henhaobio
Sign in

iScienceMolecular BiologyPeer-reviewed journal article

High Resolution Slide-seqV2 Spatial Transcriptomics Enables Discovery of Disease-Specific Cell Neighborhoods and Pathways

Jamie L. MarshalliD, Teia NoeliD, Qingbo S. WangiD, Haiqi CheniD, Evan M. MurrayiD, Ayshwarya SubramanianiD, Katherine A. VernoniD, Silvana Bazúa‐ValentiiD, Katie Liguori, Keith H. KelleriD, Robert R. StickelsiD, Breanna Nicole McBeaniD, Rowan M. HeneghaniD, Astrid WeinsiD, Evan Z. MacoskoiD, Fei CheniD, Anna GrekaiD

PDFDOIPreprint

Abstract

High resolution spatial transcriptomics is a transformative technology that enables mapping of RNA expression directly from intact tissue sections; however, its utility for the elucidation of disease processes and therapeutically actionable pathways remain largely unexplored. Here we applied Slide-seqV2 to mouse and human kidneys, in healthy and in distinct disease paradigms. First, we established the feasibility of Slide-seqV2 in human kidney by analyzing tissue from 9 distinct donors, 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 also found perturbations in 77 genes associated with the unfolded protein response (UPR). Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods. One-Sentence SummaryHigh resolution Slide-seqV2 spatial transcriptomics in human and mouse kidneys.

Citations
88
FWCI
5.80
Field percentile
top 2%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISRaghubar '20Vo '25Danaher '23Abedini '22Stickels '20Rodriques '19
67% semantic matchMolecular Biology
Arti M. Raghubar, Duy T. Pham, Xiao Tan+15 more·bioRxiv·Sep 29, 2020· 5 citations