Pregnant Female Reproductive Tissue Mapping Center

孕妇生殖组织测绘中心

• 批准号: 10670431
• 负责人: LOUISE CHANG LAURENT
• 金额: $ 220.03万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN DIEGO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10670431
• 关键词: 3-Dimensional; ATAC-seq; Adoption; Antibodies; Atlases; Award; Biological Assay; Biology; Blood; Cell Communication; Cell Differentiation process; Cell Nucleus; Cells; Chromatin; Circulation; Clinical; Clinical Data; Collaborations; Collection; Communication; Communities; Computational Biology; Cytometry; Data; Data Analyses; Data Set; Development; Discipline of obstetrics; Disease; Distant; Endothelial Cells; Endothelium; Evaluation; Extracellular Matrix; Female; Freezing; Functional disorder; Funding; Future; Generations; Goals; Grant; Gynecology; Histologic; Histology; Hormone Responsive; Human; Human BioMolecular Atlas Program; Image; Immunoassay; Immunohistochemistry; Inflammation; Infrastructure; Kidney; Lymphatic System; Magnetic Resonance; Magnetic Resonance Imaging; Mammalian Oviducts; Maps; Mediating; Metadata; Methods; Microscopic; Modality; Molecular; Molecular Profiling; Morphology; Normal tissue morphology; Nucleic Acids; Operative Surgical Procedures; Organ; Outcome; Pathology; Perfusion; Perinatal; Phase; Placenta; Placentation; Population; Pre-Eclampsia; Pregnancy; Pregnancy Complications; Pregnancy Outcome; Pregnant Uterus; Pregnant Women; Premature Labor; Process; Proteomics; Public Health; Quality Control; RNA; Research; Research Infrastructure; Research Personnel; Resolution; Resource Sharing; Sampling; Signal Transduction; Structure; Study models; System; Techniques; Technology; Time; Tissue Sample; Tissues; Translational Research; Ultrasonography; Villous; Visualization; Work; XCL1 gene; calcification; candidate identification; cell component function; cell motility; cell type; cohort; collaboratory; data harmonization; data integration; data management; data sharing; data standards; diverse data; extracellular; healthy pregnancy; human female; image reconstruction; imaging modality; in vivo; in vivo imaging; indexing; innovation; interest; interoperability; metadata standards; migration; mimicry; multiple data types; multiple omics; multiscale data; new technology; pregnant; preservation; recruit; reproductive; reproductive organ; senescence; spatiotemporal; tissue mapping; tool; transcriptome; transcriptome sequencing; transcriptomics; trophoblast; ultrasound

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.

概括 胎盘，子宫和输卵管协同起作用，以实现成功的妊娠结局。他们 怀孕期间的结构和功能发生了明显的变化，彼此之间的协调 孕产妇器官通过直接和遥远的细胞相互作用。在这里，我们建议生成和集成数据 从体内成像和离体组织病理学和多氨基散装，单核和空间分析数据， 为了生成参考的多尺度3D地图，健康的人类怀孕的女性生殖器官 整个怀孕。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。我们的团队设备齐全 为了实现这一目标，具有临床妇产科和胎盘/围产期病理学方面的专业知识， 成像，空间分子谱分析，单细胞法，细胞外基质（ECM）生物学，数据管理， 和计算生物学。我们将利用良好的转化研究基础设施来招募 多样化的健康孕妇。然后，我们将使用MRI和超声检查进行体内成像 描绘组织结构，灌注，炎症，钙化和其他特征。分娩/手术后， 组织将通过多种方式迅速采样，处理和存储（新鲜，闪光冷冻，保存在 最佳核酸分析的解决方案，以及FFPE），可以使用一种品种生成高质量数据 分子方法，并保留了其他样本以进行未来的研究。临床数据的详细审查 并将对相邻组织切片进行正式的组织病理学评估，以确认正常 从具有正常结果的受试者获得组织。初始的离体分析包括细胞外 基质蛋白质组学，散装和单核RNASEQ和ATACSEQ。这些研究的结果将是 分析以识别随后成像质量细胞仪（IMC）和空间转录组的靶标 研究。这些数据类型将集成以启用不同单元类型之间的关系映射 在细胞和周围的细胞外基质之间在微观水平上。我们注意到那一代 来自相邻样品的多种数据类型以及使用多组分的使用（该测定法 和Atacseq数据索引到相同的核）和空间转录方法，并具有 基于免疫组织化学的预知将使我们能够在不同的数据集之间桥接。独特 胎盘中内皮细胞的种群和跨滋养细胞的内皮模仿将 提供独特的机会与其他以内皮为中心的Hubmap项目集成（例如 系统，内皮地图集和肾脏地图集）。将建立与其他Hubmap中心的密切互动 为了实现数据和元数据标准的协调，共享资源（例如，使用HubMap的抗体 正在开发/使用codex和mibi-tof的中心，快速采用新技术，协作 数据分析，并与Hive和更广泛的科学界快速共享数据。