker S, Kohrs F, Bettenbrock K. The impact of ackA, PTA, and ackA-PTA mutations on growth, gene expression and protein Acetylation in Escherichia coli K-12. Front Microbiol 2020; 11:233 [View Article]
     [Google Scholar]
  73. Amabebe E, Reynolds S, Stern V, Stafford G, Paley M et al. Cervicovaginal fluid acetate: A metabolite marker of preterm Birth in symptomatic pregnant women. Front Med 2016; 3:48 [View Article] [PubMed]
     [Google Scholar]
  74. Molloy S. MutS2: key to diversity?. Nat Rev Microbiol 2005; 3:191 [View Article]
     [Google Scholar]
  75. Muscariello L, Marasco R, De Felice M, Sacco M. The functional ccpA gene is required for carbon catabolite repression in Lactobacillus plantarum. Appl Environ Microbiol 2001; 67:2903–2907 [View Article] [PubMed]
     [Google Scholar]
/content/journal/mgen/10.1099/mgen.0.001137
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Profiling of vaginal Lactobacillus jensenii isolated from preterm and full-term pregnancies reveals strain-specific factors relating to host interaction
M Gen 9, 001137 (2023); https://doi.org/10.1099/mgen.0.001137
/content/journal/mgen/10.1099/mgen.0.001137
/content/journal/mgen/10.1099/mgen.0.001137
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