BMC BiotechnologySynthetic BiologyPeer-reviewed journal article
A copper switch for inducing CRISPR/Cas9-based transcriptional activation tightly regulates gene expression in Nicotiana benthamiana.
Elena Garcia‐PereziD, Borja Diego‐MartiniD, Alfredo Quijano‐RubioiD, Elena Moreno GiméneziD, Sara SelmaiD, Diego OrzáeziD, Marta Vázquez‐VilariD
Abstract
CRISPR-based programmable transcriptional activators (PTAs) are used in plants for rewiring gene networks. Better tuning of their activity in a time and dose-dependent manner should allow precise control of gene expression. Here, we report the optimization of a Copper Inducible system called CI-switch for conditional gene activation in Nicotiana benthamiana. In the presence of copper, the copper-responsive factor CUP2 undergoes a conformational change and binds a DNA motif named copper-binding site (CBS). In this study, we tested several activation domains fused to CUP2 and found that the non-viral Gal4 domain results in strong activation of a reporter gene equipped with a minimal promoter, offering advantages over previous designs. To connect copper regulation with downstream programable elements, several copper-dependent configurations of the strong dCasEV2.1 PTA were assayed, aiming at maximizing activation range, while minimizing undesired background expression. The best configuration involved a dual copper regulation of the two protein components of the PTA, namely dCas9:EDLL and MS2:VPR, and a constitutive RNA pol III-driven expression of the third component, a guide RNA with anchoring sites for the MS2 RNA-binding domain. With these optimizations in place, the CI/dCasEV2.1 system resulted in copper-dependent activation rates of 2,600-fold for the endogenous N. benthamiana DFR gene, with negligible expression in the absence of the trigger. The tight regulation of copper over CI/dCasEV2.1 makes this system ideal for the conditional production of plant-derived metabolites and recombinant proteins in the field.
- organism: plant (other)
- assay: CRISPR screen
- research focus: gene regulatory network inference
- research focus: perturbation response prediction
- approach: experimental assay
- Citations
- 44
- FWCI
- 2.86
- Field percentile
- top 7%
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