BSim: An Agent-Based Tool for Modeling Bacterial Populations in Systems and Synthetic Biology

Abstract

Large-scale collective behaviors such as synchronization and coordination spontaneously arise in many bacterial populations. With systems biology attempting to understand these phenomena, and synthetic biology opening up the possibility of engineering them for our own benefit, there is growing interest in how bacterial populations are best modeled. Here we introduce BSim, a highly flexible agent-based computational tool for analyzing the relationships between single-cell dynamics and population level features. BSim includes reference implementations of many bacterial traits to enable the quick development of new models partially built from existing ones. Unlike existing modeling tools, BSim fully considers spatial aspects of a model allowing for the description of intricate micro-scale structures, enabling the modeling of bacterial behavior in more realistic three-dimensional, complex environments. The new opportunities that BSim opens are illustrated through several diverse examples covering: spatial multicellular computing, modeling complex environments, population dynamics of the lac operon, and the synchronization of genetic oscillators. BSim is open source software that is freely available from http://bsim-bccs.sf.net and distributed under the Open Source Initiative (OSI) recognized MIT license. Developer documentation and a wide range of example simulations are also available from the website. BSim requires Java version 1.6 or higher.

Entrainment and Control of Bacterial Populations: An in Silico Study over a Spatially Extended Agent Based Model

“…BSim is a 3D framework for simulating bacterial populations [32,33] and has numerical solvers for both ODEs and partial differential equations (PDEs). We used the Runge-Kutta order four-to-five ODE solver when solving the system of ODEs presented in equations (4)- (7).…”

“…The simulations were carried out in BSim, a 3D framework for simulating bacterial populations [32,33].…”

“…As in Mina et al [21], we implement the model in BSim [32] an open software platform [33] developed using the Java language [34] to study bacterial populations in silico. In order to do so in full, we extend the BSim software [33] by creating methods which can accommodate for the control techniques we are interested in studying.…”

“…Additional material with regards to the computational implementation of the model in BSim [32,33] and the post-processing of results may be found in the supplementary material that accompanies this manuscript.…”

Agent-based modelling of biofilm formation and inhibition in Escherichia coli

“…The study of bacterial coordination, communication and cooperation as required for biofilm formation and growth, can mitigate the cumbersome and expensive process of testing every hypothesis experimentally. Agent-based models demonstrate the relationships between microscopic properties of the agents and macroscopic behaviours of the community 22 . In this work, an agent-based model is used to understand and mathematically evaluate the behaviour and interactions of Escherichia coli bacteria, with each biofilmforming cluster (which may initially consist of a single bacterium, but may reach a much larger maximum size) considered an individual agent.…”