Multimodal histologic atlas of human bone marrow

项目概要-总体 骨髓产生血细胞，其功能范围从氧气输送到抗微生物防御， 止血，全部源自造血干细胞（HSC）。为了维持和调节这一过程，骨 骨髓基质细胞形成多个小生境微环境，每个小生境微环境都是针对特定发育中的细胞的需要而定制的。 血细胞数量使用高度多路复用的成像技术，我们提出的骨髓组织 制图中心（TMC）旨在系统和定量地剖析细胞组成和空间分布， 组织的人骨髓微环境。由此产生的详细地图将作为一个开放的， 了解哪些细胞和相互作用对造血系统的每个分支至关重要的全球平台 成熟，以及这些如何因解剖部位和不同患者人口统计学而变化。 TMC将在转录、翻译和转录后阶段定义细胞身份和细胞状态。 使用Nanostring DSP、多路复用离子束成像（MIBI）和MALDI-MSI， 分别生成RNA、蛋白质和N-聚糖的定量空间图。我们的跨学科团队 不仅包括MIBI的发明者和MALDI-MSI的先驱，而且还包括人类HSC和人类造血干细胞的专家。 一位具有骨髓组织病理学诊断专业知识的执业血液病理学家。到 克服与坚硬，矿化骨工作的独特挑战，我们将利用平行，强大， 经临床验证的骨髓处理管道，可最大限度地提高和标准化样本质量， 与当前和未来技术的兼容性。无缝集成到标准临床工作流程中，我们的 管道使得能够方便地与组织芯共享预期收集的材料。样品将 从三个不同的来源收集：（1）前瞻性，患者匹配的多个地点收集死者 供体以检查解剖部位之间的差异，（2）从髋关节前瞻性收集股骨头 年龄范围间差异的关节成形术标本，（3）斯坦福大学病理学档案中的髂嵴骨 种族和性别的差异。这些多个收集策略，多个站点， 研究重点补充了以前的HuBMAP项目。数据分析核心团队开创了 多个新颖的数据处理流水线，包括基于像素的分析、基于细胞的分析，包括 现有技术的细胞分割和细胞聚类和计数，以及邻域分析。这些工具 广泛适用于所有高度多重定量成像技术。总的来说，我们的团队和战略是 非常适合执行拟议的骨髓TMC的愿景。 骨髓的空间结构反映了骨骼的进化机制， 独特的微环境，满足不同功能的血细胞发育的营养需求。的 骨髓组织结构和造血之间相互依赖不仅在血细胞中 成熟，但了解代谢，衰老和细胞疗法的发展。

Project Summary – Overall Bone marrow produces blood cells whose functions range from oxygen delivery to anti-microbial defense to hemostasis, all originating from hematopoietic stem cells (HSC). To sustain and regulate this process, bone marrow stromal cells form multiple niche microenvironments, each tailored to the needs of a particular developing blood cell population. Using highly-multiplexed imaging technologies, our proposed Bone Marrow Tissue Mapping Center (TMC) aims to systematically and quantitatively dissect the cellular composition and spatial organization of human bone marrow microenvironments. The resulting detailed maps will serve as an open and global platform for understanding which cells and interactions are critical for each branch of hematopoietic maturation, and how these vary by anatomical site and across diverse patient demographics. The TMC will define cellular identities and cell states at the transcriptional, translational, and post- translational levels using Nanostring DSP, Multiplexed Ion Beam Imaging (MIBI), and MALDI-MSI, which generate quantitative spatial maps of RNA, protein, and N-glycans, respectively. Our cross-disciplinary team not only includes the inventors of MIBI and a pioneer of MALDI-MSI, but also experts in human HSCs and human hematopoiesis and a practicing hematopathologist with expertise in histopathologic bone marrow diagnosis. To overcome the unique challenges of working with hard, mineralized bone, we will leverage parallel, robust, clinically-validated bone marrow processing pipelines which maximize and standardize sample quality and compatibility with current and future technologies. Integrating seamlessly into standard clinical workflows, our pipelines enable convenient sharing of prospectively-collected materials with the Tissue Core. Samples will be collected from three different sources: (1) prospective, patient-matched multi-site collection from deceased donors to examine differences between anatomical sites, (2) prospective collection of femoral head from hip arthroplasty specimens for differences between age ranges, (3) iliac crest bone in the Stanford Pathology archive for differences between races and genders. These multiple collection strategies, multiple sites, and different investigational focuses complement prior HuBMAP projects. The Data Analysis Core team has pioneered multiple novel data processing pipelines, including pixel-based analyses, cell-based analyses including state-of- the-art cell segmentation and cell clustering and enumeration, and neighborhood analyses. These tools are broadly-applicable to all highly-multiplexed quantitative imaging technologies. Overall, our team and strategy are exceedingly well-suited for executing the vision of the proposed Bone Marrow TMC. The spatial structure of bone marrow reflects the evolutionary mechanisms that terraformed bone to create unique microenvironments meeting the nutritional needs of developing blood cells with divergent functions. The interdependence between bone marrow tissue structure and hematopoiesis is informative not just in blood cell maturation, but for understanding metabolism, aging, and development of cellular therapies.