PP2A/B55α substrate recruitment as defined by the retinoblastoma-related protein p107
- Temple University Lewis Katz School of Medicine, United States
- Fox Chase Cancer Center, United States
- University of Arizona, United States
- Hitchcock Medical Center at Dartmouth, United States
- UConn Health, United States
Abstract
Protein phosphorylation is a reversible post-translation modification essential in cell signaling. This study addresses a long-standing question as to how the most abundant serine/threonine Protein Phosphatase 2 (PP2A) holoenzyme, PP2A/B55α, specifically recognizes substrates and presents them to the enzyme active site. Here, we show how the PP2A regulatory subunit B55α recruits p107, a pRB-related tumor suppressor and B55α substrate. Using molecular and cellular approaches, we identified a conserved region 1 (R1, residues 615-626) encompassing the strongest p107 binding site. This enabled us to identify an 'HxRVxxV619-625' short linear motif (SLiM) in p107 as necessary for B55α binding and dephosphorylation of the proximal pSer-615 in vitro and in cells. Numerous B55α/PP2A substrates, including TAU, contain a related SLiM C-terminal from a proximal phosphosite, 'p[ST]-P-x(4,10)-[RK]-V-x-x-[VI]-R'. Mutation of conserved SLiM residues in TAU dramatically inhibits dephosphorylation by PP2A/B55α, validating its generality. A data-guided computational model details the interaction of residues from the conserved p107 SLiM, the B55α groove, and phosphosite presentation. Altogether these data provide key insights into PP2A/B55α mechanisms of substrate recruitment and active site engagement, and also facilitate identification and validation of new substrates, a key step towards understanding PP2A/B55α role in multiple cellular processes.
Data availability
Raw MS data for the the data depicted in Figure 6B are available at MassIVEhttps://massive.ucsd.edu/ProteoSAFe/dataset.jsp?task=9c21e08f6a524d7097e8bd45f0d2f375PXD028612.All NMR chemical shifts (Figure 1E-F) have been deposited in the BioMagResBank (BMRB: 28091).Source code folder (PeptideDock_sourceCode) for Figure 7 is a C# project, including retrieval of peptide structures from PDB and other sources such as PISCES, and calculation of distances and data analyses. https://github.com/DunbrackLab/PP2A_PeptideDock.All other data generated or analysed during this study are included in the manuscript and supporting files. Source Data files have been provided.
Article and author information
Author details
Arminja N Kettenbach
Funding
National Institute of General Medical Sciences (R01 GM117437)
- Xavier Graña
National Cancer Institute (R03 CA216134-01)
- Xavier Graña
WW Smith charitable Trust Award (no reference number)
- Xavier Graña
National Cancer Institute (P30 CA006927)
- Roland L Dunbrack Jr.
- Xavier Graña
National Cancer Institute (U54 CA221704)
- Holly Fowle
- Ziran Zhao
National Institute of General Medical Sciences (R01GM134683)
- Wolfgang Peti
National Institute of Neurological Disorders and Stroke (R01NS091336)
- Wolfgang Peti
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2021, Fowle et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,317
- views
-
- 308
- downloads
-
- 26
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
PP2A/B55α substrate recruitment as defined by the retinoblastoma-related protein p107
eLife 10:e63181.
https://doi.org/10.7554/eLife.63181
Further reading
-
- Biochemistry and Chemical Biology
- Microbiology and Infectious Disease
Teichoic acids (TA) are linear phospho-saccharidic polymers and important constituents of the cell envelope of Gram-positive bacteria, either bound to the peptidoglycan as wall teichoic acids (WTA) or to the membrane as lipoteichoic acids (LTA). The composition of TA varies greatly but the presence of both WTA and LTA is highly conserved, hinting at an underlying fundamental function that is distinct from their specific roles in diverse organisms. We report the observation of a periplasmic space in Streptococcus pneumoniae by cryo-electron microscopy of vitreous sections. The thickness and appearance of this region change upon deletion of genes involved in the attachment of TA, supporting their role in the maintenance of a periplasmic space in Gram-positive bacteria as a possible universal function. Consequences of these mutations were further examined by super-resolved microscopy, following metabolic labeling and fluorophore coupling by click chemistry. This novel labeling method also enabled in-gel analysis of cell fractions. With this approach, we were able to titrate the actual amount of TA per cell and to determine the ratio of WTA to LTA. In addition, we followed the change of TA length during growth phases, and discovered that a mutant devoid of LTA accumulates the membrane-bound polymerized TA precursor.
-
- Biochemistry and Chemical Biology
- Computational and Systems Biology
Protein–protein interactions are fundamental to understanding the molecular functions and regulation of proteins. Despite the availability of extensive databases, many interactions remain uncharacterized due to the labor-intensive nature of experimental validation. In this study, we utilized the AlphaFold2 program to predict interactions among proteins localized in the nuage, a germline-specific non-membrane organelle essential for piRNA biogenesis in Drosophila. We screened 20 nuage proteins for 1:1 interactions and predicted dimer structures. Among these, five represented novel interaction candidates. Three pairs, including Spn-E_Squ, were verified by co-immunoprecipitation. Disruption of the salt bridges at the Spn-E_Squ interface confirmed their functional importance, underscoring the predictive model’s accuracy. We extended our analysis to include interactions between three representative nuage components—Vas, Squ, and Tej—and approximately 430 oogenesis-related proteins. Co-immunoprecipitation verified interactions for three pairs: Mei-W68_Squ, CSN3_Squ, and Pka-C1_Tej. Furthermore, we screened the majority of Drosophila proteins (~12,000) for potential interaction with the Piwi protein, a central player in the piRNA pathway, identifying 164 pairs as potential binding partners. This in silico approach not only efficiently identifies potential interaction partners but also significantly bridges the gap by facilitating the integration of bioinformatics and experimental biology.
