Stephen Tate
Applied Biosystems
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Featured researches published by Stephen Tate.
Molecular & Cellular Proteomics | 2012
Ludovic C. Gillet; Pedro Navarro; Stephen Tate; Hannes L. Röst; Nathalie Selevsek; Lukas Reiter; Ron Bonner; Ruedi Aebersold
Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400–1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.
Nature Biotechnology | 2011
Nicolas Bisson; D Andrew James; Gordana Ivosev; Stephen Tate; Ron Bonner; Lorne Taylor; Tony Pawson
Signaling pathways are commonly organized through inducible protein-protein interactions, mediated by adaptor proteins that link activated receptors to cytoplasmic effectors. However, we have little quantitative data regarding the kinetics with which such networks assemble and dissolve to generate specific cellular responses. To address this deficiency, we designed a mass spectrometry method, affinity purification–selected reaction monitoring (AP-SRM), which we used to comprehensively and quantitatively investigate changes in protein interactions with GRB2, an adaptor protein that participates in a remarkably diverse set of protein complexes involved in multiple aspects of cellular function. Our data reliably define context-specific and time-dependent networks that form around GRB2 after stimulation, and reveal core and growth factor–selective complexes comprising 90 proteins identified as interacting with GRB2 in HEK293T cells. Capturing a key hub protein and dissecting its interactions by SRM should be equally applicable to quantifying signaling dynamics for a range of hubs in protein interaction networks.
Nature | 2013
Yong Zheng; Cunjie Zhang; David R. Croucher; Mohamed A. Soliman; Nicole St-Denis; Adrian Pasculescu; Lorne Taylor; Stephen Tate; W. Rod Hardy; Karen Colwill; Anna Yue Dai; Rick Bagshaw; James W. Dennis; Anne-Claude Gingras; Roger J. Daly; Tony Pawson
Cell-surface receptors frequently use scaffold proteins to recruit cytoplasmic targets, but the rationale for this is uncertain. Activated receptor tyrosine kinases, for example, engage scaffolds such as Shc1 that contain phosphotyrosine (pTyr)-binding (PTB) domains. Using quantitative mass spectrometry, here we show that mammalian Shc1 responds to epidermal growth factor (EGF) stimulation through multiple waves of distinct phosphorylation events and protein interactions. After stimulation, Shc1 rapidly binds a group of proteins that activate pro-mitogenic or survival pathways dependent on recruitment of the Grb2 adaptor to Shc1 pTyr sites. Akt-mediated feedback phosphorylation of Shc1 Ser 29 then recruits the Ptpn12 tyrosine phosphatase. This is followed by a sub-network of proteins involved in cytoskeletal reorganization, trafficking and signal termination that binds Shc1 with delayed kinetics, largely through the SgK269 pseudokinase/adaptor protein. Ptpn12 acts as a switch to convert Shc1 from pTyr/Grb2-based signalling to SgK269-mediated pathways that regulate cell invasion and morphogenesis. The Shc1 scaffold therefore directs the temporal flow of signalling information after EGF stimulation.
Nature Methods | 2013
Jean-Philippe Lambert; Gordana Ivosev; Amber L. Couzens; Brett Larsen; Mikko Taipale; Zhen-Yuan Lin; Quan Zhong; Susan Lindquist; Marc Vidal; Ruedi Aebersold; Tony Pawson; Ron Bonner; Stephen Tate; Anne-Claude Gingras
Characterizing changes in protein-protein interactions associated with sequence variants (e.g., disease-associated mutations or splice forms) or following exposure to drugs, growth factors or hormones is critical to understanding how protein complexes are built, localized and regulated. Affinity purification (AP) coupled with mass spectrometry permits the analysis of protein interactions under near-physiological conditions, yet monitoring interaction changes requires the development of a robust and sensitive quantitative approach, especially for large-scale studies in which cost and time are major considerations. We have coupled AP to data-independent mass spectrometric acquisition (sequential window acquisition of all theoretical spectra, SWATH) and implemented an automated data extraction and statistical analysis pipeline to score modulated interactions. We used AP-SWATH to characterize changes in protein-protein interactions imparted by the HSP90 inhibitor NVP-AUY922 or melanoma-associated mutations in the human kinase CDK4. We show that AP-SWATH is a robust label-free approach to characterize such changes and propose a scalable pipeline for systems biology studies.
Scientific Data | 2014
George Rosenberger; Ching Chiek Koh; Tiannan Guo; Hannes L. Röst; Petri Kouvonen; Ben C. Collins; Moritz Heusel; Yansheng Liu; Etienne Caron; Anton Vichalkovski; Marco Faini; Olga T. Schubert; Pouya Faridi; H. Alexander Ebhardt; Mariette Matondo; Henry H N Lam; Samuel L. Bader; David S. Campbell; Eric W. Deutsch; Robert L. Moritz; Stephen Tate; Ruedi Aebersold
Mass spectrometry is the method of choice for deep and reliable exploration of the (human) proteome. Targeted mass spectrometry reliably detects and quantifies pre-determined sets of proteins in a complex biological matrix and is used in studies that rely on the quantitatively accurate and reproducible measurement of proteins across multiple samples. It requires the one-time, a priori generation of a specific measurement assay for each targeted protein. SWATH-MS is a mass spectrometric method that combines data-independent acquisition (DIA) and targeted data analysis and vastly extends the throughput of proteins that can be targeted in a sample compared to selected reaction monitoring (SRM). Here we present a compendium of highly specific assays covering more than 10,000 human proteins and enabling their targeted analysis in SWATH-MS datasets acquired from research or clinical specimens. This resource supports the confident detection and quantification of 50.9% of all human proteins annotated by UniProtKB/Swiss-Prot and is therefore expected to find wide application in basic and clinical research. Data are available via ProteomeXchange (PXD000953-954) and SWATHAtlas (SAL00016-35).
