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AMMPER-2: A spatially explicit agent-based model of microbial radiobiology with redox dye simulation

Palacios, D.; Lee, J.; Sharma, P.; Marous, M.; Mejia, D.; Liddell, L.; Gentry, D.; Santa Maria, S.

2026-10-10 microbiology
10.64898/2026.10.08.757403 bioRxiv
Show abstract

To reduce health risks for human space exploration, it is important to model the effects of deep-space radiation on biological systems. The budding yeast Saccharomyces cerevisiae is a common model organism in space radiobiology, but little is known about how radiation damage to individual cells translates into the population-level effects that experiments measure. The Agent-Based Model for Microbial Populations Exposed to Radiation (AMMPER) is a spatially explicit agent-based model that simulates the effects of ionizing radiation on S. cerevisiae cells and produces population-level results. Its goal is to improve experiment design and data interpretation. AMMPER-1 demonstrated that agent-based simulations can qualitatively reproduce the effects of proton radiation on the growth rate of wild-type and DNA-repair mutant yeast. Here, we present AMMPER-2, which addresses limitations of the first model and expands its capabilities. AMMPER-2 incorporates the dynamics of the redox dye alamarBlue, a data type commonly generated in spaceflight microbiology experiments, and models the fate of reactive oxygen species in more detail. It also adds an improved graphical interface and runs faster. AMMPER-2 remains easy to execute in Python on a standard personal laptop, providing space biologists a tool to explore experimental conditions, generate hypotheses, and interpret data from microbial space radiation experiments.

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