Characterization of cervico-vaginal microbiota in women developing persistent high-risk Human Papillomavirus infection.
Monica Di PaolaCristina SaniAnn Maria ClementeAnna IossaEloisa PerissiGiuseppe CastronovoMichele TanturliDamariz RiveroFederico CozzolinoDuccio CavalieriFrancesca CarozziCarlotta De FilippoMaria Gabriella TorciaPublished in: Scientific reports (2017)
Changes in cervico-vaginal microbiota with Lactobacillus depletion and increased microbial diversity facilitate human papillomavirus (HPV) infection and might be involved in viral persistence and cancer development. To define the microbial Community State Types (CSTs) associated with high-risk HPV-persistence, we analysed 55 cervico-vaginal samples from HPV positive (HPV+) women out of 1029 screened women and performed pyrosequencing of 16S rDNA. A total of 17 samples from age-matched HPV negative (HPV-) women were used as control. Clearance or Persistence groups were defined by recalling women after one year for HPV screening and genotyping. A CST IV subgroup, with bacterial genera such as Gardnerella, Prevotella, Megasphoera, Atopobium, frequently associated with anaerobic consortium in bacterial vaginosis (BV), was present at baseline sampling in 43% of women in Persistence group, and only in 7.4% of women in Clearance group. Atopobium genus was significantly enriched in Persistence group compared to the other groups. Sialidase-encoding gene from Gardnerella vaginalis, involved in biofilm formation, was significantly more represented in Persistence group compared to the other groups. Based on these data, we consider the CST IV-BV as a risk factor for HPV persistence and we propose Atopobium spp and sialidase gene from G. vaginalis as microbial markers of HPV-persistence.
Keyphrases
- cervical cancer screening
- microbial community
- polycystic ovary syndrome
- high grade
- biofilm formation
- genome wide
- clinical trial
- escherichia coli
- breast cancer risk
- staphylococcus aureus
- adipose tissue
- type diabetes
- machine learning
- cystic fibrosis
- insulin resistance
- dna methylation
- sars cov
- lipopolysaccharide induced
- transcription factor
- antibiotic resistance genes
- pregnant women
- artificial intelligence
- study protocol
- candida albicans