Scientists from TU Delft, SoundCell and RHMDC (laboratory of Reinier de Graaf hospital) have discovered that different bacterial species produce their own characteristic sounds. Building on an earlier development from the same team, they have now shown that bacteria can be identified and their antibiotic susceptibility determined simultaneously, based solely on their sound. This combined approach delivers results within hours instead of days, offering a major step forward in the diagnosis and treatment of bacterial infections. The study is published in ACS Sensors.Â
âIn previous work we discovered that nanodrums made of graphene were able to capture the subtle sound of a single bacterium. We used this concept to determine which antibiotics would be effective, which eventually resulted in TU Delft spin-off SoundCell,â explains associate professor Farbod Alijani. âWith this new study, we take a significant leap forward: we show that each bacterial species has its own nanomotion signature.â They developed a machine learning model that can recognise a bacterial species by analysing the unique nanoscale vibrational pattern it produces.
âBy combining SoundCellâs existing antimicrobial testing prototype with this machine learning model, we can identify the bacterial infection and determine which drug is effective at the same time, based purely on the sound of a single bacterium,â says SoundCell CTO, Aleksandre Japaridze. Leo Smeets, physician microbiologist RHMDC adds: âThis approach eliminates the need for culturing, which normally takes days. And because the diagnostic steps are no longer performed sequentially, we can save even more time.â
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