Resource competition in CRISPR-mediated gene regulation

Abstract

CRISPR-mediated gene regulation is known for its ability to control multiple targets simultaneously due to its modular nature: the same dCas9 effector can target different genes simply by changing the associated gRNA. However, multiplexing requires the sharing of limited amounts of dCas9 protein among multiple gRNAs, leading to resource competition. In turn, competition between gRNAs for the same resource may hamper network function. In this thesis, we develop a general model that takes into account the sharing of limited amounts of dCas9 protein for arbitrary CRISPR-mediated gene repression networks. We demonstrate that, as a result of resource competition, hidden interactions appear, which modifies the intended network regulations. As a case study, we analyze the effects of these hidden interactions on repression cascades. In particular, we illustrate that perfect adaptation to resource fluctuations can be achieved for certain network topology. Then, we analyze the stability properties of uncertain systems that are affected by resource competition via contraction analysis. Finally, we perform a combined analytical and experimental study on a two gRNA parallel network to demonstrate the resource competition effect.