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Sean A Beausoleil

Publications and source records attributed to Sean A Beausoleil.

6 recordsLinked to original sources

A probability-based approach for high-throughput protein phosphorylation analysis and site localization.

Data analysis and interpretation remain major logistical challenges when attempting to identify large numbers of protein phosphorylation sites by nanoscale reverse-phase liquid chromatography/tandem mass spectrometry (LC-MS/MS) (Supplementary Figure 1 online). In this report we address challenges that are often only addressable by laborious manual validation, including data set error, data set sensitivity and phosphorylation site localization. We provide a large-scale phosphorylation data set with a measured error rate as determined by the target-decoy approach, we demonstrate an approach to maximize data set sensitivity by efficiently distracting incorrect peptide spectral matches (PSMs), and we present a probability-based score, the Ascore, that measures the probability of correct phosphorylation site localization based on the presence and intensity of site-determining ions in MS/MS spectra. We applied our methods in a fully automated fashion to nocodazole-arrested HeLa cell lysate where we identified 1,761 nonredundant phosphorylation sites from 491 proteins with a peptide false-positive rate of 1.3%.

Algorithms↗

Optimization and use of peptide mass measurement accuracy in shotgun proteomics.

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.

Calibration↗

Enhanced analysis of metastatic prostate cancer using stable isotopes and high mass accuracy instrumentation.

The primary goal of proteomics is to gain a better understanding of biological function at the protein expression level. As the field matures, numerous technologies are being developed to aid in the identification, quantification and characterization of protein expression and post-translational modifications on a near-global scale. Stable isotope labeling by amino acids in cell culture is one such technique that has shown broad biological applications. While we have recently shown the application of this technology to a model of metastatic prostate cancer, we now report a substantial improvement in quantitative analysis using a linear ion-trap Fourier transform ion cyclotron resonance mass spectrometer (LTQ FT) and novel quantification software. This resulted in the quantification of nearly 1400 proteins, a greater than 3-fold increase in comparison to our earlier study. This dramatic increase in proteome coverage can be attributed to (1) use of a double-labeling strategy, (2) greater sensitivity, speed and mass accuracy provided by the LTQ FT mass spectrometer, and (3) more robust quantification software. Finally, by using a concatenated target/decoy protein database for our peptide searches, we now report these data in the context of an estimated false-positive rate of one percent.

Arginine↗

Characterization of mouse spleen cells by subtractive proteomics.

Major analytical challenges encountered by shotgun proteome analysis include both the diversity and dynamic range of protein expression. Often new instrumentation can provide breakthroughs in areas where other analytical improvements have not been successful. In the current study, we utilized new instrumentation (LTQ FT) to characterize complex protein samples by shotgun proteomics. Proteomic analyses were performed on murine spleen tissue separated by magnetic beads into distinct CD45- and CD45+ cell populations. Using shotgun protein analysis we identified approximately 2,000 proteins per cell group by over 12,000 peptides with mass deviations of less than 4.5 ppm. Datasets obtained by LTQ FT analysis provided a significant increase in the number of proteins identified and greater confidence in those identifications and improved reproducibility in replicate analyses. Because CD45- and not CD45+ cells are able to regenerate functional pancreatic islet cells in a mouse model of type I diabetes, protein expression was further compared by a subtractive proteomic approach in search of an exclusive protein expression profile in CD45- cells. Characterization of the proteins exclusively identified in CD45- cells was performed using gene ontology terms via the Javascript GoMiner. The CD45- cell subset readily revealed proteins involved in development, suggesting the persistence of a fetal stem cell in an adult animal.

Animals↗

Phosphoproteomic analysis of the developing mouse brain.

Proper development of the mammalian brain requires the precise integration of numerous temporally and spatially regulated stimuli. Many of these signals transduce their cues via the reversible phosphorylation of downstream effector molecules. Neuronal stimuli acting in concert have the potential of generating enormous arrays of regulatory phosphoproteins. Toward the global profiling of phosphoproteins in the developing brain, we report here the use of a mass spectrometry-based methodology permitting the first proteomic-scale phosphorylation site analysis of primary animal tissue, identifying over 500 protein phosphorylation sites in the developing mouse brain.

Amino Acid Sequence↗

Large-scale characterization of HeLa cell nuclear phosphoproteins.

Determining the site of a regulatory phosphorylation event is often essential for elucidating specific kinase-substrate relationships, providing a handle for understanding essential signaling pathways and ultimately allowing insights into numerous disease pathologies. Despite intense research efforts to elucidate mechanisms of protein phosphorylation regulation, efficient, large-scale identification and characterization of phosphorylation sites remains an unsolved problem. In this report we describe an application of existing technology for the isolation and identification of phosphorylation sites. By using a strategy based on strong cation exchange chromatography, phosphopeptides were enriched from the nuclear fraction of HeLa cell lysate. From 967 proteins, 2,002 phosphorylation sites were determined by tandem MS. This unprecedented large collection of sites permitted a detailed accounting of known and unknown kinase motifs and substrates.

Amino Acid Sequence↗