Tandem mass spectrometry of human tryptic blood peptides calculated by a statistical algorithm and captured by a relational database with exploration by a general statistical analysis system.

A goodness of fit test may be used to assign tandem mass spectra of peptides to amino acid sequences and to directly calculate the expected probability of mis-identification. The product of the peptide expectation values directly yields the probability that the parent protein has been mis-identified. A relational database could capture the mass spectral data, the best fit results, and permit subsequent calculations by a general statistical analysis system. The many files of the Hupo blood protein data correlated by X!TANDEM against the proteins of ENSEMBL were collected into a relational database. A redundant set of 247,077 proteins and peptides were correlated by X!TANDEM, and that was collapsed to a set of 34,956 peptides from 13,379 distinct proteins. About 6875 distinct proteins were only represented by a single distinct peptide, 2866 proteins showed 2 distinct peptides, and 3454 proteins showed at least three distinct peptides by X!TANDEM. More than 99% of the peptides were associated with proteins that had cumulative expectation values, i.e. probability of false positive identification, of one in one hundred or less. The distribution of peptides per protein from X!TANDEM was significantly different than those expected from random assignment of peptides.

A HUPO test sample study reveals common problems in mass spectrometry-based proteomics.

We performed a test sample study to try to identify errors leading to irreproducibility, including incompleteness of peptide sampling, in liquid chromatography-mass spectrometry-based proteomics. We distributed an equimolar test sample, comprising 20 highly purified recombinant human proteins, to 27 laboratories. Each protein contained one or more unique tryptic peptides of 1,250 Da to test for ion selection and sampling in the mass spectrometer. Of the 27 labs, members of only 7 labs initially reported all 20 proteins correctly, and members of only 1 lab reported all tryptic peptides of 1,250 Da. Centralized analysis of the raw data, however, revealed that all 20 proteins and most of the 1,250 Da peptides had been detected in all 27 labs. Our centralized analysis determined missed identifications (false negatives), environmental contamination, database matching and curation of protein identifications as sources of problems. Improved search engines and databases are needed for mass spectrometry-based proteomics.

The identification and characterization of membranome components.

Analyses of proteins from a number of proteomic studies of cell membranes have demonstrated that a significant component of the identified proteins is not predicted to contain transmembrane regions. The presence of such proteins may arise as a result of contamination of the membrane preparations or through real associations. Our aim was to identify integral proteins as well as those that are intimately associated with the microsomal membranes of K562 cells. Isolated membranes were treated under conditions reported to remove noncovalently associated 'peripheral' proteins and the residual proteins were SDS-PAGE-separated and analyzed by LC-MS/MS. Tandem lectin affinity was also examined as a complementary approach for the enrichment of membrane glycoproteins. Approximately 41% of the isolated proteins were assigned as membrane proteins based on the presence of transmembrane regions or covalent post-translational modifications that could account for membrane association. Collectively, these results indicate that there is a significant component of non integral proteins that appear to be as closely associated with membranes as integral elements.