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Resource competition shapes CRISPR-mediated gene activation

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ABSTRACT CRISPR-mediated gene activation (CRISPRa) allows concurrent transcriptional activation of many genes and has found widespread use in genome-wide screening, bioproduction, and therapeutics. Scaffold RNAs (scRNAs) recruit dCas9 and an activator protein (RBP-AD) to the target gene for activation with high sequence specificity. Here, we show that, despite this specificity, orthogonal scRNAs interfere with each other because they compete for dCas9 and RBP-AD. Specifically, we demonstrate that the expression of an scRNA that binds to these resources results in repression of genes targeted by different scRNAs. Intriguingly, we also discover that transcriptional gene regulation by an scRNA is biphasic, wherein increased level of the scRNA leads to gene repression instead of activation. These effects are significant even when dCas9 and RBP-AD are expressed at the maximum level tolerable by the cell. Our results demonstrate that CRISPRa systems are not as modular as previously thought and establish predictive modeling tools to assess the emergent behavior of multi-module CRISPRa networks.
Title: Resource competition shapes CRISPR-mediated gene activation
Description:
ABSTRACT CRISPR-mediated gene activation (CRISPRa) allows concurrent transcriptional activation of many genes and has found widespread use in genome-wide screening, bioproduction, and therapeutics.
Scaffold RNAs (scRNAs) recruit dCas9 and an activator protein (RBP-AD) to the target gene for activation with high sequence specificity.
Here, we show that, despite this specificity, orthogonal scRNAs interfere with each other because they compete for dCas9 and RBP-AD.
Specifically, we demonstrate that the expression of an scRNA that binds to these resources results in repression of genes targeted by different scRNAs.
Intriguingly, we also discover that transcriptional gene regulation by an scRNA is biphasic, wherein increased level of the scRNA leads to gene repression instead of activation.
These effects are significant even when dCas9 and RBP-AD are expressed at the maximum level tolerable by the cell.
Our results demonstrate that CRISPRa systems are not as modular as previously thought and establish predictive modeling tools to assess the emergent behavior of multi-module CRISPRa networks.

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