With this project, we aim to develop a selectively permeable synthetic cell for degradation of nerve agents. Nerve agent degrading enzymes are promising methods for treating contaminated environments but have proven sensitive to solvents and heat. Synthetic cells with controlled partitioning and organization offer features that would enable the use of these enzymes in the field. Here, we propose protecting nerve agent degrading enzymes in two ways: encapsulating within protein shells (eg bacterial microcompartments or virus-like particles) within the lipid droplets, or directly partitioning these enzymes into the lipid droplets. As a model, organophosphate hydroloase and diisopropyl-fluorophosphatase will be used. The first produces a charged dialkyl phosphate product, while the other release a toxic fluorine atom, allowing us to also probe the benefits of encapsulation and controlled sequestration in synthetic cell-like systems. In the first aim, we will determine whether protein assemblies can be entrapped in lipid droplets, with functional enzyme inside. We will also directly entrap the enzymes as part of this aim. The stability and function of the enzymes will be tested in both cases, and compared to enzyme in standard buffers. We anticipate a large increase in thermostability for encapsulated and enmeshed enzyme, and expect to maintain higher activity in the protein-encapsulated form. In the second aim, we will decorate the established lipid droplets using proteins that self-assemble into hexamers with a selectively permeable pore, in order to further control the transport into and out of these droplets. We have several variants in MS2 coat protein with demonstrated distinct permeabilities, and can use the droplet system to directly quantify diffusion across these pores to identify those best suited for sequestration of fluorine or release of phosphate.
|Effective start/end date||6/1/20 → 11/30/22|
- University of California, San Diego (703559//W911NF-13-1-0383)
- Army Research Office (703559//W911NF-13-1-0383)
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