Electronic detection of apoptotic cells on a microchip.

Annexin V assay Apoptosis sensor Cell death detection Electronic cell viability assay Microchip-based apoptosis test Phosphatidylserine externalization

Journal

Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289

Informations de publication

Date de publication:
05 Sep 2024
Historique:
received: 01 04 2024
revised: 02 09 2024
accepted: 04 09 2024
medline: 23 9 2024
pubmed: 23 9 2024
entrez: 22 9 2024
Statut: aheadofprint

Résumé

Robust and rapid detection of apoptosis in cells is crucially needed for diagnostics, drug discovery, studying pathogenic mechanisms and tracking patient response to medical interventions and treatments. Traditionally, the methods employed to detect apoptosis rely on complex instrumentation like flow cytometers and fluorescence microscopes, which are both expensive and complex-to-operate except in centralized laboratories with trained labor. In this work, we introduce a microfluidic device that can screen cells in a suspension for apoptosis markers and report the assays results as electronic data. Specifically, our device identifies apoptotic cells by detecting externalized phosphatidylserine on a cell membrane - a well-established biomarker that is also targeted by fluorophore-based labeling in conventional assays. In our device, apoptotic cells are discriminated from others through biochemical capture followed by transduction of individual capture events into electrical signals via integrated electrical sensors. The developed technology was tested on simulated samples containing controlled amounts of cells with artificially-induced apoptosis and validated by benchmarking against conventional flow cytometry. Combining sample manipulation and electronic detection on a disposable microfluidic chip, our cell apoptosis assay is amenable to be implemented in a variety of settings and therefore has the potential to create new opportunities for cell-based diagnostics and therapeutics and contribute to improved healthcare outcomes on a large scale.

Identifiants

pubmed: 39307034
pii: S0956-5663(24)00756-5
doi: 10.1016/j.bios.2024.116750
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

116750

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

A K M Arifuzzman (AKM)

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Norh Asmare (N)

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Tevhide Ozkaya (T)

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

Aref Valipour (A)

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.

A Fatih Sarioglu (AF)

School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, GA, 30332, USA; Institute for Electronics and Nanotechnology, Georgia Institute of Technology, Atlanta, GA, 30332, USA. Electronic address: sarioglu@gatech.edu.

Classifications MeSH