Unlike humans on Earth, extraterrestrial life may be entirely different. Hence, methods to detect specific molecules as biosignatures may be improper as extraterrestrials might have different evolutionary histories.
The search for life includes listening for radio signals from advanced civilizations in deep space, looking for subtle differences in the atmospheric composition of planets around other stars, and directly trying to measure it in soil and ice samples collected using spacecraft in our solar system.
This last classification permits them to directly offer their most advanced chemical analytical instrumentation as a powerful influence for extraterrestrial samples. Maybe, in any event, take a portion of the samples back to Earth.
Mass spectrometry (MS) is an essential method that scientists will depend on to look for extraterrestrial life. The technique can measure large numbers of mixtures present in examples, and along these lines, give a kind of “fingerprint” of their composition. Nevertheless, deciphering those fingerprints can be precarious.
On Earth, life relies on the same highly coordinated molecular principles. However, in simulations of the primitive processes that scientists accept may have added to life’s origins on Earth, numerous comparable yet marginally various adaptations of the particular molecules terrestrial life utilizes are frequently distinguished. Besides, normally happening substance measures are likewise ready to create a significant number of the building blocks of biological molecules.
It has long troubled scientists that biases toward life forms similar to Earth life might cause their detection methods to fail.
Scientists at the Earth-Life Science Institute at the Tokyo Institute of Technology in Japan and the National High Magnetic Field Laboratory (The National MagLab) in the U.S. addressed this problem using a combined experimental and machine learning computational approach.
Their approach could access complex organic mixtures using mass spectrometry to classify them as biological or abiological.
Scientists used ultra-high-resolution MS to measure the mass spectra of a wide variety of complex organic mixtures, including those derived from abiological samples made in the lab, organic mixtures found in meteorites, laboratory-grown microorganisms that fit all the modern criteria of life, including novel microbial organisms isolated and cultured by ELSI co-author Tomohiro Mochizuki, and unprocessed petroleum, which is derived from organisms that lived long ago on Earth, providing an example of how the “fingerprint” of known living organisms might change over geological time.
These samples each contained tens of thousands of discrete molecular compounds, which provided a large set of MS spectra that could be compared and classified.
When scientists fed their raw data into a machine-learning algorithm, they found that the algorithms could accurately classify the samples as living or non-living with ~95% accuracy. It simplified raw data considerably, making it plausible that lower-precision instruments used on spacecraft could obtain data of sufficient resolution to enable the biological classification accuracy the team obtained.
Co-author Huan Chen of the U.S. National MagLab said, “This work opens many exciting avenues for using ultra-high resolution mass spectrometry for astrobiological applications.”
Lead author Nicholas Guttenberg adds, “While it is difficult if not impossible to characterize every peak in a complex chemical mixture, the broad distribution of components can contain patterns and relationships which are informative about the process by which that mixture came about or developed. Suppose we’re going to understand complex prebiotic chemistry. In that case, we need ways of thinking about these broad patterns—how they come about, what they imply, and how they change—rather than the presence or absence of individual molecules. This paper is an initial investigation into the feasibility and methods of characterization at that level. It shows that even discarding high-precision mass measurements, there is important information in peak distribution that can be used to identify samples by the type of process that produced them.”
Co-author Jim Cleaves of ELSI says, “This sort of relational analysis may offer broad advantages for searching for life in the solar system, and perhaps even in laboratory experiments designed to recreate the origins of life.”
Scientists are further planning to understand precisely what aspects of this type of data analysis allow for such successful classification.
- Nicholas Guttenberg et al., Classification of the Biogenicity of Complex Organic Mixtures for the Detection of Extraterrestrial Life, Life (2021). DOI: 10.3390/life11030234