Author
Listed:
- Noah M. Lancaster
(University of Wisconsin-Madison
University of Wisconsin-Madison)
- Pavel Sinitcyn
(Morgridge Institute for Research)
- Patrick Forny
(Washington University School of Medicine)
- Trenton M. Peters-Clarke
(University of Wisconsin-Madison
University of Wisconsin-Madison)
- Caroline Fecher
(Washington University School of Medicine)
- Andrew J. Smith
(Washington University School of Medicine)
- Evgenia Shishkova
(University of Wisconsin-Madison
National Center for Quantitative Biology of Complex Systems)
- Tabiwang N. Arrey
(Thermo Fisher Scientific (Bremen) GmbH)
- Anna Pashkova
(Thermo Fisher Scientific (Bremen) GmbH)
- Margaret Lea Robinson
(University of Wisconsin-Madison)
- Nicholas Arp
(Morgridge Institute for Research
University of Wisconsin-Madison)
- Jing Fan
(Morgridge Institute for Research
University of Wisconsin-Madison
University of Wisconsin-Madison)
- Juli Hansen
(University of Wisconsin-Madison, School of Medicine and Public Health)
- Andrea Galmozzi
(University of Wisconsin-Madison
University of Wisconsin-Madison, School of Medicine and Public Health
University of Wisconsin-Madison School of Medicine and Public Health)
- Lia R. Serrano
(University of Wisconsin-Madison
University of Wisconsin-Madison)
- Julie Rojas
(University of Wisconsin-Madison)
- Audrey P. Gasch
(University of Wisconsin-Madison
University of Wisconsin-Madison
University of Wisconsin-Madison)
- Michael S. Westphall
(University of Wisconsin-Madison
National Center for Quantitative Biology of Complex Systems)
- Hamish Stewart
(Thermo Fisher Scientific (Bremen) GmbH)
- Christian Hock
(Thermo Fisher Scientific (Bremen) GmbH)
- Eugen Damoc
(Thermo Fisher Scientific (Bremen) GmbH)
- David J. Pagliarini
(Washington University School of Medicine
Washington University School of Medicine
Washington University School of Medicine)
- Vlad Zabrouskov
(Thermo Fisher Scientific)
- Joshua J. Coon
(University of Wisconsin-Madison
University of Wisconsin-Madison
Morgridge Institute for Research
National Center for Quantitative Biology of Complex Systems)
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.
Suggested Citation
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 & Nich, 2024.
"Fast and deep phosphoproteome analysis with the Orbitrap Astral mass spectrometer,"
Nature Communications, Nature, vol. 15(1), pages 1-18, December.
Handle:
RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-51274-0
DOI: 10.1038/s41467-024-51274-0
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