Optogenetic Repressors of Gene Expression in Yeasts Using Light-Controlled Nuclear Localization
Controlling gene expression is a fundamental goal of basic and synthetic biology because it allows insight into cellular function and control of cellular activity. We explored the possibility of generating an optogenetic repressor of gene expression in the model organism Saccharomyces cerevisiae by using light to control the nuclear localization of nuclease-dead Cas9, dCas9.
The dCas9 protein acts as a repressor for a gene of interest when localized to the nucleus in the presence of an appropriate guide RNA (sgRNA). We engineered dCas9, the mammalian transcriptional repressor Mxi1, and an optogenetic tool to control nuclear localization (LINuS) as parts in an existing yeast optogenetic toolkit. This allowed expression cassettes containing novel dCas9 repressor configurations and guide RNAs to be rapidly constructed and integrated into yeast.
Our library of repressors displays a range of basal repression without the need for inducers or promoter modification. Populations of cells containing these repressors can be combined to generate a heterogeneous population of yeast with a 100-fold expression range. We find that repression can be dialed modestly in a light dose- and intensity-dependent manner. We used this library to repress expression of the lanosterol 14-alpha-demethylase Erg11, generating yeast with a range of sensitivity to the important antifungal drug fluconazole.
This toolkit will be useful for spatiotemporal perturbation of gene expression in Saccharomyces cerevisiae. Additionally, we believe that the simplicity of our scheme will allow these repressors to be easily modified to control gene expression in medically relevant fungi, such as pathogenic yeasts.
KeywordsOptogenetics dCas9 Gene expression LINuS Fungal drug resistance
The authors would like to acknowledge discussion and helpful comments from the members of the McClean lab throughout the project. We acknowledge Taylor Scott for help analyzing the growth curve data, Kieran Sweeney for supplying MATLAB code to analyze nuclear localization, and Jidapas (My) An-Adirekkun for assistance with figures. This work was supported by the American Cancer Society [IRG-15-213-51] to M.N.M and by the BMBF 031L0079 grant to B.D.V. Flow cytometry was enabled by the University of Wisconsin Carbone Cancer Center Support Grant P30 CA014520. Megan Nicole McClean, Ph.D., holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund.
Conflict of interest
Authors Stephanie H. Geller, Enoch B. Antwi, Barbara Di Ventura and Megan N. McClean declare that they have no conflicts of interest.
No human or animal studies were carried out by the authors for this article.
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