Network and topological modelling of transition states in the Wnt signalling pathway.

要理解细胞内生物信号是如何传递的，以及它们支持的复杂决策过程，需要对单个信号通路及其在更广泛的信号网络中的作用有非常精确的了解。该项目将开发和适应最近开发的图论和拓扑工具，以揭示不同类型Wnt信号之间的复杂关系。Wnt信号是调控许多最基本的细胞过程的关键途径，如细胞扩增和增殖、细胞命运决定和细胞迁移。Wnt信号在许多疾病中失调，通常是肿瘤发展的驱动因素。已知两种相关类型的Wnt信号，规范和非规范，虽然这两种类型都使用许多相同的蛋白质成分，但它们的功能和活性可能非常不同。几项研究表明，规范和非规范Wnt信号之间存在复杂的相互关系，细胞和组织可以在这些模式之间切换（Florian等人，Nature, 2013； Upadhyay等人，PLoS Genetics, 2018； Ewing等人，J. Proteome Research, 2018）。在这个项目中，我们将通过重建实验观察（单细胞RNA-Seq和大量基因表达数据）的潜在动态来确定控制这两种Wnt信号传导模式之间转换的潜在机制。也就是说，我们的项目结合了网络建模和拓扑：我们将实验单细胞基因表达数据叠加在已知的调节相互作用网络上，以获得考虑到定向网络结构的距离度量，然后从这些距离重建潜在动力系统的拓扑结构。这将允许识别不同信号模式之间的过渡状态，并将它们优先用于实验/实验室研究。然后，我们将在结直肠癌（Ewing实验室）或造血干细胞（Morgan实验室）中使用特征良好的基于细胞的Wnt信号活性模型来测试和验证预测的潜在生物学机制。最终目标是对癌症中Wnt信号传导和不同模式的Wnt信号传导有一个基本的了解。虽然重点是Wnt信号，但我们希望这个博士项目的结果能广泛适用于其他生物信号网络。

Understanding how biological signals are communicated within cells and the complex decision making they support, requires a very precise knowledge of individual pathways and of their role in the wider signalling network. This project will develop and adapt recently developed graph theoretic and topological tools to unravel the complex relationships between different types of Wnt signalling. Wnt signalling is a key pathway that regulates many of the most fundamental cellular processes such as cell expansion and proliferation, cell fate decisions and cell migration. Wnt signalling is dysregulated in many diseases and is often a driver of tumour development. Two related types of Wnt signalling are known, canonical and non-canonical, and whilst both types use many of the same protein components, their functions and activity can be quitedistinct. Several studies have shown that there are complex interrelationships between canonical and noncanonical Wnt signalling , with cells and tissues switching between these modes (Florian et al, Nature, 2013; Upadhyay et al, PLoS Genetics, 2018; Ewing et al, J. Proteome Research, 2018). In this project, we will identify the underlying mechanisms controlling the transitions between these two modes of Wnt signalling by reconstructing the underlying dynamics from experimental observations (single-cell RNA-Seq and bulk gene-expression data). Namely, our project combines network modelling and topology: we superimpose experimental single-cell gene expression data on known regulatory interaction networks to obtain a distance measure that takes into account the directed network structure, and then reconstruct the topology of the underlying dynamical system from these distances. This will allow the identification of transition states between the different signalling modes and to prioritise them for experimental/laboratory study. We will then use wellcharacterized cell-based models of Wnt signalling activity in colorectal cancer (Ewing lab) or in haemopoietic stemcells (Morgan lab) to test and validate the predicted underlying biological mechanisms. The ultimate goal is to develop a fundamental understanding of Wnt signalling and of different modes of Wnt signalling in cancer. Although focused on Wnt signalling, we expect the results of this PhD project to be widely applicable to other biological signalling networks.