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Efficient proximity labeling in living cells and organisms with TurboID

An Author Correction to this article was published on 20 November 2019

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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Figure 1: Directed evolution of TurboID.
Figure 2: Characterization of TurboID and miniTurbo in mammalian cells.
Figure 3: TurboID and miniTurbo in flies, worms, and other species.

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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.

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Authors

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.

Corresponding author

Correspondence to Alice Y Ting.

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

Supplementary information

Supplementary Figures, Tables, and Notes

Supplementary Figures 1–16, Supplementary Table 1 and 8–9, Supplementary Notes 1–5 (PDF 7844 kb)

Reporting Summary (PDF 1346 kb)

Supplementary Table 2

True positive and false positive lists used to filter and analyze ERM datasets (XLSX 1721 kb)

Supplementary Table 3

True positive and false positive lists used to filter and analyse nuclear proteomic datasets. (XLSX 1038 kb)

Supplementary Table 4

True positive and false positive lists used to filter and analyse mitochondrial matrix proteomic datasets. (XLSX 377 kb)

Supplementary Table 5

ER membrane (ERM) proteomic data. (XLSX 1331 kb)

Supplementary Table 6

Nuclear proteomic data (XLSX 1393 kb)

Supplementary Table 7

Mitochondrial matrix proteomic data. (XLSX 1064 kb)

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Branon, T., Bosch, J., Sanchez, A. et al. Efficient proximity labeling in living cells and organisms with TurboID. Nat Biotechnol 36, 880–887 (2018). https://doi.org/10.1038/nbt.4201

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