Developing a DNA based synthetic cytoskeleton

细胞的质膜机械特性被认为在疟疾、动脉粥样硬化和癌症等多种疾病中发挥着关键作用。细胞膜的力学行为不仅取决于脂质双层的组成，还取决于无数其他膜锚定的细胞元件，包括膜蛋白和细胞骨架，然而，通过细胞骨架组装来模仿生物学的精细膜机械控制在合成组装中仍然是难以实现的。自下而上合成生物学的这一缺陷限制了我们探索支撑膜行为和应激反应的分子相互作用的能力，例如渗透压或剪切流，并限制了自下而上合成生物学方法在环境修复和工业加工等恶劣环境中的应用。在本项目中，我们将开发使用合成DNA纳米结构构建模型脂质膜的方法，其可以聚合形成支撑支架。使用这些定制设计的DNA结构，其大小，相互作用和刚度可以精细控制，我们将能够调整膜的刚性和粘度，以及对环境因素（例如温度，pH值，酶活性）的响应。我们将通过独特的内部合成的粘度敏感的荧光探针（分子转子）以及其他技术，如膜的热波动的傅立叶分析和微量吸管抽吸来表征DNA支架对膜的机械性能的影响。这个高度多学科的项目将提供软物质科学的实验培训。膜生物物理学、DNA纳米技术、荧光光谱学和显微镜、快速原型制作方法、自动化和机器学习将构成该项目的主要支柱。

The cell's plasma membrane mechanical properties are thought to play a key role in a wide range of diseases, including malaria, atherosclerosis and cancer. The mechanical behaviour of cellular-membranes is not only determined by the composition of the lipid bilayer, but also by a myriad of other membrane-anchored cellular elements, including membrane proteins and the cytoskeleton.However, mimicking biology's exquisite membrane mechanical control via cytoskeleton assembly remains elusive in synthetic assemblies. This shortcoming in bottom-up synthetic biology limits our ability to probe the molecular interactions that underpin membrane behaviour and responses under stress, such as osmotic pressure or shear flow, and constricts the application of bottom-up synthetic biology approaches in harsh environments such as environmental remediation and industrial processing.In this project, we will develop methods to build model lipid membranes with synthetic DNA-nanostructures, which can be polymerized to form a supporting scaffold. Using these custom-designed DNA architectures, whose size, interactions, and stiffness can be finely controlled, we will be able to tune membrane rigidity and viscosity, as well as enabling response to environmental cues (e.g. temperature, pH, enzymatic activity). We will characterize the effect of the DNA scaffolds on the membrane's mechanical properties by unique in-house synthesized viscosity-sensitive fluorescent probes (molecular rotors) together with other techniques such as the Fourier analysis of membrane's thermal fluctuations and micropipette aspiration.This highly multidisciplinary project will provide experimental training in soft matter science. membrane biophysics, DNA nanotechnology, fluorescence spectroscopy and microscopy, and rapid prototyping approaches, automation and machine learning will form key pillars of the project.