Standard mixtures for proteome studies.

Mixtures of moderate complexity were formed from 23 peptides and 12 proteins digested with trypsin, all individually characterized. These mixtures were analyzed with replicates in full and windowed m/z ranges using online high-performance reverse phase liquid chromatography coupled via electrospray ionization to an ion trap mass spectrometer. The resulting spectra were searched using SEQUEST against databases of different sizes and contents and confidences of the observed identifications were evaluated by our earlier statistical model. These data were then combined with biologically derived spectral data, searched, and further evaluated. All peptides but one and all proteins were identified with high confidence. Additionally, the presence and behavior of quadruply charged peptides was analyzed. The properties of the proposed peptide and protein mixtures as well as the performance of the statistical model were carefully investigated. These mixtures mimic the complexity seen in large-scale proteomics experiments, and are proposed to serve as quality assessment standards for future proteome studies.

[1]  J. Yates,et al.  Direct analysis of protein complexes using mass spectrometry , 1999, Nature Biotechnology.

[2]  Richard D. Smith,et al.  Gene expression profiling using advanced mass spectrometric approaches. , 2002, Journal of mass spectrometry : JMS.

[3]  John I. Clark,et al.  Shotgun identification of protein modifications from protein complexes and lens tissue , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[4]  A. Nesvizhskii,et al.  Experimental protein mixture for validating tandem mass spectral analysis. , 2002, Omics : a journal of integrative biology.

[5]  Alexey I Nesvizhskii,et al.  Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. , 2002, Analytical chemistry.

[6]  Gordon A Anderson,et al.  The use of accurate mass tags for high-throughput microbial proteomics. , 2002, Omics : a journal of integrative biology.

[7]  Gordon A Anderson,et al.  Direct mass spectrometric analysis of intact proteins of the yeast large ribosomal subunit using capillary LC/FTICR , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[8]  O. White,et al.  Genome sequence of the dissimilatory metal ion–reducing bacterium Shewanella oneidensis , 2002, Nature Biotechnology.

[9]  Richard D. Smith,et al.  Increased proteome coverage for quantitative peptide abundance measurements based upon high performance separations and DREAMS FTICR mass spectrometry , 2002, Journal of the American Society for Mass Spectrometry.

[10]  J. Yates,et al.  Charting the Protein Complexome in Yeast by Mass Spectrometry* , 2002, Molecular & Cellular Proteomics.

[11]  Chris F. Taylor,et al.  A systematic approach to modeling, capturing, and disseminating proteomics experimental data , 2003, Nature Biotechnology.

[12]  Alexey I Nesvizhskii,et al.  Initial Proteome Analysis of Model Microorganism Haemophilus influenzae Strain Rd KW20 , 2003, Journal of bacteriology.

[13]  R. Aebersold,et al.  A statistical model for identifying proteins by tandem mass spectrometry. , 2003, Analytical chemistry.

[14]  Samuel I. Miller,et al.  Quantitative proteomic analysis indicates increased synthesis of a quinolone by Pseudomonas aeruginosa isolates from cystic fibrosis airways , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Michael I. Jordan,et al.  Toward a protein profile of Escherichia coli: Comparison to its transcription profile , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[16]  Michael Y. Galperin,et al.  In Silico Metabolic Model and Protein Expression of Haemophilus influenzae Strain Rd KW20 in Rich Medium. , 2004, Omics : a journal of integrative biology.

[17]  E. Kolker,et al.  Spectral quality assessment for high-throughput tandem mass spectrometry proteomics. , 2004, Omics : a journal of integrative biology.

[18]  E. Kolker,et al.  LIP index for peptide classification using MS/MS and SEQUEST search via logistic regression. , 2004, Omics : a journal of integrative biology.

[19]  Eugene Kolker,et al.  Charge state estimation for tandem mass spectrometry proteomics. , 2005, Omics : a journal of integrative biology.

[20]  Eugene Kolker,et al.  Randomized sequence databases for tandem mass spectrometry peptide and protein identification. , 2005, Omics : a journal of integrative biology.

[21]  Gordon A Anderson,et al.  Global profiling of Shewanella oneidensis MR-1: expression of hypothetical genes and improved functional annotations. , 2005, Proceedings of the National Academy of Sciences of the United States of America.