ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells

The presence of cellular defects of multifactorial nature can be hard to characterize accurately and early due to the complex interplay of genetic, environmental, and lifestyle factors. With this study, by bridging optically-induced dielectrophoresis (ODEP), microfluidics, live-cell imaging, and mac...

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Main Authors: 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
Format: Article
Language:English
Published: American Association for the Advancement of Science (AAAS) 2025-01-01
Series:Cyborg and Bionic Systems
Online Access:https://spj.science.org/doi/10.34133/cbsystems.0234
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author 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
author_facet 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
author_sort Joanna Filippi
collection DOAJ
description The presence of cellular defects of multifactorial nature can be hard to characterize accurately and early due to the complex interplay of genetic, environmental, and lifestyle factors. With this study, by bridging optically-induced dielectrophoresis (ODEP), microfluidics, live-cell imaging, and machine learning, we provide the ground for devising a robotic micromanipulation and analysis system for single-cell phenotyping. Cells under the influence of nonuniform electric fields generated via ODEP can be recorded and measured. The induced responses obtained under time-variant ODEP stimulation reflect the cells’ chemical, morphological, and structural characteristics in an automated, flexible, and label-free manner. By complementing the electrokinetic fingerprint of the cell centroid motion with data on the dynamics of electro-deformation and orientation, we show that subtle differences at the single-cell level can be elucidated. Specifically, here, we demonstrate, for the first time, the ability of the combined ODEP-based robotic and automatic analysis platform to discriminate between primary endometrial stromal cells obtained from fertile patients and patients with disrupted receptivity/selectivity equilibrium. When multiple cells were considered at the patient level, the performance achieved an average accuracy of 98%. Single-cell micro-operation and analysis systems may find a more general application in the clinical diagnosis and management of patients with pathological alterations at the cellular level.
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spelling doaj-art-5becf720ba6b4df19b891f091d86b6be2025-08-20T03:12:20ZengAmerican Association for the Advancement of Science (AAAS)Cyborg and Bionic Systems2692-76322025-01-01610.34133/cbsystems.0234ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary CellsJoanna Filippi0Paola Casti1Valentina Lacconi2Gianni Antonelli3Michele D’Orazio4Giorgia Curci5Carlo Ticconi6Rocco Rago7Massimiliano De Luca8Alessandro Pecora9Arianna Mencattini10Steven L. Neale11Luisa Campagnolo12Eugenio Martinelli13Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.Department of Surgical Sciences, Section of Gynecology and Obstetrics, University of Rome Tor Vergata, Rome, Italy.Department of Gender, Parenting, Child and Adolescent Medicine, Physiopathology of Reproduction and Andrology Unit, Sandro Pertini Hospital, Rome, Italy.Italian Nation Research Council (CNR), Rome, Italy.Italian Nation Research Council (CNR), Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.James Watt School of Engineering, University of Glasgow, Glasgow, UK.Department of Biomedicine and Prevention, Tor Vergata University, 00133 Rome, Italy.Department of Electronic Engineering, University of Rome Tor Vergata, 00133 Rome, Italy.The presence of cellular defects of multifactorial nature can be hard to characterize accurately and early due to the complex interplay of genetic, environmental, and lifestyle factors. With this study, by bridging optically-induced dielectrophoresis (ODEP), microfluidics, live-cell imaging, and machine learning, we provide the ground for devising a robotic micromanipulation and analysis system for single-cell phenotyping. Cells under the influence of nonuniform electric fields generated via ODEP can be recorded and measured. The induced responses obtained under time-variant ODEP stimulation reflect the cells’ chemical, morphological, and structural characteristics in an automated, flexible, and label-free manner. By complementing the electrokinetic fingerprint of the cell centroid motion with data on the dynamics of electro-deformation and orientation, we show that subtle differences at the single-cell level can be elucidated. Specifically, here, we demonstrate, for the first time, the ability of the combined ODEP-based robotic and automatic analysis platform to discriminate between primary endometrial stromal cells obtained from fertile patients and patients with disrupted receptivity/selectivity equilibrium. When multiple cells were considered at the patient level, the performance achieved an average accuracy of 98%. Single-cell micro-operation and analysis systems may find a more general application in the clinical diagnosis and management of patients with pathological alterations at the cellular level.https://spj.science.org/doi/10.34133/cbsystems.0234
spellingShingle 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
ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
Cyborg and Bionic Systems
title ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
title_full ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
title_fullStr ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
title_full_unstemmed ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
title_short ODEP-Based Robotic System for Micromanipulation and In-Flow Analysis of Primary Cells
title_sort odep based robotic system for micromanipulation and in flow analysis of primary cells
url https://spj.science.org/doi/10.34133/cbsystems.0234
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