Classification of the Biogenicity of Complex Organic Mixtures for the Detection of Extraterrestrial Life

Abstract

Searching for life in the Universe depends on unambiguously distinguishing biological features from background signals, which could take the form of chemical, morphological, or spectral signatures. The discovery and direct measurement of organic compounds unambiguously indicative of extraterrestrial (ET) life is a major goal of Solar System exploration. Biology processes matter and energy differently from abiological systems, and materials produced by biological systems may become enriched in planetary environments where biology is operative. However, ET biology might be composed of different components than terrestrial life. As ET sample return is difficult, in situ methods for identifying biology will be useful. Mass spectrometry (MS) is a potentially versatile life detection technique, which will be used to analyze numerous Solar System environments in the near future. We show here that simple algorithmic analysis of MS data from abiotic synthesis (natural and synthetic), microbial cells, and thermally processed biological materials (lab-grown organisms and petroleum) easily identifies relational organic compound distributions that distinguish pristine and aged biological and abiological materials, which likely can be attributed to the types of compounds these processes produce, as well as how they are formed and decompose. This method is independent of the detection of particular masses or molecular species samples may contain. This suggests a general method to agnostically detect evidence of biology using MS given a sufficiently strong signal in which the majority of the material in a sample has either a biological or abiological origin. Such metrics are also likely to be useful for studies of possible emergent living phenomena, and paleobiological samples.

Keywords

• astrobiology
• life detection
• biosignatures
• machine learning
• mass spectrometry
• complexity