RUI: Study of parasite-host model and its biological applications: simulations and theory

该奖项支持理论和计算研究和教育，以调查软物质与生物学之间的界面问题，并推进对远离熟悉的平静但稳健的平衡状态的系统的基本理解。这些系统涵盖了从材料合成和生长到生物。不同物种的生命系统表现出丰富的动态行为，如共存、竞争和共生。对这些现象的定量理解需要结合不同的方法，如建模和计算机模拟，以及从应用于生命系统的基本物理定律的综合视角。本项目重点研究寄主-寄主类型在质粒（小DNA分子）背景下的相互作用，使细菌对抗生素治疗从易感转变为耐药。在模型中，抗生素耐药性的传播取决于质粒与细菌细胞之间的物理接触，以及易感细胞和耐药细胞之间的物理接触。通过调整物理相关参数，如细菌繁殖率、质粒扩散率和细胞之间的相互作用，研究小组的目标是深入了解人群中抗生素耐药性的快速出现，并激发与生物学家跨学科合作的进一步兴趣。此外，该项目将涉及六名本科生，他们将通过解决现实世界的问题来磨练他们的计算技能。他们也将通过这个项目提高他们对复杂系统和随机过程主题的理解。这有助于拓宽学生的研究视野，架起从学习者到科学家的桥梁。该奖项支持理论和计算研究和教育，以调查软物质与生物学之间的界面问题，并推进对远离平衡的系统的基本理解。不同物种的生命系统表现出丰富的动态行为，如共存、竞争和共生。在非平衡统计力学和计算机模拟的辅助下建立的理论框架促进了对这些现象的定量理解。在这个项目中，旨在将非平衡统计力学、种群动力学和细胞生物学的基本概念与蒙特卡罗模拟相结合，探索一类重点复杂系统：寄生虫-宿主（PH）模型及其生物学意义。PH动力学没有被系统地探索，本质上是不同的，在生命科学中非常重要。本项目重点研究寄主-寄主类型在质粒（小DNA分子）背景下的相互作用，使细菌对抗生素治疗从易感转变为耐药。耐药群体的出现来自两个机制：质粒转化和细胞-细胞结合。这两种动态，如出生和死亡，以及细菌种群的空间结构将被调查。用反应扩散系统的语言来解决这个问题，并以理论结果为基础，研究小组计划开发工具来探测PH系统在混合良好的情况下和具有空间结构的情况下的稳态特性和动力学。通过这种方式，PI旨在确定定义特征以抑制抗性种群的增长。此外，该团队计划对该类ph样模型及其在控制流行病和细菌耐药性进化方面的潜在应用进行更全面的描述。研究小组将包括六名本科生，为期三年。他们将通过解决现实世界的问题来磨练自己的计算技能。他们也将通过这个项目提高他们对复杂系统和随机过程主题的理解。这有助于拓宽学生的研究视野，架起从学习者到科学家的桥梁。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。

NONTECHNICAL SUMMARYThis award supports theoretical and computational research and education to investigate problems at the interface between soft matter and biology and to advance fundamental understanding of systems far from the familiar tranquil but robust state of equilibrium. These systems span from materials synthesis and growth to living things. Different species of living systems exhibit rich dynamical behaviors such as coexistence, competition, and symbiosis. The quantitative understanding of these phenomena requires a combination of different methods, such as modeling and computer simulations, as well as an integrated perspective from fundamental physical laws applied to living systems. This project focuses on the parasite-host type interaction in the context of plasmids - small DNA molecules - transforming bacteria from susceptible to resistant to antibiotic treatments. In the model, the spread of antibiotic resistance depends on the physical contact between the plasmid and the bacteria cells, as well as the susceptible and the resistance cells. By tuning the physically relevant parameters, such as the bacteria reproduction rate, plasmid diffusion rate, and the interactions amongst cells, the research team aims to gain insight into the rapid emergence of antibiotic resistance in a population, and spark further interest in interdisciplinary collaborations with biologists.Furthermore, this project will involve six undergraduate students, who will hone their computational skills through solving a real-world problem. They will also advance their understanding of complex systems and topics on stochastic processes through this project. These help broaden the research horizon of the students and bridge the transition from a learner to a scientist.TECHNICAL SUMMARYThis award supports theoretical and computational research and education to investigate problems at the interface between soft matter and biology and to advance fundamental understanding of systems far from equilibrium. Different species of living systems exhibit rich dynamical behaviors such as coexistence, competition, and symbiosis. The quantitative understanding of these phenomena is facilitated by the theoretical framework established in non-equilibrium statistical mechanics and modeling aided by computer simulations. In this project, the aims to integrate fundamental concepts in non-equilibrium statistical mechanics, population dynamics and cell biology with Monte Carlo simulations to explore a focused class of complex systems: the parasite-host (PH) model and its biological implications.The PH dynamics is less systematically explored, fundamentally different, and immensely important in life sciences. This project focuses on the parasite-host type interaction in the context of plasmids - small DNA molecules - transforming bacteria from susceptible to resistant to antibiotic treatments. The emergence of a resistant population comes from two mechanisms: plasmid-transformation and cell-cell conjugation. Both the dynamics, such as birth and death, and the spatial structure of the bacterial populations will be investigated. Casting this problem in the language of reaction-diffusion systems and using the theoretical results as a foundation, the research team plans to develop tools for probing the steady state properties and the dynamics of the PH system both in a well-mixed scenario and one with spatial structure. In this way, the PI aims to identify defining characteristics to curb the growth of a resistant population. Furthermore, the team plans to provide a more general description of the class of PH-like models and potential applications in the control of epidemics and the evolution of drug resistance in bacteria.The research team will involve six undergraduate students over three years. They will hone their computational skills through solving a real-world problem. They will also advance their understanding of complex system and topics on stochastic processes through this project. These help broaden the research horizon of students and bridge the transition from a learner to a scientist.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.