A straightforward and trustworthy test for indicators of extant or past
life on other planets has been found by scientists—dubbed "the holy grail of
astrobiology."
A seven-person team reports in the Proceedings of the National Academy of
Sciences journal that its artificial intelligence-based system separated
biological samples from abiotic ones with 90% accuracy.
"According to Dr. Hazen, this standard analytical technique has the
potential to completely transform the hunt for extraterrestrial life and
expand our knowledge of the chemistry and origin of the first life on
Earth." Before the samples return to Earth, it paves the way for the use of
intelligent sensors on robotic spacecraft, landers, and rovers to look for
indications of life.
First and foremost, the new test may provide light on the origins of
enigmatic, old rocks on Earth, as well as potentially on samples previously
gathered by the Sample Analysis at Mars (SAM) instrument on the Mars
Curiosity rover. An analytical tool aboard called "SAM" (for Sample Analysis
at Mars) may be used for the latter experiments.
"To find out if there are molecules from an organic Martian biosphere on
Mars, we may already have data in hand. We'll just need to adjust our
approach to fit SAM's protocols."
Lead author Jim Cleaves of the Earth and Planets Laboratory, Carnegie
Institution for Science, Washington, DC, states that "the search for
extraterrestrial life remains one of the most tantalizing endeavors in
modern science."
"This new discovery has a lot of ramifications, but three main ones are as
follows: First, biochemistry and abiotic organic chemistry are fundamentally
different; second, we can determine whether ancient Earth and Mars were once
home to life by examining their samples; and third, this new technique may
be able to differentiate other biospheres from Earth, which could have a big
impact on astrobiology missions in the future."
The cutting-edge analytical technique depends on more than just locating a
particular molecule or collection of molecules in a sample.
Instead, using pyrolysis gas chromatography analysis, which separates and
identifies a sample's component parts, and mass spectrometry, which
calculates the molecular weights of those components, the researchers showed
that AI can distinguish biotic from abiotic samples by identifying subtle
differences within a sample's molecular patterns.
AI was trained to estimate the origin of a new sample using vast
multidimensional data from the molecular analyses of 134 known abiotic or
biotic carbon-rich samples. AI was able to accurately identify samples with
an estimated 90% origin accuracy from:
Things that have been preserved in fine-grained rock, including living
things like human hair, leaves, grains, insects, teeth, bones, and
contemporary shells
samples having abiotic origins, such as pure laboratory substances (such
amino acids) and carbon-rich meteorites, or remnants of past life that have
been modified by geological processes (such as coal, oil, amber, and
carbon-rich fossils).
The authors also note that because collections of organic molecules,
whether biotic or abiotic, have a tendency to deteriorate with time, it has
been challenging to pinpoint the origins of many ancient carbon-bearing
materials up until this point.
Remarkably, the new analytical technique found evidence of biology survived
in some cases across hundreds of millions of years, despite extensive
degradation and modification.
According to Dr. Hazen, "We started with the premise that there are
'chemical laws of life' that impact the variety and distribution of
biomolecules; that is, that the chemistry of life is fundamentally different
from that of the inanimate universe. If we could figure out such guidelines,
we could use them to direct our efforts in simulating the beginnings of life
or looking for hints of life on other planets."
These findings suggest that, despite the fact that extraterrestrial life
may differ greatly from that of Earth, we might be able to locate life on
other planets or in other biospheres. Furthermore, we can determine if life
on Earth and other planets originated from a shared or distinct source if we
do discover evidence of life elsewhere."
Stated differently, both Earthly life and extraterrestrial biochemistries
should be detectable by the technique. That is significant because, although
it is not unreasonable to anticipate that extraterrestrial life will employ
DNA, amino acids, and other biomarkers, it is not possible to identify the
molecular biomarkers of Earth life. With our approach, we search for
patterns in molecular distributions that result from the need for
"functional" molecules in life."
We taught our machine-learning model to predict only two sample types:
biotic or abiotic, thus it truly surprised us when the system found three
different populations: abiotic, live biotic, and fossil biotic.
Put otherwise, it has the ability to distinguish between more recent
biological samples derived from fossil samples—for example, a freshly picked
vegetable or leaf against a long-dead object. We are encouraged by this
unexpected discovery that further characteristics, such photosynthetic life
or eukaryotes (cells with a nucleus), may potentially be identified."
