Researchers are using artificial intelligence to investigate whether microbes best known for thriving in extreme environments like hydrothermal vents could be a source of new antibiotics.
Scientists at the University of Pennsylvania have detailed how they are using AI to identify previously unknown compounds in microbes called Archaea.
The team said that because these microbes thrive in extreme environments such as salt lakes and hot springs and deep-sea vents - as well as widely in more moderate environments - their biology has evolved in unusual ways. That makes them a promising source of new molecular tools, including compounds that may function like antibiotics but operate differently from those used currently.
Previous efforts to find new antibiotics have looked mostly at fungi, bacteria and animals said César de la Fuente, Presidential Associate Professor at the University of Pennsylvania, where he leads the Machine Biology Group.
The lab has previously used AI models to identify antibiotic candidates in the DNA of extinct organisms, including the woolly mammoth, the extinct straight-toothed elephant, giant elk, and the mylodon, a cave-dwelling sloth-like creature that vanished around 12,000 years ago.
Archaea are distinct from both bacteria and from eukaryotes, which include plants, animals and fungi, and fundamentally differ in their genetics, cell membranes and biochemistry. “We were drawn to Archaea because they’ve had to evolve biochemical defenses in unusual environments,” said Marcelo Torres, a research associate in de la Fuente’s lab and the paper’s co-first author. The paper is published in Nature Microbiology.
“We thought, if they’ve survived for billions of years under those conditions, maybe they’ve developed unique ways to fight off microbial competitors, and maybe we could learn from that," Torres said.
The researchers used APEX, an updated version of their deep learning framework, trained on thousands of peptides plus information about bacteria that cause diseases in humans to predict which peptides in Archaea might inhibit bacterial growth.
Across 233 species of Archaea the team identified 12,000 antibiotic candidates, then selected 80 compounds to test against actual bacteria. In tests against a range of drug-resistant bacteria, 93% of the 80 compounds demonstrated antimicrobial activity against at least one bacterium.
The researchers then selected three candidates to test in animal models, and said that four days after a single dose, all three had arrested the spread of a drug-resistant bacterium often acquired in hospitals. One of the three compounds demonstrated activity comparable to polymyxin B, an antibiotic commonly used as a last-line of defense against drug-resistant infections, the researchers said.
“This research shows that there are potentially many antibiotics waiting to be discovered in Archaea,” said de La Fuente. “With more and more bacteria developing resistance to existing antibiotics, it’s critical to find new antibiotics in unconventional places to replace them.”
Earlier this year in a study published in Nature Communications, the team used the APEX to analyse a database of venoms featuring more than 40 million venom encrypted peptides - proteins evolved by animals for attack or as a defense mechanism. The tool flagged 386 compounds of potential interest. From the AI-selected shortlist, the team synthesized 58 venom peptides for laboratory testing: 53 killed drug-resistant bacteria—including Escherichia coli and Staphylococcus aureus—at doses that were harmless to human red blood cells.
Further reading
- How AI could fuel a mammoth antibiotic discovery
- AI targets antimicrobial resistance [C&I premium content]
- Data with discovery
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