Multimodal histologic atlas of human bone marrow

项目摘要--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，再到 止血，全部来源于造血干细胞(HSC)。为了维持和调节这一过程，骨骼 骨髓基质细胞形成多个利基微环境，每个微环境都适合特定发育阶段的需要 血细胞数量。利用高度多元化的成像技术，我们提出的骨髓组织 测绘中心(TMC)的目标是系统地、定量地剖析细胞组成和空间 人类骨髓微环境的组织。由此产生的详细地图将作为一个开放的 全球平台，了解哪些细胞和相互作用对每个造血分支至关重要 成熟度，以及这些因素在不同解剖部位和不同患者人群中的差异。 TMC将在转录、翻译和后转录过程中定义细胞身份和细胞状态 使用纳米串DSP、多路离子束成像(MIBI)和MALDI-MSI的翻译水平， 分别生成RNA、蛋白质和N-糖链的定量空间地图。我们的跨学科团队不 不仅包括MIBI的发明者和MALDI-MSI的先驱，还包括人类造血干细胞和人类 造血学和具有组织病理学骨髓诊断专长的执业血液病理学家。至 克服处理坚硬的矿化骨的独特挑战，我们将利用并行、强大、 经临床验证的骨髓处理管道，最大限度地提高和标准化样本质量和 与当前和未来的技术兼容。无缝集成到标准临床工作流程中，我们的 管道可以方便地与组织核心共享预期收集的材料。样品将会是 从三个不同的来源收集：(1)预期的、与患者匹配的死者多地点收集 供者检查解剖部位的差异，(2)预期从髋关节采集股骨头 关节置换术标本的年龄差异，(3)斯坦福大学病理学档案中的髂骨 种族和性别之间的差异。这些多个收集策略、多个站点和不同 研究重点是对之前的HuBMAP项目的补充。数据分析核心团队开创了 多种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 最先进的细胞分割和细胞聚集和计数，以及邻域分析。这些工具是 广泛适用于所有高度多元化的定量成像技术。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地形化骨创造的进化机制 独特的微环境，满足发育不同功能的血细胞的营养需求。这个 骨髓组织结构和造血之间的相互依赖不仅在血细胞中具有信息性 成熟，但了解新陈代谢、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.