A comprehensive map of the human urinary proteome

Abstract

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.

Figure 1

Workflow employed to characterize the urinary proteome. Pooled urine from healthy individuals was processed by two different approaches. A fraction of pooled urine was resolved by SDS-PAGE without any enrichment. Gel bands were excised followed by in-gel digestion. Another fraction was subjected to lectin affinity chromatography using three lectins (Concanavalin A, wheat germ agglutinin and jacalin) followed by SDS-PAGE and in-gel digestion. In-gel digested gel bands from two different approaches were further analyzed by liquid chromatography tandem mass spectrometry (LC–MS/MS) on an LTQ-Orbitrap Velos mass spectrometer. Data derived from mass spectrometric analysis were then searched using Mascot and Sequest search engines.

Figure 2

Venn diagram comparing large scale studies on urinary proteome. Protein identifications from the current study were compared to two other studies (Adachi et al., 2006 and Li et al., 2010) that were carried out using high-resolution mass spectrometers. A total of 744 proteins were unique to this study, whereas 373 proteins were unique to Adachi et al. and 308 were unique to Li et al.

Figure 3

Representative MS/MS spectra of peptides from selected proteins that were identified based on single peptide evidence. (A) Shroom2 (SHROOM2). (B) Tumor suppressor candidate 2 (TUSC2). (C) Kallikrein-11. (D) Folate receptor beta (FOLR2).

Figure 4

Gene Ontology based classification of proteins. (A) Cellular component, (B) molecular function and (C) biological process based classification of identified proteins in this study.