Quantitative control of phosphorylation and mechanistic links to immune cell decisions

摘要 细胞通过生物化学信号通路整合不同的刺激，以诱导适当的转录， 程序.在这些信号传导到转录的网络中，快速添加和去除翻译后的 这些修饰影响转录因子（TF）的活性和特异性，以告知所得的细胞功能。 了解细胞外信号如何与基因表达相联系是生物学中的一个基本挑战。 生物学现有的信号传导到转录的努力通常在范围上受到限制，描述信号传导事件， 细节与转录的见解很少，或专注于一些静态信号功能，同时解决更多 全面的基因组问题。我的实验室正在解决这个问题的背景下，信号传感器 和转录激活因子（STAT），转录因子的一个家族，其整合复杂的细胞因子刺激以告知一系列的 从促炎到抗炎的免疫程序。我们提出了数据驱动和机械建模 整合TF动力学、全局磷酸化和转录组学数据的方法，以1）探索信号传导 形成刺激特异性STAT磷酸化动力学和依赖于这些的功能的机制 动力学，和2）系统地识别磷酸化事件和STAT合作TF，预测特定的 基因组这些将动态信号传导与基因表达谱联系起来的努力是朝着识别和 操纵健康与病理相关基因表达所需的生化事件。

ABSTRACT Cells integrate distinct stimuli through biochemical signaling pathways to induce the appropriate transcriptional programs. In these signaling-to-transcription networks, the rapid addition and removal of post-translational modifications impact the activity and specificity of transcription factors (TFs) to inform resultant cellular function. Understanding how extracellular cues are linked to gene expression is a fundamental challenge in biology. Existing signaling-to-transcription efforts are often constrained in scope, describing signaling events in detail with little transcriptional insights, or focusing on a few static signaling features while addressing more comprehensive genomic questions. My laboratory is addressing this problem in the context of signal transducers and activators of transcription (STATs), a family of TFs that integrate complex cytokine stimuli to inform a range of pro- to anti-inflammatory immune programs. We propose both data-driven and mechanistic modeling approaches to integrate TF dynamics, global phosphorylation, and transcriptomic data to 1) explore signaling mechanisms that shape stimulus-specific STAT phosphorylation dynamics and functions dependent on these dynamics, and 2) systematically identify phosphorylation events and STAT-cooperating TFs that predict specific gene sets. These efforts to link dynamic signaling to gene expression profiles are a step towards identifying and manipulating the biochemical events required for healthy versus pathology-associated gene expression.