PIXEL-seq-based spatial, multi-omic profiling for senescent cell mapping with single-cell resolution

摘要 对形态完整的人体组织中衰老细胞的全面鉴定和表征是 这对于理解体内衰老和有针对性地去除这些细胞以改善健康状况非常重要 和寿命。由于缺乏通用和明确的标志物表征，这项任务一直具有挑战性。 衰老状态反映了衰老表型的复杂性和衰老过程中存在的高度依赖性， 异质衰老程序。用于发现衰老标志物的优选途径是空间地 以单细胞分辨率绘制不同组织和生命阶段中细胞类型的“组学”状态。的总目标 该项目是（i）开发一种空间，单细胞分辨率，多模式方法，同时分析 转录组、开放染色质和蛋白质组（或分泌组），以及（ii）优化和缩放它以进行映射 人体组织中的衰老细胞。PI的实验室最近开发了一种新技术PIXEL-seq （polony索引库测序），并将其应用于空间分布转录组，分辨率为1 μm， RNA捕获效率。实现其在研究体内衰老机制和生产规模方面的潜力 数据生成，将追求三个具体目标：1）在UG 3第1年，展示基于PIXEL-seq的空间 转录组、蛋白质组和ATAC-seq分析，具有单细胞分辨率; 2）在UH 3第2年，优化和 联合收割机用于人体组织绘图;和3）在UH 3第3-4年，扩大对人体心脏的应用， 肝脏和肺组织绘图。根据第一个目标，PIXEL-seq将被开发以实现单细胞分辨率 通过图像引导的细胞分割（Aim 1A）并扩展到空间蛋白质组（Aim 1B）和开放染色质 可接近性测定（Aim 1C），通过使DNA标记的抗体和Tn 5处理的染色体DNA， 分别通过聚合物凝胶捕获。对于第二个目标，将对蛋白质组测定进行优化和扩展， 200-使用多克隆微型结合剂的plex，允许衰老标记物和相关的 异构体和翻译后修饰（目的2A）。这些检测试剂盒将整合用于多模式数据 捕获并使用人体组织进行验证（目标2B）。在第三个目标中，应用程序将通过以下方式扩大规模： 提高聚合物凝胶制造的生产量（Aim 3A），并将其交付给CODCC用于公开发布高 来自几个个体组织供体的多个器官的几个部位的质量数据（目标3B和3C）。的 调查人员还将参加联合会的共同项目和其他尚未形成的合作。 所提出的项目是创新的，因为这种方法将首次产生空间多模态人 以前所未有的深度和分辨率获取组织数据。这是重要的，因为测定不需要专门的 该方法可以在SenNet和其他单小区联盟中广泛实施。

ABSTRACT Comprehensive identification and characterization of senescent cells in morphologically intact human tissues is important for understanding senescence in vivo and the targeted removal of these cells to improve healthspan and lifespan. This task has been challenging due to the lack of universal and unequivocal markers characterizing the senescence state, which reflects the complexity of the senescence phenotype and the existence of highly heterogeneous senescence programs. A preferred avenue for discovering senescence markers is to spatially map ‘omics’ states of cell types in different tissues and life stages at single cell resolution. The overall goal of this project is to (i) develop a spatial, single-cell-resolution, multimodal method that simultaneously analyze transcriptome, open chromatin, and proteome (or secretome), and (ii) optimize and scale it for mapping senescent cells in human tissues. The PI’s laboratory has recently developed a novel technique PIXEL-seq (polony-indexed library-sequencing) and applied it to spatially profile transcriptome with 1-µm resolution and high RNA capture efficiency. To realize its potential for studying in vivo senescence mechanism and production-scale data generation, three specific aims will be pursued: 1) In UG3 Year 1, demonstrate PIXEL-seq-based spatial transcriptome, proteome, and ATAC-seq assays with single-cell resolution; 2) In UH3 Year 2, optimize and combine these assays for human tissue mapping; and 3) In UH3 Years 3-4, scale up application to human heart, liver, and lung tissue mapping. Under the first aim, PIXEL-seq will be developed to achieve single-cell resolution by image-guided cell segmentation (Aim 1A) and expanded to spatial proteome (Aim 1B) and open chromatin accessibility assays (Aim 1C) by rendering DNA-tagged antibodies and Tn5-treated chromosomal DNAs, respectively, to capture by polony gels. For the second aim, the proteome assay will be optimized and scaled to 200-plex using polyclonal mini-binders, allowing the cross-validation of senescence markers and associated isoforms and post-translational modifications (Aim 2A). These assays will be integrated for multimodal data capture and validated using human tissues (Aim 2B). In the third aim, the application will be scaled up by increasing throughput of polony gel fabrication (Aim 3A) and to deliver to the CODCC for public release of high- quality data on several sites of multiple organs from several individual tissue donors (Aim 3B and 3C). The investigators will also participate in the Consortium common project and other collaborations yet to be formed. The proposed project is innovative in that this method will for the first time generate the spatial multimodal human tissue data at unprecedented depth and resolution. It is significant because the assays do not require specialized equipment and can be widely implemented in the SenNet and other single cell consortia.