Abstract
Small ubiquitin-like modifiers (SUMOs) are post-translational modifications (PTMs) that regulate nuclear cellular processes. Here we used an augmented K0–SUMO proteomics strategy to identify 40,765 SUMO acceptor sites and quantify their fractional contribution for 6,747 human proteins. Structural–predictive analyses revealed that lysines residing in disordered regions are preferentially targeted by SUMO, in notable contrast to other widespread lysine modifications. In our data set, we identified 807 SUMOylated peptides that were co-modified by phosphorylation, along with dozens of SUMOylated peptides that were co-modified by ubiquitylation, acetylation and methylation. Notably, 9% of the identified SUMOylome occurred proximal to phosphorylation, and numerous SUMOylation sites were found to be fully dependent on prior phosphorylation events. SUMO-proximal phosphorylation occurred primarily in a proline-directed manner, and inhibition of cyclin-dependent kinases dynamically affected co-modification. Collectively, we present a comprehensive analysis of the SUMOylated proteome, uncovering the structural preferences for SUMO and providing system-wide evidence for a remarkable degree of cross-talk between SUMOylation and other major PTMs.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$189.00 per year
only $15.75 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
References
Hendriks, I.A. et al. Uncovering global SUMOylation signaling networks in a site-specific manner. Nat. Struct. Mol. Biol. 21, 927–936 (2014).
Hendriks, I.A. & Vertegaal, A.C. A comprehensive compilation of SUMO proteomics. Nat. Rev. Mol. Cell Biol. 17, 581–595 (2016).
Enserink, J.M. SUMO and the cellular stress response. Cell Div. 10, 4 (2015).
Psakhye, I. & Jentsch, S. Protein group modification and synergy in the SUMO pathway as exemplified in DNA repair. Cell 151, 807–820 (2012).
Dantuma, N.P. & van Attikum, H. Spatiotemporal regulation of post-translational modifications in the DNA damage response. EMBO J. 35, 6–23 (2016).
Sahin, U., de Thé, H. & Lallemand-Breitenbach, V. PML nuclear bodies: assembly and oxidative-stress-sensitive SUMOylation. Nucleus 5, 499–507 (2014).
Flotho, A. & Melchior, F. SUMOylation: a regulatory protein modification in health and disease. Annu. Rev. Biochem. 82, 357–385 (2013).
Eifler, K. & Vertegaal, A.C. SUMOylation-mediated regulation of cell cycle progression and cancer. Trends Biochem. Sci. 40, 779–793 (2015).
Wang, L. et al. SUMO2 is essential while SUMO3 is dispensable for mouse embryonic development. EMBO Rep. 15, 878–885 (2014).
Johnson, E.S. Protein modification by SUMO. Annu. Rev. Biochem. 73, 355–382 (2004).
Hershko, A. & Ciechanover, A. The ubiquitin system. Annu. Rev. Biochem. 67, 425–479 (1998).
Hay, R.T. SUMO-specific proteases: a twist in the tail. Trends Cell Biol. 17, 370–376 (2007).
Vertegaal, A.C. SUMO chains: polymeric signals. Biochem. Soc. Trans. 38, 46–49 (2010).
Mann, M., Kulak, N.A., Nagaraj, N. & Cox, J. The coming age of complete, accurate and ubiquitous proteomes. Mol. Cell 49, 583–590 (2013).
Olsen, J.V. et al. Quantitative phosphoproteomics reveals widespread full phosphorylation-site occupancy during mitosis. Sci. Signal. 3, ra3 (2010).
Kim, W. et al. Systematic and quantitative assessment of the ubiquitin-modified proteome. Mol. Cell 44, 325–340 (2011).
Choudhary, C. et al. Lysine acetylation targets protein complexes and co-regulates major cellular functions. Science 325, 834–840 (2009).
Zielinska, D.F., Gnad, F., Wis´niewski, J.R. & Mann, M. Precision mapping of an in vivo N-glycoproteome reveals rigid topological and sequence constraints. Cell 141, 897–907 (2010).