Co-author Anirudh Prabhu of the Carnegie Institution for Science uses the
example of sorting coins based on various characteristics—monetary value,
metal, year, weight, or radius, for example—and then combining those
attributes to find more complex groupings and separations to illustrate the
role of AI. "And AI algorithms are invaluable to collate the data and create
highly nuanced insights when hundreds of such attributes are
involved."
"The distinctions between biotic and abiotic samples pertain to chemical
aspects such as solubility in water, molecular weights, volatility, and
other related factors," Dr. Cleaves continued.
"A cell contains a membrane and an interior known as the cytosol; the
content of the cell is mostly water soluble, while the membrane is largely
water-insoluble. That's how I would conceptualize things simply. This
configuration both prevents the "inner components" from leaking through the
membrane and maintains the membrane together in an effort to reduce the
number of times its components come into contact with water."
"Inside components, such as proteins and chromosomes, can also remain
dissolved in water despite their enormous size," he explains.
Thus, dissecting a live cell or tissue into its constituent parts yields a
mixture of extremely water-soluble and extremely water-insoluble molecules
dispersed along a spectrum. Over their lengthy histories, materials like
coal and petroleum have lost the majority of their water-soluble
content."
"Biological distributions are not the same as those of abiological samples,
which can have distinct distributions across this spectrum with respect to
one another."
The method might soon provide answers to many of the planet's scientific
puzzles, such as where the black sediments from Western Australia, which
date back 3.5 billion years, came from. These are controversial rocks that
some scientists believe contain the oldest fossil bacteria on Earth, while
others maintain they contain no indications of life.
Similar arguments are raised by other samples from ancient rocks found in
China, South Africa, and Northern Canada.
"We are currently utilizing our techniques to tackle these enduring
inquiries regarding the biogenicity of the organic matter within these
rocks," states Hazen.
Furthermore, fresh concepts on the possible benefits of this novel strategy
in other disciplines including biology, paleontology, and archaeology have
proliferated.
What more insights would we be able to obtain if AI is able to discern
between biotic and abiotic, as well as between current and ancient life with
ease? Could we, for instance, determine if a prehistoric fossil cell was
photosynthetic or had a nucleus?" asks Dr. Hazen.
Could it distinguish between several types of wood from an archaeological
site based on its analysis of charred remains? It seems as though we are
only beginning to scratch the surface of an enormous ocean of
opportunities."
"Students of Earth's early history may find Cleaves and colleagues'
inventive technique for separating abiotic organic matter from living matter
to be a gift for astrobiologists. Although much remains to be discovered,
one day a next-generation version of their system may very well travel to
Mars to assess the likelihood of life there while its Earthbound sisters
demonstrate the age of life on Earth," stated Andrew H. Knoll, Fisher
Research Professor of Natural History and Research Professor of Earth and
Planetary Sciences Emeritus, Harvard University Department of Organismic and
Evolutionary Biology
"This new study intrigues me greatly! As it seems to separate abiotic from
biotic organic matter based on its molecular complexity, it is a novel line
of inquiry to pursue and might prove to be an invaluable instrument for
astrobiology missions, stated Emmanuelle J. Javaux, Head of the Early Life
Traces and Evolution-Astrobiology Lab and Director of the Astrobiology
Research Unit at the University of Liège in Belgium.
Testing this novel technique on ancient and extant creatures from the three
domains of life as well as on some of the earliest disputed and hypothesized
signs of Earth life would be fascinating! This might settle some heated
arguments in our neighborhood."
According to Karen Lloyd, a professor in the University of Tennessee,
Knoxville's Department of Microbiology, "we are in great need of
biosignatures for life that don't depend on looking for a specific type of
biomolecule that may be universal to all life on Earth, but not universal to
all life outside of Earth."
"This work outlines a future direction for assessing the likelihood of a
chemical signature being suggestive of life or not, without assuming that
extraterrestrial life will utilize the same biomolecules as terrestrial
life. The range of measures that may be utilized to discover agnostic
biosignatures of life may be increased by using the same statistical method
to other kinds of measurements as well."
This offers a valuable prospective tool for identifying life on other
planets and in the far past of Earth. Importantly, the method may already be
applied on spacecraft that can explore various solar system regions in our
quest for extraterrestrial life," said Daniel Gregory, assistant professor
at the University of Toronto's Department of Earth Sciences.
