Understanding the structural mechanism of spontaneous ubiquitin cargo clustering on the cell plasma membrane

摘要 PI建议研究自发性泛素(UB)在细胞膜上聚集的作用。 利用膜重构模型进行囊泡转运。泡囊运输是物质的一种过程 通过膜结合细胞器之间的脂泡运输。这个过程是非常基本的细胞过程之一 在高等生物体的大多数生命过程中起着重要作用。然而，其分子机制是 人们对此仍知之甚少。泛素化是UB的一种酶促连接，参与了许多转运过程， 但通常情况下，UB Cargo只被认为是下游运输蛋白的被动结合体。 在生活中，货物的聚合物泛素化及其与结合蛋白的多价相互作用是非常常见的 导致细胞膜上自发形成蛋白质凝聚结构域的细胞。这些货物集群- ING结构域也被认为与脂筏结构域相互作用非常紧密。理解自然而然 UB货物集群作为囊泡运输过程的积极空间组织者，可以促进我们目前的 通过洞察传统上被忽视的作用来理解囊泡运输机制 UB货物在这个过程中。本研究的主要方法是荧光显微镜(FM)和原子显微镜 力显微镜(AFM)。利用深度学习辅助分析软件对图像数据进行分析。目标 该建议的主要内容是：(1)鉴定由以下蛋白质产生的UB货物簇的结构组织 不同的结构；(2)了解UB簇组织的脂组成依赖关系。《少年派》 在本提案中，强调对货物集群域形成的结构性理解。调频是 用于许多具有不同蛋白质结构的样品的高通量成像，以了解结构 导致聚集域形成的线索。原子力显微镜被用来研究团簇的结构组织 在分子水平上获得直接的结构快照来测试假设模型。这项提议将增强 蒙特克莱尔州立大学的研究环境通过协同启用高敏感度 这所大学最近获得了AFM仪器。此外，该提案将解决目前的高需求 的本科生参与研究，同时为他们进入研究生课程做准备 与健康相关的科学。在GS-LSAMP计划的合作下，服务不足的学生将 要积极招募。学生需要获得实验技能，学习数据分析，并在 与该领域的科学家见面和交流的会议。 1

Abstract The PI proposes to study the role of spontaneous Ubiquitin (UB) cargo clustering on the plasma membranes in vesicular trafficking using the model membrane reconstitution. Vesicular trafficking is a process of material transport by lipid vesicles between membrane bound organelles. The process is one of the very basic cellular functions and thus is involved in most life processes of higher organisms. However, its molecular mechanism is still poorly understood. Ubiquitylation, an enzymatic attachment of UB, is involved in many trafficking processes, but canonically, UB cargo has been considered only as a passive binder to the downstream trafficking proteins. Polymeric ubiquitylation of cargos and their multivalent interaction with binder proteins are very common in living cells leading to spontaneous protein condensate domain formation on the cell membranes. These cargo cluster- ing domains are also known to very closely interact with lipid raft domains. Understanding the spontaneous clustering of UB cargo as an active spatial organizer of the vesicular trafficking process can advance our current understanding of the vesicular trafficking mechanism by providing insight into the traditionally overlooked roles of UB cargo in the process. The main methods of this investigation are fluorescence microscopy (FM) and atomic force microscopy (AFM). Image data are analyzed by the deep-learning-assisted analysis software. The goals of this proposal are: (1) Identifying the structural organization of UB cargo clusters created by proteins with different structures; (2) Understanding the lipid composition dependence of the UB cluster organization. The PI places an emphasis on structural understanding of the cargo clustering domain formation in this proposal. FM is used for high throughput imaging of many samples with different protein structures to understand the structural cues that lead to clustering domain formation. AFM is used to study the structural organization of the clusters at the molecular level to obtain direct structural snapshots to test hypothetical models. The proposal will enhance the research environment at Montclair State University by synergistically enabling the use of the high-sensitivity AFM instrument the university recently obtained. Moreover, the proposal will address the current high demand of undergraduate students to participate in research while preparing them to advance to graduate programs in health-related sciences. In collaboration with the GS-LSAMP program, students of underserved population will be actively recruited. Students are expected to acquire experimental skills, learn data analysis, and present in conferences to meet and communicates with scientists in the field. 1