A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a “ping-pong” match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.

Filippi, J., Casti, P., Antonelli, G., Murdocca, M., Mencattini, A., Corsi, F., et al. (2024). Cell electrokinetic fingerprint: a novel approach based on optically induced dielectrophoresis (ODEP) for in-flow identification of single cells. SMALL METHODS, 1-18 [10.1002/smtd.202300923].

Cell electrokinetic fingerprint: a novel approach based on optically induced dielectrophoresis (ODEP) for in-flow identification of single cells

Filippi J.;Casti P.;Antonelli G.;Murdocca M.;Mencattini A.;Corsi F.;D'Orazio M.;Curci G.;Ghibelli L.;Sangiuolo F.;Martinelli E.
2024-01-01

Abstract

A novel optically induced dielectrophoresis (ODEP) system that can operate under flow conditions is designed for automatic trapping of cells and subsequent induction of 2D multi-frequency cell trajectories. Like in a “ping-pong” match, two virtual electrode barriers operate in an alternate mode with varying frequencies of the input voltage. The so-derived cell motions are characterized via time-lapse microscopy, cell tracking, and state-of-the-art machine learning algorithms, like the wavelet scattering transform (WST). As a cell-electrokinetic fingerprint, the dynamic of variation of the cell displacements happening, over time, is quantified in response to different frequency values of the induced electric field. When tested on two biological scenarios in the cancer domain, the proposed approach discriminates cellular dielectric phenotypes obtained, respectively, at different early phases of drug-induced apoptosis in prostate cancer (PC3) cells and for differential expression of the lectine-like oxidized low-density lipoprotein receptor-1 (LOX-1) transcript levels in human colorectal adenocarcinoma (DLD-1) cells. The results demonstrate increased discrimination of the proposed system and pose an additional basis for making ODEP-based assays addressing cancer heterogeneity for precision medicine and pharmacological research.
2024
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore ING-INF/07
English
electrokinetics
machine learning
optically-induced dielectrophoresis
single-cell analysis
wavelet scattering transform
Filippi, J., Casti, P., Antonelli, G., Murdocca, M., Mencattini, A., Corsi, F., et al. (2024). Cell electrokinetic fingerprint: a novel approach based on optically induced dielectrophoresis (ODEP) for in-flow identification of single cells. SMALL METHODS, 1-18 [10.1002/smtd.202300923].
Filippi, J; Casti, P; Antonelli, G; Murdocca, M; Mencattini, A; Corsi, F; D'Orazio, M; Pecora, A; De Luca, M; Curci, G; Ghibelli, L; Sangiuolo, F; Neale, Sl; Martinelli, E
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/364106
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