Automated nanopore sensing by current-feedback membrane reformation.

Authors

Hiroto Ishizuka, Yuki Nakayama, Shun Okada, Kan Shoji

Published in

Analytica chimica acta. Volume 1424. Pages 346229. Nov 22, 2026. Epub Sep 05, 2026.

Abstract

Stochastic nanopore sensing relies on large numbers of current blockage signals for statistical molecular analysis. Automated formation of planar bilayer lipid membranes (pBLMs) has been reported, but sustaining a single biological nanopore remains challenging, since nanopore reconstitution is inherently probabilistic. Here, we report an automated, current-feedback nanopore sensing platform that autonomously sustains single alpha-hemolysin (αHL) nanopores through repeated pBLM reformation. The sensing platform locates the pBLM formation position by measuring membrane capacitance, recognizes nanopore reconstitution through ion current feedback, and automatically reforms the pBLM once multiple nanopores have reconstituted. We first optimized the experimental parameters, including stage velocity, calibration interval, and αHL concentration, to achieve stable long-term operation. Under these optimized conditions, the system repeatedly formed pBLMs over 6 h with almost no spontaneous membrane rupture, while autonomously maintaining single-nanopore measurements. We then applied the platform to automated stochastic nanopore sensing of single-stranded DNA. Over 3 h of continuous operation, the dwell time, current blockage rate, and translocation event frequency remained unchanged, confirming stable sensing performance during long-term autonomous measurements. These results demonstrate that combining capacitance-based determination of the pBLM formation position with current-feedback-controlled pBLM reformation realizes long-term nanopore measurements with substantially reduced operator intervention. Although signals analyses are currently performed retrospectively, the present platform provides a basis for further development toward fully automated single-molecule analysis.

PMID:
42887973
Bibliographic data and abstract were imported from PubMed on 17 Oct 2026.

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