High-resolution Slide-seqV2 Spatial Transcriptomics Enables Discovery of Disease-specific Cell Neighborhoods and Pathways

Overview

Journal iScience

Publisher Cell Press

Date 2022 Apr 4

PMID 35372810

Authors

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

Affiliations

Soon will be listed here.

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 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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