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Data from: A surface acoustic wave (SAW)-based lab-on-chip for the detection of active α-glycosidase

Cite this dataset

Gagliardi, Mariacristina et al. (2022). Data from: A surface acoustic wave (SAW)-based lab-on-chip for the detection of active α-glycosidase [Dataset]. Dryad.


Enzyme detection in liquid samples is a complex laboratory procedure, based on assays that are generally time- and cost-consuming, and require specialized personnel. Surface acoustic wave sensors can be used for this application, overcoming the cited limitations. To give our contribution, in this work we present the bottom-up development of a surface acoustic wave biosensor to detect active α-glycosidase in aqueous solutions. Our device, optimized to work at an ultra-high frequency (around 740 MHz), is functionalized with a newly synthesized probe 7-mercapto-1-eptyl-D-maltoside, bringing one maltoside terminal moiety. The probe is designed ad hoc for this application and tested in-cuvette to analyze the enzymatic conversion kinetics at different times, temperatures and enzyme concentrations. Preliminary data are used to optimize the detection protocol with the SAW device. In around 60 min, the SAW device is able to detect the enzymatic conversion of the maltoside unit into glucose in the presence of the active enzyme. We obtained successful α-glycosidase detection in the concentration range 0.15–150 U/mL, with an increasing signal in the range up to 15 U/mL. We also checked the sensor performance in the presence of an enzyme inhibitor as a control test, with a signal decrease of 80% in the presence of the inhibitor. The results demonstrate the synergic effect of our SAW Lab-on-a-Chip and probe design as a valid alternative to conventional laboratory tests.


UV data were acquired via UV-Vis spectroscopy with a JASCO V550 spectrophotometer (JASCO Europe, Cremello, Italy); the raw data were used without any further processing.

QCM data were acquired with a QCM-D E4 model (Q-Sense AB, Sweden); the raw data were processed by MATLAB to eliminate any offset or drift.

SAW-LoC data were acquired with a vectorial network analyzer E5071C (Agilent Technologies) connected to an RF switch 34980A (Agilent Technologies); an in-house software based on LabView® is used to pilot the RF-switch and the vectorial network analyzer.

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Regione Toscana, Award: CUP CIPE: D51B18000750009