Abstract
Defining the biologically active structures of proteins in their cellular environments remains challenging for proteins with multiple conformations and functions, where only a minor conformer might be associated with a given function. Here, we use deep mutational scanning to probe the structure and dynamics of α-synuclein, a protein known to adopt disordered, helical and amyloid conformations. We examined the effects of 2,600 single-residue substitutions on the ability of intracellularly expressed α-synuclein to slow the growth of yeast. Computational analysis of the data showed that the conformation responsible for this phenotype is a long, uninterrupted, amphiphilic helix with increasing dynamics toward the C terminus. Deep mutational scanning can therefore determine biologically active conformations in cellular environments, even for a highly dynamic multi-conformational protein.
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Data availability
Raw sequencing data are available at the NCBI Sequence Read Archive (PRJNA564806). Source data for Figs. 2–4 and Supplementary Fig. 2 are available online. Unprocessed images are available upon request.
Code availability
Programs developed to analyze the data reported are available at github.com/rnewberry17.
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Acknowledgements
We thank D. Larsen for technical assistance. We acknowledge students of the Integrated Program in Quantitative Biology at UCSF for contributions to our analytical approach and initial models of toxicity; their findings regarding α-synuclein DMS under different environmental conditions will be described in a manuscript currently in preparation. We thank the laboratory of H. El-Samad (University of California, San Francisco) for yeast strains, the laboratory of V. M.-Y. Lee for plasmids (University of Pennsylvania) and Twist Bioscience for providing the dsDNA variant library in support of our educational efforts. This work was supported by grants from the NIH to M.K. (grant no. DP2 GM119139) and to W.F.D. (grant nos. R35-122603, P01-AG002132, R01-GM117593) and by the UCSF Program in Breakthrough Biomedical Research, which is funded in part by the Sandler Foundation, through grants to M.K. R.W.N. was supported by NIH training grant no. T32-HL007731 and a UCSF Program in Breakthrough Biomedical Research Postdoc Independent Research Grant, which is funded in part by the Sandler Foundation. Flow cytometry was supported by grant no. P30-CA082103 (NIH).
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R.W.N. and M.K. conceived the project. R.W.N., M.K. and W.F.D. formulated the hypotheses and designed the experiments. R.W.N., E.D.C. and M.K. designed the library and sequencing strategy. R.W.N. constructed and screened the variant library and yeast strains. R.W.N., J.T.L. and M. K. designed the cell sorting strategy. J.T.L. performed flow cytometry. E.D.C. collected next-generation sequencing data. R.W.N. purified proteins and performed circular dichroism spectroscopy and fluorescence microscopy. R.W.N. and W.F.D. developed structural models. R.W.N., M.K. and W.F.D analyzed the data and drafted the manuscript. All authors contributed to the writing of the manuscript.
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Newberry, R.W., Leong, J.T., Chow, E.D. et al. Deep mutational scanning reveals the structural basis for α-synuclein activity. Nat Chem Biol 16, 653–659 (2020). https://doi.org/10.1038/s41589-020-0480-6
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DOI: https://doi.org/10.1038/s41589-020-0480-6
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