Literature DB >> 32926042

In-droplet cell separation based on bipolar dielectrophoretic response to facilitate cellular droplet assays.

Song-I Han1, Can Huang, Arum Han.   

Abstract

Precise manipulation of cells within water-in-oil emulsion droplets has the potential to vastly expand the type of cellular assays that can be conducted in droplet-based microfluidics systems. However, achieving such manipulation remains challenging. Here, we present an in-droplet label-free cell separation technology by utilizing different dielectrophoretic responses of two different cell types. Two pairs of angled planar electrodes were utilized to generate positive or negative dielectrophoretic force acting on each cell type, which results in selective in-droplet movement of only one specific cell type at a time. A downstream asymmetric Y-shaped microfluidic junction splits the mother droplet into two daughter droplets, each of which contains only one cell type. The capability of this platform was successfully demonstrated by conducting in-droplet separation from a mixture of Salmonella cells and macrophages, two cell types commonly used as a bacterial pathogenicity analysis model. This technology enable the precise manipulation of cells within droplets, which can be exploited as a critical function in implementing broader ranges of droplet-based microfluidics cellular assays.

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Year:  2020        PMID: 32926042     DOI: 10.1039/d0lc00710b

Source DB:  PubMed          Journal:  Lab Chip        ISSN: 1473-0189            Impact factor:   6.799


  3 in total

Review 1.  Methods of Generating Dielectrophoretic Force for Microfluidic Manipulation of Bioparticles.

Authors:  Elyahb A Kwizera; Mingrui Sun; Alisa M White; Jianrong Li; Xiaoming He
Journal:  ACS Biomater Sci Eng       Date:  2021-04-19

2.  FIDELITY: A quality control system for droplet microfluidics.

Authors:  Han Zhang; Can Huang; Yuwen Li; Rohit Gupte; Ryan Samuel; Jing Dai; Adrian Guzman; Rushant Sabnis; Paul de Figueiredo; Arum Han
Journal:  Sci Adv       Date:  2022-07-08       Impact factor: 14.957

3.  Artificial Intelligence Algorithms Enable Automated Characterization of the Positive and Negative Dielectrophoretic Ranges of Applied Frequency.

Authors:  Matthew Michaels; Shih-Yuan Yu; Tuo Zhou; Fangzhou Du; Mohammad Abdullah Al Faruque; Lawrence Kulinsky
Journal:  Micromachines (Basel)       Date:  2022-02-28       Impact factor: 2.891

  3 in total

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