Larsen, S.C. et al. Proteome-wide analysis of arginine monomethylation reveals widespread occurrence in human cells. Sci. Signal. 9, rs9 (2016).
Martello, R. et al. Proteome-wide identification of the endogenous ADP-ribosylome of mammalian cells and tissue. Nat. Commun. 7, 12917 (2016).
Schimmel, J. et al. Uncovering SUMOylation dynamics during cell cycle progression reveals FoxM1 as a key mitotic SUMO target protein. Mol. Cell 53, 1053–1066 (2014).
Becker, J. et al. Detecting endogenous SUMO targets in mammalian cells and tissues. Nat. Struct. Mol. Biol. 20, 525–531 (2013).
Matic, I. et al. Site-specific identification of SUMO2 targets in cells reveals an inverted SUMOylation motif and a hydrophobic-cluster SUMOylation motif. Mol. Cell 39, 641–652 (2010).
Tammsalu, T. et al. Proteome-wide identification of SUMO2 modification sites. Sci. Signal. 7, rs2 (2014).
Lamoliatte, F. et al. Large-scale analysis of lysine SUMOylation by SUMO remnant immunoaffinity profiling. Nat. Commun. 5, 5409 (2014).
Eifler, K. & Vertegaal, A.C. Mapping the SUMOylated landscape. FEBS J. 282, 3669–3680 (2015).
Xiao, Z. et al. System-wide analysis of SUMOylation dynamics in response to replication stress reveals novel SUMO target proteins and acceptor lysines relevant for genome stability. Mol. Cell. Proteomics 14, 1419–1434 (2015).
Hendriks, I.A., Treffers, L.W., Verlaan-de Vries, M., Olsen, J.V. & Vertegaal, A.C. SUMO2 orchestrates chromatin modifiers in response to DNA damage. Cell Rep. 10, 1778–1791 (2015).
Linding, R. et al. Systematic discovery of in vivo phosphorylation networks. Cell 129, 1415–1426 (2007).
Hendriks, I.A. & Vertegaal, A.C. A high-yield double-purification proteomics strategy for the identification of SUMO sites. Nat. Protoc. 11, 1630–1649 (2016).
Nagaraj, N. et al. Deep proteome and transcriptome mapping of a human cancer cell line. Mol. Syst. Biol. 7, 548 (2011).
Batth, T.S., Francavilla, C. & Olsen, J.V. Off-line high-pH reversed-phase fractionation for in-depth phosphoproteomics. J. Proteome Res. 13, 6176–6186 (2014).
Rodriguez, M.S., Dargemont, C. & Hay, R.T. SUMO1 conjugation in vivo requires both a consensus modification motif and nuclear targeting. J. Biol. Chem. 276, 12654–12659 (2001).
Danielsen, J.M. et al. Mass spectrometric analysis of lysine ubiquitylation reveals promiscuity at site level. Mol. Cell. Proteomics 10, 003590 (2011).
Mahajan, R., Delphin, C., Guan, T., Gerace, L. & Melchior, F. A small ubiquitin-related polypeptide involved in targeting RanGAP1 to nuclear pore complex protein RanBP2. Cell 88, 97–107 (1997).
Matunis, M.J., Coutavas, E. & Blobel, G. A novel ubiquitin-like modification modulates the partitioning of the Ran-GTPase-activating protein RanGAP1 between the cytosol and the nuclear pore complex. J. Cell Biol. 135, 1457–1470 (1996).
Mahajan, R., Gerace, L. & Melchior, F. Molecular characterization of the SUMO1 modification of RanGAP1 and its role in nuclear envelope association. J. Cell Biol. 140, 259–270 (1998).
Kamitani, T. et al. Identification of three major sentrinization sites in PML. J. Biol. Chem. 273, 26675–26682 (1998).
Golebiowski, F. et al. System-wide changes to SUMO modifications in response to heat shock. Sci. Signal. 2, ra24 (2009).
Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 13, 2513–2526 (2014).
