eGUT: a Tool for Predictive Computer Simulation of the Gut Microbiota and Host Interactions

We propose the development of a generic computer simulation tool to reduce and replace animal experiments by simulating the gut microbiota and their interactions with the host. This tool, called eGUT, will be built by extending the individual-based Dynamics of Microbial Communities Simulator iDynoMiCS, which we have developed with many colleagues and published in Environmental Microbiology last year and made available as open source on www.idynomics.org. Using an individual-based model (IbM) as the engine for the tool has the advantage that the tool will be very flexible, e.g., the number of species or the types of interactions or the rules of behaviour can be chosen by the scientist user - as required of a generic tool. Moreover, IbMs merely describe the activities of the individual organisms or host cells. Their behaviour is described by equations for the kinetics of growth and by rules for cell division (if larger than threshold divide) and other decisions. These kinetics and rules are typically based on laboratory experiments under defined conditions. It is quite important to realize that simple rules can lead to complex dynamics and spatial patterns so that complexity of a system does not mean that it cannot be understood or modelled because it is too complex. Complexity simply emerges from the multitude of local interactions of various individuals with the environment and with the host cells, as running an IbM will demonstrate. The gut microbiota has profound effects on our health, a realization leading to a surge of animal experiments in this area, so that the development of a computer simulation tool to reduce or replace these animal experiments is a gap that is becoming increasingly urgent to fill. Our specific aims are to build eGUT, apply eGUT to model the spread and replacement of antibiotic resistance plasmids in the gut, apply eGUT to two further test cases from our collaborators, and to disseminate eGUT to actively increase the user base.

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Project grant

Status:

Closed

Principal investigator

Dr Jan-Ulrich Kreft

Institution

University of Birmingham

Co-Investigator

Professor Christopher Morton
Dr Shan He

Grant reference number

NC/K000683/1

Award date:

Jan 2013 - Jun 2016

Grant amount

£259,264