Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2023 Apr 24;28(9):3675.
doi: 10.3390/molecules28093675.

Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates

Affiliations
Review

Phosphoproteomic Approaches for Identifying Phosphatase and Kinase Substrates

Andrew G DeMarco et al. Molecules. .

Abstract

Protein phosphorylation is a ubiquitous post-translational modification controlled by the opposing activities of protein kinases and phosphatases, which regulate diverse biological processes in all kingdoms of life. One of the key challenges to a complete understanding of phosphoregulatory networks is the unambiguous identification of kinase and phosphatase substrates. Liquid chromatography-coupled mass spectrometry (LC-MS/MS) and associated phosphoproteomic tools enable global surveys of phosphoproteome changes in response to signaling events or perturbation of phosphoregulatory network components. Despite the power of LC-MS/MS, it is still challenging to directly link kinases and phosphatases to specific substrate phosphorylation sites in many experiments. Here, we survey common LC-MS/MS-based phosphoproteomic workflows for identifying protein kinase and phosphatase substrates, noting key advantages and limitations of each. We conclude by discussing the value of inducible degradation technologies coupled with phosphoproteomics as a new approach that overcomes some limitations of current methods for substrate identification of kinases, phosphatases, and other regulatory enzymes.

Keywords: PTM; kinase; mass spectrometry; phosphatase; phosphoproteomics; phosphorylation; post-translation modification; quantitative proteomics; substrate identification.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Example experimental design to identify candidate phosphatase substrates by altering target enzyme activity. Biological samples differing only in the activity state of the target of interest (in this case a phosphatase, but it could also be a kinase) are grown and harvested. Metabolic stable isotope labeling of proteins for MS quantification is optional at this step. Proteins are extracted from both samples, digested with a protease like trypsin, and phosphopeptides selectively enriched. Chemical labeling of peptides is another option for stable isotope incorporation for quantification. When stable isotopes are used, the two phosphoproteomes can be analyzed together by LC-MS/MS, with relative differences in peak intensities reflecting sites regulated by the target enzyme. Phosphopeptide sequences are identified using database search software and significant differences in abundance between samples, reflecting candidate substrates, are determined using statistical tools. Created with BioRender.com.
Figure 2
Figure 2
Example experimental workflow for substrate trap AP-MS approach to identify candidate phosphatase substrates. See text for details. The substrate trap and wild-type phosphatases with bound proteins are captured from extracts on antibody or other affinity beads and then digested with a protease prior to LC-MS/MS analysis and protein identification. Other AP-MS methods would have similar workflow, but typically just experimental and control samples. Isotope labeling is not essential, but chemical labeling of peptides can be incorporated if desired. Subtracting proteins identified in the wild-type and control samples reveals candidate substrates. Proteins identified in wild-type but not control reflect non-substrate interaction partners. Created with BioRender.com.
Figure 3
Figure 3
Example experimental workflow for in vivo proximity labeling to identify candidate kinase/phosphatase substrates. See text for details. The target protein of interest (POI) is expressed in the biological system as a fusion with the engineered catalytic domain of a biotin ligase or peroxidase (labeled “Enzyme”), resulting in biotinylation of proteins in the immediate proximity. An appropriate negative control protein fused to the same enzyme is essential for measuring and eliminating non-specific background biotinylation. Streptavidin affinity capture is used to selectively isolate biotinylated proteins from both samples for LC-MS/MS and protein identification. Created with BioRender.com.
Figure 4
Figure 4
Experimental design of AID-based phosphoproteomic experiment to identify candidate kinase or phosphatase substrates. The biological system is engineered to express a plant Tir1 F-box protein, and the target of interest fused to a plant ABD (the “AID Cell Line”). Addition of auxin triggers rapid polyubiquitylation and proteasomal degradation of the target, mediated by interaction of Tir1 with the endogenous SCF ubiquitin ligase (see cartoon immunoblot at right). Two samples (+/− auxin) are collected, proteins extracted and digested, and phosphopeptides enriched, followed by LC-MS/MS analysis to identify regulated phosphosites. Either metabolic or chemical isotope labeling can be used for direct sample comparison in a single LC-MS/MS run. Created with BioRender.com.

Similar articles

Cited by

References

    1. Chen M.J., Dixon J.E., Manning G. Genomics and evolution of protein phosphatases. Sci. Signal. 2017;10:eaag1796. doi: 10.1126/scisignal.aag1796. - DOI - PubMed
    1. Humphrey S.J., Karayel O., James D.E., Mann M. High-throughput and high-sensitivity phosphoproteomics with the EasyPhos platform. Nat. Protoc. 2018;13:1897–1916. doi: 10.1038/s41596-018-0014-9. - DOI - PubMed
    1. Mertins P., Tang L.C., Krug K., Clark D.J., Gritsenko M.A., Chen L., Clauser K.R., Clauss T.R., Shah P., Gillette M.A., et al. Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography–mass spectrometry. Nat. Protoc. 2018;13:1632–1661. doi: 10.1038/s41596-018-0006-9. - DOI - PMC - PubMed
    1. Pino L.K., Searle B.C., Bollinger J.G., Nunn B., MacLean B., MacCoss M.J. The Skyline ecosystem: Informatics for quantitative mass spectrometry proteomics. Mass Spectrom. Rev. 2020;39:229–244. doi: 10.1002/mas.21540. - DOI - PMC - PubMed
    1. Palomba A., Abbondio M., Fiorito G., Uzzau S., Pagnozzi D., Tanca A. Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools. J. Proteome Res. 2021;20:3497–3507. doi: 10.1021/acs.jproteome.1c00143. - DOI - PMC - PubMed

MeSH terms

LinkOut - more resources