AMMPER-2: A spatially explicit agent-based model of microbial radiobiology with redox dye simulation
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…
The development of AMMPER-2, a spatially explicit agent-based model of microbial radiobiology, aims to enhance the understanding of microbial responses to deep-space radiation for human space exploration. Using the budding yeast Saccharomyces cerevisiae as a model organism, AMMPER-2 simulates the effects of ionizing radiation on individual cells and translates those data into population-level outcomes, facilitating experiment design and data interpretation.
The first version of AMMPER, AMMPER-1, successfully demonstrated the capability of agent-based simulations to qualitatively reproduce the effects of proton radiation on the growth rate of both wild-type and DNA-repair mutant yeast. Building upon the successes and addressing the limitations of its predecessor, AMMPER-2 introduces several improvements.
It incorporates the dynamics of the redox dye alamarBlue, a critical data type often generated in spaceflight microbiology experiments. This addition allows for a more detailed modeling of the fate of reactive oxygen species, a key factor in understanding radiation-induced damage.
Additionally, AMMPER-2 features an improved graphical interface, making it more user-friendly for space biologists. This interface enables them to explore experimental conditions, generate hypotheses, and interpret data from microbial space radiation experiments. Importantly, AMMPER-2 maintains its computational efficiency, running smoothly on a standard personal laptop, ensuring accessibility for researchers without the need for high-performance computing resources.
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