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An autonomous microchip for real-time, label-free immune cell analysis.
Arifuzzman, A K M; Asmare, Norh; Ozkaya-Ahmadov, Tevhide; Civelekoglu, Ozgun; Wang, Ningquan; Sarioglu, A Fatih.
Affiliation
  • Arifuzzman AKM; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Asmare N; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Ozkaya-Ahmadov T; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Civelekoglu O; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • Wang N; School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, 30332, USA.
  • 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 Technolog
Biosens Bioelectron ; 222: 114916, 2023 Feb 15.
Article in En | MEDLINE | ID: mdl-36462431
ABSTRACT
Characterization of cell populations and identification of distinct subtypes based on surface markers are needed in a variety of applications from basic research and clinical assays to cell manufacturing. Conventional immunophenotyping techniques such as flow cytometry or fluorescence microscopy require immunolabeling of cells, expensive and complex instrumentation, skilled operators, and are therefore incompatible with field deployment and automated cell manufacturing systems. In this work, we introduce an autonomous microchip that can electronically quantify the immunophenotypical composition of a cell suspension. Our microchip identifies different cell subtypes by capturing each in different microfluidic chambers functionalized against the markers of the target populations. All on-chip activity is electronically monitored by an integrated sensor network, which informs an algorithm determining subpopulation fractions from chip-wide immunocapture statistics in real time. Moreover, optimal operational conditions within the chip are enforced through a closed-loop feedback control on the sensor data and the cell flow speed, and hence, the antibody-antigen interaction time is maintained within its optimal range for selective immunocapture. We apply our microchip to analyze a mixture of unlabeled CD4+ and CD8+ T cell sub-populations and then validated the results against flow cytometry measurements. The demonstrated capability to quantitatively analyze immune cells with no labels has the potential to enable not only autonomous biochip-based immunoassays for remote testing but also cell manufacturing bioreactors with built-in, adaptive quality control.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biosensing Techniques Language: En Journal: Biosens Bioelectron Journal subject: BIOTECNOLOGIA Year: 2023 Document type: Article Affiliation country:

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Biosensing Techniques Language: En Journal: Biosens Bioelectron Journal subject: BIOTECNOLOGIA Year: 2023 Document type: Article Affiliation country:
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