08/26/2024 | Press release | Distributed by Public on 08/26/2024 09:51
The average human gut contains roughly 100 trillion microbes, many of which are constantly competing for limited resources. "It's such a harsh environment," says César de la Fuente, presidential assistant professor in bioengineering and in chemical and biomolecular engineering in the School of Engineering and Applied Science, in psychiatry and microbiology in the Perelman School of Medicine, and in chemistry in the School of Arts & Sciences. "You have all these bacteria coexisting, but also fighting each other. Such an environment may foster innovation."
In that conflict, de la Fuente's lab sees potential for new antibiotics, which may one day contribute to humanity's own defensive stockpile against drug-resistant bacteria. After all, if the bacteria in the human gut have to develop new tools in the fight against one another to survive, why not use their own weapons against them?
In a new paper in Cell, the labs of de la Fuente and Ami S. Bhattat Stanford surveyed the gut microbiomes of nearly 2,000 people, discovering dozens of potential new antibiotics. "We think of biology as an information source," says de la Fuente. "Everything is just code. And if we can come up with algorithms that can sort through that code, we can dramatically accelerate antibiotic discovery."
The group focused on peptides, short chains of amino acids, which have previously shown promise as novel antibiotics. "We computationally mined over 400,000 proteins," de la Fuente says, referring to the process whereby AI reads the letters of genetic code and, having been trained on a set of known antibiotics, predicts which genetic sequences might have antimicrobial properties.
"Interestingly, these molecules have a different composition from what has traditionally been considered antimicrobial," says Marcelo D.T. Torres, a research associate in the de la Fuente lab, and the paper's first author. "The compounds we have discovered constitute a new class, and their unique properties will help us understand and expand the sequence space of antimicrobials."
Read more at Penn Engineering Today.