Literature DB >> 29665553

Development of microfluidic impedance cytometry enabling the quantification of specific membrane capacitance and cytoplasm conductivity from 100,000 single cells.

Yang Zhao1, Ke Wang2, Deyong Chen2, Beiyuan Fan2, Ying Xu3, Yifei Ye4, Junbo Wang5, Jian Chen6, Chengjun Huang7.   

Abstract

This paper presents a new microfluidic impedance cytometry with crossing constriction microchannels, enabling the characterization of cellular electrical markers (e.g., specific membrane capacitance (Csm) and cytoplasm conductivity (σcy)) in large cell populations (~ 100,000 cells) at a rate greater than 100 cells/s. Single cells were aspirated continuously through the major constriction channel with a proper sealing of the side constriction channel. An equivalent circuit model was developed and the measured impedance values were translated to Csm and σcy. Neural network was used to classify different cell populations where classification success rates were calculated. To evaluate the developed technique, different tumour cell lines, and the effects of epithelial-mesenchymal transitions on tumour cells were examined. Significant differences in both Csm and σcy were found for H1299 and HeLa cell lines with a classification success rate of 90.9% in combination of the two parameters. Meanwhile, tumour cells A549 showed significant decreases in both Csm and σcy after epithelial-mesenchymal transitions with a classification success rate of 76.5%. As a high-throughput microfluidic impedance cytometry, this technique can add a new marker-free dimension to flow cytometry in single-cell analysis.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cellular electrical properties; High throughput; Microfluidic impedance cytometry; Neural network based cell type classification; Single-cell analysis

Mesh:

Year:  2018        PMID: 29665553     DOI: 10.1016/j.bios.2018.04.015

Source DB:  PubMed          Journal:  Biosens Bioelectron        ISSN: 0956-5663            Impact factor:   10.618


  7 in total

1.  Aluminum Oxide-Coated Particle Differentiation Employing Supervised Machine Learning and Impedance Cytometry.

Authors:  Brandon K Ashley; Jianye Sui; Mehdi Javanmard; Umer Hassan
Journal:  IEEE Int Conf Nano Micro Eng Mol Syst       Date:  2022-06-10

2.  Assessment of the electrical penetration of cell membranes using four-frequency impedance cytometry.

Authors:  Tao Tang; Xun Liu; Yapeng Yuan; Tianlong Zhang; Ryota Kiya; Yang Yang; Kengo Suzuki; Yo Tanaka; Ming Li; Yoichiroh Hosokawa; Yaxiaer Yalikun
Journal:  Microsyst Nanoeng       Date:  2022-06-24       Impact factor: 8.006

Review 3.  Application of Microfluidics in Detection of Circulating Tumor Cells.

Authors:  Can Li; Wei He; Nan Wang; Zhipeng Xi; Rongrong Deng; Xiyu Liu; Ran Kang; Lin Xie; Xin Liu
Journal:  Front Bioeng Biotechnol       Date:  2022-05-12

4.  Single-cell microfluidic impedance cytometry: from raw signals to cell phenotypes using data analytics.

Authors:  Carlos Honrado; Paolo Bisegna; Nathan S Swami; Federica Caselli
Journal:  Lab Chip       Date:  2021-01-05       Impact factor: 6.799

5.  Ten-Second Electrophysiology: Evaluation of the 3DEP Platform for high-speed, high-accuracy cell analysis.

Authors:  Kai F Hoettges; Erin A Henslee; Ruth M Torcal Serrano; Rita I Jabr; Rula G Abdallat; Andrew D Beale; Abdul Waheed; Patrizia Camelliti; Christopher H Fry; Daan R van der Veen; Fatima H Labeed; Michael P Hughes
Journal:  Sci Rep       Date:  2019-12-16       Impact factor: 4.379

6.  Single-Cell Electroporation with Real-Time Impedance Assessment Using a Constriction Microchannel.

Authors:  Yifei Ye; Xiaofeng Luan; Lingqian Zhang; Wenjie Zhao; Jie Cheng; Mingxiao Li; Yang Zhao; Chengjun Huang
Journal:  Micromachines (Basel)       Date:  2020-09-16       Impact factor: 2.891

Review 7.  Recent Advances in Electrical Impedance Sensing Technology for Single-Cell Analysis.

Authors:  Zhao Zhang; Xiaowen Huang; Ke Liu; Tiancong Lan; Zixin Wang; Zhen Zhu
Journal:  Biosensors (Basel)       Date:  2021-11-22
  7 in total

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