Kirisako, T. et al. A ubiquitin ligase complex assembles linear polyubiquitin chains. EMBO J. 25, 4877–4887 (2006).
Tatham, M.H. et al. RNF4 is a poly-SUMO-specific E3 ubiquitin ligase required for arsenic-induced PML degradation. Nat. Cell Biol. 10, 538–546 (2008).
Lallemand-Breitenbach, V. et al. Arsenic degrades PML or PML-RARα through a SUMO-triggered RNF4-ubiquitin-mediated pathway. Nat. Cell Biol. 10, 547–555 (2008).
Hietakangas, V. et al. PDSM, a motif for phosphorylation-dependent SUMO modification. Proc. Natl. Acad. Sci. USA 103, 45–50 (2006).
Picard, N. et al. Identification of estrogen receptor (as a SUMO1 target reveals a novel phosphorylated SUMOylation motif and regulation by glycogen synthase kinase 3β. Mol. Cell. Biol. 32, 2709–2721 (2012).
Hayakawa, F. & Privalsky, M.L. Phosphorylation of PML by mitogen-activated protein kinases plays a key role in arsenic trioxide–mediated apoptosis. Cancer Cell 5, 389–401 (2004).
Nakayama, M., Kikuno, R. & Ohara, O. Protein-protein interactions between large proteins: two-hybrid screening using a functionally classified library composed of long cDNAs. Genome Res. 12, 1773–1784 (2002).
Bernier-Villamor, V., Sampson, D.A., Matunis, M.J. & Lima, C.D. Structural basis for E2-mediated SUMO conjugation revealed by a complex between ubiquitin-conjugating enzyme Ubc9 and RanGAP1. Cell 108, 345–356 (2002).
Macauley, M.S. et al. Beads-on-a-string, characterization of ETS1 SUMOylated within its flexible N-terminal sequence. J. Biol. Chem. 281, 4164–4172 (2006).
Pichler, A. et al. SUMO modification of the ubiquitin-conjugating enzyme E2-25K. Nat. Struct. Mol. Biol. 12, 264–269 (2005).
Yavuz, A.S. & Sezerman, O.U. Predicting SUMOylation sites using support vector machines based on various sequence features, conformational flexibility and disorder. BMC Genomics 15 (Suppl. 9), S18 (2014).
Iakoucheva, L.M. et al. The importance of intrinsic disorder for protein phosphorylation. Nucleic Acids Res. 32, 1037–1049 (2004).
Yau, R. & Rape, M. The increasing complexity of the ubiquitin code. Nat. Cell Biol. 18, 579–586 (2016).
Ye, Y. et al. Ubiquitin chain conformation regulates recognition and activity of interacting proteins. Nature 492, 266–270 (2012).
Ulrich, H.D. The fast-growing business of SUMO chains. Mol. Cell 32, 301–305 (2008).
Wang, Y., Tang, C., Wang, E. & Wang, J. Polyubiquitin chain linkage topology selects the functions from the underlying binding landscape. PLoS Comput. Biol. 10, e1003691 (2014).
Lundby, A. et al. Quantitative maps of protein phosphorylation sites across 14 different rat organs and tissues. Nat. Commun. 3, 876 (2012).
Tyanova, S., Cox, J., Olsen, J., Mann, M. & Frishman, D. Phosphorylation variation during the cell cycle scales with structural propensities of proteins. PLoS Comput. Biol. 9, e1002842 (2013).
Nguyen, L.K., Kolch, W. & Kholodenko, B.N. When ubiquitination meets phosphorylation: a systems biology perspective of EGFR-MAPK signaling. Cell Commun. Signal. 11, 52 (2013).
Bracken, C.P. et al. Regulation of cyclin D1 RNA stability by SNIP1. Cancer Res. 68, 7621–7628 (2008).
Rappsilber, J., Mann, M. & Ishihama, Y. Protocol for micropurification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat. Protoc. 2, 1896–1906 (2007).
Vizcaíno, J.A. et al. ProteomeXchange provides globally coordinated proteomics data submission and dissemination. Nat. Biotechnol. 32, 223–226 (2014).
Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).
Horn, H. et al. KinomeXplorer: an integrated platform for kinome biology studies. Nat. Methods 11, 603–604 (2014).
Hornbeck, P.V. et al. PhosphoSitePlus, 2014: mutations, PTMs and recalibrations. Nucleic Acids Res. 43, D512–D520 (2015).
Dosztányi, Z., Csizmók, V., Tompa, P. & Simon, I. The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins. J. Mol. Biol. 347, 827–839 (2005).
Magnan, C.N. & Baldi, P. SSpro/ACCpro 5: almost perfect prediction of protein secondary structure and relative solvent accessibility using profiles, machine learning and structural similarity. Bioinformatics 30, 2592–2597 (2014).
Colaert, N., Helsens, K., Martens, L., Vandekerckhove, J. & Gevaert, K. Improved visualization of protein consensus sequences by iceLogo. Nat. Methods 6, 786–787 (2009).
Impens, F., Radoshevich, L., Cossart, P. & Ribet, D. Mapping of SUMO sites and analysis of SUMOylation changes induced by external stimuli. Proc. Natl. Acad. Sci. USA 111, 12432–12437 (2014).
Hendriks, I.A., D'Souza, R.C., Chang, J.G., Mann, M. & Vertegaal, A.C. System-wide identification of wild-type SUMO2 conjugation sites. Nat. Commun. 6, 7289 (2015).
Acknowledgements
We thank members of the NNF-CPR for fruitful discussions and careful reading of the manuscript and the CPR Mass Spectrometry Platform for instrument support and assistance. The work was in part supported by the Novo Nordisk Foundation Center for Protein Research (to M.L.N.), the Novo Nordisk Foundation (grants NNF14CC0001 and NNF13OC0006477 (to M.L.N.)) and the Danish Council of Independent Research, grant agreement number DFF 4002-00051 (Sapere Aude) and grant agreement number DFF 4183-00322A (to M.L.N.). I.A.H. is supported by the European Molecular Biology Organization (grant ALTF 503-2016). A.C.O.V. is supported by the Netherlands Organization for Scientific Research (NWO) and the European Research Council (ERC grant 310913). The authors thank C.N. Magnan for running the ACCpro predictions and J.B. Hein for advice on CDK inhibitors.
Author information
Authors and Affiliations
Contributions
I.A.H. and M.L.N. designed the experiments; I.A.H. optimized the K0-SUMO workflow, implemented sample fractionation, performed all experiments, measured all samples on MS and processed all MS raw data; I.A.H. and C.Y. optimized MS methodology; D.L. and L.J.J. performed structural predictions; I.A.H. and M.L.N. performed bioinformatics analyses; A.C.O.V. and I.A.H. conceived the original biochemical K0-SUMO methodology; M.L.N. supervised and conceived the project; and I.A.H. and M.L.N. wrote the manuscript with input from all authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing financial interests.
Integrated supplementary information
Supplementary Figure 1 SUMO site peptide detection across multiple replicates.
(A) The MaxQuant Andromeda scores assigned to the identified SUMO sites, with control-condition and stress-induced sites indicated separately. (B) The number of SUMO sites detected by the exact number of replicates. MS/MS detection and evidence-matching detection are indicated. (C) As B, but with the number of sites detected in at least the number of replicates.
Supplementary Figure 2 Full coverage of all previously identified SUMO sites and proteins.
(A) Venn diagram visualizing identified SUMO sites in this study as compared to the three largest published SUMO-site studies. In this case, only 530 out of 5,213 SUMO sites were not found in this study. (B) Schematic representation of all previously MS-identified SUMO sites, and their re-identification in this study. Blue: re-identified in this work, red: not identified in this work. The number at the top of the bars indicates the exact number of SUMO sites not identified. (C) Venn diagram comparison of all SUMO sites identified in this study, all SUMO sites MS-identified in any other published study, and all ubiquitin sites MS-identified in any other study (data derived from PhosphoSitePlus (PSP). (D) Same as A, but for SUMO target proteins. In this case, only 145 out of 1,880 SUMO target proteins were not found in this study. (E) Same as B, but for SUMO target proteins. Note that external studies include non-site and endogenous studies. (F) Venn diagram comparison of all SUMO target proteins identified in this study, all SUMO target proteins identified in any other published study, all proteins identified in a deep total proteome study, and all proteins scored at least 3 out of 5 by UniProt.
