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

• 批准号: 10375968
• 负责人: Liangcai Gu
• 金额: $ 54.25万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-24 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10375968
• 关键词: ATAC-seq; Acrylamides; Adult; Affinity; Aging; Animal Model; Antibodies; Bar Codes; Biological Assay; Cell Aging; Cell Communication; Cell model; Cells; Chromatin; 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; Tissues; United States National Institutes of Health; Validation; Work; base; cell type; cellular imaging; combinatorial; cost; healthspan; human tissue; image guided; improved; in vivo; indexing; innovation; luminescence resonance energy transfer; multimodal data; multimodality; multiple omics; multiplexed imaging; nanobodies; new technology; novel; olfactory bulb; paracrine; programs; scale up; senescence; success; transcriptome; transcriptome sequencing

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.

摘要