A comprehensive analysis and annotation of human normal urinary proteome

Abstract

Biomarkers are measurable changes associated with the disease. Urine can reflect the changes of the body while blood is under control of the homeostatic mechanisms; thus, urine is considered an important source for early and sensitive disease biomarker discovery. A comprehensive profile of the urinary proteome will provide a basic understanding of urinary proteins. In this paper, we present an in-depth analysis of the urinary proteome based on different separation strategies, including direct one dimensional liquid chromatography-tandem mass spectrometry (LC/MS/MS), two dimensional LC/MS/MS, and gel-eluted liquid fraction entrapment electrophoresis/liquid-phase isoelectric focusing followed by two dimensional LC/MS/MS. A total of 6085 proteins were identified in healthy urine, of which 2001 were not reported in previous studies and the concentrations of 2571 proteins were estimated (spanning a magnitude of 10⁶) with an intensity-based absolute quantification algorithm. The urinary proteins were annotated by their tissue distribution. Detailed information can be accessed at the "Human Urine Proteome Database" (www.urimarker.com/urine).

Figure 1

The workflow of urinary proteome analysis. Pooled urine from 24 humans was analyzed using three separation strategies. 1D: Urinary peptides were directly analyzed via 1DLC/MS/MS without fractionation. 2D: Urinary peptides were analyzed via offline RPLC and 1DLC/MS/MS. 3D: Urinary proteins were first fractionated by GELFrEE/LP-IEF prior to offline RPLC. A total of 383 fractions were analyzed by LC/MS/MS using high-resolution TripleTOF 5600 MS. A urine proteome database was then constructed based on bioinformatics analyses.

Figure 2

The results from three separation strategies. (A) A Coomassie-stained Bis-Tris gel image of 12 GELFrEE fractions over a broad mass range. (B) Coomassie-stained Bis-Tris gel image of 10 LP-IEF fractions over a pI range from 3 to 10. (C) Venn diagram of proteins identified by three separation strategies. (D) Venn diagram of proteins identified from this study as well as previous urine and exosome proteome studies. (E) Comparative analysis of the urine, kidney and plasma proteome.

Figure 3

Quantitative analysis of urinary proteins by the iBAQ method. (A) The relative expression and concentrations of 2,571 proteins in the 2D analysis were estimated by iBAQ. The left y-axis represents relative abundance, and the right y axis represents estimated concentration (pg/mL). (1) ALB: albumin; UROM: uromodulin, the two most abundant proteins. (2) RARS: arginine-tRNA ligase, the least abundant protein in 2D analysis; (3) RNASE 6: ribonuclease K6, the least abundant protein in 1D analysis. (B) Correlation plot between estimated concentrations and immunoassays results.

Figure 4

Cellular component and canonical pathway analyses of three separation groups. (A) Cellular component analysis of the three groups. (B) The top 10 canonical pathways from the three groups. The y-axis denotes the negative log of the p value.

Figure 5

Tissue distribution of urinary proteins at protein level. (A) Urinary proteome distributions across 44 tissues. The numbers in the bracket denote the number of highly expressed proteins of the tissue detected in urine. (B) The distribution of tissue-related proteins and the corresponding separation strategy for top ten tissues.

Figure 6

An overview of the human urinary proteome database. (A) The protein level results include the unique peptide count, total peptide count and relative quantitation and estimated concentration. Proteins are linked to the UniProt website by clicking the accessions. (B) The peptide level results include peptide sequences and observed m/z values. (C) The database provides the experimental pI and MW distribution of all identified proteins. (D) The “MW-PI” section provides a succinct figure summarizing the theoretical MW and pI information for each protein. (E) Biomarker application of all identified proteins.