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

这项研究的目标是确定细胞集合，例如形成生物膜的一群细菌细胞，如何协调它们的行为，以实现仅靠分离的单个细胞不可能实现的目标。特别是，该项目研究了细胞集体如何合作以更好地感知环境，以努力确定生存所需的重要资源的空间位置。计算和实验方法在研究集体细胞感知中涉及的遗传相互作用的研究中被整合。这些研究被用来产生模型，以促进对细胞相互作用本质的理解。然后用实验数据对模型进行了验证。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，这些系统可应用于生物制造、环境修复或再生医学的组织形成。除了科学进步，该项目还通过课程开发、培训从中学生到博士后研究人员的学生以及通过大众媒体公开传播科学来提供社会效益。该项目结合数学建模和实验合成生物学，以克服与研究天然细胞信号通路相关的挑战，并对遗传和网络组件提供更精确的控制。假设是通过易于分析的数学模型产生的。由此产生的预测在多细胞集落上用现实的、基于代理的计算机模型进行了测试。接下来，在大肠杆菌中构建包含适当的细胞间和细胞内调节机制的合成基因电路。然后对这些基因回路进行实验检查，以确定它们的集体表型。最后，研究小组将数学模型与结果数据进行匹配，并在不同的实验集上验证他们的预测。该奖项由分子和细胞生物科学部的系统和合成生物学计划和数学科学部的数学生物学计划共同资助。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

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.