Tunable and Multifunctional Eukaryotic Transcription Factors Based on CRISPR/Cas
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Farzadfard_2013-Tunable and multifunctional.pdf
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Author(s)
Farzadfard, Fahim
Perli, Samuel David
Lu, Timothy K
Date Issued
August 2013
Journal
ACS Synthetic Biology
Publisher
American Chemical Society (ACS)
Citation
Farzadfard, Fahim, Samuel D. Perli, and Timothy K. Lu. “Tunable and Multifunctional Eukaryotic Transcription Factors Based on CRISPR/Cas.” ACS Synthetic Biology 2, no. 10 (October 18, 2013): 604-613. © 2013 American Chemical Society
Version
Final published version
Abstract
Transcriptional regulation is central to the complex behavior of natural biological systems and synthetic gene circuits. Platforms for the scalable, tunable, and simple modulation of transcription would enable new abilities to study natural systems and implement artificial capabilities in living cells. Previous approaches to synthetic transcriptional regulation have relied on engineering DNA-binding proteins, which necessitate multistep processes for construction and optimization of function. Here, we show that the CRISPR/Cas system of Streptococcus pyogenes can be programmed to direct both activation and repression to natural and artificial eukaryotic promoters through the simple engineering of guide RNAs with base-pairing complementarity to target DNA sites. We demonstrate that the activity of CRISPR-based transcription factors (crisprTFs) can be tuned by directing multiple crisprTFs to different positions in natural promoters and by arraying multiple crisprTF-binding sites in the context of synthetic promoters in yeast and human cells. Furthermore, externally controllable regulatory modules can be engineered by layering gRNAs with small molecule-responsive proteins. Additionally, single nucleotide substitutions within promoters are sufficient to render them orthogonal with respect to the same gRNA-guided crisprTF. We envision that CRISPR-based eukaryotic gene regulation will enable the facile construction of scalable synthetic gene circuits and open up new approaches for mapping natural gene networks and their effects on complex cellular phenotypes.
MIT Department
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Synthetic Biology Center
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1021/sb400081r
