Exploiting an artificial APC to induce different T cell subsets

 描述(由申请人提供)：人类T细胞亚群包含不同的T细胞亚群，在体外扩增和收养转移后，它们的持续和反应能力非常不同。T细胞编程为不同的T细胞亚群在很大程度上取决于专业抗原传递给T细胞的信号的质量和数量 递呈细胞(APC)。这刺激了开发人工抗原提呈细胞(AAPC)的努力，这种细胞允许对提供给T细胞的信号进行最佳控制。为了更好地模拟自然系统，脂质双层表面被用作aAPC，从而展示了膜流动性对T细胞激活的显著影响。然而，到目前为止已经开发的这种膜模拟物和其他膜模拟物不能用来将膜蛋白组织成微域，在微域内细胞表面受体聚集。主要组织相容性复合体(MHC)蛋白在抗原提呈细胞(APC)表面呈递抗原肽，彼此之间以及与其他细胞表面蛋白形成簇。MHC聚集性和共聚集性的变化可能是调节T细胞反应性的敏感机制。该应用程序的目标是开发能够以受控方式概括免疫受体聚集的模型膜系统。我们建议利用可生物降解的纳米脂蛋白颗粒(NLP)作为模拟分子膜聚集的通用平台。NLP在溶液中自组装形成盘状纳米结构，其中包含由载脂蛋白分子稳定在周长的脂双层。NLP的尺寸范围从8到30 nm，允许捕获多达50个可溶性配体分子，并使我们能够获得接近生理的模型簇大小和密度。我们将使用NLP将pMHC和其他膜配体组装成模型膜贴片。我们将研究这些补片的配体密度和组成的变化如何影响模型膜补片与活T细胞的结合，以及TCR介导的信号的动力学和大小。这将为AAPC的工程应用提供基础，将模型膜贴片结合到覆盖在玻璃微珠表面的脂质双层中。这样的aAPC将使我们能够校准T细胞刺激的强度。我们将利用这些新颖的aAPC来改变 对来自OT-1TCR转基因小鼠的幼稚CD8+T细胞的刺激强度，以诱导具有相同特异性的不同亚群的活化T细胞。AAPC的建设 有望使我们能够通过教学计划来扩大T细胞，允许T细胞在领养转移后以所需的方式持续、功能和迁移。这些实验数据还将为建立数学模型提供基础，以表征APC表面配体的聚集如何通过激活和幼稚的CD8T细胞决定pMHC I配体的速度、灵敏度和识别能力。

 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.