Astrobiologists face the question of detecting extraterrestrial life; new methods must distinguish living from non-living samples, with microbial motility emerging as a promising biosignature.
Motility as a biosignature was proposed in the 1960s, but only now, with advanced technology, can automated observations occur on Mars and icy moons, thanks to more powerful micro-computers.
In our lab, we use machine learning algorithms to track microbial movement in liquid water, achieving over 99% accuracy in distinguishing motility from Brownian motion, providing a clear method for life detection.
Our research shows how E. coli’s movement patterns change under Mars-like conditions, such as high-salt environments, suggesting that microbial behavior can be indicative of life beyond Earth.
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