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Submitted on March 4, 2004
Laboratory of Proteomics and Analytical Technologies, SAIC-Frederick Inc., NCI-Frederick, Frederick, MD 21702-1201
Corresponding Author: veenstra{at}ncifcrf.gov
In this study, a multidimensional fractionation approach was combined with tandem mass spectrometry (MS/MS) to increase the capability of characterizing complex protein profiles of mammalian neuronal cells. Proteins extracted from primary cultures of cortical neurons were digested with trypsin followed by fractionation using strong cation exchange chromatography. Each of these fractions was analyzed by microcapillary reversed-phase liquid chromatography MS/MS (µLC-MS/MS). The analysis of the MS/MS data resulted in the identification of over 15000 unique peptides from which 3590 unique proteins were identified based on Protein-specific Peptide Tags (PPTs) that are unique to a single protein in the searched database. In addition, 952 protein clusters were identified using cluster analysis of the proteins identified by the peptides not unique to a single protein. This identification revealed that a minimum of 4542 proteins could be identified from this experiment, representing approximately 16% of all known mouse proteins. An evaluation of the number of false positive identifications was undertaken by searching the entire MS/MS dataset against a database containing the sequences of over 12000 proteins from archaea. This analysis allowed a systematic determination of the level of confidence in the identification of peptides as a function of SEQUEST cross correlation (Xcorr) and delta correlation (DCn) scores. Correlation charts were also constructed to show the number of unique peptides identified for proteins from specific classes. The results show that low abundance proteins involved in signal transduction and transcription are generally identified by fewer peptides than high abundance proteins that play a role in maintaining cellular structure and motility. The results presented here provide the broadest proteome coverage for a cell to date and show that MS-based proteomics has the potential to provide high coverage of the proteins expressed within a cell.
Revised on June 23, 2004
Accepted on June 30, 2004
Global analysis of the cortical neuron proteome
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