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Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy

Authors: Shuya Liu; Yu Zhao; Shun Lu; Tianran Zhang; Maja T. Lindenmeyer; Viji Nair; Sydney E. Gies; +17 Authors

Single-cell transcriptomics reveals a mechanosensitive injury signaling pathway in early diabetic nephropathy

Abstract

Abstract Background Diabetic nephropathy (DN) is the leading cause of end-stage renal disease, and histopathologic glomerular lesions are among the earliest structural alterations of DN. However, the signaling pathways that initiate these glomerular alterations are incompletely understood. Methods To delineate the cellular and molecular basis for DN initiation, we performed single-cell and bulk RNA sequencing of renal cells from type 2 diabetes mice (BTBR ob/ob) at the early stage of DN. Results Analysis of differentially expressed genes revealed glucose-independent responses in glomerular cell types. The gene regulatory network upstream of glomerular cell programs suggested the activation of mechanosensitive transcriptional pathway MRTF-SRF predominantly taking place in mesangial cells. Importantly, activation of MRTF-SRF transcriptional pathway was also identified in DN glomeruli in independent patient cohort datasets. Furthermore, ex vivo kidney perfusion suggested that the regulation of MRTF-SRF is a common mechanism in response to glomerular hyperfiltration. Conclusions Overall, our study presents a comprehensive single-cell transcriptomic landscape of early DN, highlighting mechanosensitive signaling pathways as novel targets of diabetic glomerulopathy.

Keywords

Research, Kidney Glomerulus, R, QH426-470, Mice, Diabetes Mellitus, Type 2, Genetics, Medicine, Animals, Diabetic Nephropathies, Transcriptome, Signal Transduction

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
33
Top 10%
Top 10%
Top 1%
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