Marcelo Der Torossian Torres lifted the clear plastic cover off of a petri dish one morning last June. The dish, still warm from its sleepover in the incubator, smelled of rancid broth. Inside it sat a rubbery bed of amber-colored agar, and on that bed lay neat rows of pinpricks—dozens of colonies of drug-resistant bacteria sampled from the skin of a lab mouse.
Torres counted each pinprick softly to himself, then did some quick calculations. Untreated for the infection, the samples taken from an abscess on the mouse had yielded billions of superbugs, or antibiotic-resistant bacteria. But to his surprise, some of the other rows on the petri dish seemed empty. These were the ones corresponding to samples from mice that received an experimental treatment—a novel antibiotic.
Torres dug up other dishes cultured from more concentrated samples, taken from the same mice who had gotten the antibiotic. These didn't look empty. When he counted them up, he found that the antibiotic had nuked the bacterial load so that it was up to a million times sparser than the sample from the untreated mouse. "I got very excited," says Torres, a postdoc specializing in chemistry at the University of Pennsylvania. But this custom antibiotic wasn't entirely his own recipe. It took an artificial intelligence algorithm scouring a database of human proteins to help Torres and his team find it.
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