In vivo metabolic labeling of photoreceptor proteins

项目摘要 视网膜通常被描述为中枢神经系统中相对简单的一部分。然而，它确实是 由大约100种不同的细胞类型组成，我们对什么知之甚少 在蛋白质水平上区分这些细胞类型。问题在于获得 仅限于特定细胞类型的蛋白质组数据是感兴趣的细胞类型必须是 与周围组织物理分离，然后才能提取蛋白质和 已确认身份。这样做的尝试总是会导致交叉污染。一种可能的解决方案是 由体内代谢标记或BONCAT提供。在这种方法中，非正则氨基酸 通过叠氮，官能团被结合到蛋白质中。叠氮化物然后用作标签， 可以标记为可视化或使用点击化学进行亲和纯化。在老鼠身上，这是可能的 限制蛋氨酸替代物氮杂环亮氨酸(ANL)的掺入，以选择细胞 类型。这是通过依赖于Cre的突变甲硫基- 酰基转移酶(MetRS*)，用ANL代替蛋氨酸给tRNA充电。因为只有蛋白质 当ANL存在时合成的将被标记，这提供了时间和空间 控制力。这个项目的目标是将这项技术应用于光感受器的研究，作为一种测试。 为未来的视网膜研究提供案例。在杆状或锥状细胞中表达Cre重组酶的小鼠将被 与MetRS*小鼠杂交。我们将验证这些新的小鼠品系，优化ANL传递， 并测试点击化学介导的蛋白质组数据收集的特异性和敏感性。我们 预计将这项技术应用于视网膜将为两种特定类型的细胞打开大门 蛋白质图谱和对疾病或各种反应的动态蛋白质变化的研究 环境刺激。

Project Summary The retina is often described as a relatively simple part of the central nervous system. Yet, it is composed of approximately 100 distinct cell types and we know very little about what differentiates these cell types from one another at the protein level. The problem with obtaining proteomic data restricted to a particular cell type is that the cell type of interest must be physically dissociated from its surrounding tissue before proteins can be extracted and identified. Attempts to do this invariably lead to cross contamination. A possible solution is offered by in vivo metabolic labeling, or BONCAT. In this approach non-canonical amino acids with azide functional groups are incorporated into protein. The azide then serves as a tag that can be labeled for visualization or affinity purification using click chemistry. In mice, it is possible to restrict the incorporation of the methionine surrogate, azidonorleucine (ANL), to select cell types. This is done through the Cre-dependent expression of a mutant methionyl- acyltransferase (MetRS*) that charges tRNA with ANL instead of methionine. Since only protein synthesized when ANL is present will be labeled, this provides both temporal and spatial control. The goal in this project is to adapt this technology to studies of photoreceptors as a test case for future retinal studies. Mice expressing Cre recombinase in either rods or cones will be crossed with MetRS* mice. We will validate these novel mouse lines, optimize ANL delivery, and test the specificity and sensitivity of click chemistry-mediated proteomic data collection. We expect that adapting this technology to the retina will open the door for both cell-type specific protein profiling and studies of dynamic protein changes in response to disease or various environmental stimulation.