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Developing a DNA based synthetic cytoskeleton

Developing a DNA based synthetic cytoskeleton
开发基于 DNA 的合成细胞骨架
批准号:
2596649
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

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英文摘要
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.
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