转录组
计算生物学
生物
细胞
人口
疾病
细胞生物学
人类疾病
基因
基因表达
病理
医学
遗传学
环境卫生
作者
Jamie L. Marshall,Teia Noel,Qingbow S. Wang,Haiqi Chen,Evan D. Murray,Ayshwarya Subramanian,Katherine A. Vernon,Silvana Bazua-Valenti,Katie Liguori,Keith Keller,Robert R. Stickels,Breanna McBean,Rowan M. Heneghan,Astrid Weins,Evan Z. Macosko,Fei Chen,Anna Greka
出处
期刊:iScience
[Cell Press]
日期:2022-03-01
卷期号:25 (4): 104097-104097
被引量:13
标识
DOI:10.1016/j.isci.2022.104097
摘要
High-resolution spatial transcriptomics enables mapping of RNA expression directly from intact tissue sections; however, its utility for the elucidation of disease processes and therapeutically actionable pathways remains unexplored. We applied Slide-seqV2 to mouse and human kidneys, in healthy and distinct disease paradigms. First, we established the feasibility of Slide-seqV2 in tissue from nine distinct human kidneys, which revealed a cell neighborhood centered around a population of LYVE1+ macrophages. Second, in a mouse model of diabetic kidney disease, we detected changes in the cellular organization of the spatially restricted kidney filter and blood-flow-regulating apparatus. Third, in a mouse model of a toxic proteinopathy, we identified previously unknown, disease-specific cell neighborhoods centered around macrophages. In a spatially restricted subpopulation of epithelial cells, we discovered perturbations in 77 genes associated with the unfolded protein response. Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods.
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