NUFEB: A massively parallel simulator for individual-based modelling of microbial communities

Abstract

We present NUFEB (Newcastle University Frontiers in Engineering Biology), a flexible, efficient, and open source software for simulating the 3D dynamics of microbial communities. The tool is based on the Individual-based Modelling (IbM) approach, where microbes are represented as discrete units and their behaviour changes over time due to a variety of processes. This approach allows us to study population behaviours that emerge from the interaction between individuals and their environment. NUFEB is built on top of the classical molecular dynamics simulator LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator), which we extended with IbM features. A wide range of biological, physical and chemical processes are implemented to explicitly model microbial systems, with particular emphasis on biofilms. NUFEB is fully parallelised and allows for the simulation of large numbers of microbes (107 individuals and beyond). The parallelisation is based on a domain decomposition scheme that divides the domain into multiple sub-domains which are distributed to different processors. NUFEB also offers a collection of post-processing routines for the visualisation and analysis of simulation output. In this article, we give an overview of NUFEB’s functionalities and implementation details. We provide examples that illustrate the type of microbial systems NUFEB can be used to model and simulate.

Toward Engineering Biosystems With Emergent Collective Functions

“…Although computational frameworks have been available since the 1980s to support this process, it is only during the past decade that tools have been tailored for synthetic biology applications and reached sufficient performance (Gorochowski et al, 2012;Oishi and Klavins, 2014;Goñi-Moreno and Amos, 2015). More recently, the effective use of highly parallel computing resources has expanded the complexity of biological models that can be simulated (Rudge et al, 2012;Naylor et al, 2017;Li et al, 2019;Cooper et al, 2020). Automated coarse-graining of representations enable faster simulation without impacting on the accuracy of predictions (Graham et al, 2017), while advanced tools allow verification, validation and uncertainty quantification for such simulations (Richardson et al, 2020).…”

Towards Engineering Biosystems with Emergent Collective Functions

“…Although computational frameworks have been available since the 1980s to support this process, it is only during the past decade that tools have been tailored for synthetic biology applications and reached sufficient performance (Gorochowski et al, 2012;Oishi and Klavins, 2014;Goñi-Moreno and Amos, 2015). More recently, the effective use of highly parallel computing resources has expanded the complexity of biological models that can be simulated (Rudge et al, 2012;Naylor et al, 2017;Li et al, 2019;Cooper et al, 2020). Automated coarse-graining of representations enable faster simulation without impacting on the accuracy of predictions (Graham et al, 2017), while advanced tools allow verification, validation and uncertainty quantification for such simulations (Richardson et al, 2020).…”

Agent Based Models of Polymicrobial Biofilms and the Microbiome—A Review

“…More recent work from this group introduces the open-source software, Newcastle University Frontiers in Engineering Biology (NUFEB) [ 36 ]. Like its predecessor, it incorporates three-dimensional modeling of biological, chemical, and mechanistic properties of individual microbes in an ABM [ 33 ].…”

“…LAAMPS is an open-source software written in C++ distributed by Sandia National Laboratories, USA, which is primarily used for atomic and material modeling ( Last accessed on 16 February 2021). The models by Jayathilake et al, Li et al, and Gogulancea et al adapted LAAMPS to microbiology and created a biophysical agent-based model of biofilms, namely, the Newcastle University Frontiers in Engineering Biology (NUFEB) model [ 30 , 33 , 36 ]. All three models included biological, chemical, and mechanistic sub-models.…”