Personalized phosphoproteomics identifies functional signaling

• Published in: Nature biotechnology Vol. 40; no. 4; pp. 576 - 584
• Main Authors: Needham, Elise J., Hingst, Janne R., Parker, Benjamin L., Morrison, Kaitlin R., Yang, Guang, Onslev, Johan, Kristensen, Jonas M., Højlund, Kurt, Ling, Naomi X. Y., Oakhill, Jonathan S., Richter, Erik A., Kiens, Bente, Petersen, Janni, Pehmøller, Christian, James, David E., Wojtaszewski, Jørgen F. P., Humphrey, Sean J.
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.04.2022; Nature Publishing Group
• Subjects: 631/114/2391; 631/45/475; 631/61/475; Agriculture; Bioinformatics; Biological activity; Biological Phenomena; Biomedical and Life Sciences; Biomedical Engineering/Biotechnology; Biomedicine; Biotechnology; Computer applications; Customization; Glucose metabolism; Information processing; Insulin; Kinases; Life Sciences; Muscles; Perturbation; Phenotypes; Phenotypic variations; Phosphoproteins - genetics; Phosphorylation; Proteins; Proteomics - methods; Signal transduction; Signal Transduction - physiology; Signaling; Skeletal muscle; TOR protein
• ISSN: 1087-0156; 1546-1696; 1546-1696
• DOI: 10.1038/s41587-021-01099-9

Protein phosphorylation dynamically integrates environmental and cellular information to control biological processes. Identifying functional phosphorylation amongst the thousands of phosphosites regulated by a perturbation at a global scale is a major challenge. Here we introduce ‘personalized phosphoproteomics’, a combination of experimental and computational analyses to link signaling with biological function by utilizing human phenotypic variance. We measure individual subject phosphoproteome responses to interventions with corresponding phenotypes measured in parallel. Applying this approach to investigate how exercise potentiates insulin signaling in human skeletal muscle, we identify both known and previously unidentified phosphosites on proteins involved in glucose metabolism. This includes a cooperative relationship between mTOR and AMPK whereby the former directly phosphorylates the latter on S377, for which we find a role in metabolic regulation. These results establish personalized phosphoproteomics as a general approach for investigating the signal transduction underlying complex biology. Functionally relevant phosphorylation sites are detected by integrating phosphoproteomic and phenotypic data.