Fluid-Derived Lattices for Unbiased Modeling of Bacterial Colony Growth

TL;DR

This paper introduces a fluid-derived disordered lattice model that reduces structural artifacts in bacterial colony simulations, enabling efficient, unbiased, large-scale modeling of colony growth with diverse shapes.

Contribution

The authors develop a novel hybrid lattice-continuum method using a disordered fluid-derived lattice to eliminate lattice-induced artifacts in bacterial colony modeling.

Findings

Disordered fluid-derived lattices remove shape biases in colony simulations.

The method allows simulation of millions of bacteria within hours on a desktop.

The approach is adaptable for various applications in colony formation studies.

Abstract

Bacterial colonies can form a wide variety of shapes and structures based on ambient and internal conditions. To help understand the mechanisms that determine the structure of and the diversity within these colonies, various numerical modeling techniques have been applied. The most commonly used ones are continuum models, agent-based models, and lattice models. Continuum models are usually computationally fast, but disregard information at the level of the individual, which can be crucial to understanding diversity in a colony. Agent-based models resolve local details to a greater level, but are computationally costly. Lattice-based approaches strike a balance between these two limiting cases. However, this is known to come at the price of introducing undesirable artifacts into the structure of the colonies. For instance, square lattices tend to produce square colonies even where an isotropic shape is expected. Here, we aim to overcome these limitations and therefore study lattice-induced orientational symmetry in a class of hybrid numerical methods that combine aspects of lattice-based and continuum descriptions. We characterize these artifacts and show that they can be circumvented through the use of a disordered lattice which derives from an unstructured fluid. The main advantage of this approach is that the lattice itself does not imbue the colony with a preferential directionality. We demonstrate that our implementation enables the study of colony growth involving millions of individuals within hours of computation time on an ordinary desktop computer, while retaining many of the desirable features of agent-based models. Furthermore, our method can be readily adapted for a wide range of applications, opening up new avenues for studying the formation of colonies with diverse shapes and complex internal interactions.