Cited by 493Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic NetworksProtein Tyrosine Phosphatases

The functional landscape of the human phosphoproteome

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Ochoa, David, Jarnuczak, Andrew F., Viéitez, Cristina, Gehre, Maja, Soucheray, Margaret, Mateus, André, Kleefeldt, Askar A., Hill, Anthony +8 more·2020·Nature Biotechnology

Published version of a preprint

Abstract

Protein phosphorylation is a key post-translational modification regulating protein function in almost all cellular processes. Although tens of thousands of phosphorylation sites have been identified in human cells, approaches to determine the functional importance of each phosphosite are lacking. Here, we manually curated 112 datasets of phospho-enriched proteins, generated from 104 different human cell types or tissues. We re-analyzed the 6,801 proteomics experiments that passed our quality control criteria, creating a reference phosphoproteome containing 119,809 human phosphosites. To prioritize functional sites, we used machine learning to identify 59 features indicative of proteomic, structural, regulatory or evolutionary relevance and integrate them into a single functional score. Our approach identifies regulatory phosphosites across different molecular mechanisms, processes and diseases, and reveals genetic susceptibilities at a genomic scale. Several regulatory phosphosites were experimentally validated, including identifying a role in neuronal differentiation for phosphosites in SMARCC2, a member of the SWI/SNF chromatin-remodeling complex.

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  • Observations link functionality of phosphosites with thermal stability.

    “The inferred transcription factors and kinases indicate the well-annotated players in the DNA damage response, whereas proteins with altered thermal stability reflect less annotated parts of the signaling space with strong links to the phosphoproteomic measurements which aligns with observations linking functionality of phosphosites with thermal stability (Ochoa et al, 2020; Potel et al, 2021).”

    From Network integration of thermal proteome profiling with multi-omics data decodes PARP inhibition (2024) · cites this paper as Ochoa et al, 2020

    The Results section on genetic variation reports that mutations at two functional TDH3 phosphosites were associated with increased thermal stability of oxidative-phosphorylation proteins. This supports a link in that yeast experiment, but not a general association between phosphosite functionality and thermal stability; the same section reports no significant stability change in TDH3 itself. Page numbers are unavailable in our copy. (LLM, conf=0.82)

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Authors
Ochoa, D., Jarnuczak, A. F., Viéitez, C., Gehre, M., Soucheray, M., Mateus, A., Kleefeldt, A. A., Hill, A., Garcia-Alonso, L., Stein, F., Krogan, N. J., Savitski, M. M., Swaney, D. L., Vizcaíno, J. A., Noh, K.-M., & Beltrao, P.
Affiliations
  • European Bioinformatics Institute (GB)
  • European Molecular Biology Laboratory (DE)
  • Gladstone Institutes (US)
Corresponding author
Ochoa, David
Venue
Nature Biotechnology
Published
2019-12-09
Volume
38
Issue
3
Pages
365-373
ISSN
  • 0733-222X (ISSN-L)
  • 1087-0156
  • 1546-1696
OpenAlex
W2994464657
Cited by
491
References
106
Citations by year
2026: 83 · 2025: 85 · 2024: 80 · 2023: 74 · 2022: 83 · 2021: 54 · 2020: 25 · 2019: 6 · 2018: 1
FWCI
16.77
Type
journal article
Language
en
Open access
Locations
  • Nature Biotechnology (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
Funders
Wellcome Trust (WT101477MA, 101477, 208391/Z/17/Z, Z/17/Z, 208391)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Tyrosine Phosphatases
Keywords
protein phosphorylation, phosphosites, post-translational modification, machine learning feature selection, genetic susceptibility, SMARCC2, SWI/SNF chromatin remodeling, neuronal differentiation
MeSH terms
Machine Learning, Binding Sites, Cell Line, DNA-Binding Proteins, HeLa Cells, Humans, Phosphoproteins, Protein Processing, Post-Translational, Mass Spectrometry, Transcription Factors, Computational Biology, Databases, Protein, Proteomics, Neurogenesis, Data Curation

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