High-resolution Slide-seqV2 spatial transcriptomics enables discovery of disease-specific cell neighborhoods and pathways

Jamie L. Marshall, Teia Noel, Qingbo S. Wang, Haiqi Chen, Evan 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

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number104097
JournaliScience
Volume25
Issue number4
DOIs
StatePublished - Apr 15 2022

Keywords

  • Cell biology
  • Pathophysiology
  • Transcriptomics

ASJC Scopus subject areas

  • General

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