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A method for deep and quantitative protein profiling of urine sediment, soluble and exosome fractions for biomarker research

Pichler, P.; Kurnikowski, A.; Matzinger, M.; Mechtler, K.

2023-06-28 biochemistry
10.1101/2023.06.26.546632 bioRxiv
Show abstract

Urine collection is painless and offers the potential for kidney liquid-biopsy(1), which appears particularly appealing with regard to the diagnosis of kidney disease (2) and patient follow-up after renal transplantation (3). From a nephrological point of view, urinary sediment and the soluble and exosome fractions of urine constitute different biological entities. We here describe a method that allows deep profiling of the protein content of the above-mentioned three fractions of urine by quantitative data-independent label-free proteomics. The method was evaluated using 19 urine samples from the Nephrology outpatient clinic at Vienna General Hospital, comprising a diverse set of chronic kidney disease (CKD) as well as patients after kidney transplantation (NTX). Peptide separation was accomplished through 60 min active gradients. A timsTOF Pro2 mass spectrometer was operated in DIA mode. The total analysis time per urine sample (three fractions) was around four hours. We demonstrate adequate technical and experimental reproducibility. Our data suggest that the protein information content of these three fractions is diverse, strengthening the importance of separate analysis. The depth of our quantitative proteomics approach permitted a detection of proteins characteristic for different parts of the nephron, such as Podocin, CD2-AP and Podocalyxin (Podocytes), SLC22A8 and SLC22A13 (proximal tubule) and Aquaporin-2 (collecting duct), suggesting that our method is sensitive enough to detect and quantify biologically relevant proteins that might serve as potential biomarkers. To the best of our knowledge, the ability to quantify up to 4000 protein groups per urine sample and more than 6000 protein groups in total makes our strategy the deepest proteome profiling study of urine to date. In conclusion, we established a method with promising figures of merit that we consider broadly applicable and useful for future clinical biomarker research studies in urine.

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