A generalizable nanopore sensor for highly specific protein detection at single-molecule precision

Mohammad Ahmad, Jeung-Hoi Ha, Lauren A. Mayse, Maria F. Presti, Aaron J. Wolfe, Kelsey J. Moody, Stewart N. Loh and Liviu Movileanu ()
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Mohammad Ahmad: Syracuse University
Jeung-Hoi Ha: State University of New York-Upstate Medical University
Lauren A. Mayse: Syracuse University
Maria F. Presti: State University of New York-Upstate Medical University
Aaron J. Wolfe: Syracuse University
Kelsey J. Moody: Syracuse University
Stewart N. Loh: State University of New York-Upstate Medical University
Liviu Movileanu: Syracuse University

Nature Communications, 2023, vol. 14, issue 1, 1-14

Abstract: Abstract Protein detection has wide-ranging implications in molecular diagnostics. Substantial progress has been made in protein analytics using nanopores and the resistive-pulse technique. Yet, a long-standing challenge is implementing specific interfaces for detecting proteins without the steric hindrance of the pore interior. Here, we formulate a class of sensing elements made of a programmable antibody-mimetic binder fused to a monomeric protein nanopore. This way, such a modular design significantly expands the utility of nanopore sensors to numerous proteins while preserving their architecture, specificity, and sensitivity. We prove the power of this approach by developing and validating nanopore sensors for protein analytes that drastically vary in size, charge, and structural complexity. These analytes produce unique electrical signatures that depend on their identity and quantity and the binder-analyte assembly at the nanopore tip. The outcomes of this work could impact biomedical diagnostics by providing a fundamental basis for biomarker detection in biofluids.

Date: 2023
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DOI: 10.1038/s41467-023-36944-9

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