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Data from: Surface Acoustic Wave-based Lab-On-a-Chip for the fast detection of Legionella pneumophila in water

Cite this dataset

Gagliardi, Mariacristina et al. (2023). Data from: Surface Acoustic Wave-based Lab-On-a-Chip for the fast detection of Legionella pneumophila in water [Dataset]. Dryad.


Surface acoustic wave (SAW) -based immuno-biosensors are used for several applications, thanks to their versatility and faster response than conventional analytical methods. SAW immuno-biosensors can be usefully applied to promptly detect bacteria and prevent bacterial infections that can lead to severe diseases. Here, we present a SAW immuno-biosensor to detect Legionella pneumophila in water. Our device, working at ultra-high frequency (740 MHz), is functionalized with an anti-L. pneumophila antibody to maximize the specificity. We report the characteristic curve of the sensor, calculated measuring bacterial samples at known densities, and its related parameters. We also measure L. pneumophila samples contaminated with different Gram-positive and Gram-negative bacterial species (Escherichia coli and Enterococcus faecium) and samples diluted in mains waters. The proposed device is able to detect L. pneumophila in the range from 1×106 to 1×108 CFU/mL, with a limit of blank of 1.22×106 CFU/mL and a limit of detection of 2.01×106 CFU/mL. The nonspecific signal due to contaminant bacteria is very limited and measurements of L. pneumophila are not affected by contamination. We obtain a good detection also in mains water, representing a realistic matrix for L. pneumophila. Our results are encouraging and pave the way to the use of fast, easy-to-use, reliable and precise sensors to prevent bacterial infections in human activities.


Optical densities in the ELISA assay were acquired with a plate reader (ThermoFisher) at 450 nm.

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.

Usage notes

Data files are uploaded as plain text.


Regione Toscana, Award: Bando FAR-FAS 2014 -- CUP CIPE: D51B18000750009

CUP Sviluppo Toscana, Award: 4421.02102014.072000081, with the project “SENSOR -- Novel real time sensors for the detection of microbiological and chemical contamination in environmental and biomedical matrices”