An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

Ross D. Jones, Yili Qian, Velia Siciliano, Breanna DiAndreth, Jin Huh, Ron Weiss () and Domitilla Del Vecchio ()
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Ross D. Jones: Massachusetts Institute of Technology
Yili Qian: Massachusetts Institute of Technology
Velia Siciliano: Massachusetts Institute of Technology
Breanna DiAndreth: Massachusetts Institute of Technology
Jin Huh: Massachusetts Institute of Technology
Ron Weiss: Massachusetts Institute of Technology
Domitilla Del Vecchio: Massachusetts Institute of Technology

Nature Communications, 2020, vol. 11, issue 1, 1-16

Abstract: Abstract Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device’s output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

Date: 2020
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DOI: 10.1038/s41467-020-19126-9

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