BRING-SynBio: Autonomous dynamic genetic control circuits to refactor and optimize virus-like particle biomanufacturing

About This Grant

Viruses are effective at delivering DNA or RNA to cells. They protect the DNA or RNA inside a small capsule constructed of proteins. Replacing the DNA or RNA normally carried by these particles with therapeutic molecules makes them potential drug delivery candidates. The shapes of the proteins that create the capsule can be changed to increase the internal volume of the capsule or to fit together more loosely to allow small molecules to enter or exit the capsule. Or, the amino acids on the outer side of the capsule can be changed to alter the way they interact with different cell types. How the proteins self-assemble has not be studied extensively despite its importance for the capsule's use in drug delivery. The objective of this project is to understand how the cell produces and assembles these capsules. This project will also engage K-12 teachers and create and share teaching materials that integrates biology, biochemistry, engineering principles, and computational modeling. This goal of this project is the production of engineered virus-like particles (eVLPs). These are nanometer-scale particles that mimic the delivery properties of viruses but cannot replicate and are not infectious. The intention is to engineer eVLPs that contain mammalian genetic circuits capable of autonomous and programmable control of gene expression. Computation will guide design of individual biomolecules and genetic circuits. A primary emphasis is designing a system to dynamically direct the efficient self-assembly of eVLPs. In some ways, this approach borrows lessons from how natural viral systems have evolved to produce similar particles, but in this case the control system is focused on optimizing manufacturing (rather than viral replication). It will bring a new type of characterization to these important systems. This work will generate new genetic parts, biomanufacturing-ready cell lines, computational models, and conceptual frameworks enabling bioengineers to extend these approaches to investigate and optimize biomanufacturing of other complex biologics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.