The discovery of life beyond Earth would be a watershed moment for astrobiology, but depending on what's out there, finding definitive evidence of extraterrestrial biology may not be as straightforward as "we'll know it when we see it." How can we reliably distinguish life from non-life, both on Earth and across the Solar System? And how can we hope to look for alien "lyfe" that differs markedly from life as we know it on Earth?
With colleagues at Carnegie, Howard, Purdue, and Johns Hopkins, we have pioneered a novel, robust method for distinguishing biotic from abiotic samples using a machine learning algorithm trained on pyrolysis–gas chromatography–mass spectrometry (py–GC–MS) data. Our hope is that this method will help determine whether samples from other worlds contain traces of present or past life—even life with non-Earthly biochemistry. In the meantime, this technique can be applied to ancient rocks on Earth to find traces of fossilized terrestrial biology to better our understanding of the evolution of life on our own planet.
Pyrolysis–gas chromatography–mass spectrometry data of an average bacterium from Cleaves et al. (2023). Figure by Michael L. Wong.
