César de la Fuente uses AI to hunt for new antibiotic candidates in unlikely places, from the DNA of extinct organisms to the proteins of ancient microbes.
2 min. read
Some of Earth’s oldest life forms—microbes called Archaea—are offering a new weapon in the fight against one of today’s most urgent health threats: antibiotic resistance.
César de la Fuente (pictured) and his team used AI to study the proteins of hundreds of ancient microbes, searching for new antibiotic candidates.
(Image: Jianing Bai)
In a new study published in Nature Microbiology, researchers at Penn used artificial intelligence to identify previously unknown compounds in Archaea that could fuel the development of next-generation antibiotics.
Because Archaea often thrive where few other organisms can—enduring crushing pressures, toxic chemicals and extreme temperatures—their biology has evolved in unusual ways. This makes them a promising but largely untapped source of new molecular tools, including compounds that may function like antibiotics but operate differently from those currently in use.
Scanning 233 species of Archaea yielded more than 12,000 antibiotic candidates. The researchers dubbed these molecules “archaeasins,” which chemical analysis revealed differ from known antimicrobial peptides (AMPs), particularly in their distribution of electric charge.
The researchers then selected 80 archaeasins to test against actual bacteria. “Trying to find new antibiotics one molecule at a time is like looking for needles in a haystack,” says Fangping Wan, a postdoctoral fellow in de la Fuente’s lab and the paper’s other co-first author. “AI speeds up the process by identifying where the needles are likely to be.”
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