Dual-pressure linear ion trap mass spectrometer improving the analysis of complex protein mixtures.

The considerable progress in high-throughput proteomics analysis via liquid chromatography-electrospray ionization-tandem mass spectrometry over the past decade has been fueled to a large degree by continuous improvements in instrumentation. High-throughput identification experiments are based on peptide sequencing and are largely accomplished through the use of tandem mass spectrometry, with ion trap and trap-based instruments having become broadly adopted analytical platforms. To satisfy increasingly demanding requirements for depth of characterization and throughput, we present a newly developed dual-pressure linear ion trap mass spectrometer (LTQ Velos) that features increased sensitivity, afforded by a new source design, and demonstrates practical cycle times 2 times shorter than that of an LTQ XL, while improving or maintaining spectral quality for MS/MS fragmentation spectra. These improvements resulted in a substantial increase in the detection and identification of both proteins and unique peptides from the complex proteome of Caenorhabditis elegans, as compared to existing platforms. The greatly increased ion flux into the mass spectrometer in combination with improved isolation of low-abundance precursor ions resulted in increased detection of low-abundance peptides. These improvements cumulatively resulted in a substantially greater penetration into the baker's yeast (Saccharomyces cerevisiae) proteome compared to LTQ XL. Alternatively, faster cycle times on the new instrument allowed for higher throughput for a given depth of proteome analysis, with more peptides and proteins identified in 60 min using an LTQ Velos than in 180 min using an LTQ XL. When mass analysis was carried out with resolution in excess of 25,000 full width at half-maximum (fwhm), it became possible to isotopically resolve a small intact protein and its fragments, opening possibilities for top down experiments.

[1]  William Stafford Noble,et al.  Assigning significance to peptides identified by tandem mass spectrometry using decoy databases. , 2008, Journal of proteome research.

[2]  R. Aebersold,et al.  Advances in proteomic workflows for systems biology. , 2007, Current opinion in biotechnology.

[3]  Brendan K Faherty,et al.  Optimization and Use of Peptide Mass Measurement Accuracy in Shotgun Proteomics*S , 2006, Molecular & Cellular Proteomics.

[4]  Gennifer E. Merrihew,et al.  Post analysis data acquisition for the iterative MS/MS sampling of proteomics mixtures. , 2009, Journal of Proteome Research.

[5]  William Stafford Noble,et al.  Semi-supervised learning for peptide identification from shotgun proteomics datasets , 2007, Nature Methods.

[6]  William Stafford Noble,et al.  Posterior error probabilities and false discovery rates: two sides of the same coin. , 2008, Journal of proteome research.

[7]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[8]  S. Elledge,et al.  A quantitative atlas of mitotic phosphorylation , 2008, Proceedings of the National Academy of Sciences.

[9]  Florian Gnad,et al.  Large-scale Proteomics Analysis of the Human Kinome , 2009, Molecular & Cellular Proteomics.

[10]  John D. Venable,et al.  MS1, MS2, and SQT-three unified, compact, and easily parsed file formats for the storage of shotgun proteomic spectra and identifications. , 2004, Rapid communications in mass spectrometry : RCM.

[11]  P. Green,et al.  Massively parallel sequencing of the polyadenylated transcriptome of C. elegans. , 2009, Genome research.

[12]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[13]  D. Tabb,et al.  Proteomic parsimony through bipartite graph analysis improves accuracy and transparency. , 2007, Journal of proteome research.

[14]  M. Mann,et al.  Comprehensive mass-spectrometry-based proteome quantification of haploid versus diploid yeast , 2008, Nature.

[15]  J. Yates,et al.  Quantitative proteomic analysis of primary neurons reveals diverse changes in synaptic protein content in fmr1 knockout mice , 2008, Proceedings of the National Academy of Sciences.

[16]  Dirk Wolters,et al.  Proteomic survey of metabolic pathways in rice , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Steven P. Gygi,et al.  Large-scale phosphorylation analysis of mouse liver , 2007, Proceedings of the National Academy of Sciences.

[18]  Michael J MacCoss,et al.  Use of shotgun proteomics for the identification, confirmation, and correction of C. elegans gene annotations. , 2008, Genome research.