journal article·2024-02-09

SERS-Based Lateral Flow Immunoassay Combined with Enzymatic Recombinase Amplification for Quantitative, High-Sensitive Detection of Influenza A Virus

Chu-shu Zhu, Siyue Xiong, Chengxuan Wang, Peitao Dong, Xuezhong Wu

ACS Applied Nano Materials· Volume 7· Issue 3
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Abstract

Accurate and convenient diagnosis of the influenza virus is of critical importance to prevent the spread of flu infections and guide therapy and treatment. This work reports the fabrication of a sensitive and quantitative surface-enhanced Raman scattering (SERS)-based lateral flow (LF) strip combined with enzymatic recombinase amplification (ERA) for the highly effective detection of the influenza A virus. Gold-shell silica-core nanoraspberries (NRbs) were used in this SERS-LF strip as a SERS substrate. Practical and convenient detection was accomplished by naked-eye visualization, and highly sensitive quantitative detection was accomplished by monitoring the intensity of the distinct Raman peaks associated with the SERS tags. Under optimal conditions, the sensitivity of this ERA-SERS-LF strip for the DNA standard of the IAV matrix gene is 10 5 copies/mL by naked-eye visualization, and the limit of detection (LOD) was estimated to be 2.63 × 10 3 copies/mL by SERS detection, lowered by nearly 40 times compared with visual results due to the signal enhancement of the SERS tags. Besides, quantitative detection for the DNA standard of the IAV matrix gene was obtained with a wide linear range (2.63 × 10 3 copies/mL to 10 9 copies/mL). Pseudoviruses of IAV and other respiratory viruses could be successfully identified by using the fabricated ERA-SERS-LF strip. Overall, the findings of this study demonstrate the prospects of the use of the ERA-SERS-LF strip as an effective tool for point-of-care testing (POCT) detection of viruses by virtue of its portability, good sensitivity, quantitative detection ability, and outstanding specificity.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Biosensors and Analytical Detection · Respiratory viral infections research · SARS-CoV-2 detection and testing

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

College of Intelligence Science and Technology, National University of Defense Technology, Changsha, Hunan 410073, China

Funding

National Natural Science Foundation of China

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