Collaborative Research: MODULUS: A synthetic biology approach to understanding environment sensing in multicellular systems

合作研究：MODULUS：一种理解多细胞系统环境感知的合成生物学方法

• 批准号: 1936761
• 负责人: Andrew Mugler
• 金额: $ 28.5万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1936761&HistoricalAwards=false
• 关键词: Collaborative; Research; MODULUS; synthetic; biology

The goal of this research is to determine how collections of cells, for example, a colony of bacterial cells forming a biofilm, coordinate their behaviors to accomplish goals that are impossible for isolated single cells alone. In particular, the project examines how cellular collectives cooperate to better sense the environment in an effort to determine the spatial location of important resources needed for survival. Computational and experimental methods are integrated in investigations that examine the genetic interactions involved in collective cell sensing. These investigations are used to produce models that advance the understanding of the nature of the cellular interactions. The models are then validated with experimental data. A better understanding of how cells cooperate will inform methods for the construction of synthetic multicellular systems that could be applied to biomanufacturing, environmental remediation or tissue formation for regenerative medicine. In addition to the scientific advances, this project provides societal benefits through curriculum development, the training of students ranging from middle-schoolers to postdoctoral researchers, and the public dissemination of science through mass media.A combination of mathematical modeling and experimental synthetic biology is used to overcome the challenges associated with studying native cell signaling pathways and provide more precise control over genetic and network components. Hypotheses are generated through analytically tractable mathematical models. The resulting predictions are tested on multicellular colonies with realistic, multi-scale agent-based computer models. Next, synthetic gene circuits that contain the proper inter- and intracellular regulatory mechanisms are constructed in Escherichia coli. These gene circuits are then examined experimentally for their collective phenotypes. Finally, the research team fits the mathematical models to the resulting data and validates their predictions on separate sets of experiments. This award was co-funded by the Systems and Synthetic Biology Program in the Division of Molecular and Cellular Biosciences and the Mathematical Biology Program in the Division of Mathematical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项研究的目的是确定细胞的收集（例如，形成生物膜的细菌细胞的菌落）如何协调其行为以实现单独孤立的单个细胞不可能的目标。特别是，该项目研究了蜂窝集体如何合作以更好地感知环境，以确定生存所需的重要资源的空间位置。计算方法和实验方法被整合到研究集体细胞传感所涉及的遗传相互作用的研究中。这些研究用于生成推动对细胞相互作用性质的理解的模型。然后使用实验数据验证模型。更好地了解细胞如何合作将为构建合成多细胞系统的方法提供信息，这些系统可以应用于生物制造，环境修复或组织形成以进行再生医学。除了科学的进步外，该项目还通过课程发展提供了社会利益，从中学生到博士后研究人员的培训以及通过大众媒体对科学进行公共传播。数学建模和实验合成生物学的组合用于克服与研究本地信号通道和网络控制相关的挑战，并提供了更精确的挑战，并且是研究了概括性的，并且是基因组合的。假设是通过可分析的数学模型生成的。在具有现实的，基于代理的计算机模型的多细胞菌落对产生的预测进行了测试。接下来，在大肠杆菌中构建了包含适当的细胞间调节机制的合成基因回路。 然后对这些基因回路进行实验检查，以了解其集体表型。最后，研究团队将数学模型符合结果数据，并在单独的一组实验集上验证他们的预测。该奖项是由系统和合成生物学计划在分子和细胞生物科学的部门和数学生物学计划中共同资助的，该奖项在数学科学划分中共同资助。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来通过评估来获得支持的。

项目成果

Signal processing capacity of the cellular sensory machinery regulates the accuracy of chemotaxis under complex cues.

• DOI: 10.1016/j.isci.2021.103242
• 发表时间: 2021-11-19
• 期刊: iScience
• 影响因子: 5.8
• 作者: Moon HR;Saha S;Mugler A;Han B
• 通讯作者: Han B

Precision of Flow Sensing by Self-Communicating Cells

自通信单元的流量传感精度

• DOI: 10.1103/physrevlett.124.168101
• 发表时间: 2020
• 期刊: Physical Review Letters
• 影响因子: 8.6
• 作者: Fancher, Sean;Vennettilli, Michael;Hilgert, Nicholas;Mugler, Andrew
• 通讯作者: Mugler, Andrew