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

生物医学研究的一个巨大挑战是了解细胞活化的调控是如何在几十种信号成分的相互作用中发生的。由于目前大多数研究只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。为了进一步开发研究复杂信号系统的方法和获得生物学见解，我们研究了CD28在T细胞活化中的信号放大。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枢调节细胞。它们的激活对病原体、癌症和自身免疫性疾病的免疫反应至关重要。激活它们需要两个输入。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，它传达了免疫系统的其他成分已经识别了相同的病原体。然后，共刺激放大了由第一个信号触发的细胞内信号过程。然而，目前尚不清楚这种放大是如何完成的。信号放大，类似于许多其他信号过程，是非常复杂的，因为许多蛋白质需要合作。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，而是在特定的亚细胞位置在特定的时间富集，从而产生复杂的时空分布。两种蛋白的共富集提高了它们的相互作用效率。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通过信号网络流动，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，这一过程被称为成像。只有像我们所做的那样大规模应用时，成像才能捕获复杂信号系统之间的信息流，作为理解细胞功能调节的有效和独特手段。为了理解CD28如何放大T细胞信号，我们将在缺乏CD28参与的T细胞中成像信号。由于这样获得的成像数据包含非常大的数据量，因此需要使用计算图像分析方法。我们合作开发这些方法。我们的工作是NSF/BBSRC美英双边试点项目的一部分。我们的美国合作伙伴卡内基梅隆大学的墨菲实验室得到了美国国家科学基金会的支持，为我们获得的成像数据开发先进的计算图像分析方法。结合大规模成像和计算图像分析有望揭示T细胞放大信号的机制。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，由于信号放大广泛存在，我们还期望在T细胞中获得的数据将为其他细胞类型的信号放大机制提供信息。理解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对癌症的免疫反应中。通过与布里斯托尔大学以及学术界和工业界的合作，我们已经开始探索信号组织在自身免疫性疾病多发性硬化症及其治疗和原发性免疫缺陷中的作用。这里产生的方法和数据将在未来被转移到这些项目中。

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.