AMMPER-2: A spatially explicit agent-based model of microbial radiobiology with redox dye simulation
- 1NASA Ames Research Center
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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BibTeX
@misc{palacios2026ammper2,
title = {{AMMPER-2: A spatially explicit agent-based model of microbial radiobiology with redox dye simulation}},
author = {D. Palacios and J. Lee and P. Sharma and M. Marous and D. Mejia and L. Liddell and D. Gentry and S. Santa Maria},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.08.757403},
url = {https://www.biorxiv.org/content/10.64898/2026.10.08.757403v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - AMMPER-2: A spatially explicit agent-based model of microbial radiobiology with redox dye simulation
AU - D. Palacios
AU - J. Lee
AU - P. Sharma
AU - M. Marous
AU - D. Mejia
AU - L. Liddell
AU - D. Gentry
AU - S. Santa Maria
PY - 2026
DA - 2026/10/08
PB - bioRxiv
DO - 10.64898/2026.10.08.757403
UR - https://www.biorxiv.org/content/10.64898/2026.10.08.757403v1
AB - 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.
ER -