Letter | Published:

Efficient proximity labeling in living cells and organisms with TurboID

Nature Biotechnology volume 36, pages 880887 (2018) | Download Citation

Abstract

Protein interaction networks and protein compartmentalization underlie all signaling and regulatory processes in cells. Enzyme-catalyzed proximity labeling (PL) has emerged as a new approach to study the spatial and interaction characteristics of proteins in living cells. However, current PL methods require over 18 h of labeling time or utilize chemicals with limited cell permeability or high toxicity. We used yeast display-based directed evolution to engineer two promiscuous mutants of biotin ligase, TurboID and miniTurbo, which catalyze PL with much greater efficiency than BioID or BioID2, and enable 10-min PL in cells with non-toxic and easily deliverable biotin. Furthermore, TurboID extends biotin-based PL to flies and worms.

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Acknowledgements

FACS was performed at the Koch Institute Flow Cytometry Core (MIT) and Stanford Shared FACS Facility. S. Han (Stanford) synthesized neutravidin-AlexaFluor647. S. Ax (Stanford) cloned the cell surface TurboID and miniTurbo constructs. We are grateful to I. Droujinine (Harvard) for advice on biotin labeling in D. melanogaster. Biotin auxotrophic E. coli MG1655bioB:kan was kindly donated by J. Cronan (University of Illinois). This work was supported by NIH R01-CA186568 (to A.Y.T.), Howard Hughes Medical Institute Collaborative Innovation Award (to A.Y.T., S.C., and N.P.), and NIH New Innovator Award DP2GM119136 (to J.L.F.). T.C.B. was supported by Dow Graduate Research and Lester Wolfe Fellowships. J.A.B. was supported by a Damon Runyon Post-Doctoral Fellowship. A.D.S. was supported by NIH Training Grant 2T32GM007276.

Author information

Affiliations

  1. Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Tess C Branon
    •  & Alice Y Ting
  2. Departments of Genetics, Stanford University, Stanford, California, USA.

    • Tess C Branon
    •  & Alice Y Ting
  3. Department of Chemistry, Stanford University, Stanford, California, USA.

    • Tess C Branon
    •  & Alice Y Ting
  4. Department of Biology, Stanford University, Stanford, California, USA.

    • Tess C Branon
    • , Ariana D Sanchez
    • , Jessica L Feldman
    •  & Alice Y Ting
  5. Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.

    • Justin A Bosch
    •  & Norbert Perrimon
  6. Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Namrata D Udeshi
    • , Tanya Svinkina
    •  & Steven A Carr
  7. Howard Hughes Medical Institute, Boston, Massachusetts, USA.

    • Norbert Perrimon
  8. Chan Zuckerberg Biohub, San Francisco, California, USA.

    • Alice Y Ting

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Contributions

T.C.B. and A.Y.T. designed the research and analyzed all the data except those noted. T.C.B. performed all experiments except those noted. T.C.B., A.Y.T., N.D.U., and S.A.C. designed the proteomics experiments. T.C.B. prepared the proteomic samples. N.D.U. and T.S. processed the proteomic samples and performed mass spectrometry. J.A.B. performed D. melanogaster experiments. J.A.B. and N.P. analyzed D. melanogaster data. T.C.B., A.Y.T., A.D.S., and J.L.F. designed the C. elegans experiments. A.D.S. performed C. elegans experiments. A.D.S. and J.L.F. analyzed C. elegans data.

Competing interests

A.Y.T. and T.C.B. have filed a patent application covering some aspects of this work.

Corresponding author

Correspondence to Alice Y Ting.

Supplementary information

PDF files

  1. 1.

    Supplementary Figures, Tables, and Notes

    Supplementary Figures 1–16, Supplementary Table 1 and 8–9, Supplementary Notes 1–5

  2. 2.

    Reporting Summary

Excel files

  1. 1.

    Supplementary Table 2

    True positive and false positive lists used to filter and analyze ERM datasets

  2. 2.

    Supplementary Table 3

    True positive and false positive lists used to filter and analyse nuclear proteomic datasets.

  3. 3.

    Supplementary Table 4

    True positive and false positive lists used to filter and analyse mitochondrial matrix proteomic datasets.

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    Supplementary Table 5

    ER membrane (ERM) proteomic data.

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    Supplementary Table 6

    Nuclear proteomic data

  6. 6.

    Supplementary Table 7

    Mitochondrial matrix proteomic data.

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DOI

https://doi.org/10.1038/nbt.4201

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