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Qiu, C.

Publications and source records attributed to Qiu, C..

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Jagged1/Notch2 Controls Kidney Fibrosis via Tfam-mediated Metabolic Reprogramming

While Notch signaling has been proposed to play a key role in fibrosis, the direct molecular pathways targeted by Notch signaling and the precise ligand and receptor pair that are responsible for kidney disease remain poorly defined.\n\nIn this study, we found that JAG1 and NOTCH2 showed the strongest correlation with the degree of interstitial fibrosis in a genome wide expression analysis of a large cohort of human kidney samples. RNA sequencing analysis of kidneys of mice with folic acid nephropathy, unilateral ureteral obstruction, or APOL1-associated kidney disease indicated that Jag1 and Notch2 levels were higher in all analyzed kidney fibrosis models. Mice with tubule-specific deletion of Jag1 or Notch2 (Kspcre/Jag1flox/flox, and Kspcre/Notch2flox/flox) had no kidney-specific alterations at baseline, but showed protection from folic acid induced kidney fibrosis. Tubule-specific genetic deletion of Notch1 and global knock-out of Notch3 had no effect on fibrosis. In vitro chromatin immunoprecipitation experiments and genome-wide expression studies identified the mitochondrial transcription factor A (Tfam) as a direct Notch target. Re-expression of Tfam in tubule cells prevented Notch-induced metabolic and profibrotic reprogramming. Kidney tubule specific deletion of Tfam resulted in perinatal lethality.\n\nIn summary, Jag1/Notch2 plays a key role in kidney fibrosis development by regulating Tfam expression and metabolic reprogramming.

pathology

High- to low-level decoding does not generally improve perceptual performance

Ding et al. (1) recently proposed that the brain automatically encodes high-level, relative stimulus information (i.e. the ordinal relation between two lines), which it then uses to constrain the decoding of low-level, absolute stimulus features (i.e. when recalling the actual lines orientation). This is an interesting idea that is in line with the self-consistent Bayesian observer model (2, 3) and may have important implications for understanding how the brain processes sensory information. However, the notion suggested in Ding et al. (1) that the brain uses this decoding strategy because it improves perceptual performance is misleading. Here we clarify the decoding model and compare its perceptual performance under various noise and signal conditions.

animal behavior and cognition

Comprehensive single cell RNAseq analysis of the kidney reveals novel cell types and unexpected cell plasticity

A key limitations to understand kidney function and disease development has been that specific cell types responsible for specific homeostatic kidney function or disease phenotypes have not been defined at the molecular level.\n\nTo fill this gap, we characterized 57,979 cells from healthy mouse kidneys using unbiased single-cell RNA sequencing. We show that genetic mutations that present with similar phenotypes mostly affect genes that are expressed in a single unique differentiated cell type. On the other hand, we found unexpected cell plasticity of epithelial cells in the final segment of the kidney (collecting duct) that is responsible for final composition of the urine. Using computational cell trajectory analysis and in vivo linage tracing, we found that, intercalated cells (that secrete protons) and principal cells (that maintain salt, water and potassium balance) undergo a Notch mediated interconversion via a newly identified transitional cell type. In disease states this transition is shifted towards the principal cell fate. Loss of intercalated cells likely contributes to metabolic acidosis observed in kidney disease.\n\nIn summary, single cell analysis advanced a mechanistic description of kidney diseases by identifying a defective homeostatic cell lineage.\n\nOne Sentence SummaryA comprehensive single cell atlas of the kidney reveals a transitional cell type and cell plasticity determined by Notch signaling which is defective in chronic kidney disease.

cell biology