Spatiotemporal analysis of gene regulatory programs associated with GBS infection during pregnancy

项目摘要 怀孕期间或产后感染与大量发病率有关， 全世界的死亡率。B族链球菌（GBS）是引起绒毛膜炎（CAM）和新生儿肺炎的主要原因 败血症胎盘作为GBS和宿主免疫反应之间的初始界面， 绒毛膜炎，构成宿主-病原体相互作用的场所。目前了解的 CAM的发病机制一直受到缺乏揭示空间和时间成分的工具的限制， 胎盘感染具体来说，我们缺乏对感染如何随着时间的推移和跨 胎盘结构单细胞基因组学和空间转录组学的突破性进展现在使 对感染过程进行公正和系统的分析。在这里，我们建议将这些方法应用于GBS 胎盘感染：检测宿主特异性反应，宿主-病原体界面， GBS感染计划在目标1中，我们将结合联合收割机空间转录组学和单细胞RNA-Seq来研究 GBS感染在一种新的上行感染和CAM小鼠模型中的进展。在目标2中， 同时研究宿主和病原体基因表达程序在原代人类感染过程中 胎盘巨噬细胞在目标3中，我们将通过系统地评估GBS感染的概念模型， 特定GBS基因的靶向缺失的影响。整合这些方法将提供一个丰富的视图， CAM期间宿主-病原体相互作用，并将导致确定新的干预目标。

PROJECT SUMMARY Infection during pregnancy or in the immediate postnatal period is associated with substantial morbidity and mortality worldwide. Group B Streptococcus (GBS) is a major cause of chorioamnionitis (CAM) and neonatal sepsis. The placenta acts as the initial interface between GBS and the host immune response during chorioamnionitis, constituting the locus of host-pathogen interaction. Current understanding of the pathogenesis of CAM has been limited by a lack of tools revealing the spatial and temporal components of placental infection. Specifically, we lack an understanding of how the infection unfolds over time and across the placental architecture. Breakthroughs in single-cell genomics and spatial transcriptomics now enable the unbiased and systematic analysis of the process of infection. Here we propose to apply these methods to GBS infection of the placenta: examining host-specific responses, the host-pathogen interface, and perturbations of the GBS infection program. In Aim 1 we will combine spatial transcriptomics and single-cell RNA-Seq to study the progression of GBS infection in a novel murine model of ascending infection and CAM. In Aim 2 we will simultaneously study host and pathogen gene expression programs during infection in primary human placental macrophages. In Aim 3 we will test a conceptual model of GBS infection by systematically assessing the effect of targeted deletions of specific GBS genes. Integrating these approaches will provide a rich view of host-pathogen interactions during CAM and will lead to the identification of new targets for intervention.