Virtual Microbes


Virtual Microbes is a computer simulation model to study the eco-evolutionary dynamics of microbes (Thomas Cuypers, 2018). Virtual Microbes is unsupervised, meaning that it targets to combine relevant biological structures (genes, genomes, metabolism, mutations, ecology, etc.) without a preconceived notion of “fitness”, which is instead an emergent phenomenon. By not explicitly defining what the model should do, it allows for a serendipitous approach to study microbial evolution:

  • How do complex cross-feeding communities form?
  • What happens when a complex microbe “wild type” is transferred to lab-like conditions?
  • What is the influence of horizontal gene transfer (HGT) on the productivity and diversity of a microbial community?

At the basis of the Virtual Microbe framework is an artificial “metabolic universe”, describing all the possible reactions that can be catalysed. For simplicity, we here display a simple metabolic universe of 4 possible metabolites in: two resources (and C), one BUILDING BLOCK, and an ENERGY carrier (pentagons). Resources are fluxed into the system, but building blocks and energy must be synthesised to express proteins and/or transport metabolites across the membrane. A Virtual Microbe only needs to express a subset of all possible reactions to be viable, and that no metabolic strategy is necessarily the “right” one. The individuals grow and reproduce on a spatial grid, and can only reproduce when there is an empty spot. Death happens stochastically or when a cell has accumulated toxicity by having excessively high concentrations of metabolites. Only cells that have grown sufficiently are allowed to reproduce.

Availability and detailed methods

For simple useage, Virtual Microbes is best installed via PyPi. See quick install for a quick introduction. For developers Virtual Microbes is also publicly availble on bitbucket. The basis of the program is uses Python synthax, while the metabolic bedrock uses C (Cython) to integrate the equations that describe the evolved metabolisms.