Mass Spectrometry-based Proteomics of Urine and Dialysate

While hundreds of laboratory parameters can be readily analyzed in blood, serum or plasma by standard clinical laboratories, available diagnostic parameters in urine are comparably sparse. Clinical decisions regarding stratification into risk-groups or even treatment of patients frequently need to rely on coarse markers of kidney damage such as the overall protein:creatinine ratio or the albumin:creatinine ratio of urine, supplementing clinical information and the results of kidney biopsy. A quantitative analysis of the protein content of urine appears appealing, as kidney diseases likely leak a protein fingerprint into urine. We will therefore establish state-of-the art technology based on mass spectrometry to compare individual rather than total protein ratios in urine, with the goal of correlating these values to states of health and disease. In the future, such markers may assist clinicians in risk stratification or treatment decisions regarding nephrological patients.

For sample preparation, urine will be fractionated into standard urinary sediment (cells, casts, and debris) and supernatant that may further be subdivided into soluble protein and nanovesicle i.e. exosome fractions. This strategy preserves the information content of these biologically diverse compartments, instead of pooling the entire urinary protein content, as established by several published proteomics analysis protocols of urine. Subsequently, protein will be isolated, disulfide bridges reduced and alkylated, and peptides produced by digestion with proteases LysC followed by trypsin. We will then apply available top-notch mass spectrometry at the IMP (Research Institute of Molecular Pathology) using a highly sensitive and fast timsTOF pro instrument to identify and quantify tens of thousands of peptides in each sample using data-dependant followed by data-independant analysis. For optimal reproducibility of peptide elution times, the mass spectrometer will be hyphenated to a UHPLC instrument equipped with a novel micro-pillar array column produced by lithographic etching of a silicon wafer. Data analysis (protein inference from peptide signals and quantification) will be performed on appropriate hardware available at the IMP (hosts with 24 cores and over 200 GB RAM). Finally, results will be correlated to clinical information available for the urine samples.

The methodology can be applied to all kinds of urine samples. We will first analyze samples from dialysis patients that still have residual urine production, as well as from used dialysate (which is conveniently available for dialysis patients) with the goal of detecting markers correlating with dialysis quality as part of the project “precision dialysis”. Second, we have a stock of urine samples that were obtained shortly after SARS-CoV-2 diagnosis, from patients who later developed severe versus mild disease. Early urine markers correlating with the risk of progressing to severe disease could help identify patients who benefit most from medical therapy (Nirmatrelvir+Ritonavir or monoclonal antibody). Our third application will be chronic kidney disease, in particular diabetes, with the goal of identifying markers correlating with disease status and risk of rapid progression.