EDTA-functionalized magnetic nanoparticles: A suitable platform for the analysis of low abundance urinary proteins

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.

keywords

ION AFFINITY-CHROMATOGRAPHY; SELECTIVE ENRICHMENT; TARGETED PROTEOMICS; KIDNEY INJURY; BINDING; DISCOVERY; PHOSPHOPEPTIDES; QUANTIFICATION; BIOMARKERS; CYTOSCAPE

subject category

Chemistry

authors

Bastos, P; Trindade, F; Ferreira, R; Leite-Moreira, A; Falcao-Pires, I; Manadas, B; Daniel-Da-Silva, AL; Vitorino, R

our authors

acknowledgements

The authors thank Portuguese Foundation for Science and Technology (FCT), European Union, Quadro de Referencia Estrategico Nacional (QREN), Fundo Europeu de Desenvolvimento Regional (FEDER) and Programa Operacional Factores de Competitividade (COMPETE) for funding iBiMED (UID/BIM/04501/2013), UnIC (UID/IC/00051/2013), CNC (PTDC/NEU-NMC/0205/2012, UID/NEU/04539/2013) and CICECO (POCI-01-0145-FEDER-007679 and UID/CTM /50011/2013) research units as well as Rui Vitorino's (IF/00286/2015), Ana Daniel-da-Silva's (IF/00405/2014) and Fabio's Fellowship Grant (SFRH/BD/111633/2015). The authors thank also the National Mass Spectrometry Network (RNEM, REDE/1506/REM/2005) and project DOCnet (NORTE-01-0145-FEDER-000003), supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, for funding this work.

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