Dissecting the effects of inhibitory signalling on T cell activation using optogenetics

使用光遗传学剖析抑制信号传导对 T 细胞激活的影响

• 批准号: 2269058
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2269058
• 关键词: Dissecting; effects; inhibitory; signalling; cell

Programme overview:This MRC-funded doctoral training partnership (DTP) brings together cutting-edge molecular and analytical sciences with innovative computational approaches in data analysis to enable students to address hypothesis-led biomedical research questions. This is a 4-year programme whose first year involves a series of taught modules and two laboratory-based research projects that lead to an MSc in Interdisciplinary Biomedical Research. The first two terms consist of a selection of taught modules that allow students to gain a solid grounding in multidisciplinary science. Students also attend a series of masterclasses led by academic and industry experts in areas of molecular, cellular and tissue dynamics, microbiology and infection, applied biomedical technologies and artificial intelligence and data science. During the third and summer terms students conduct two eleven-week research projects in labs of their choice.Project overview:T cells are an essential part of our immune system that eliminate infections to keep us healthy despite constant exposure to pathogens. T cells contain an intricate signalling network that decides whether the cells of our body have become infected, but sometimes this decision-making process is ineffective and leads to disease. Many current drugs are designed to manipulate these signalling pathways to improve the immune response to infection or cancer. Whilst great progress has been made in identifying the parts of these networks, we must also understand the dynamic connections between them to know how these therapies work and hopefully improve them. However, for most signalling networks this knowledge remains very limited. To address this, we develop new molecular tools to investigate the dynamics of the T cell signalling network by engineering inputs that are light-responsive, giving us precise control over signalling in space and time.In this project, we will explore the effect inhibitory receptors expressed by T cells have on the downstream output response. It has been suggested that these inhibitory receptors only control one part of the signalling network, but this result has been hard to verify. We will develop and implement new tools to investigate this hypothesis at the mechanistic level. The result has important consequences, as many of the 'checkpoint' inhibitors currently used for cancer immunotherapy target inhibitory receptors such as PD 1, so elucidating how they work is required to improve their clinical function.The PhD student undertaking this project will master an array of biochemical and cell-biological techniques required to investigate questions relevant to medical research using quantitative approaches. The student will also get an excellent grounding in the principles and application of dataset modelling using computational and mathematical approaches from the second supervisor, which will provide strong interdisciplinary skills-training.

项目概述：这个由 MRC 资助的博士培训合作伙伴关系 (DTP) 将尖端的分子和分析科学与数据分析中的创新计算方法结合在一起，使学生能够解决以假设为主导的生物医学研究问题。这是一个为期 4 年的课程，第一年涉及一系列教学模块和两个基于实验室的研究项目，最终获得跨学科生物医学研究硕士学位。前两个学期包括精选的教学模块，使学生能够在多学科科学方面打下坚实的基础。学生还参加由分子、细胞和组织动力学、微生物学和感染、应用生物医学技术以及人工智能和数据科学领域的学术和行业专家主持的一系列大师班。在第三学期和夏季学期，学生们在自己选择的实验室进行两个为期 11 周的研究项目。项目概述：T 细胞是我们免疫系统的重要组成部分，它可以消除感染，使我们在不断接触病原体的情况下保持健康。 T细胞包含一个复杂的信号网络，可以决定我们身体的细胞是否被感染，但有时这个决策过程是无效的并会导致疾病。目前许多药物旨在操纵这些信号通路，以改善对感染或癌症的免疫反应。虽然在识别这些网络的各个部分方面已经取得了巨大进展，但我们还必须了解它们之间的动态联系，以了解这些疗法如何发挥作用并有望改进它们。然而，对于大多数信令网络来说，这方面的知识仍然非常有限。为了解决这个问题，我们开发了新的分子工具，通过设计光响应输入来研究 T 细胞信号网络的动态，使我们能够精确控制空间和时间上的信号传导。在这个项目中，我们将探索 T 细胞表达的抑制性受体对下游输出响应的影响。有人认为这些抑制性受体仅控制信号网络的一部分，但这一结果很难验证。我们将开发和实施新的工具来从机械层面研究这一假设。这一结果具有重要的影响，因为目前用于癌症免疫治疗的许多“检查点”抑制剂都以PD 1等抑制性受体为目标，因此需要阐明它们的工作原理以改善其临床功能。承担该项目的博士生将掌握一系列使用定量方法研究与医学研究相关问题所需的生化和细胞生物学技术。学生还将通过第二位导师的计算和数学方法，在数据集建模的原理和应用方面获得良好的基础，这将提供强大的跨学科技能培训。