Description
Electrokinetic techniques are increasingly adopted to characterize cellular dielectric properties due to their non-invasive and label-free nature [E. O. Adekanmbi et al., 2019]. Among these, electrorotation (ROT) emerges as a particularly accurate method for probing dielectric response at the single-cell level [A. Goater et al., 1999].
ROT involves the application of a rotating electric field with varying frequency to suspended cells, inducing a measurable rotational motion that depends on their dielectric properties. Analysis of the rotation rate as a function of frequency yields a characteristic rotation spectrum, which enables quantitative estimation of key parameters such as membrane capacitance and cytoplasmic conductivity.
Conventional ROT platforms are constrained by complex and expensive instrumentation, predominantly low-frequency operation, and the absence of integrated automation for signal generation and data analysis. This results in workflows that depend heavily on manual procedures reducing reproducibility, limiting throughput, and hindering widespread adoption in biological laboratories.
In this context, we developed the Electro-Cell Physiometry (ECP) Platform, an integrated ROT system that combines hardware, software, and standardized experimental workflows into a single, user-friendly platform [Moscato et al, 2024]. The ECP Platform consists of three main components: (i) a ROT-chip optimized for high-frequency operation; (ii) a High-Frequency Quadrature Signal Generator (HF-QSG) that delivers wideband rotating electric fields for full-spectrum dielectric characterization; and (iii) the ECP-Framework, a computational environment that fully automates ROT experiments, including cell segmentation, tracking, angular velocity calculation, and dielectric parameter extraction [Moscato et al., 2025].
The ECP platform was initially validated in the low-frequency regime (30 kHz–1 MHz) [Moscato et al., 2024]. Distinct area-specific membrane capacitances were measured, with CaCo-2 cells showing the highest values (25.47 ± 4.6 mF/m²), CCD-841 intermediate values (19.02 ± 1 mF/m²), and OPM2 the lowest (12.58 ± 1.1 mF/m²). Statistical analysis confirmed these differences to be significant, reflecting distinct membrane structures and demonstrating the system’s ability to resolve meaningful dielectric variations.
Subsequently, full-spectrum ROT measurements were performed up to 200 MHz on HL-60 and HeLa cells, covering both low- and high-frequency regimes. Low-frequency measurements revealed cell-specific membrane properties, with statistically significant differences in membrane capacitance (HL-60: 14.8 ± 2.68 mF/m²; HeLa: 30.4 ± 5.74 mF/m²). High-frequency analysis further enabled the estimation of cytoplasmic conductivity, which was found to be comparable between the two cell lines (HL-60: 0.516 ± 0.14 S/m; HeLa: 0.425 ± 0.07 S/m). These results demonstrate the platform’s capability to extract both membrane and cytoplasmic dielectric parameters reliably, highlighting its potential for comprehensive single-cell characterization across a broad frequency spectrum.
Overall, the proposed ECP platform advances electrorotation beyond a specialized laboratory technique, establishing a standardized, automated, and accessible system for cell dielectric characterization, enabling simultaneous manipulation and measurement of multiple cells within a high-throughput platform.
Future work will focus on integrating microfluidic architectures with embedded flow-control functionalities to support fully automated sample replacements, including cell transport, and repositioning, while leveraging AI-enhanced analysis for real-time angular velocity estimation and further advancing embedded optics toward a compact, self-contained electrorotation system.