Published in

Oxford University Press, Function, 1(1), 2020

DOI: 10.1093/function/zqaa007

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Viewing Cortical Collecting Duct Function Through Phenotype-Guided Single-Tubule Proteomics

Distributing this paper is prohibited by the publisher
Distributing this paper is prohibited by the publisher

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Data provided by SHERPA/RoMEO

Abstract

AbstractThe revolution of the omics technologies has enabled profiling of the molecules of any sample. However, the heterogeneity of the kidney with highly specialized nephron segments like the cortical collecting duct (CCD) poses a challenge regarding integration of omics data and functional analysis. We examined function and proteome from the same single CCDs of C57Bl6 mice by investigating them in a double-barreled perfusion system before targeted mass spectrometry. Transepithelial voltage (Vte), transepithelial resistance, as well as amiloride-sensitive voltage (ΔVteamil) were recorded. CCDs were of 400–600 µm of length, showed lumen negative Vte between −8.5 and −32.5 mV and an equivalent short circuit current I’sc between 54 and 192 µA/cm2. On a single-tubule proteome level, intercalated cell (IC) markers strongly correlated with other intercalated cell markers and negatively with principal cell markers. Integration of proteome data with phenotype data revealed that tubular length correlated with actin and Na+-K+-ATPase expression. ΔVte(amil) reflected the expression level of the β-subunit of the epithelial sodium channel. Intriguingly, ΔVte(amil) correlated inversely with the water channel AQP2 and the negative regulator protein NEDD4L (NEDD4-2). In pendrin knockout (KO) mice, the CCD proteome was accompanied by strong downregulation of other IC markers like CLCNKB, BSND (Barttin), and VAA (vH+-ATPase), a configuration that may contribute to the salt-losing phenotype of Pendred syndrome. Proteins normally coexpressed with pendrin were decreased in pendrin KO CCDs. In conclusion, we show that functional proteomics on a single nephron segment scale allows function–proteome correlations, and may potentially help predicting function from omics data.