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人工合成多细胞斑图
Synthetic pattern formation

Views:722       Publish Time: 2022-06-05


      斑图形成指的是系统形成空间有序结构的过程,在生物界广泛存在,对于生物体生长发育、形态建成、生态系统稳定性等有着重要意义。理解生物斑图形成的原理是生命科学的基本问题之一,也是构建具有有序空间结构的生命体系的重要基础。

      用传统生物学研究方法研究自然系统中的斑图形成有很大的局限,原因在于这一现象涉及因素极其繁多,从基因到表型涉及的生理生化过程极其复杂,难以对单一因素进行控制从而验证假说。用合成生物学方法重构生物斑图提供了简化、控制斑图系统的可能性,是研究斑图形成的重要手段与研究范式,也是合成生物学的经典领域,并为未来构造形态结构可控的生物材料、人工组织器官提供了可能性。

      本研究方向将建立数学模型,系统研究斑图形成所依赖的拓扑结构,设计基因线路,构建基因线路与菌株。本项目的完成将阐明细菌空间扩张过程中斑图的产生机制,揭示生物斑图的设计原理。


Pattern formation refers to the generation of regular and complex spatial structures. Patterns are ubiquitous in the biological world and play essential roles in the development of organisms and ecosystems. How biosystems develop patterns autonomously is one of the fundamental questions in life science, and understanding the principle of pattern formation provides the foundation for engineering living systems with desired spatial structures.


Because of the extreme complexity and myriads of physiological/biochemical factors involved in pattern formation, it is often difficult to perturb or control a single factor in natural systems. Therefore, there is a great limitation to study pattern formation by conventional methods. Reconstructing biological patterns with synthetic biology allows us to simplify and control the systems, providing a new tool and research paradigm for studying pattern formation, which is one of the classical fields in synthetic biology. The design and construction of biosystems with spatial patterns also provides the possibility of synthetic biomaterials, tissues, and organs with controllable spatial structures.


The aim of this project is to elucidate the design principle of pattern formation. In this project, we will develop mathematical models to systematically investigate the system topologies that allow pattern formation during the range expansion of bacteria. Based on the quantitative predictions of modeling, we will design gene circuits and engineer synthetic bacterial strains. 




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合成生物学中的细菌细胞周期
Understanding bacterial cell cycle using synthetic biology