Center for Nanomedicine at the Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Department of Chemical & Biomolecular Engineering, Johns Hopkins University, Baltimore, MD, United States.
Front Cell Infect Microbiol. 2023 Mar 31;13:1015625. doi: 10.3389/fcimb.2023.1015625. eCollection 2023.
Mucus in the female reproductive tract acts as a barrier that traps and eliminates pathogens and foreign particles via steric and adhesive interactions. During pregnancy, mucus protects the uterine environment from ascension of pathogens and bacteria from the vagina into the uterus, a potential contributor to intrauterine inflammation and preterm birth. As recent work has demonstrated the benefit of vaginal drug delivery in treating women's health indications, we sought to define the barrier properties of human cervicovaginal mucus (CVM) during pregnancy to inform the design of vaginally delivered therapeutics during pregnancy.
CVM samples were self-collected by pregnant participants over the course of pregnancy, and barrier properties were quantified using multiple particle tracking. 16S rRNA gene sequencing was performed to analyze the composition of the vaginal microbiome.
Participant demographics differed between term delivery and preterm delivery cohorts, with Black or African American participants being significantly more likely to delivery prematurely. We observed that vaginal microbiota is most predictive of CVM barrier properties and of timing of parturition. Lactobacillus crispatus dominated CVM samples showed increased barrier properties compared to polymicrobial CVM samples.
This work informs our understanding of how infections occur during pregnancy, and directs the engineering of targeted drug treatments for indications during pregnancy.
女性生殖道中的黏液起到屏障作用，通过空间和黏附相互作用捕获并消除病原体和外来颗粒。在怀孕期间，黏液可防止病原体和细菌从阴道上行进入子宫，这可能导致子宫内炎症和早产。最近的研究表明，阴道给药在治疗女性健康疾病方面具有益处，因此我们旨在确定妊娠期间人宫颈阴道黏液（CVM）的屏障特性，为妊娠期间阴道给药治疗方法的设计提供信息。
孕妇在妊娠期间自行采集 CVM 样本，并使用多种粒子追踪技术来定量测量屏障特性。进行 16S rRNA 基因测序以分析阴道微生物组的组成。
足月分娩组和早产分娩组的参与者人口统计学特征存在差异，黑人和非裔美国人更有可能早产。我们发现阴道微生物群最能预测 CVM 屏障特性和分娩时间。与多微生物群 CVM 样本相比，占主导地位的卷曲乳杆菌 CVM 样本显示出更高的屏障特性。
这项工作有助于我们了解怀孕期间感染是如何发生的，并指导针对妊娠期间特定适应症的靶向药物治疗的设计。
