Using encoded hydrogel microparticles in a 96-well filter plate system for enhanced rinsing efficiency in multiplexed nucleic acid detection

Abstract

Accurate and efficient nucleic acid detection is crucial for biomedical applications, including disease diagnostics and molecular-level insights into disease mechanisms. Among various detection methods, hydrogel microparticle-based assays have garnered significant attention for their high sensitivity and multiplexing capability. However, these assays are often hindered by time-consuming, non-reproducible, and unstable rinsing steps, which compromise sensitivity and reliability. While filter plates hold great potential for streamlining the rinsing process, challenges such as sample evaporation and difficulty in temperature control have limited their integration into hydrogel microparticle-based nucleic acid assays. In this study, we present a 96-well filter plate-based detection system incorporating evaporation-minimizing films and printed circuit board heaters. This system enables nucleic acid assays within a filter plate while ensuring uniform temperature control across wells and significantly enhancing rinsing efficiency. Additionally, our platform demonstrates a two-fold improvement in the limit of detection compared to conventional tube-based assays, while maintaining high reproducibility across wells. By addressing the key challenges associated with integrating hydrogel microparticle-based assays with filter plates, this system provides a facile, rapid, reliable, and sensitive approach for multiplex nucleic acid detection.

Graphical abstract: Using encoded hydrogel microparticles in a 96-well filter plate system for enhanced rinsing efficiency in multiplexed nucleic acid detection

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Article information

Article type
Paper
Submitted
31 Jul 2025
Accepted
05 Oct 2025
First published
29 Oct 2025

Anal. Methods, 2025, Advance Article

Using encoded hydrogel microparticles in a 96-well filter plate system for enhanced rinsing efficiency in multiplexed nucleic acid detection

S. J. Mun, H. K. Roh, E. L. Song, J. H. Choi, W. Jang and K. W. Bong, Anal. Methods, 2025, Advance Article , DOI: 10.1039/D5AY01264C

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