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Proteome-wide identification of ubiquitin interactions using UbIA-MS

Nature Protocols volume 13, pages 530–550 (2018)Cite this article

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Abstract

Ubiquitin-binding proteins play an important role in eukaryotes by translating differently linked polyubiquitin chains into proper cellular responses. Current knowledge about ubiquitin-binding proteins and ubiquitin linkage-selective interactions is mostly based on case-by-case studies. We have recently reported a method called ubiquitin interactor affinity enrichment–mass spectrometry (UbIA-MS), which enables comprehensive identification of ubiquitin interactors for all ubiquitin linkages from crude cell lysates. One major strength of UbIA-MS is the fact that ubiquitin interactors are enriched from crude cell lysates, in which proteins are present at endogenous levels, contain biologically relevant post-translational modifications (PTMs) and are assembled in native protein complexes. In addition, UbIA-MS uses chemically synthesized nonhydrolyzable diubiquitin, which mimics native diubiquitin and is inert to cleavage by endogenous deubiquitinases (DUBs). Here, we present a detailed protocol for UbIA-MS that proceeds in five stages: (i) chemical synthesis of ubiquitin precursors and click chemistry for the generation of biotinylated nonhydrolyzable diubiquitin baits, (ii) in vitro affinity purification of ubiquitin interactors, (iii) on-bead interactor digestion, (iv) liquid chromatography (LC)–MS/MS analysis and (v) data analysis to identify differentially enriched proteins. The computational analysis tools are freely available as an open-source R software package, including a graphical interface. Typically, UbIA-MS allows the identification of dozens to hundreds of ubiquitin interactors from any type of cell lysate, and can be used to study cell type or stimulus-dependent ubiquitin interactions. The nonhydrolyzable diubiquitin synthesis can be completed in 3 weeks, followed by ubiquitin interactor enrichment and identification, which can be completed within another 2 weeks.

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Figure 1: Schematic overview of UbIA-MS workflow.
Figure 2: Schematic representation of the DEP analysis workflow.
Figure 3: Interactors of different diubiquitin linkages in HeLa cells.
Figure 4: K48 diubiquitin interactors.
Figure 5: Distribution of the number of diubiquitin linkages bound by each interactor.

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Acknowledgements

We thank B. Klaus for statistical advice and members of the Vermeulen and Ovaa labs for fruitful discussions. Work in the Zhang lab was supported by the “Hundred Talents Program C” of the Chinese Academy of Sciences (no. 2017-045) and by Guangdong Science and Technology Projects (2014B050504008, 2014B050502012, 2014B020225002 and 2014B030301058). Work in the Vermeulen lab was supported by the NWO Gravitation program CGC.nl. Work in the Ovaa lab was supported by the ERC grant Ubicode (no. 281699). A.H.S. was supported by a fellowship from the EMBL Interdisciplinary Postdoc (EIPOD) Programme under a grant from the Marie Sklodowska-Curie Actions COFUND (no. 664726).

Author information

Author notes

  1. Xiaofei Zhang, Arne H Smits and Gabrielle BA van Tilburg: These authors contributed equally to this work.

Authors and Affiliations

  1. CAS Key Laboratory of Regenerative Biology, Guangdong Provincial Key Laboratory of Stem Cells and Regenerative Medicine, South China Institute for Stem Cell Biology and Regenerative Medicine, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China

    Xiaofei Zhang

  2. Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Radboud University Nijmegen, Nijmegen, the Netherlands

    Xiaofei Zhang & Michiel Vermeulen

  3. Genome Biology Unit, European Molecular Biology Laboratory, Heidelberg, Germany

    Arne H Smits & Wolfgang Huber

  4. Department of Chemical Immunology, Leiden University Medical Center, Leiden, the Netherlands

    Gabrielle BA van Tilburg & Huib Ovaa

Authors
  1. Xiaofei Zhang
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  4. Huib Ovaa
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  6. Michiel Vermeulen
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Contributions

X.Z. and M.V. designed the method with input from A.H.S., G.B.A.v.T., W.H. and H.O. A.H.S. prepared figures, and developed and maintained the R package. X.Z., A.H.S., G.B.A.v.T. and M.V. wrote the manuscript with input from H.O. and W.H.

Corresponding authors

Correspondence to Xiaofei Zhang, Arne H Smits or Michiel Vermeulen.

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Competing interests

H.O. is a shareholder in the biotechnology company UbiQ. The other authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Quality-control plots.

(a) The number of proteins identified in every sample. Colors indicate the conditions and the solid line indicates the number of proteins identified in all samples (b) Stacked barplot to visualize the total number of proteins classified by the number of samples they are identified in (stacks and colors). (c) Barplot to visualize the number of proteins identified classified by the number of samples they are identified in (colors). (d) Boxplots of protein intensity distributions before (bottom) and after (top) normalization. (e) Heatmap of the proteins with missing values. Colors indicate whether the values are missing (white) or are valid (black).

Supplementary Figure 2 Heatmap of linkage-selective interactors of diubiquitin linkages in HeLa cells.

Layout, clustering and colors are as in Figure 3.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1 and 2. (PDF 795 kb)

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Zhang, X., Smits, A., van Tilburg, G. et al. Proteome-wide identification of ubiquitin interactions using UbIA-MS. Nat Protoc 13, 530–550 (2018). https://doi.org/10.1038/nprot.2017.147

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