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

摘要 PI建议研究质膜上自发性泛素（UB）货物聚集的作用， 使用模型膜重构的囊泡运输。囊泡运输是一个物质 通过膜结合细胞器之间的脂质囊泡运输。这个过程是一个非常基本的细胞 功能，因此参与了高等生物的大多数生命过程。然而，其分子机制是 仍然知之甚少。泛素化是UB的酶促附着，参与许多运输过程， 但通常，UB货物仅被认为是下游运输蛋白的被动结合剂。 货物的聚合泛素化及其与结合蛋白的多价相互作用在生活中非常普遍 导致细胞膜上自发形成蛋白质缩合物结构域。这些货物集群- 还已知ing结构域与脂筏结构域非常密切地相互作用。理解自发性 UB货物作为囊泡运输过程的积极空间组织者的聚集可以促进我们目前的研究。 通过深入了解传统上被忽视的作用，了解囊泡运输机制 在过程中的UB货物。本研究的主要方法是荧光显微镜（FM）和原子吸收光谱法。 力显微镜（AFM）。图像数据由深度学习辅助分析软件进行分析。的目标 （1）确定由蛋白质产生的UB货物簇的结构组织， 不同的结构;（2）了解UB簇组织的脂质组成依赖性。的PI 在此建议中，强调对货物聚集域形成的结构理解。FM是 用于具有不同蛋白质结构的许多样品的高通量成像，以了解结构 线索，导致集群域的形成。原子力显微镜是用来研究结构组织的集群在 在分子水平上获得直接的结构快照来测试假设模型。该提案将加强 蒙特克莱尔州立大学的研究环境，通过协同使用高灵敏度 大学最近获得的AFM仪器。此外，该提案将解决目前的高需求， 的本科生参加研究，同时准备他们提前到研究生课程， 与健康有关的科学。与GS-LSAMP计划合作，服务不足人口的学生将 积极招募。学生将获得实验技能，学习数据分析，并在 与该领域的科学家会面和交流。 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