Exploiting an artificial APC to induce different T cell subsets

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 DESCRIPTION (provided by applicant): The human T cell compartment contains distinct T cell subsets that are very different in their capacity to persist and to respond after ex vivo expansion and adoptive transfer. T cell programming into distinct T cell subsets depends in a large extent on the quality and quantity of the signal delivered to T cells by professional antigen presenting cells (APC). This has stimulated efforts to develop artificial antigen presenting cells (aAPC) that allow for optimal control over the signals provided to T cells. To more closely mimic natural systems, lipid bilayer surfaces have been used as aAPCs, thereby demonstrating a significant effect of membrane fluidity on T cell activation. However, this and other membrane mimics, which have been exploited thus far, cannot be used to organize membrane proteins into microdomains, within which cell surface receptors are clustered. Major histocompatibility complex (MHC) proteins that present antigenic peptides on the surface of antigen- presenting cells (APC) form clusters with each other and with other cell surface proteins. The changes in MHC clustering and co-clustering could serve as a sensitive mechanism to modulate T cell responsiveness. The goal of the application is to develop the model membrane systems that can recapitulate clustering of immune receptors in a controlled manner. We propose to utilize biodegradable nanolipoprotein particles (NLPs) as a universal platform to mimic molecular membrane clustering. NLPs are self-assembled in solution to form discoidal nanostructures containing lipid bilayers stabilized at the perimeter by apolipoprotein molecules. The size of the NLP ranges from 8 to 30 nm that allow capturing up to 50 molecules of soluble ligands and enable us to achieve model cluster size and density close to physiological. We will use the NLPs to assemble pMHC and other membrane ligands into model membrane patches. We will study how changes in the ligands density and composition of these patches affect binding of the model membrane patches to live T cells and the kinetics and magnitude of TCR-mediated signaling. This will provide a basis for the engineering of aAPC bearing the model membrane patches incorporated into lipid bilayers covering the surface of glass beads. Such aAPCs will allow us to calibrate the strength of T cell stimulation. We will utilize these novel aAPCs to vary the strength of stimulation of naïve CD8+ T cells derived from OT-1 TCR transgenic mice in order to induce different subsets of activated T cells with the same specificity. Building of aAPCs is expected to enable us to expand T cells with instructional programs that allow T cells to persist, function, and migrate in a desired fashion after adoptive transfer. The experimental data will also provide the basis for building a mathematical model to characterize how clustering of ligands on an APC surface determines speed, sensitivity and discrimination of the pMHC I ligand by activated and naïve CD8 T cells.