PeerJ (Nov 2019)

Characteristics of the vaginal microbiome in cross-border female sex workers in China: a case-control study

  • Xiang Hong,
  • Shenghao Fang,
  • Kaiping Huang,
  • Jiechen Yin,
  • Jianshuang Chen,
  • Yan Xuan,
  • Jing Zhu,
  • Jun Ma,
  • Pengfei Qin,
  • Danhong Peng,
  • Ning Wang,
  • Bei Wang

DOI
https://doi.org/10.7717/peerj.8131
Journal volume & issue
Vol. 7
p. e8131

Abstract

Read online Read online

Background Female sex workers (FSWs) are key groups in the transmission of sexual transmitted infections (STI), and vaginal microbiome variations play an important role in transmission. We aimed to explore the characteristics of vaginal microbiome among FSWs. Materials and Methods A total of 24 cross-border FSWs were randomly selected from a cross-sectional survey for female sex workers in southwest China. Thirty-seven female non-sex workers (FNSWs) were randomly selected from the gynecology clinic and health examination center. Vaginal swabs were collected, bacterial DNA extracted and 16S rRNA genes were sequenced. Differences in the vaginal microbiome between both groups were compared using bioinformatics analysis. Results One DNA sample was excluded due to unqualified concentration, therefore 60 samples were sequenced. FSWs had significantly different vaginal microbiota β diversity, but undifferentiated α diversity when compared with non-sex workers. The average relative abundance of Sneathia, Shigella, Neisseria, Chlamydia, Prevotella, Enterococcus and Ureaplasma among FSWs was higher than FNSWs, and relative abundance of Atopobium in FSWs was lower than FNSWs. The Lactobacillus genus was the major genus in both groups. At the species level, Lactobacllus crispatus, Lactobacllus gasseri and Lactobacllus jensenii, in female sex workers, were lower when compared to FNSWs. Conclusion There were distinct differences in vaginal bacteria variety between FSWs and FNSWs. Some disease-related genus were also more abundant in FSWs. Based on these observations, further research is required to identify microbiome communities related to high STI risks and other diseases in these cohorts.

Keywords