COMBO: CONTROL-BASED BIODESIGN OF MAMMALIAN CELL DYNAMICS

系统生物学家通过将细胞生物学与数学方法相结合，已经表明分子调节网络中的反馈回路严格控制细胞内稳态和反应。内源性反馈和细胞外环境之间的相互作用导致复杂和非线性的细胞动力学。数学模型可以帮助解决这种复杂性，帮助描述细胞动力学和细胞决策之间的联系。然而，模型的有效性依赖于建模假设和用于参数拟合的数据质量：随机性和噪声限制了系统生物学和系统药理学应用中模型预测的能力。相反，合成生物学家经常使用的概括天然细胞行为的外源基因表达动力学的正向工程受到物理参数变化、不同模块化部分和底盘选择的鲁棒性差的限制。为了应对这些挑战，该奖学金提出直接和自动编程哺乳动物细胞中的复杂动力学，通过结合外部反馈控制来确保鲁棒性和微流体/显微镜平台来实时观察和扰动细胞。利用这项技术将能够：i）解开耦合过程中的因果关系，并剖析跨尺度的时间模式（即基因表达动力学和细胞周期）在干细胞命运中的作用，最终利用这种动力学来设计上级干细胞培养方案。ii）从实验中直接跟踪非线性生化动力学，而不需要数学模型，以分别使用实验和基于控制的连续定量确定复杂的天然/工程行为的原因/鲁棒性。将探索直接的工业应用，包括跨培养规模的干细胞培养方案的表征，以及使用反馈控制来设计针对靶向癌细胞反应的最佳药物给药方案。我们的目标是在跨学科学科的界面上通过两个高度协同的研究轨道来支撑。从控制理论，合成，系统和干细胞生物学的方法的组合将提供一个定量的框架和高度新颖的工具来理解，引导和设计哺乳动物细胞的动态表型，具有巨大的潜力，为未来的治疗目的。

Systems Biologists, by combining cell biology with mathematical approaches, have shown that feedback loops in molecular regulatory networks tightly control cellular homeostasis and responses. The interplay between endogenous feedbacks and the extracellular environment results in complex and non-linear cellular dynamics. Mathematical models can help in tackling this complexity, aiding in characterising the links between cellular dynamics and cell-decision making. However, the validity of models relies on modelling assumptions and the quality of data used for parameter fitting: stochasticity and noise limit the power of model predictions across Systems Biology and Systems Pharmacology applications. Conversely, the forward engineering of exogenous gene expression dynamics that recapitulate native cellular behaviours, often used by Synthetic Biologists, is limited by poor robustness to physical parameter variations, diverse modular parts and choice of chassis. To tackle these challenges, this Fellowship proposes to directly and automatically program complex dynamics in mammalian cells, by combining external feedback control to ensure robustness and a microfluidics/microscopy platform to observe and perturb cells in real-time. Exploitation of this technology will allow to:i) Unravel causation in coupled processes and dissect the role that temporal patterns across scales (i.e. gene expression dynamics and cell-cycle) play in stem cell fate, ultimately exploiting such dynamics for the design of superior stem cell culture protocols.ii) Directly track from experiments non-linear biochemical dynamics, without the need of mathematical models, to quantitatively determine causes/robustness of complex native/engineered behaviours, respectively, using experimental and Control-Based Continuation.Direct industrial applications will be explored, including the characterisation of stem cell culture protocols across culture scales, and the use of feedback control to design optimal drug dosing schedules for target cancer cell responses.Our aims are underpinned by two highly synergetic research tracks at the interface of interdisciplinary disciplines. The combination of methodologies from control theory, Synthetic, Systems and Stem cell biology will provide a quantitative framework and highly novel tools to understand, steer and design mammalian cell dynamic phenotypes, with great potential for future therapeutic purposes.