BSim 2.0: An Advanced Agent-Based Cell Simulator

Area of Science:

• Computational biology
• Microbial modeling
• Systems biology

Background:

• Traditional continuum models have limitations in capturing single-cell behaviors.
• Agent-based models (ABMs) allow detailed in silico simulations of complex biological systems.
• Previous versions of BSim provided a framework for bacterial dynamics.

Purpose of the Study:

• To present BSim 2.0, a significantly updated agent-based modeling framework.
• To enhance the simulation of bacterial dynamics in experimental environments.
• To incorporate greater detail and realism into bacterial population modeling.

Main Methods:

• Development of BSim 2.0, a new agent-based model (ABM) framework.
• Implementation of cells with capsular geometry for physical and chemical interactions.
• Inclusion of a realistic cellular growth model and a delay differential equation solver.
• Modeling of realistic environmental geometries, including microfluidic chemostats.

Main Results:

• BSim 2.0 enables detailed tracking of single-cell behaviors.
• The model correlates individual cell actions with emergent macroscopic effects.
• Enhanced realism in simulating bacterial interactions and growth dynamics.
• Accurate representation of bacteria within complex experimental environments.

Conclusions:

• BSim 2.0 represents a significant advancement in computational modeling of bacterial dynamics.
• The framework facilitates realistic in silico experiments for microbial systems.
• This tool aids in understanding the link between single-cell behavior and population-level phenomena.