Proceedings of the National Academy of Sciences of the United States of America | 2008
Andreas Traweger; Giselle Wiggin; Lorne Taylor; Stephen Tate; Pavel Metalnikov; Tony Pawson
Phosphorylation of the polarity protein Par-3 by the serine/threonine kinases aPKCζ/ι and Par-1 (EMK1/MARK2) regulates various aspects of epithelial cell polarity, but little is known about the mechanisms by which these posttranslational modifications are reversed. We find that the serine/threonine protein phosphatase PP1 (predominantly the α isoform) binds Par-3, which localizes to tight junctions in MDCKII cells. PP1α can associate with multiple sites on Par-3 while retaining its phosphatase activity. By using a quantitative mass spectrometry-based technique, multiple reaction monitoring, we show that PP1α specifically dephosphorylates Ser-144 and Ser-824 of mouse Par-3, as well as a peptide encompassing Ser-885. Consistent with these observations, PP1α regulates the binding of 14-3-3 proteins and the atypical protein kinase C (aPKC) ζ to Par-3. Furthermore, the induced expression of a catalytically inactive mutant of PP1α severely delays the formation of functional tight junctions in MDCKII cells. Collectively, these results show that Par-3 functions as a scaffold, coordinating both serine/threonine kinases and the PP1α phosphatase, thereby providing dynamic control of the phosphorylation events that regulate the Par-3/aPKC complex.
Journal of Chromatography B | 2008
Lyle Burton; Gordana Ivosev; Stephen Tate; Gary Impey; Julie Wingate; Ron Bonner
The experimental complexity of a metabolomics study can cause uncontrolled variance that is not related to the biological effect being studied and may distort or obscure the data analysis. While some sources can be controlled with good experimental techniques and careful sample handling, others are inherent in the analytical technique used and cannot easily be avoided. We discuss the sources and appearance of some of these artifacts and show ways in which they can be detected using visualization and statistical tools, allowing appropriate treatment prior to multivariate analysis (MVA).
Journal of Proteomics | 2013
Stephen Tate; Brett Larsen; Ron Bonner; Anne-Claude Gingras
Understanding protein interactions within the complexity of a living cell is challenging, but techniques coupling affinity purification and mass spectrometry have enabled important progress to be made in the past 15 years. As identification of protein-protein interactions is becoming easier, the quantification of the interaction dynamics is the next frontier. Several quantitative mass spectrometric approaches have been developed to address this issue that vary in their strengths and weaknesses. While isotopic labeling approaches continue to contribute to the identification of regulated interactions, techniques that do not require labeling are becoming increasingly used in the field. Here, we describe the major types of label-free quantification used in interaction proteomics, and discuss the relative merits of data dependent and data independent acquisition approaches in label-free quantification. This article is part of a Special Issue entitled: From protein structures to clinical applications.
Nature Biotechnology | 2016
Pedro Navarro; Jörg Kuharev; Ludovic C. Gillet; Oliver M. Bernhardt; Brendan MacLean; Hannes L. Röst; Stephen Tate; Chih Chiang Tsou; Lukas Reiter; Ute Distler; George Rosenberger; Yasset Perez-Riverol; Alexey I. Nesvizhskii; Ruedi Aebersold; Stefan Tenzer
Consistent and accurate quantification of proteins by mass spectrometry (MS)-based proteomics depends on the performance of instruments, acquisition methods and data analysis software. In collaboration with the software developers, we evaluated OpenSWATH, SWATH 2.0, Skyline, Spectronaut and DIA-Umpire, five of the most widely used software methods for processing data from sequential window acquisition of all theoretical fragment-ion spectra (SWATH)-MS, which uses data-independent acquisition (DIA) for label-free protein quantification. We analyzed high-complexity test data sets from hybrid proteome samples of defined quantitative composition acquired on two different MS instruments using different SWATH isolation-window setups. For consistent evaluation, we developed LFQbench, an R package, to calculate metrics of precision and accuracy in label-free quantitative MS and report the identification performance, robustness and specificity of each software tool. Our reference data sets enabled developers to improve their software tools. After optimization, all tools provided highly convergent identification and reliable quantification performance, underscoring their robustness for label-free quantitative proteomics.
Nature Methods | 2015
Jian Wang; Monika Tucholska; James D.R. Knight; Jean-Philippe Lambert; Stephen Tate; Brett Larsen; Anne-Claude Gingras; Nuno Bandeira
ACKNOWLEDGMENTS We thank Z. Xu and Y. Yu for help with the high-performance computer. This work was supported by the National Science Foundation (NSF) of China (grants 91429301 and 31221065), 973 Program 2015CB553800, National Major Project 2013ZX10002-002, 111 Project B12001, funding from Xiamen City (grant 3502Z20130027) and the NSF of China for Fostering Talents in Basic Research (grant J1310027).