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Machine learning enabled acoustic detection of sub-nanomolar concentration of trypsin and plasmin in solution...

Publication Type
Journal Name
Sensors and Actuators B: Chemical
Publication Date
Page Numbers
282 to 288

We demonstrate a machine learning enabled low-cost acoustic detection of protease which may find application in assuring quality and safety of dairy products, drug screening, molecular profiling, and disease diagnostics. A hydrophilic SiO2-coated quartz crystal microbalance (QCM) acts as a substrate to assemble α-, β-, and ĸ-casein layers (protease reporters) and as a transducer for measuring changes in frequency as casein is removed by protease. We demonstrate that α-, β-, and ĸ-caseins can form stable assembly on SiO2 from phosphate-buffered solution (PBS) solution. Exposure to protease results in cleaving of casein which changes the frequency of the 1st–11th odd harmonics of QCM. Monitoring β-casein cleavage allows ∼0.2 nM detection of trypsin and ∼0.5 nM detection of plasmin and enables differentiation between trypsin and plasmin after <2 min of protease exposure. The casein-coated QCM allows sub-nanomolar detection and classification of protease.