Discriminating single-bacterial shape using low-aspect-ratio pores

Makusu Tsutsui, Takeshi Yoshida, Kazumichi Yokota, Hirotoshi Yasaki, Takao Yasui, Akihide Arima, Wataru Tonomura, Kazuki Nagashima, Takeshi Yanagida, Noritada Kaji, Masateru Taniguchi, Takashi Washio, Yoshinobu Baba, Tomoji Kawai

研究成果: ジャーナルへの寄稿記事

21 引用 (Scopus)


Conventional concepts of resistive pulse analysis is to discriminate particles in liquid by the difference in their size through comparing the amount of ionic current blockage. In sharp contrast, we herein report a proof-of-concept demonstration of the shape sensing capability of solid-state pore sensors by leveraging the synergy between nanopore technology and machine learning. We found ionic current spikes of similar patterns for two bacteria reflecting the closely resembled morphology and size in an ultra-low thickness-to-diameter aspect-ratio pore. We examined the feasibility of a machine learning strategy to pattern-analyse the sub-nanoampere corrugations in each ionic current waveform and identify characteristic electrical signatures signifying nanoscopic differences in the microbial shape, thereby demonstrating discrimination of single-bacterial cells with accuracy up to 90%. This data-analytics-driven microporescopy capability opens new applications of resistive pulse analyses for screening viruses and bacteria by their unique morphologies at a single-particle level.

ジャーナルScientific reports
出版物ステータス出版済み - 12 1 2017


All Science Journal Classification (ASJC) codes

  • General


Tsutsui, M., Yoshida, T., Yokota, K., Yasaki, H., Yasui, T., Arima, A., ... Kawai, T. (2017). Discriminating single-bacterial shape using low-aspect-ratio pores. Scientific reports, 7(1), [17371]. https://doi.org/10.1038/s41598-017-17443-6