Medical student Case Western Reserve Univ. Sch. of Med., United States
Disclosure(s):
Yong Guang Jiang: No financial relationships to disclose
Introduction/Rationale: A healthy human vaginal microbiome is characterized by low microbial diversity and is dominated by Lactobacillus spp. Notably, a Lactobacillus-dominant vaginal microbiome has been associated with reduced risk of human papillomavirus (HPV) infection and persistence. Although HPV infections are prevalent, it is unclear why some high-risk HPV-infected individuals develop squamous intraepithelial lesions (SIL) and cervical cancer. A clinical study revealed that the proportion of Lactobacillus inversely correlated with SIL grade, suggesting that the vaginal microbiome may influence epithelial oncogenesis. Antibody-coating of bacteria plays an important role in regulating microbial composition and activity. In the vagina, L. crispatus-dominant microbiomes are associated with higher levels of IgA-coated bacteria. In this study, we aim to define the associations between the proportion and composition of antibody-coated and uncoated bacteria in women with low-grade SIL (L-SIL) and high-grade SIL (H-SIL).
Methods: We utilized fluorescence-activated cell sorting to sort vaginal bacteria from women with L-SIL or H-SIL into IgA+IgG-, IgA-IgG+, IgA-IgG-, and IgA+IgG+ subsets. Additionally, we visualized antibody-coated vaginal bacteria with a spectral flow cytometer.
Results: The proportion of antibody-coated bacteria subsets described above did not differ between women with HSIL and LSIL. However, gating on IgG+ and total IgA+ populations revealed that women with LSIL have significantly higher levels of IgG-coated bacteria than women with HSIL. Additionally, we found that IgA and IgG exhibit distinct and non-overlapping patterns on vaginal bacteria.
Conclusion: The reduced IgG coating observed in HSIL may reflect the underlying epithelial disruption and dysbiosis associated with advanced lesion progression. The divergent IgG and IgA coating patterns potentially reflect differences in epitope recognition. Future work will use 16S rRNA sequencing to identify bacterial taxa associated with IgA and IgG binding.
