High Resolution Slide-seqV2 Spatial Transcriptomics Enables Discovery of Disease-Specific Cell Neighborhoods and Pathways
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Summary
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), including Tmed9. Treatment with a TMED9-targeting compound showed efficient removal of toxic mutant proteins and reversal of the UPR. Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods and actionable targets.
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), including Tmed9. Treatment with a TMED9-targeting compound showed efficient removal of toxic mutant proteins and reversal of the UPR. Our studies illustrate and experimentally validate the utility of Slide-seqV2 for the discovery of disease-specific cell neighborhoods and actionable targets.
Overall design
For the BTBR experiments, the BTBR-wt/wt are controls and BTBR-ob/ob are diabetic samples. Seven arrays per mouse and 4 mice of each gentoptype were processed. For the UMOD experiments, UMOD-WT are controls and UMOD-KI are ADTKD samples. Five arrays per mouse and 3 WT mice and 5 KI mice were processed. There are 3 separate files types: BAMs, raw data which is unmapped spatial data, and processed data which contains QCed and mapped kidney cell types.
For the BTBR experiments, the BTBR-wt/wt are controls and BTBR-ob/ob are diabetic samples. Seven arrays per mouse and 4 mice of each gentoptype were processed. For the UMOD experiments, UMOD-WT are controls and UMOD-KI are ADTKD samples. Five arrays per mouse and 3 WT mice and 5 KI mice were processed. There are 3 separate files types: BAMs, raw data which is unmapped spatial data, and processed data which contains QCed and mapped kidney cell types.
Technology
Slide-seqV2
Slide-seqV2
Platform
Illumina NovaSeq 6000 (Mus musculus)
Illumina NovaSeq 6000 (Mus musculus)
Species
Mus musculus
Tissues
kidney cross-section
kidney cross-section
Organ parts
cortex, medulla, and renal pelvis
cortex, medulla, and renal pelvis
Development stage
6 month
6 month
Disease
control
control
Citation
Marshall JL, Noel T, Wang QS, et al. High-resolution Slide-seqV2 spatial transcriptomics enables discovery of disease-specific cell neighborhoods and pathways. iScience. 2022;25(4):104097. Published 2022 Mar 16. doi:10.1016/j.isci.2022.104097
Marshall JL, Noel T, Wang QS, et al. High-resolution Slide-seqV2 spatial transcriptomics enables discovery of disease-specific cell neighborhoods and pathways. iScience. 2022;25(4):104097. Published 2022 Mar 16. doi:10.1016/j.isci.2022.104097
Submission date: 2021-12-03Update date: 2022-04-07
Contributors
Marshall, Jamie L; Noel, Teia; Wang, Qingbo S; Greka, Anna
Accessions
GEO Series Accessions:
GSE190094