A scalable mass spectrometry platform for proteome mapping of brain tissues

摘要 大脑是哺乳动物身体中最复杂的器官。整体分析掩盖了细胞的异质性 即使在最小的大脑区域也存在这种类型。脑的多组学单细胞分辨率三维表征 组织对于创建全面的脑细胞普查和替代方案至关重要。最新技术 进展允许哺乳动物大脑的单细胞转录组图谱，但单细胞蛋白质组学 技术远远落后于转录组技术。缺乏高分辨率蛋白质组 BICCN财团中脑组织的特征代表了两个组织之间的显著知识差距 蛋白质和信使核糖核酸更全面地了解不同的脑细胞是如何组织成 不同的解剖和功能区域。此应用程序的目标是通过开发 用于脑组织高分辨率3D蛋白质组图的强健可伸缩质谱学(MS)平台。 我们最近在技术开发方面的进展和我们在以下方面的经验有力地支持了这一可行性 小鼠组织的蛋白质组图谱。目标1将专注于开发健壮的、可伸缩的MS平台 通过1)进一步改进样品制备，快速有效地处理单细胞和小组织 体素，以及2)利用我们集团开发的多种颠覆性技术显著改进 检测灵敏度和样品吞吐量。预计新平台将允许可靠的量化 每天约500个样本，单个细胞中含有3,000个蛋白质，100个细胞中含有6,500个蛋白质。目标2将 优化和演示可扩展的MS平台用于小鼠MOP和人M1的2D蛋白质组图 当与激光捕获组织体素显微解剖相结合时。AIM 3将把新平台应用于 BICCN联合体内MOP/M1的三维蛋白质组图谱及其与现有蛋白质组数据的整合 蛋白质组分析的转录组数据。我们设想，新的平台将成为一个方便的 BICCN财团高分辨率3D蛋白质组图谱的不可或缺的工具 扩展BICCN工具箱。反过来，它可以为提高我们对 大脑在健康和疾病中的功能。

ABSTRACT The brain is the most complex organ in the mammalian body. Bulk analysis obscures heterogeneity of cell types present even in the smallest brain regions. Multi-omics single-cell resolution 3D-characterization of brain tissue is critically important to create comprehensive brain cell censuses and altas. Recent technological advances allow for single-cell transcriptome mapping of mammalian brains, but single-cell proteomics technologies are lagging far behind transcriptomics technologies. The lack of high-resolution proteome characterization of brain tissues in the BICCN consortium represents a significant knowledge gap between protein and mRNA for achieving a more complete understanding of how diverse brain cells are organized into distinct anatomical and functional regions. The objective of this application is to address this gap by developing a robust scalable mass spectrometry (MS) platform for high-resolution 3D-proteome mapping of brain tissues. The feasibility is strongly supported by our recent progress in technology development and our experiences in proteome mapping of mouse tissues. Aim 1 will focus on the development of a robust scalable MS platform through 1) further improving sample preparation for rapid effective processing of single cells and small tissue voxels, and 2) leveraging multiple disruptive technologies developed at our group for significantly improving detection sensitivity and sample throughput. The new platform is expected to allow for reliable quantification of >3,000 proteins in single cells and >6500 proteins in 100 cells with ~500 samples per day. Aim 2 will optimize and demonstrate the scalable MS platform for 2D-proteome mapping of mouse MOp and human M1 when combined with laser capture microdissection for tissue voxels. Aim 3 will apply the new platform for 3D-proteome mapping of MOp/M1 within the BICCN consortium and integrate proteomic data with existing transcriptomic data for proteogenomic analysis. We envision that the new platform will become a convenient indispensable tool for high-resolution 3D-proteome mapping of brain tissues in the BICCN consortium and extend the BICCN toolbox. In turn, it could make substantial contributions to improve our understanding of brain function in health and disease.