A research paper by scientists at University of Rome Tor Vergata represented proof of principle of the use of optically-induced dielectrophoresis (ODEP) analysis for the classification of patient-derived endometrial stromal cells, which could be exploited to help clinicians to stratify patients experiencing reproductive failure.
The new research paper, published on Mar. 6 in the journal Cyborg and Bionic Systems, provided the ground for devising a robotic micromanipulation and analysis system for single-cell phenotyping by bridging ODEP, microfluidics, live-cell imaging, and machine learning.
The presence of cellular defects of multifactorial nature can be hard to character-ize accurately and early due to the complex interplay of genetic, environmental, and lifestyle factors. Techniques such as micropipette aspiration, atomic force microscopy, Raman spectroscopy, or tweezers exploiting optical, optoelectronic, magnetic, and acoustic principles offer unique insights and are continually evolving to provide data not only on the cell organization structure but also on the way cells sense and respond to the surrounding microenvironment. "Paired with the analytical capabilities of the methods, devising an automated micro-operation system is also pivotal to facilitate efficient management of the pipeline for cell analysis." Explained study author Eugenio Martinelli, a professor at University of Rome Tor Vergata. However, most of them have limited temporal or spatial resolution or do not possess the reconfiguration properties required to be extended to multiple biological experimental domains.
Optoelectronic tweezers, also known as ODEP, exploiting a locally nonuniform electric field concentrated by virtual electrodes, provide powerful versatility and large forces with low light power intensity (10−2 to 10 W/cm2). This unique feature, paired with electrode reconfigurability, allows easy adaptation to diversified biological case studies and the elucidation of diversified local cell properties. Provided the extreme flexibility of projected light patterns, ODEP represents a powerful technology for single-cell manipulation and characterization. Studies in the literature have demonstrated incredible ODEP performance for the characterization of bacteria subclones with antibiotic resistance, manipulation and sorting of circulating tumor cells, recognition of cell types with different levels of drug resistance and viability, apoptosis levels even at the very early stage, differentiation of cell populations and chemotherapy effects, as well as different transcript levels of selected genes. "These achievements have been sustained by technological developments in the microfluidics and microfabrication, allowing for handling cells in scenarios of lab-on-chips. These devices provide an environment with controllable experimental conditions, e.g., laminar flow, possibility of serialization and parallelization of operations, integrability with live-cell microscopy, and machine learning modules." said Joanna Filippi.
ODEP has also allowed to extract a portrait of the cell heterogeneity in the presence of nonuniform electric fields. "In particular, with an in-flow ODEP platform, we demonstrated the close link between cell frequency-dependent dielectric characteristics and ODEP-induced motions, paired with the possibility to analyze single cells based on the electrokinetics of their centroid." said Joanna Filippi. With this in mind, in this work, we propose a robotic system for the in-flow micromanipulation, measurement, and analysis of single cells. The automated control system allows to fully harness the ODEP concept by projecting highly reconfigurable electrodes and by varying the stimuli characteristics over time. Such a system enables the collection and elucidation of a set of cell responses to better represent their phenotypes and so increase the analytical perspective.
To fully assess the potential diagnostic and prognostic applications of the proposed approach, the authors investigated, for the first time, the electrokinetic patterns of patient-de-rived primary endometrial stromal cells in response to ODEP at the single-cell level, aiming to stratify patients according to their reproductive history. To this end, we enrolled in the study fertile patients and patients with 2 types of recurrent reproductive failure (RRF), namely, recurrent implantation failure (RIF) and unexplained recurrent pregnancy loss (uRPL). They demonstrated that endometrial cells derived from fertile, RIF, and uRPL patients exhibit different dielectric responses, not only in terms of electrokinetics of the cell centroid but also in terms of cell electrokinetics of deformation and orientation. These pieces of information may complement standard biological investigations to allow dis-crimination of the 3 conditions. Totally, this lays the foundation for future applications of ODEP-based robotic systems to support cell characterization in the presence of multifactorial defects.
Authors of the paper include Joanna Filippi, Paola Casti, Valentina Lacconi, Gianni Antonelli, Michele D'Orazio, Giorgia Curci, Carlo Ticconi, Rocco Rago, Massimiliano De Luca, Alessandro Pecora, Arianna Mencattini, Steven L. Neale, Luisa Campagnolo, Eugenio Martinelli.
The paper, "ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells" was published in the journal Cyborg and Bionic Systems on Mar 6, 2025, at DOI: 10.34133/cbsystems.0234.
