Pregnant Female Reproductive Tissue Mapping Center

总结 胎盘、子宫和输卵管协同作用以实现成功的妊娠结局。他们 在怀孕期间发生结构和功能的显着变化，相互协调， 通过直接和远距离的细胞-细胞相互作用。在这里，我们建议生成和整合数据 根据体内成像和离体组织病理学和多组学体积、单核和空间分布数据， 为了生成健康人类妊娠女性生殖器官的参考多尺度3D图， 在怀孕期间。这些将作为未来研究的关键参考框架，旨在发现如何 组织结构和功能的扰动导致器官功能障碍和疾病。我们的队伍装备精良 为了实现这一目标，在临床妇产科和胎盘/围产期病理学的专业知识， 成像、空间分子谱、单细胞组学、细胞外基质（ECM）生物学、数据管理 和计算生物学。我们将利用我们完善的转化研究基础设施， 健康孕妇的不同队列。然后，我们将使用MRI和超声进行体内成像， 描绘组织结构、灌注、炎症、钙化和其他特征。分娩/手术后， 组织将以多种方式（新鲜、快速冷冻、保存在 用于最佳核酸分析的解决方案和FFPE），以使用各种 分子方法，并保留额外的样本用于未来的研究。临床数据的详细审查 并对相邻组织切片进行正式的组织病理学评价，以确认正常组织和正常组织的组织学特征。 从具有正常结果的受试者获得组织。初始离体分析包括细胞外 基质蛋白质组学，以及大量和单核RNAseq和ATACseq。这些研究的结果将是 分析以确定随后的成像质谱细胞术（IMC）和空间转录组学的靶点。 问题研究这些数据类型将被集成，以实现不同单元格类型之间关系的映射 以及细胞与周围细胞外基质之间的微观联系。我们注意到， 来自相邻样品的多种数据类型，以及使用Multi-Ome测定（其执行RNAseq 和索引到相同核的ATACseq数据）和空间转录组学方法， 基于化学的预成像将使我们能够在不同的数据集之间架起桥梁。独特的 胎盘中的内皮细胞群和绒毛外滋养层的内皮拟态将 提供与其他以内皮为中心的HuBMAP项目（例如淋巴 系统、内皮图谱和肾图谱）。将与其他HuBMAP中心建立密切互动 实现数据和元数据标准的协调，资源共享（例如，与HuBMAP的抗体 正在开发/使用CODEX和MIBI-TOF的中心），快速采用新技术， 数据分析，并与HIVE和更广泛的科学界快速共享数据。

SUMMARY The placenta, uterus, and fallopian tubes act in concert to achieve successful pregnancy outcomes. They undergo marked changes in structure and function during pregnancy, coordinating with one another and other maternal organs via direct and distant cell-cell interactions. Here, we propose to generate and integrate data from in vivo imaging and ex vivo histopathologic and multi-omic bulk, single-nucleus, and spatial profiling data, in order to generate reference multiscale 3D maps of healthy human pregnant female reproductive organs across pregnancy. These will serve as key frames of reference for future studies aiming to discover how perturbation of tissue structure and function leads to organ dysfunction and disease. Our team is well-equipped to achieve this goal, with expertise in clinical Obstetrics & Gynecology and Placental/Perinatal Pathology, imaging, spatial molecular profiling, single-cell omics, extracellular matrix (ECM) biology, data management, and computational biology. We will leverage our well-established translational research infrastructure to recruit diverse cohorts of healthy pregnant women. We will then perform in vivo imaging using MRI and ultrasound to delineate tissue structure, perfusion, inflammation, calcifications, and other features. After delivery/surgery, tissues will be rapidly sampled, processed, and stored in multiple ways (fresh, flash frozen, preserved in solutions for optimal nucleic acid analysis, and FFPE) to enable generation of high-quality data using a variety of molecular approaches, with additional samples retained for future studies. Detailed review of clinical data and formal histopathologic evaluation of adjacent tissue sections will be performed to confirm that normal tissue has been obtained from subjects with normal outcomes. Initial ex vivo analysis includes extracellular matrix proteomics, and bulk and single-nucleus RNAseq and ATACseq. The results of these studies will be analyzed to identify targets for the subsequent imaging mass cytometry (IMC) and spatial transcriptomic studies. These data types will be integrated to enable mapping of the relationships among different cell types and between cells and the surrounding extracellular matrix on the microscopic level. We note that generation of multiple data types from adjacent samples, and the use of the Multi-Ome assay (which performs RNAseq and ATACseq data indexed to the same nuclei) and spatial transcriptomic methods with immunohistochemistry-based pre-imaging, will enable us to bridge between diverse datasets. The unique populations of endothelial cells in the placenta and the endothelial mimicry of the extravillous trophoblast will provide unique opportunities to integrate with other endothelial-centric HuBMAP projects (e.g. lymphatic system, endothelial atlas, and kidney atlas). Close interactions with other HuBMAP Centers will be established to enable harmonization of data and metadata standards, sharing of resources (e.g. antibodies with HuBMAP Centers that are developing/using CODEX and MIBI-TOF), rapid adoption of new technologies, collaborative data analysis, and rapid sharing of data with the HIVE and the broader scientific community.