Supplementary Figure 3 Data-reproducibility assessment.
(A) The number of SUMO sites detected on average and cumulatively for all experiments. Error bars represent standard deviation (SD). MS/MS detection and evidence-matching detection are indicated. (B) As A, but with cellular treatments or cell lines merged. (C) Pearson correlation analysis of SUMO sites identified in all replicates. “Same experiment” indicates correlation between the four replicates, “Other experiment” indicates correlation to all other-condition replicates. Error bars represent SD. (D) Principal component analysis of SUMO sites identified in all replicates. (E) Venn diagram visualizing the number of SUMO sites in any combination of treatments, compensated for matching evidence between runs. (F) Same as E, but compensated for matching evidence between runs.
Supplementary Figure 4 Global SUMO functions and stress dynamics.
(A) Term enrichment analysis visualizing terms that were significantly enriched for all (6,747) SUMO target proteins, as compared to the entire human proteome. Numbers in parentheses indicate participation size and category size. Score is a relative factor derived from enrichment ratio and significance. All changes were significant by Fisher Exact testing with Benjamini–Hochberg multiple-hypotheses corrected P<0.02. (B) The top 500 control-condition specific SUMO sites, as derived through profile clustering after Z-scoring and extraction of sites with the smallest Pearson distance, were compared through term enrichment analysis against all (40,765) SUMO sites detected in this study. Enriched terms are displayed in blue, and depleted terms in red. Numbers in parentheses indicate participation size and category size. Score is a relative factor derived from enrichment ratio and significance. All changes were significant by Fisher Exact testing with Benjamini–Hochberg multiple-hypotheses corrected P<0.02. (C) Same as B, but for Bortezomib treatment. (D) Same as B, but for heat shock. (E) Same as B, but for MG132 treatment, and using the top 1,000 sites. (F) Same as B, but for HeLa-exclusive sites. (G) Same as B, but for U2OS-exclusive sites.
Supplementary Figure 5 STRING network analysis of SUMO and phosphorylation co-modified proteins.
STRING visualization of all SUMO and phosphorylation co-modified proteins. Thickness of connecting lines represents STRING interaction significance. Thickness of the line around the nodes represents number of co-modified peptides, size of the nodes represents co-modification degree, and similarly colored nodes were found to be highly interconnected through MCODE clustering. Only proteins that were connected to the network at high STRING confidence (>0.7) are displayed, and SUMO family members were removed to prevent clustering bias.
Supplementary Figure 6 CDK inhibition reveals SUMO-phospho dynamics.
(A) Term enrichment analysis portraying terms that were significantly enriched (blue) or depleted (red) for (454) SUMO target proteins co-modified with phosphorylation, as compared to all (6,747) SUMO target proteins identified in this study. Co-modification in all cases was observed at the peptide level, with both modifications directly detected through MS/MS. Numbers in parentheses indicate participation size and category size. Score is a relative factor derived from enrichment ratio and significance. All changes were significant by Fisher Exact testing with Benjamini–Hochberg multiple-hypotheses corrected P<0.02. (B) Same as Fig. 7D, but using 67,810 phosphorylation sites detected in at least 3 studies as a reference set (data derived from PSP). (C) Visualization of the predicted structural properties of subsets of lysine residues within the context of SUMO-phospho co-modification. Enrichment is compared to the average properties of all lysine residues within SUMO target proteins. All displayed values were significant by Fisher Exact testing with Benjamini–Hochberg multiple-hypotheses corrected P<0.02. (D) Overview of the CDK inhibition follow-up experiment. SUMO site enrichments were performed in HeLa and U2OS, under standard growth (Control) conditions and in response to CDK1- and CDK2 inhibition (CDKi). Experiments were performed in quadruplicate (n=4 cell culture replicates), and all replicates were analyzed by mass spectrometry as single-shots as well as fractions. (E) Venn diagram visualizing the number of MS/MS-identified SUMO sites in the CDKi experiment. (F) Same as E, but visualizing by site MS/MS-identified SUMO target proteins. (G) Hierarchical clustering analysis of Z-scored intensity values of SUMO sites detected in the CDKi experiment. Clustering hierarchy is indicated at the top. Black: <-0.5 SD (absent or depleted), blue: 0.5 SD (present), cyan: >1.5 SD (enriched). (H) Same as G, but only for SUMO-phospho co-modified sites.
