Development of droplet microfluidics capable of quantitative estimation of single-cell multiplex proteins

Yang, Hongyu and Yang, Guang and Zhang, Ting and Chen, Deyong and Wang, Junbo and Chen, Jian (2022) Development of droplet microfluidics capable of quantitative estimation of single-cell multiplex proteins. Journal of Micromechanics and Microengineering, 32 (2). 024002. ISSN 0960-1317

[thumbnail of Yang_2022_J._Micromech._Microeng._32_024002.pdf] Text
Yang_2022_J._Micromech._Microeng._32_024002.pdf - Published Version

Download (1MB)

Abstract

This study presented constriction microchannel based droplet microfluidics realizing quantitative measurements of multiplex types of single-cell proteins with high throughput. Cell encapsulation with evenly distributed fluorescence labelled antibodies stripped from targeted proteins by proteinase K was injected into the constriction microchannel with the generated fluorescence signals captured and translated into protein numbers leveraging the equivalent detection volume formed by constriction microchannels in both droplet measurements and fluorescence calibration. In order to form the even distribution of fluorescence molecules within each droplet, the stripping effect of proteinase K to decouple binding forces between targeted proteins and fluorescence labelled antibodies was investigated and optimized. Using this microfluidic system, binding sites for beta-actin, alpha-tubulin, and beta-tubulin were measured as 1.15 ± 0.59 × 106, 2.49 ± 1.44 × 105, and 2.16 ± 1.01 × 105 per cell of CAL 27 (Ncell = 15 486), 0.98 ± 0.58 × 106, 1.76 ± 1.34 × 105 and 0.74 ± 0.74 × 105 per cell of Hep G2 (Ncell = 18 266). Neural net pattern recognition was used to differentiate CAL 27 and Hep G2 cells, producing successful rates of 59.4% (beta-actin), 64.9% (alpha-tubulin), 88.8% (beta-tubulin), and 93.0% in combination, validating the importance of quantifying multiple types of proteins. As a quantitative tool, this approach could provide a new perspective for single-cell proteomic analysis.

Item Type: Article
Subjects: OA Library Press > Multidisciplinary
Depositing User: Unnamed user with email support@oalibrarypress.com
Date Deposited: 08 Jun 2023 07:33
Last Modified: 24 Jul 2024 09:23
URI: http://archive.submissionwrite.com/id/eprint/1143

Actions (login required)

View Item
View Item