4.8 Article

Selective Single-Cell Sorting Using a Multisectorial Electroactive Nanowell Platform

Journal

ACS NANO
Volume 16, Issue 1, Pages 211-220

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acsnano.1c05668

Keywords

single-cell sorting; cell capture; nanowell; dielectrophoresis; microfluidics; point-of-care; malignant cell sorting

Funding

  1. MITACS [23446]

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In this paper, a microfluidic platform is introduced to overcome the limitation of cell sorters and achieve selective single-cell sorting by capturing a large number of different cell types. The platform demonstrates high accuracy, versatility, and simplicity, making it suitable for reliable sorting of varying complex samples in clinical environments.
Current approaches in targeted patient treatments often require the rapid isolation of specific rare target cells. Stream-based dielectrophoresis (DEP) based cell sorters have the limitation that the maximum number of sortable cell types is equivalent to the number of output channels, which makes upscaling to a higher number of different cell types technically challenging. Here, we present a microfluidic platform for selective single-cell sorting that bypasses this limitation. The platform consists of 10 000 nanoliter wells which are placed on top of interdigitated electrodes (IDEs) that facilitate dielectrophoresis-driven capture of cells. By use of a multisectorial design formed by 10 individually addressable IDE structures, our platform can capture a large number of different cell types. The sectorial approach allows for fast and straightforward modification to sort complex samples as different cell types are captured in different sectors and therefore removes the need for individual output channels per cell type. Experimental results obtained with a mixed sample of benign (MCF-10A) and malignant (MDA-MB231) breast cells showed a target to nontarget sorting accuracy of over 95%. We envision that the high accuracy of our platform, in addition to its versatility and simplicity, will aid clinical environments where reliable sorting of varying complex samples is essential.

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