Optically Gated Discovery of Protein-Biomolecule Interactions

GERI实验室研究的总体目标是使用发现技术绘制蛋白质相互作用图 在时空分辨率方面比目前最先进的水平提高了数量级。这个 这项工作的动机是提高蛋白质相互作用组发现技术的分辨率 里程碑，如单细胞和单蛋白阈值，将产生类似于类似的全领域影响 转录学和显微技术的进展。实验室的前三年工作将专注于创造 通过结合光催化邻近标记的新技术，其中光动力催化剂附着在 亲和手柄驱动合成亲和探针与附近蛋白质的交联，利用图案化的光和 相互作用门控激活，以同时实施多个方面的特异性。第四次和第五次 多年的工作将集中在应用成熟的技术上。总体战略分为两个阶段， 其中通过外部光学控制或内部化学控制获得标记特异性，并且具有 通过最大限度地减少项目之间的相互依赖，设计成在编程上具有健壮性。本质上有选择性 系统将利用光催化标记(5 Nm)的高空间分辨率，并使用可 当确定的蛋白质靶点接近时进行操作。最初的工作将使用自然表达的孤儿多肽作为 邻近标记基因座以发现其目前未知的受体。这项工作将涵盖数千种多肽 通过使用无标记离子迁移率质谱学进行蛋白质组学，最大限度地利用优化的 标记探头设计。分离系统将结合针对不同感兴趣蛋白质的多个光催化剂 使共定位成为一种特异性的维度，并将最初应用于定位存在于膜上的蛋白质 交汇点。外部控制系统将在人体组织切片中实现亚细胞分辨率标记 以及用于研究瞬时蛋白质相互作用的毫秒分辨率时间控制。两种方法都已启用 通过将光本身的时空控制的光学工具与总的和瞬时的响应相结合 (&lt；1 S)光催化效率和当地光供应之间的依赖关系，两者都允许三 与目前的工具相比，分辨率提高了数量级。空间选择性标记将侧重于识别 人类组织中细胞亚群特有的蛋白质相互作用，最初的研究重点是发现 人体扁桃体和胸腺中驱动淋巴细胞功能的位置条件相互作用。以后的研究将集中在 关于发现翻译相关组织样本之间的相互作用组差异。暂时解决 标记将结合光遗传工具和光催化邻近标记来同步和询问 瞬时蛋白质相互作用。这种方法的力量将通过研究神经元的胞吐作用而得到充分利用。 以毫秒的分辨率，这是已知最快的动态生物过程之一。成功的开发和 这些发现蛋白质相互作用的系统的部署将使研究大的相互作用组空间成为可能 这是第一次，预计将对分子生物界产生广泛的影响。

The overall goal of research in the Geri lab is to map protein interactomes using discovery technologies that provide orders of magnitude improvements in spatiotemporal resolution over the current state-of-the-art. The motivation for this work is that advancing the resolution of protein interactome discovery technology beyond key milestones, such as single cell and single protein thresholds, will have a field-wide impact analogous to similar advances in transcriptomics and microscopy. The first three years of work in the lab will be focused on creating new technologies by combining photocatalytic proximity labeling, in which light-powered catalysts attached to an affinity handle drive the crosslinking of synthetic affinity probes with nearby proteins, with patterned light and interaction-gated activation to simultaneously enforce multiple dimensions of specificity. The fourth and fifth years of work will focus on applying the mature technologies. The overall strategy is divided along two thrusts, in which labeling specificity is obtained through extrinsic optical control or intrinsic chemical control, and has been designed to be programmatically robust by minimizing project interdependency. Intrinsically selective systems will exploit the high spatial resolution of photocatalytic labeling (5 nm) and use “split” systems that operate when defined protein targets are in proximity. Initial work will use natively expressed orphan peptides as proximity labeling loci to discover their currently unknown receptors. The effort will cover thousands of peptides by using label free ion mobility mass spectrometry for proteomics, maximally leveraged by using optimized labeling probe designs. Split systems will combine multiple photocatalysts targeted to different proteins of interest to make colocalization a dimension of specificity, and will be initially applied to map proteins present at membrane junctions. Extrinsically controlled systems will enable subcellular resolution labeling in human tissue sections and ms-resolution temporal control for the study of transient protein interactions. Both approaches are enabled by combining optical tools for spatiotemporal control of light itself with the total and instantaneously responsive (<1µs) dependence between photocatalytic efficiency and the local supply of light, and each allow for a three order of magnitude increase in resolution vs current tools. Spatially selective labeling will focus on identifying protein interactions unique to cell subpopulations in human tissues, with initial studies focusing on discovering location-conditional interactions driving lymphocyte function in human tonsil and thymus. Later studies will focus on discovering interactome differences between translationally relevant tissue samples. Temporally resolved labeling will combine optogenetic tools and photocatalytic proximity labeling to synchronize and interrogate transient protein interactions. The power of this approach will be fully exploited by studying exocytosis in neurons with millisecond resolution, one of the fastest dynamic biological processes known. Successful development and deployment of these systems for protein interaction discovery will enable the study of large interactome spaces for the first time, and is expected to have a broad impact on the molecular biology community.