Rapid diagnosis of ocular viral infections via single virus detection using solid-state nanopore: A diagnostic evaluation study

Hashida, Noriyasu, Takei, Hiroyasu, Taniguchi, Masateru, Naono, Norihiko, Soma, Takeshi, Oie, Yoshinori, Maruyama, Kazuichi, Handayani, Lidya, Mori, Yasuko, Quantock, Andrew ORCID: https://orcid.org/0000-0002-2484-3120 and Nishida, Kohji 2025. Rapid diagnosis of ocular viral infections via single virus detection using solid-state nanopore: A diagnostic evaluation study. PNAS Nexus , pgaf161. 10.1093/pnasnexus/pgaf161

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Abstract

Rapid and precise identification and discrimination of causative pathogens are required in the treatment of infectious diseases. Quantitative real-time polymerase chain reaction is used to detect and identify infectious viruses before treatment. Although it is an established modality, results take several hours, even in well-equipped hospitals. It is difficult to simultaneously detect many pathogen types because only a single virus genome can be amplified per polymerase chain reaction. Recently, an artificial intelligence (AI)-based nanopore machine has been used to identify individual viruses based on electrical conductivity. Here, we recognized a single virus using an AI-based detection system and successfully identified viral particles in clinical samples without the need for any prior treatment. We used a nanopore detector and discriminated among viruses using an AI-based waveform analysis. The efficacy of the AI nanopore detector as an on-site clinical analysis device was validated in cultured herpesvirus samples, and its discrimination capability was verified with clinical samples. The AI nanopore analysis of cultured viruses revealed that Alphaherpesvirinae and Betaherpesvirinae within the same Herpesviridae family can be distinguished with a relatively high accuracy. The AI nanopore rapidly detected viral particles and can be useful as an on-site clinical diagnosis tool. We demonstrated the multiplex discrimination of herpetic viruses in clinical ocular samples, proving that the AI nanopore is an ultra-high-speed and highly-sensitive detection tool that can be used in various medical fields.

Item Type:	Article
Date Type:	Published Online
Status:	In Press
Schools:	Schools > Optometry and Vision Sciences
Additional Information:	License information from Publisher: LICENSE 1: URL: https://creativecommons.org/licenses/by-nc/4.0/, Start Date: 2025-05-21
Publisher:	Oxford University Press
Date of First Compliant Deposit:	10 June 2025
Date of Acceptance:	1 May 2025
Last Modified:	10 Jun 2025 11:00
URI:	https://orca.cardiff.ac.uk/id/eprint/178967

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