Back to Search Start Over

Label-free peptide nucleic acid biosensor for visual detection of multiple strains of influenza A virus suitable for field applications.

Authors :
Kumar N
Bhatia S
Pateriya AK
Sood R
Nagarajan S
Murugkar HV
Kumar S
Singh P
Singh VP
Source :
Analytica chimica acta [Anal Chim Acta] 2020 Jan 06; Vol. 1093, pp. 123-130. Date of Electronic Publication: 2019 Sep 25.
Publication Year :
2020

Abstract

Accurate and rapid diagnosis of Influenza A viruses (IAVs) is challenging because of multiple strains circulating in humans and animal populations, and the emergence of new strains. In this study, we demonstrate a simple and rapid strategy for visual detection of multiple strains of IAVs (H1 to H16 subtypes) using peptide nucleic acid (PNA) as a biosensor and unmodified gold nanoparticles (AuNPs) as a reporter. The design principle of the assay is based on the color change on account of free PNA-induced aggregation of AuNPs in the presence of non-complementary viral RNA sequence and vice-versa. The assay could detect IAV RNA with a visual limit of detection of 2.3 ng. The quantification of RNA with a considerable accuracy on a simple spectrophotometer was achieved on plotting the PNA-induced colorimetric changes (absorption ratio of A <subscript>640</subscript> /A <subscript>520</subscript> ) in the presence of a varying concentration of complementary RNA. As a proof-of-concept, the visual assay was validated on 419 avian clinical samples and receiver operating characteristic (ROC) curve analysis showed a high diagnostic specificity (96.46%, 95% CI = 93.8 to 98.2) and sensitivity (82.41%, 95% CI = 73.9 to 89.1) when RT-qPCR was used as reference test. Hence, the simplicity, rapidity, and universality of this strategy make it a potential candidate visual assay for clinical diagnosis and surveillance of IAVs, especially in the resource-limited settings. The proposed strategy establishes new avenues for developing a simple and rapid diagnostic system for viral infections and biomolecules.<br /> (Copyright © 2019 Elsevier B.V. All rights reserved.)

Details

Language :
English
ISSN :
1873-4324
Volume :
1093
Database :
MEDLINE
Journal :
Analytica chimica acta
Publication Type :
Academic Journal
Accession number :
31735205
Full Text :
https://doi.org/10.1016/j.aca.2019.09.060