Investigating small non-coding RNA as mediators of extracellular vesicle communication

细胞外囊泡（EV）曾经被认为是细胞卸载废物的一种方式，现在被认为是细胞分泌RNA，DNA和蛋白质的货物以重塑组织并充当信号载体的一种故意方式。这些有些被忽视的细胞器可能是理解我们体内组织和系统如何交流的关键，特别是在复杂疾病中。詹姆斯实验室领导通过RNA研究EV介导的通信，该项目将扩展我们在这一领域的工作。基于试验数据，该项目将寻求确定装载到囊泡中的不同类别的非编码RNA以及调节这种选择性装载过程的机制。上述目标将通过以下方式实现，利用两种疾病模型系统，癌症（前列腺）和骨关节炎来产生EV材料以与非疾病对照一起研究：1.使用来自该小组和合作者的现有数据集，记录EV中识别的RNA类型及其在疾病和非疾病背景下的丰度。这项工作可以在远离实验室的地方进行，也可以在当前的家庭工作期间进行。我们内部有数据集，并且已经确定了我们可以使用的公开数据。2.通过表征来自非疾病和疾病模型的EV中存在的不同非编码RNA类型来验证试验数据。针对定量PCR方法，选择该项目的学生已经完成了这一目标的要素，作为他们轮换的一部分）。3.确定与EV RNA的关键类别相关的蛋白质复合物，例如，存在核糖体RNA的地方是否也存在核糖体蛋白的完整互补物。亲和捕获技术将与蛋白质组学方法（靶向或非偏倚全局）合作。4.确定这些蛋白质复合物的操作是否改变RNA负载，以确定控制EV货物的潜在靶向方法。复合物内关键蛋白（和/或与复合物相关的蛋白）的过表达和消耗将用于确定对EV内不同类别RNA丰度的影响。我们正在寻找对整个RNA类别的影响，例如核糖体RNA或SnoRNA，而不是单个RNA，因此将寻找靶向主要蛋白质/途径。在该小组中，我们有经验和原理数据证明，通过耗尽miRNA相互作用复合物的成员来破坏miRNA加载到EV中。

Once thought to be little more than a way for cells to offload waste, extracellular vesicles (EVs) are now recognised to be a deliberate way for a cell to secrete cargos of RNA, DNA and proteins to reshape tissues and act as signal carriers. These somewhat overlooked organelles may hold the key to understanding how tissues and systems in our bodies communicate, particularly within complex diseases. The James lab lead in the study of EV mediated communication via RNAs and this project will expand upon our work in this area. Based on pilot data, the project will seek to determine the different categories of non-coding RNA loaded into vesicles and the mechanisms that regulate this selective loading process. The above aims will be achieved though the following, utilising two disease models systems, cancer (prostate) and osteoarthritis to produce EV materials to study alongside non-disease controls: 1. Use existing datasets from the group and collaborators to document the RNA types identified in EVs and their abundance in disease and non-disease contexts. This work can be carried out away from the labs and during the current period of home-working. We have data sets in house and have already identified publicly available data which we can work with. 2. Validate our pilot data by characterising the different non-coding RNA types present in EVs from both non-disease and disease models. Focused quantitative PCR approach, the student selected for the project has already completed elements of this aim as part of their rotation). 3. Determine the protein complexes associated with key classes of EV RNA e.g. where ribosomal RNAs are present is the full complement of ribosomal proteins also present. Affinity capture techniques will be teamed with proteomics approaches (either targeted or non-biased global). 4. Identify if manipulation of these protein complexes alters RNA loading to determine a potential targetable means of controlling EV cargos. Over-expression and depletion of key proteins within the complexes (and/or proteins associated with the complex) will be used to determine the impact on the abundance of different classes of RNA within EVs. We are looking to identify effects on entire classes of RNA e.g. ribosomal RNA or SnoRNAs rather than an individual RNA, so will be looking to target major proteins/pathways. Within the group we have experience and proof of principle data by depleting members of the miRNA interaction complexes to disrupt miRNA loading into EVs.