Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer

Noah M. Lancaster, Pavel Sinitcyn, Patrick Forny, Trenton M. Peters-Clarke, Caroline Fecher, Andrew J. Smith, Evgenia Shishkova, Tabiwang N. Arrey, Anna Pashkova, Margaret Lea Robinson, Nicholas Arp, Jing Fan, Juli Hansen, Andrea Galmozzi, Lia R. Serrano, Julie Rojas, Audrey P. Gasch, Michael S. Westphall, Hamish Stewart, Christian HockEugen Damoc, David J. Pagliarini, Vlad Zabrouskov, Joshua J. Coon*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Owing to its roles in cellular signal transduction, protein phosphorylation plays critical roles in myriad cell processes. That said, detecting and quantifying protein phosphorylation has remained a challenge. We describe the use of a novel mass spectrometer (Orbitrap Astral) coupled with data-independent acquisition (DIA) to achieve rapid and deep analysis of human and mouse phosphoproteomes. With this method, we map approximately 30,000 unique human phosphorylation sites within a half-hour of data collection. The technology is benchmarked to other state-of-the-art MS platforms using both synthetic peptide standards and with EGF-stimulated HeLa cells. We apply this approach to generate a phosphoproteome multi-tissue atlas of the mouse. Altogether, we detect 81,120 unique phosphorylation sites within 12 hours of measurement. With this unique dataset, we examine the sequence, structural, and kinase specificity context of protein phosphorylation. Finally, we highlight the discovery potential of this resource with multiple examples of phosphorylation events relevant to mitochondrial and brain biology.
Original languageEnglish
Article number7016
JournalNature Communications
Volume15
Issue number1
DOIs
Publication statusPublished - 15 Aug 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Funding

We are grateful for support from the National Institutes of Health (grants P41GM108538 and R35GM118110 to J.J.C., R01DK098672 to D.J.P., R35GM150899 to A.G., and R35GM147014 to J.F.), the National Science Foundation grant 2010789, and the Department of Energy grant number DE-SC0018409. P.S. is supported by a Morgridge Interdisciplinary Postdoctoral Fellowship. T.M.P.C. and L.R.S. acknowledge support from the National Human Genome Research Institution through a training grant to the Genomic Science Training Program (NIH T32HG002760). M.L.R. acknowledges support from the UW-Madison Biotechnology Training Program (NIH T32GM135066). T.M.P.C. also acknowledges the ACS Division of Analytical Chemistry and Agilent for support through a graduate fellowship. P.F. acknowledges the support of postdoctoral fellowships by the European Molecular Biology Organization (ALTF 263-2022) and the Swiss National Science Foundation (P500PB_211038). D.J.P. acknowledges the support of funds from the BJC Investigators Program. J.J.C. acknowledges support by the Great Lakes Bioenergy Research Center (GLBRC) from United States Department of Energy grant DE-SC0018409.

FundersFunder number
Great Lakes Bioenergy Research Center
National Human Genome Research Institute
National Institutes of HealthR01DK098672, R35GM150899, R35GM118110, T32HG002760, R35GM147014, P41GM108538
European Molecular Biology OrganizationALTF 263-2022
College of Engineering, University of Wisconsin-MadisonT32GM135066
U.S. Department of EnergyDE-SC0018409
National Science Foundation2010789
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungP500PB_211038

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