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High-Content Label-Free Single-Cell Analysis with a Microfluidic Device Using Programmable Scanning Electrochemical

Mi Shi1, Lin Wang1, Zhenda Xie2

  • 1Beijing Key Laboratory for Bioengineering and Sensing Technology, School of Chemistry and Biological Engineering, University of Science and Technology Beijing, Beijing 100083, China.

Analytical Chemistry
|August 31, 2021
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Summary

This study introduces a faster, label-free method for analyzing single-cell activity using programmable scanning electrochemical microscopy (P-SECM) and microwells. The technique reveals higher alkaline phosphatase (ALP) activity in cancer cells and its heterogeneous distribution.

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Area of Science:

  • Electrochemistry
  • Cell Biology
  • Microfluidics

Background:

  • Conventional bulk assays obscure cellular heterogeneity and plasticity.
  • Label-based single-cell imaging can disrupt cell homeostasis.
  • Scanning electrochemical microscopy (SECM) offers label-free imaging but is time-consuming for large-scale analysis.

Purpose of the Study:

  • To develop a rapid, label-free method for single-cell analysis.
  • To investigate alkaline phosphatase (ALP) activity in heterogeneous cell populations.
  • To establish a high-content screening platform for single-cell analysis.

Main Methods:

  • Integration of programmable SECM (P-SECM) with an addressable microwell array.
  • Utilized a line scanning approach for rapid topography detection and activity evaluation.
  • Employed dual-mediator voltage-switching (VSM) mode for ALP activity measurement.

Main Results:

  • Achieved a 10-fold increase in speed, analyzing over 900 microwells in 1.2 hours.
  • Detected higher ALP activity in cancer cells compared to other cell types.
  • Revealed heterogeneous distribution of ALP kinetic constants (kf) at the single-cell level.

Conclusions:

  • The P-SECM microwell platform enables high-throughput, label-free single-cell analysis.
  • The method accurately quantifies enzyme activity heterogeneity in cell populations.
  • This scalable platform holds potential for cancer stem cell marker screening and drug discovery.