Life on Earth may have emerged much earlier than scientists thought, according to new chemical evidence preserved in rocks more than 3.3 billion years old. An international team led by the Carnegie Institution for Science has discovered molecular signals indicating that oxygen-producing photosynthesis arose nearly a billion years earlier than previous records.
Results published in Proceedings of the National Academy of Sciencesrely on high-resolution chemistry coupled with artificial intelligence to discover biological patterns long after their original molecules have disappeared.
“Ancient rocks are full of interesting mysteries that tell us the story of life on Earth, but some pieces are always missing,” said Katie Maloney, co-author, in press release. “The combination of chemical analysis and machine learning has revealed biological clues about ancient life that were previously invisible.”
Read more: The first evidence of a proto-Earth may be a chemical imbalance hidden inside ancient rocks
Why early life is hard to detect
The early Earth was home to microbial mats and simple cells that rarely fossilized. Over billions of years, these materials were buried, heated, crushed, and destroyed as the Earth's crust shifted. These transformations have largely erased the biosignatures that once held clues to the origins and early evolution of life. Because of this, scientists have traditionally only been able to identify reliable molecular signatures in rocks less than 1.7 billion years old.
This has made it difficult to reconstruct Earth's ancient biosphere and the timing of major events such as the emergence of photosynthesis.
A new study challenges this limitation. This shows that even when the original biomolecules disappeared, the structure of the molecular fragments was preserved in ancient rocks may still carry information about whether life once existed.
Identifying Ancient Life Using AI
To uncover these patterns, the team analyzed organic and inorganic material from ancient times. rocks breaking them down into molecular fragments. The machine learning model was trained on more than 400 samples, including modern plants, animals, billion-year-old fossils, microbial mats and meteorites, allowing it to detect chemical signatures of life.
The samples included exceptionally well-preserved algae dating back one billion years. fossils from the Yukon Territory, which helped AI learn what early photosynthetic organisms look like in molecular form.
Once trained, the AI system distinguished biological from non-biological chemistry with over 90 percent accuracy. It also revealed molecular signatures of photosynthesis in rocks at least 2.5 billion years old, pushing chemical evidence of the process hundreds of millions of years earlier than previous work and showing that the distribution of degraded molecular fragments can still reveal whether life once existed.
“Ancient life leaves behind more than just fossils; it leaves chemical echoes,” Dr. Robert Hazen, co-author of the study, said in a press release. “Using machine learning, we can now reliably interpret these echoes for the first time.”
The search for life on other worlds
Overall, the work offers a clearer picture of Earth's earliest biosphere and expands the tools available to study it. And because this method can detect biological chemistry even after billions of years of change, it could prove useful far beyond Earth. The same analytical approach can be applied to samples from Mars or other worlds to assess whether they ever supported life.
“This innovative method helps us read the ancient fossil record in new ways,” Maloney said. “This could help in the search for life on other planets.”
Read more: The Earth was formed 4.54 billion years ago – how do scientists know?
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