Solid-State Nanopore Platform Integrated with Machine Learning for Digital Diagnosis of Virus Infection

Arima, Akihide; Tsutsui, Makusu; Baba, Yoshinobu; Kawai, Tomoji

doi:10.1021/acs.analchem.0c04353

Cited by 61 publications

(56 citation statements)

References 99 publications

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“… 11 A more general topic on ML-based algorithms for signals from biosensors touches upon nanopore sensing. 12 In addition, mini-reviews on some specific issues of signal processing for nanopore sensors and related sensors can be found, such as ML for identification of single biomolecules, 13 virus detection, 14 and nanopore electrochemistry. 15 Concomitantly, signal processing algorithms for nanopore sensing have been rapidly developed by adopting various strategies and techniques.…”

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confidence: 99%

A Guide to Signal Processing Algorithms for Nanopore Sensors

2021

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Nanopore technology holds great promise for a wide range of applications such as biomedical sensing, chemical detection, desalination, and energy conversion. For sensing performed in electrolytes in particular, abundant information about the translocating analytes is hidden in the fluctuating monitoring ionic current contributed from interactions between the analytes and the nanopore. Such ionic currents are inevitably affected by noise; hence, signal processing is an inseparable component of sensing in order to identify the hidden features in the signals and to analyze them. This Guide starts from untangling the signal processing flow and categorizing the various algorithms developed to extracting the useful information. By sorting the algorithms under Machine Learning (ML)-based versus non-ML-based, their underlying architectures and properties are systematically evaluated. For each category, the development tactics and features of the algorithms with implementation examples are discussed by referring to their common signal processing flow graphically summarized in a chart and by highlighting their key issues tabulated for clear comparison. How to get started with building up an ML-based algorithm is subsequently presented. The specific properties of the ML-based algorithms are then discussed in terms of learning strategy, performance evaluation, experimental repeatability and reliability, data preparation, and data utilization strategy. This Guide is concluded by outlining strategies and considerations for prospect algorithms.

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confidence: 99%

A Guide to Signal Processing Algorithms for Nanopore Sensors

2021

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“…Though there is no explicit role for it in nature and its exact mechanism is not yet known, the regulation of Vh ChiP/chitosan hexaose interaction has potential technical applications. Observations from the plethora of published studies ( 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ) are seen here as possible starting points in explorations of such a nanoscopic functional unit. Recently, carbon nanotubes (CNTs) were successfully incorporated in planar lipid bilayers and shown to function as synthetic porins ( 80 , 81 , 82 ).…”

Section: Discussionmentioning

confidence: 84%

“…This set of experiments does not mimic native conditions, but the results demonstrate the unique possibility to control the flux of molecules and ions through biological nanopores in synthetic membranes through choice of the transmembrane potential and the pH of the electrolyte on either side, if the substrate can, for instance, be adequately positively charged through induced protonation. The application of this principle to modulate nanofluidic ionic diodes, ion-mediated switches, electrostatic nanosieves or ion-mediated nanovalves ( 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 ) is feasible but will require cross-disciplinary collaboration. While the potential for such development certainly exists, it is obviously a challenging task to adapt the fundamental properties of the chitoporin reported in this study to final technical applications.…”

Section: Resultsmentioning

confidence: 99%

“…, ( 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 )) and original articles ( e.g. , ( 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 )) and include, for instance, use as nanoscopic components of ionic circuits ( 45 , 46 , 47 , 48 , 49 ), switches of molecular hydrodynamics and transport ( 50 , 51 , 52 , 53 ), tools for molecular analytics ( 54 , 55 , 56 , 57 , 58 , 59 ), and nanosieving and nanovalves ( 60 , 61 ).…”

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confidence: 99%

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The C2 entity of chitosugars is crucial in molecular selectivity of the Vibrio campbellii chitoporin

Suginta

Sanram

Aunkham

et al. 2021

Journal of Biological Chemistry

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This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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“…These extra structures will provide characteristic local spikes on top of the ionic current blockade signal (Yang et al, 2018). In addition, the integration of machine learning with solid-state nanopore technology made great progress in the digital detection of viruses at a single-particle level (Arima et al, 2021).…”

Section: Nps Detection and Other Applicationsmentioning

confidence: 99%

Single-Entity Detection With TEM-Fabricated Nanopores

Saqib

Hao

2021

Front. Chem.

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Nanopore-based single-entity detection shows immense potential in sensing and sequencing technologies. Solid-state nanopores permit unprecedented detail while preserving mechanical robustness, reusability, adjustable pore size, and stability in different physical and chemical environments. The transmission electron microscope (TEM) has evolved into a powerful tool for fabricating and characterizing nanometer-sized pores within a solid-state ultrathin membrane. By detecting differences in the ionic current signals due to single-entity translocation through the nanopore, solid-state nanopores can enable gene sequencing and single molecule/nanoparticle detection with high sensitivity, improved acquisition speed, and low cost. Here we briefly discuss the recent progress in the modification and characterization of TEM-fabricated nanopores. Moreover, we highlight some key applications of these nanopores in nucleic acids, protein, and nanoparticle detection. Additionally, we discuss the future of computer simulations in DNA and protein sequencing strategies. We also attempt to identify the challenges and discuss the future development of nanopore-detection technology aiming to promote the next-generation sequencing technology.

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Solid-State Nanopore Platform Integrated with Machine Learning for Digital Diagnosis of Virus Infection

Cited by 61 publications

References 99 publications

A Guide to Signal Processing Algorithms for Nanopore Sensors

A Guide to Signal Processing Algorithms for Nanopore Sensors

The C2 entity of chitosugars is crucial in molecular selectivity of the Vibrio campbellii chitoporin

Single-Entity Detection With TEM-Fabricated Nanopores

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