In situ self-referenced intracellular two-electrode system for enhanced accuracy in single-cell analysis

Biosens Bioelectron. 2024 Jun 1:253:116173. doi: 10.1016/j.bios.2024.116173. Epub 2024 Feb 28.

Abstract

Since the emergence of single-cell electroanalysis, the two-electrode system has become the predominant electrochemical system for real-time behavioral analysis of single-cell and multicellular populations. However, due to the transmembrane placement of the two electrodes, cellular activities can be interrupted by the transmembrane potentials, and the test results are susceptible to influences from factors such as intracellular solution, membrane, and bulk solution. These limitations impede the advancement of single-cell analysis. Here, we propose a highly miniaturized and integrated in situ self-referenced intracellular two-electrode system (IS-SRITES), wherein both the working and reference electrodes are positioned inside the cell. Additionally, we demonstrated the stability (0.28 mV/h) of the solid-contact in situ Ag/AgCl reference electrode and the ability of the system to conduct standard electrochemical testing in a wide pH range (pH 6.0-8.0). Cell experiments confirmed the non-destructive performance of the electrode system towards cells and its capacity for real-time monitoring of intra- and extracellular pH values. Moreover, through equivalent circuits, finite element simulations, and drug delivery experiments, we illustrated that the IS-SRITES can yield more accurate test results and exhibit enhanced resistance to interference from the extracellular environment. Our proposed system holds the potential to enable the precise detection of intracellular substances and optimize the existing model of the electrode system for intracellular signal detection, thereby spearheading advancements in single-cell analysis.

Keywords: Drug delivery; Intracellular sensing; Nanopipette; Self-referenced electrode; Two-electrode system; pH sensing.

MeSH terms

  • Biosensing Techniques* / methods
  • Electrodes
  • Single-Cell Analysis