4.7 Article

Quantitative Proteomics of All 14 Renal Tubule Segments in Rat

期刊

JOURNAL OF THE AMERICAN SOCIETY OF NEPHROLOGY
卷 31, 期 6, 页码 1255-1266

出版社

AMER SOC NEPHROLOGY
DOI: 10.1681/ASN.2020010071

关键词

kidney tubule; Mass spectrometry; Database; Systems Biology

资金

  1. National Heart, Lung, and Blood Institute (NHLBI) Division of Intramural Research [ZIA-HL001285, ZIA-HL006129]

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Background Previous research has used RNA sequencing in microdissected kidney tubules or single cells isolated from the kidney to profile gene expression in each type of kidney tubule epithelial cell. However, because proteins, not mRNA molecules, mediate most cellular functions, it is desirable to know the identity and amounts of each protein species to understand function. Recent improvements in the sensitivity of mass spectrometers offered us the ability to quantify the proteins expressed in each of 14 different renal tubule segments from rat. Methods We manually dissected kidney tubules from rat kidneys and subjected samples to protein mass spectrometry. We used the proteomic ruler technique to estimate the number of molecules of each protein per cell. Results Over the 44 samples analyzed, the average number of quantified proteins per segment was 4234, accounting for at least 99% of protein molecules in each cell. We have made the data publicly available online at the Kidney Tubule Expression Atlas website (https://esbl.nhlbi.nih.gov/KTEA/). Protein abundance along the renal tubule for many commonly studied water and solute transport proteins and metabolic enzymes matched expectations from prior localization studies, demonstrating the overall reliability of the data. The site features a correlated protein function, which we used to identify cell type-specific transcription factors expressed along the renal tubule. Conclusions We identified and quantified proteins expressed in each of the 14 segments of rat kidney tubules and used the proteomic data that we obtained to create an online information resource, the Kidney Tubule Expression Atlas. This resource will allow users throughout the world to browse segment-specific protein expression data and download them for their own research.

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