Previous models & software

Jump to: BacSim | Framework | Phobia

BacSim

BacSim was developed as an extension of Gecko, an ecological flight simulator written by Ginger Booth, a programmer with the Center for Computational Ecology, Yale Institute for Biospheric Studies, which has been renamed Center for Biodiversity Conservation and Science. Gecko started as a prototype based on John Holland's Echo models. It then became one of the first programs to be based on the Swarm toolkit for multi-agent based simulations written in Objective-C, originally developed at the Santa Fe Institute. Later Gecko was rewritten in Java, in order to make it independent of Swarm and all its dependencies, using Ginger's own CourseWare, a Java Toolkit for online simulators for the teaching of ecology. Gecko in its various guises has been applied to grassland foodwebs and forest simulations.

Bacsim model structure diagram

The structure of the model is shown in this sketch: parameters in red are randomly varied in order to model the individual variability of bacteria.

Since Gecko/BacSim has been rewritten in Java which allows you to run the program as an applet in a browser, you can try it out in your browser (Must be a Java 1.1 enabled browser, such as Netscape 4.5+ or Internet Explorer 4.0+). More information on BacSim is available on the Kreft Group website. iDynoMiCS has replaced BacSim in our research, so BacSim is no longer developed or supported.

Some of the publications using BacSim:

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Grijspeerdt K, Kreft JU, Messens W (2005). Individual-based modelling of growth and migration of Salmonella enteritidis in hen's eggs. International Journal of Food Microbiology 100: 323-333

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Kreft JU (2004). Biofilms promote altruism. Microbiology 150: 2751-2760

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Kreft JU, Wimpenny JWT (2001). Effect of EPS on biofilm structure and function as revealed by an individual-based model of biofilm growth. Water Science and Technology 43(6): 135-141

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Kreft JU, Picioreanu C, Wimpenny JWT, van Loosdrecht MCM (2001). Individual-based modelling of biofilms. Microbiology 147: 2897-2912

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Kreft JU, Booth G, Wimpenny JWT (1998). BacSim, a simulator for individual-based modelling of bacterial colony growth. Microbiology 144: 3275-3287

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Framework

A numerical framework for describing the dynamics of bacterial biofilm structure and composition in 2D or 3D. The model allows the description of multi-species biofilms with arbitrary solute species (e.g. carbon sources, dissolved oxygen, soluble metabolites) as well as an arbitrary number of bacteria types composed of particulate species (e.g. active biomass, inert biomass, EPS). For each biofilm system to analyze, a set of mass balance equations is used to define relations between involved species. Diffusion-reaction equations are solved numerically to compute concentration fields for solute species and local conversion rates for particulate species. Spreading of the biomass is modeled using an individual-based approach in which hard spherical bacteria (which can be composed of several particulte compartments) consume nutrients, grow, divide producing new individuals of the same species, and push each other as they grow. The effect of biomass detachment on overall dynamics of the system is implemented using a moving front approach simulated by the level set method. This modeling concept constitutes a bottom-up approach were overall behavior of the community is derived from the actions and interactions occurring at the scale of the unicellular organisms that constitute it.

Model developed by the Biofilm Group at the TU Delft

Some of the publications using the Framework:

 

Xavier JB, Picioreanu C, van Loosdrecht MCM A framework for multidimensional modelling of activity and structure of multispecies biofilms. Environmental Microbiology, 7(8), 1085-1103 (2005).

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Xavier JB, Picioreanu C, van Loosdrecht MCM A general description of detachment for multidimensional modelling of biofilms. Biotechnology and Bioengineering, 91(6), 651-669 (2005).

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Phobia

A project funded by he European Commission (QLK3-CT-2002-01938), that carried out basic research on the functioning of aquatic phototrophic biofilms in freshwater and marine environments. These complex microbial communities are attached to solid substrata and are dominated by cyanobacteria and microalgae that have close interactions with either the heterotrophic components, to which they supply organic matter and oxygen, or the external water phase which is characterised by physical and chemical heterogeneities. To understand the development and functioning of biofilms grown under the various experimental conditions, data were collected on microenvironment, biofilm architecture and its spatio-temporal growth, species composition and diversity, exopolymeric matrix properties, photosynthesis and metabolic interactions of phototrophs vs heterotrophs.The data were then used to develop a mechanistic model and an artificial neural network tool to predict the development of phototrophic biofilms in aquatic environments.

More information is available here.

Some of the publications using PHOBIA:

 

Wolf G, Picioreanu C, van Loosdrecht MCM Kinetic modelling of photototrophic biofilms: the PHOBIA model. Biotechnology and Bioengineering, 97(5), 1064-1079 (2007).

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