Supplementary information
Supplementary Text and Figures
Supplementary Figures 1–6 and Supplementary Note 1 (PDF 2237 kb)
Supplementary Table 1
A list of all 40,765 identified SUMOylation sites, complete with qualitative and quantitative information. (XLSX 63397 kb)
Supplementary Table 2
A list of all 6,747 identified SUMO target proteins, complete with qualitative and quantitative information. (XLSX 11425 kb)
Supplementary Table 3
An extensive comparison of SUMOylation sites identified in this study to 9 other site-specific SUMOylation studies. (XLSX 13903 kb)
Supplementary Table 4
An extensive comparison of SUMO target proteins identified in this study to 10 other SUMO proteomics studies, mapped to the entire human proteome. (XLSX 3188 kb)
Supplementary Table 5
An overview of all term enrichment comparisons made across this study, in order to assess functional differences between selected groups of SUMO target proteins and sites. (XLSX 820 kb)
Supplementary Table 6
Full-scale prediction of the structural context of all lysine residues within SUMO target proteins identified in this study. (XLSX 7071 kb)
Supplementary Table 7
A list of all identified SUMO peptides co-modified with ubiquitin, acetyl, or methyl, complete with qualitative and quantitative information. (XLSX 130 kb)
Supplementary Table 8
A list of all 807 identified SUMO-phospho peptides, complete with qualitative and quantitative information. (XLSX 896 kb)
Supplementary Table 9
A list of all 8,044 identified SUMOylation sites in the CDKi follow-up experiment, complete with qualitative and quantitative information. (XLSX 8551 kb)
Supplementary Table 10
A list of all 2,104 identified SUMO target proteins in the CDKi follow-up experiment, complete with qualitative and quantitative information. (XLSX 1871 kb)
Supplementary Table 11
A list of all 350 identified SUMO-phospho peptides in the CDKi follow-up experiment, complete with qualitative and quantitative information. (XLSX 396 kb)
Supplementary Data Set 1
Six fully annotated MS/MS spectra corresponding to the six SUMO sites identified on endogenous NEDD8. (PDF 1102 kb)
Rights and permissions
About this article
Cite this article
Hendriks, I., Lyon, D., Young, C. et al. Site-specific mapping of the human SUMO proteome reveals co-modification with phosphorylation. Nat Struct Mol Biol 24, 325–336 (2017). https://doi.org/10.1038/nsmb.3366
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/nsmb.3366
This article is cited by
-
A quantitative and site-specific atlas of the citrullinome reveals widespread existence of citrullination and insights into PADI4 substrates
Nature Structural & Molecular Biology (2024)
-
1,10-phenanthroline inhibits sumoylation and reveals that yeast SUMO modifications are highly transient
EMBO Reports (2024)
-
Phase separations in oncogenesis, tumor progressions and metastasis: a glance from hallmarks of cancer
Journal of Hematology & Oncology (2023)
-
LncRNA INHEG promotes glioma stem cell maintenance and tumorigenicity through regulating rRNA 2’-O-methylation
Nature Communications (2023)
-
Histone demethylase KDM5B licenses macrophage-mediated inflammatory responses by repressing Nfkbia transcription
Cell Death & Differentiation (2023)