
By KIM BELLARD
Most of us can identify dogs from cats just by the sounds they make. We could probably even separate a dog’s bark from a wolf’s howl. If you are a nature lover, you might be able to identify different species of birds by their calls. If you are a cetologist, you might be able to separate the vocalizations whales make versus those dolphins make. Across the animal world, we’ve learned the different sounds that different species make, which has been useful in our survival.
But did you ever wonder if you can identify, say, e coli from other bacteria?
It turns out that you can, thanks to research at Delft University of Technology (TU Delft) in the Netherlands. Four years ago, they showed that bacteria made noise, which was, in itself, a startling finding (admit it: would you have ever guessed that?). They used a thin layer of graphene to create a graphene “drum” small enough to fit a single bacterium. Team member Cees Dekker observed: “What we saw was striking! When a single bacterium adheres to the surface of a graphene drum, it generates random oscillations with amplitudes as low as a few nanometers that we could detect. We could hear the sound of a single bacterium!”
The team used this finding to accomplish an important purpose: to find out if bacteria were resistant to specific antibiotics. If an antibiotic was applied and the sound continued; it hadn’t worked. If the sounds stopped, the bacteria had been killed.
The team wasted no time in creating a start-up – SoundCell – to commercialize the finding. It promised to identify the “right” antibiotic in one hour, rather than subjecting patients to rounds of different antibiotics in search of one the bacteria wasn’t resistant to.
The team isn’t resting on their laurels. Some of them got to wondering, huh, I wonder if different bacteria make different sounds. And, their latest research shows, not only do they but, through machine learning, those different species can be distinguished. Team lead Farbod Alijani says. “With this new study, we take a significant leap forward: we show that each bacterial species has its own nanomotion signature.”
Mind. Blown.
The researchers focused on three bacteria that are common in hospital settings: E. coli, S. aureus (which causes staph infections) and K. pneumoniae (which causes pneumonia). They tested two different machine learning models; one correctly classified the bacteria 87% of the time, and the other 88% of the time.
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