Dissecting protein function: An efficient protocol for identifying separation-of-function mutations that encode structurally stable proteins

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Abstract

Mutations that confer the loss of a single biochemical property (separation-of-function mutations) can often uncover a previously unknown role for a protein in a particular biological process. However, most mutations are identified based on loss-offunction phenotypes, which cannot differentiate between separation-of-function alleles vs. mutations that encode unstable/unfolded proteins. An alternative approach is to use overexpression dominant-negative (ODN) phenotypes to identify mutant proteins that disrupt function in an otherwise wild-type strain when overexpressed. This is based on the assumption that such mutant proteins retain an overall structure that is comparable to that of the wild-type protein and are able to compete with the endogenous protein (Herskowitz 1987). To test this, the in vivo phenotypes of mutations in the Est3 telomerase subunit from Saccharomyces cerevisiae were compared with the in vitro secondary structure of these mutant proteins as analyzed by circular-dichroism spectroscopy, which demonstrates that ODN is a more sensitive assessment of protein stability than the commonly used method of monitoring protein levels from extracts. Reverse mutagenesis of EST3, which targeted different categories of amino acids, also showed that mutating highly conserved charged residues to the oppositely charged amino acid had an increased likelihood of generating a severely defective est32 mutation, which nevertheless encoded a structurally stable protein. These results suggest that charge-swap mutagenesis directed at a limited subset of highly conserved charged residues, combined with ODN screening to eliminate partially unfolded proteins, may provide a widely applicable and efficient strategy for generating separation-of-function mutations. © 2013 by the Genetics Society of America.

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Lubin, J. W., Rao, T., Mandel, E. K., Wuttke, D. S., & Lundblad, V. (2013). Dissecting protein function: An efficient protocol for identifying separation-of-function mutations that encode structurally stable proteins. Genetics, 193(3), 715–725. https://doi.org/10.1534/genetics.112.147801

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