authors |
Bastos, P; Trindade, F; Ferreira, R; Leite-Moreira, A; Falcao-Pires, I; Manadas, B; Daniel-Da-Silva, AL; Vitorino, R |
nationality |
International |
journal |
TALANTA |
author keywords |
Magnetic Nanoparticles; Proteomics; Urine; Fractionation; Mass spectrometry |
keywords |
ION AFFINITY-CHROMATOGRAPHY; SELECTIVE ENRICHMENT; TARGETED PROTEOMICS; KIDNEY INJURY; BINDING; DISCOVERY; PHOSPHOPEPTIDES; QUANTIFICATION; BIOMARKERS; CYTOSCAPE |
abstract |
Urine is a highly attractive source of biological information and disease biomarkers, whose proteome characterization is ongoing. To that end, depletion/enrichment strategies for protein analysis can be of great convenience. We have thus developed a method based on the use of EDTA-functionalized magnetic nanoparticles (NPs@EDTA), to fractionate urine samples before liquid chromatography-mass spectrometry analysis and compared the identified proteins with those obtained from ultrafiltrated/unfractionated (UF) urine samples. NPs@EDTA allowed larger urine volumes to be processed, resulting in a greater number of protein identifications (similar to 2-fold) at a lower cost when compared to UF samples. Proteins of greater abundance (such as albumin and uromodulin) were, at least partially, depleted with NPs@EDTA while those of lower abundance were enriched. Bioinformatics analysis showed that approximately 27% of NPs@EDTA-enriched proteins were annotated as displaying enzymatic activity, most of these being hydrolytic enzymes (56%), particularly proteases/peptidases (48%). Also, post-translational modifications were prominently predicted across NPs@ EDTA-enriched proteins (90%), particularly glycosylation (52%), phosphorylation (47%) and acetylation (30%). NPs@EDTA allowed the identification of 109 proteins in urine for the first time, showing high potential as a platform for urine's fractionation prior to proteomic analysis. |
publisher |
ELSEVIER SCIENCE BV |
issn |
0039-9140 |
isbn |
1873-3573 |
year published |
2017 |
volume |
170 |
beginning page |
81 |
ending page |
88 |
digital object identifier (doi) |
10.1016/j.talanta.2017.03.087 |
web of science category |
Chemistry, Analytical |
subject category |
Chemistry |
unique article identifier |
WOS:000402343200012
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ciceco authors
impact metrics
journal analysis (jcr 2019):
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journal impact factor |
5.339 |
5 year journal impact factor |
4.711 |
category normalized journal impact factor percentile |
87.791 |
dimensions (citation analysis):
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altmetrics (social interaction):
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