Issue 41, 2024

Establishment and characterization of noro-VLP measurement by digital ELISA

Abstract

Highly sensitive viral analytical techniques are essential tools for preventing the spread of infections. In this study, we established a digital enzyme-linked immunosorbent assay (ELISA) system to quantify norovirus proteins with high sensitivity. We used norovirus-like particles (noro-VLPs) as a surrogate for norovirus and constructed two digital ELISA systems using two different antibody pairs. The quantitative performance of the noro-VLP measurement using each digital ELISA system was evaluated. Both assay systems exhibited high sensitivity, good linearity, and high stability. The first system exhibited a limit of detection (LOD) of 87 pg mL−1 and correlation coefficient (R2) of 0.9984. Analysis of samples containing 5 ng per mL noro-VLP confirmed inter-assay variation of 5.5%, and intra-assay variation of 5.2%. The second system exhibited an LOD of 19 pg mL−1 and R2 of 0.9984. Analysis of samples containing 5 ng per mL noro-VLP confirmed inter-assay variation of 4.5%, and intra-assay variation of 2.5%. Comparison of the two systems using the same calibrant for unpurified and fractionated noro-VLPs revealed that the quantitative values for unpurified noro-VLPs were the same, whereas those for fractionated noro-VLPs were dramatically different. Our findings indicate that the reactivity to various components in the noro-VLP solution was altered depending on the different antibodies. Furthermore, our study highlights the importance of using appropriate calibrants, which contain the same ratio of components as the noro-VLP analyte, to afford accurate measurements.

Graphical abstract: Establishment and characterization of noro-VLP measurement by digital ELISA

Associated articles

Article information

Article type
Technical Note
Submitted
30 May 2024
Accepted
08 Oct 2024
First published
09 Oct 2024

Anal. Methods, 2024,16, 7089-7094

Establishment and characterization of noro-VLP measurement by digital ELISA

T. Hasegawa, Y. Adachi, K. Saikusa and M. Kato, Anal. Methods, 2024, 16, 7089 DOI: 10.1039/D4AY01012D

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