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Updated: Sep 25, 2026

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Published on: February 27, 2015
Application of nano-LC-MALDI-TOF/TOF-MS for proteomic analysis of microvesicles
Joanna Kasprzyk1, Ewa Stępień2, Wojciech Piekoszewski1
1Department of Analytical Chemistry, Faculty of Chemistry, Jagiellonian University, Krakow, Poland.
Abstract:
Activated platelets and platelet derived microvesicles (PMVs) emerged recently to be promising biomarkers. There is no universal procedure to carry out the proteomic analysis on microvesicles. In this study we proposed a nano-liquid chromatography (nano-LC) technique coupled off-line with a spectrometric measurement MALDI-TOF-MS/MS as a throughput and time-saving procedure. In this study we developed a simplified method to evaluate the protein composition of platelet organelles and PMVs. Platelet-rich plasma (PRP) was collected from healthy donors. PMVs were generated from washed and thrombin activated platelets. Activated platelets from every donor were used to compare the PMV proteome. Enzymatic digestion of protein lysate was carried out using Filter Aided Sample Preparation (FASP) method with trypsin as a proteolytic enzyme. Tryptic peptides derived from PMVs and activated platelets were analysed using nano-LC coupled off-line mode with a MALDI-TOF/TOF-MS. PMV and platelet protein identification was performed using the Mascot engine for searching against the Swiss-Prot human database. The precision tolerance was 100ppm for peptide masses and 0.7Da for fragment ion masses. Individual peptide matches with a score above 28 were considered statistically significant. In total, 446 proteins were identified in PMVs and 513 proteins in activated platelets. Among them 190 were specific for activated platelets and 123 were PMV specific. Cellular component analysis of identified proteins revealed that PMVs contained relatively more extracellular proteins than activated platelets (9.6 vs. 6.0 %) and unique synaptic proteins (0.3%). A new simplified bottom-up method for PMV proteome analysis allowed eliminating the drawbacks of the previously used protocols. This approach can be used in PMV proteome identification.
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