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

基于 PIXEL-seq 的空间多组学分析，用于具有单细胞分辨率的衰老细胞作图

基本信息

批准号：
10907054
负责人：
Liangcai Gu
金额：
$ 85.15万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-09-24 至 2025-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10907054
关键词：
ATAC-seq Acrylamides Adult Affinity Aging Antibodies Bar Codes Biological Assay Cell Aging Cell Communication Cell model Cells Chromatin Chromosome Mapping Collaborations Complex DNA Data Detection Disease Dissociation Equipment Excision Fishes Gel Gene Expression Gene Expression Regulation Generations Goals Heart Heterogeneity Human Human Cell Line In Situ In Vitro Individual Laboratories Libraries Life Liver Longevity Lung Maps Methodology Methods Microfluidics Mission Modification Molecular Morphology Mus Organ Phase Phenotype Post-Translational Protein Processing Process Production Protein Isoforms Proteins Proteome Public Health RNA Reagent Research Research Personnel Resolution Running Site Slide Spatial Distribution Specificity Structure of parenchyma of lung Surface Surgeon Techniques Technology Time Tissue Donors Tissue Procurements Tissues United States National Institutes of Health Validation Work cell type cellular imaging combinatorial cost fabrication healthspan human tissue image guided improved in vivo indexing innovation luminescence resonance energy transfer meter model organism multimodal data multimodality multiple omics multiplexed imaging nanobodies new technology novel olfactory bulb paracrine programs scale up senescence success tissue mapping transcriptome transcriptome sequencing transcriptomic profiling

项目摘要

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.

抽象的形态完整的人体组织中衰老细胞的综合鉴定和表征对于了解体内衰老和有针对性地去除这些细胞以改善健康寿命很重要由于缺乏普遍且明确的特征标记，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高度的存在发现衰老标记的首选途径是在空间上进行研究。以单细胞分辨率绘制不同组织和生命阶段细胞类型的“组学”状态。该项目旨在 (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) 对其进行优化和缩放以进行绘图 PI 实验室最近开发了一种新技术 PIXEL-seq。（聚合酶索引文库测序）并将其应用于具有 1 µm 分辨率和高分辨率的转录组空间分析 RNA捕获效率。实现其研究体内衰老机制和生产规模的潜力。数据生成，将追求三个具体目标：1）在 UG3 第 1 年，展示基于 PIXEL-seq 的空间具有单细胞分辨率的转录组、蛋白质组和 ATAC-seq 分析；2) 在 UH3 第 2 年，优化和将这些检测结合起来进行人体组织绘图；3) 在 UH3 第 3-4 年，扩大在人类心脏的应用，在第一个目标下，将开发 PIXEL-seq 以实现单细胞分辨率。通过图像引导细胞分割（目标 1A）并扩展到空间蛋白质组（目标 1B）和开放染色质通过渲染 DNA 标记抗体和 Tn5 处理的染色体 DNA 进行可及性测定（目标 1C），分别通过聚合酶凝胶捕获对于第二个目标，蛋白质组测定将被优化并扩展至使用多克隆微型结合剂进行 200 重，允许交叉验证衰老标记物和相关的同种型和翻译后修饰（目标 2A）将整合这些测定以获取多模式数据。使用人体组织进行捕获和验证（目标 2B）。提高聚合酶凝胶制造的通量（目标 3A），并交付给 CODCC 公开发布高来自多个个体组织捐献者的多个器官的多个位点的质量数据（目标 3B 和 3C）。研究人员还将参与联盟共同项目和其他尚未形成的合作。该项目的创新之处在于该方法将首次生成空间多模态人类具有前所未有的深度和分辨率的组织数据非常重要，因为该检测不需要专门的分析。设备，可以在 SenNet 和其他单细胞联盟中广泛实施。