The human platelet proteome mapped by peptide‐centric proteomics: a functional protein profile

L Martens, P Van Damme, J Van Damme, A Staes… - …, 2005 - Wiley Online Library
L Martens, P Van Damme, J Van Damme, A Staes, E Timmerman, B Ghesquière
Proteomics, 2005Wiley Online Library
Several studies have been published in which holistic approaches were used to
characterise the proteome and transcriptome of human platelets. The key intent being that a
deeper understanding of the normal and aberrant physiological functions of platelets can
only be achieved if most biomolecular building blocks are mapped. Here we present the
application of recently developed novel technologies that overcome some of the
shortcomings of gel‐based proteomics. Central in our approach is the so‐called combined …
Abstract
Several studies have been published in which holistic approaches were used to characterise the proteome and transcriptome of human platelets. The key intent being that a deeper understanding of the normal and aberrant physiological functions of platelets can only be achieved if most biomolecular building blocks are mapped. Here we present the application of recently developed novel technologies that overcome some of the shortcomings of gel‐based proteomics. Central in our approach is the so‐called combined fractional diagonal chromatography (COFRADIC)‐technology in which sets of representative peptides are sorted in a diagonal RP chromatographic system through a specific modification of their side chain. In this study we combined three different COFRADIC sorting techniques to analyse the proteome of human platelets. Methionyl, cysteinyl and amino terminal peptides were isolated and analysed by MS/MS. Merging the peptide identifications obtained after database searching resulted in a core set of 641 platelet proteins, which comprises the largest set identified today. In comparison to previously published platelet proteomes, we identified 404 novel platelet proteins containing a high number of hydrophobic membrane proteins and hypothetical proteins. Furthermore we discuss the observed characteristics and potential benefits of each of the different COFRADIC technologies for proteome analysis and highlight important issues that need to be considered when searching sequence databases using data obtained in peptide‐centric, non‐gel proteomics studies.
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