The role of cervical microbiome in cervical incompetence: insights from 16 S rRNA metagenomic sequencing

Abstract

Cervical incompetence (CI) is recognized as a critical factor contributing to mid-pregnancy miscarriage and preterm delivery, significantly affecting pregnancy outcomes. Despite this, the specific role of the microbiome in this pathological process remains inadequately understood. This study seeks to elucidate the core microbiome associated with CI in pregnant women and explore its potential biological mechanisms. Utilizing 16 S rRNA metagenomic sequencing, we examined the cervical mucus microbiota of women with CI both pre-operatively (PreOp) and post-operatively (PostOp). Subsequently, the immunomodulatory effects of these microbial communities on the immune system were systematically assessed using quantitative real-time PCR, Western blotting, and enzyme-linked immunosorbent assay. The findings revealed a significant reduction in microbial diversity and richness in PostOp cervical mucus, alongside notable alterations in microbiota composition. The genera Lactobacillus, Bifidobacterium, Gardnerella, Streptococcus, and Anaerococcus were identified as predominant. Further analysis demonstrated that treatment with 25% Lactobacillus crispatus (L. crispatus) supernatants, in comparison to 25% Group B Streptococcus (GBS) supernatants, resulted in high cell viability and normal morphology in HcerEpic cells. Importantly, the combination of 25% L. crispatus and 25% GBS supernatants significantly reduced the mRNA and protein expression levels of Toll-like receptor 4 (TLR4), Toll-like receptor 2 (TLR2), and nuclear factor kappa B (NF-κB) in vitro. These results indicate that L. crispatus may play a role in modulating cervical inflammation in CI by suppressing the TLR/NF-κB signaling pathway, potentially contributing to a more stable cervical microenvironment during pregnancy.

Keywords: Cervical incompetence; Cervical microbiome; Preterm birth; TLR/NF-κB signaling pathway.

Fig. 1

Characteristics of cervical mucus microbial community in the PreOp and PostOp. (A) Alpha diversity analysis. Sample species richness sobs index (a), sample core species number analysis (b), Alpha diversity index inter-group difference test (c); (B) Beta diversity analysis. Principal Component Analysis (PCA) on OUT level(a), principal co-ordinates analysis (PCoA) on OUT level (b), Partial Least Squares Discriminant Analysis (PLS-DA) on family level (c)

Fig. 2

Analysis of microbial load, microbial diversity and functional enrichment of cervical mucus in the PreOp and PostOp. A KEGG pathway analysis of differential microbiota. B GO functional enrichment analysis of differential microbiota. C MDI index comparison. D Venn diagram of unique OTUs in PreOp and PostOp samples. E Microflora composition analysis

Fig. 3

HcerEpic cells were stimulated with bacterial supernatants in vitro. A Microscopic images of cells after bacterial supernatants treatment. B Cell viability as measured by CCK8 assay for 24 h post-stimulation

Fig. 4

Relative gene expression levels of TLR4, TLR2, and NF-κB in HcerEpic stimulated with bacterial supernatants in vitro

Fig. 5

Relative expression of protein in c HcerEpic stimulated by bacterial supernatants in vitro. A Protein band of TLR4, TLR2, and NF-κB protein; B Statistical diagram of TLR4, TLR2, and NF-κB protein expression levels

Fig. 6

Changes in IL-1β, IL-6, and TNF-α cytokine levels in the supernatant of HcerEpic stimulated by bacterial supernatants for 24 h