Collaborative Research: Mechanisms of Multicellular Self-Organization in Myxococcus Xanthus

该项目由实验微生物学家、计算生物学家和数学家组成的合作团队参与，旨在了解土壤细菌黄粘球菌（Myxococcus xanthus）在饥饿状态下聚集成多细胞土堆的机制。利用数学和生物学方法，该团队将揭示控制发育自组织不同阶段的相互作用：(1)预聚集细胞排列和细胞流的形成；(2)初始团聚体的形成和生长；(3)聚集体粗化、分散和脉动。该项目有望阐明其他生物中运动细胞集体行为背后的一些一般机制，并开发广泛适用的数学方法。从单细胞到多细胞的转变对于增加对许多致病菌的了解和阐明更复杂系统中的自组织是至关重要的。尽管单个细菌细胞被认为是独立和自主的，但许多细菌群体将集体行动，交流，移动和自组织成多细胞结构。黄原草是研究生物自组织的一个很好的模型系统：它的细胞单独运作良好，但根据环境条件合作形成各种不同的动态模式。然而，这些行为的机制目前还不完全清楚。为参与计划的学生提供培训机会，将进一步提升计划的广泛影响。解决复杂的生物学问题需要在实验和计算方法方面受过跨学科训练的新一代生命科学家。这项研究将通过联合会议和学员合作等密切互动，为所有参与者提供这些培训机会。这个项目的重点是解决现代发育生物学的一个基本问题：单个细胞如何自组织成多细胞结构。特别是，该研究的目的是揭示控制由黄原菌形成的生物膜的发育程序的机制。这种土壤细菌易于处理，具有相对简单的基因组，因此是一个很好的模型系统，可以开发新的数学模型并通过实验验证其预测。在饥饿状态下，黄芽孢杆菌细胞协调它们在空间和时间上的运动，将成千上万的细胞聚集在一起形成多细胞聚集体，分化成孢子。这种原核生物的发育模型在实验上是易于处理的，并且具有许多在发育系统中普遍存在的复杂性。结合数学建模方法和定量实验，本项目将揭示控制发育自组织三个不同阶段的相互作用和信号机制。为此，该研究建立在先前卓有成效的方法上，将这些相互作用与观察到的群体表型联系起来。本研究的数学部分的重点是基于主体和动力学模型的进步，这些模型超越了现有的、过度简化的、假设和分析单一自组织机制的现象模型。由此得出的预测将通过基因或环境扰动进行实验检验。更广泛的影响包括开发新的和广泛适用的方法来理解多细胞模式，为参与的学生提供跨学科培训，以及基于研究结果和方法的教育和推广活动。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project engages a collaborating team of experimental microbiologists, computational biologists, and mathematicians to understand the mechanisms by which soil bacterium Myxococcus xanthus aggregates into multicellular mounds in response to starvation. Using mathematical and biological approaches, the team will uncover interactions that control different stages of developmental self-organization: (1) pre-aggregation cell alignment and formation of cellular streams; (2) formation and growth of initial aggregates; and (3) aggregate coarsening, dispersal, and pulsing. This project is expected to elucidate some of the general mechanisms behind the collective behavior of motile cells in other organisms and to develop widely applicable mathematical approaches. Transition from single cells to multicellularity is fundamentally important to increase understanding of many pathogenic bacteria and to elucidate self-organization in more complex systems. Even though individual bacterial cells are considered to function independently and to be autonomous, many bacterial populations will act collectively, communicating, moving and self-organizing into multicellular structures. M. xanthus is a great model system for studying biological self-organization: its cells function fine alone, but cooperate to form variety of distinct, dynamic patterns depending on environmental conditions. However, the mechanisms of these behaviors are currently not fully understood. Broader impacts of the project will be further enhanced by training opportunities for participating students. Solving complex biological problems requires a new generation of life scientists with cross-disciplinary training in both experimental and computational methods. This research will provide those training opportunities for all participants, facilitated by close interactions such as joint meetings and trainee collaborations. This project focuses on solving one of the fundamental problems of modern developmental biology: how individual cells self-organize into multicellular structures. In particular, the goal of the research is to uncover mechanisms controlling the developmental program of a biofilm formed by M. xanthus. This soil bacterium is tractable and has a relatively simple genome and as such is an excellent model system to develop novel mathematical models and experimentally test their predictions. Under starvation, M. xanthus cells coordinate their movement in space and time, bringing tens of thousands of cells together into multicellular aggregates to differentiate into spores. This model of prokaryotic development is experimentally tractable and shares many of the complexities that are ubiquitous in developmental systems. With a combination of mathematical modeling approaches and quantitative experiments, this project will uncover the interactions and signaling mechanisms that control three distinct stages of developmental self-organization. To this end, the research builds on the previously fruitful methodology to connect these interactions with the observed population phenotypes. The emphasis of the mathematical component of this research is on the advancement of agent-based and kinetic models that go beyond the existing, oversimplified models of the phenomena that postulate and analyze a single mechanism for self-organization. The resulting predictions will be tested experimentally using genetic or environmental perturbations. Broader impacts include developing novel and widely applicable methodology to understand multicellular patterns, cross-disciplinary training for participating students, and educational and outreach activities based on the research results and methods.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.