A proteomic glimpse into human ureter proteome. Issue 1 (17th November 2015)

• Record Type: Journal Article
• Authors: Magdeldin, Sameh; Hirao, Yoshitoshi; Elguoshy, Amr; Xu, Bo; Zhang, Ying; Fujinaka, Hidehiko; Yamamoto, Keiko; Yates, John R.; Yamamoto, Tadashi
• Is Part Of: Proteomics. Volume 16:Issue 1(2016)
• Page Start: 80
• Page End: 84
• Publication Date: 2015-11-17
• Subjects: Biomarker -- Cell biology -- Dataset -- OFFGel fractionation -- Ureter -- Urine; Proteins -- Separation -- Periodicals; Bioinformatics -- Periodicals; Proteomics -- Periodicals; Genomes -- Periodicals; Molecular genetics -- Periodicals; 572.605
• DOI: 10.1002/pmic.201500214
• Languages: English
• ISSNs: 1615-9853

Abstract

Abstract : Urine has evolved as one of the most important biofluids in clinical proteomics due to its noninvasive sampling and its stability. Yet, it is used in clinical diagnostics of several disorders by detecting changes in its components including urinary protein/polypeptide profile. Despite the fact that majority of proteins detected in urine are primarily originated from the urogenital (UG) tract, determining its precise source within the UG tract remains elusive. In this article, we performed a comprehensive analysis of ureter proteome to assemble the first unbiased ureter dataset. Next, we compared these data to urine, urinary exosome, and kidney mass spectrometric datasets. Our result concluded that among 2217 nonredundant ureter proteins, 751 protein candidates (33.8%) were detected in urine as urinary protein/polypeptide or exosomal protein. On the other hand, comparing ureter protein hits (48) that are not shown in corresponding databases to urinary bladder and prostate human protein atlas databases pinpointed 21 proteins that might be unique to ureter tissue. In conclusion, this finding offers future perspectives for possible identification of ureter disease‐associated biomarkers such as ureter carcinoma. In addition, the ureter proteomic dataset published in this article will provide a valuable resource for researchers working in the field of urology and urine biomarker discovery. All MS data have been deposited in the ProteomeXchange with identifier PXD002620 (http://proteomecentral.proteomexchange.org/dataset/PXD002620 ).