15 NSFBIO: Causal modeling of T cell signaling in time and space

15 NSFBIO：T 细胞信号传导在时间和空间上的因果模型

基本信息

批准号：
BB/P011578/1
负责人：
Christoph Weulfing
金额：
$ 44.4万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2016
资助国家：
英国
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=BB%2FP011578%2F1
关键词：
15 NSFBIO Causal modeling cell

项目摘要

A great challenge in biomedical research is to understand how the regulation of cellular activation occurs in the interaction of dozens of signalling components. As most current research only addresses single components of signalling systems, new strategies to address entire signalling systems are required. With the dual objective to further develop methods for the investigation of complex signalling systems and to gain biological insight we study signal amplification in T cell activation by CD28. To explain what that means: T cells or T lymphocytes are central regulatory cells in the immune system. Their activation is critical in immune responses to pathogens, in cancer, and in autoimmune disease. For their activation they require two inputs. The first signal directly communicates the presence of a pathogen; the second signal, costimulation by CD28, communicates that other components of the immune system have recognised the same pathogen. Costimulation then amplifies the intracellular signalling processes triggered by the first signal. However, it remains unknown how this amplification is accomplished.Signal amplification, similar to many other signalling processes, is of great complexity, as many proteins need to collaborate. A critical component of such complexity is that proteins are rarely evenly distributed throughout cells but enrich at particular subcellular locations at particular times, thus generating complex spatiotemporal distributions. Co-enrichment of two proteins enhances their interaction efficiency. At the scale of many signalling proteins of a cell, spatiotemporal distributions thus determine how information flows through signalling networks in time and space thus regulating cellular function. Microscopy can determine the subcellular distributions of signalling proteins in live cells over time, a process referred to as imaging. Only when applied at a large scale as we uniquely do, imaging can capture the information flow across complex signalling systems as an efficient and unique means to understand the regulation of cellular function. To understand how CD28 amplifies T cell signalling, we will image signalling in T cells lacking CD28 engagement. As the imaging data thus acquired contains very large amounts of data, computational image analysis approaches are required. We develop such approaches collaboratively. Our work is part of a NSF/BBSRC US/UK binational pilot programme. Our US partner, the Murphy laboratory at Carnegie Mellon University, is supported by the NSF to develop advanced computational image analysis approaches for the imaging data we acquire. In combination large-scale imaging and computational image analysis are expected to reveal the mechanisms used by T cells to amplify signalling. Importantly, our strategy will be generally applicable to the analysis of complex signalling systems and thus can be transferred to the analysis of cellular activation in many other physiologically important settings. In addition, as signal amplification is wide spread, we also expect that data gained in T cells will inform mechanisms of signal amplification in other cell types.Understanding T cell signal amplification is also of medical interest. T cells are of great medical importance, particularly in autoimmune diseases and the immune response to cancer. In collaboration with groups at the University of Bristol and outside in academia and industry, we have begun to explore the role of signalling organisation in the autoimmune disease multiple sclerosis and its therapy and in primary immunodeficiency. Methods and data generated here will be transferred to these projects in the future.

生物医学研究的一个巨大挑战是了解细胞激活的调节如何在数十种信号成分的相互作用中发生。由于当前大多数研究仅涉及信号系统的单个组件，因此需要解决整个信号系统的新策略。出于进一步开发研究复杂信号系统的方法和获得生物学见解的双重目标，我们研究了 CD28 激活 T 细胞的信号放大。解释一下这意味着什么：T 细胞或 T 淋巴细胞是免疫系统中的中央调节细胞。它们的激活对于病原体的免疫反应、癌症和自身免疫性疾病至关重要。为了激活它们，它们需要两个输入。第一个信号直接传达病原体的存在；第二个信号是 CD28 的共刺激，表明免疫系统的其他组成部分已识别出相同的病原体。然后，共刺激会放大由第一个信号触发的细胞内信号传导过程。然而，这种放大是如何完成的仍然未知。信号放大与许多其他信号传导过程类似，非常复杂，因为许多蛋白质需要协作。这种复杂性的一个关键组成部分是蛋白质很少均匀分布在整个细胞中，而是在特定时间富集在特定的亚细胞位置，从而产生复杂的时空分布。两种蛋白质的共富集提高了它们的相互作用效率。因此，在细胞的许多信号蛋白的尺度上，时空分布决定了信息如何在时间和空间上流过信号网络，从而调节细胞功能。显微镜可以确定活细胞中信号蛋白随时间的亚细胞分布，这一过程称为成像。只有像我们独特的那样大规模应用时，成像才能捕获复杂信号系统中的信息流，作为了解细胞功能调节的有效而独特的手段。为了了解 CD28 如何放大 T 细胞信号传导，我们将对缺乏 CD28 参与的 T 细胞中的信号传导进行成像。由于由此获取的成像数据包含非常大量的数据，因此需要计算图像分析方法。我们合作开发此类方法。我们的工作是 NSF/BBSRC 美国/英国两国试点计划的一部分。我们的美国合作伙伴卡内基梅隆大学墨菲实验室在 NSF 的支持下为我们获取的成像数据开发先进的计算图像分析方法。大规模成像和计算图像分析相结合有望揭示 T 细胞放大信号传导的机制。重要的是，我们的策略将普遍适用于复杂信号系统的分析，因此可以转移到许多其他重要生理环境中的细胞激活分析。此外，随着信号放大的广泛传播，我们还期望在 T 细胞中获得的数据将为其他细胞类型中的信号放大机制提供信息。了解 T 细胞信号放大也具有医学意义。 T 细胞具有重要的医学意义，特别是在自身免疫性疾病和癌症免疫反应中。我们与布里斯托大学以及学术界和工业界以外的团体合作，开始探索信号传导组织在自身免疫性疾病多发性硬化症及其治疗以及原发性免疫缺陷中的作用。这里生成的方法和数据将来将转移到这些项目中。