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

Bucknell University, Lewisburg PA

Investigators

Abstract

NONTECHNICAL SUMMARY This 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 SUMMARY This 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.