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A fast sample processing strategy for large-scale profiling of human urine phosphoproteome by mass spectrometry.

Authors :
Zhao X
Zhang W
Liu T
Dong H
Huang J
Sun C
Wang G
Qian X
Qin W
Source :
Talanta [Talanta] 2018 Aug 01; Vol. 185, pp. 166-173. Date of Electronic Publication: 2018 Mar 17.
Publication Year :
2018

Abstract

Liquid biopsies using body fluids have gained much attention in recent years due to their multiple advantages in clinical diagnosis, such as less/non-invasive collection, suitability for longitudinal disease monitoring, and better representation of tumor heterogeneity. As an attractive choice for liquid biopsy, urine proteins and their post-translational modifications (PTMs) have the potential to offer significant insights into physiological variations and pathological changes in the human body. However, due to the intrinsically large variability of urine proteins and their PTMs among different individuals, there is a high demand for strategies for high-throughput analysis of a large number of samples to obtain a comprehensive view and a reliable reference interval of the urine proteome. In this work, we proposed a new urine phosphoproteome sample processing strategy that combines fast protein extraction, efficient multiple immobilized-proteases digestion, and tandemly connected centrifugal tips device-based facile phosphopeptide enrichment & fractionation. This strategy is capable of paralleled sample processing with an approximate five-fold reduction in processing time and is therefore particularly suitable for handling a large number of urine samples. Totally, we identified 4196 phosphosites in human urine proteins by mass spectrometry in replicated tests, a number which is dozens of times larger than those previously reported. Therefore, this strategy may have great potential in urine-based phosphoprotein biomarker screening and drug response studies.<br /> (Copyright © 2018 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-3573
Volume :
185
Database :
MEDLINE
Journal :
Talanta
Publication Type :
Academic Journal
Accession number :
29759185
Full Text :
https://doi.org/10.1016/j.talanta.2018.03.047