Systematic optimization of UCNPs-LFA for Helicobacter pylori nucleic acid detection at point-of-care.

ABSTRACT

Helicobacter pylori (Hp) prevail globally as the primary cause of gastritis, gastric ulcer, and potential gastric cancer, highlighting the need for rapid and precise point-of-care (POC) detection of Hp nucleic acid. Upconversion nanoparticle-based lateral flow assay (UCNPs-LFA) exhibit great potential in POC detection, due to their high optical stability and absence of background fluorescence. However, insufficient sensitivity for nucleic acid detection remains a key challenge. This study systematically optimizes UCNPs-LFA by focusing on target capture, signal transduction, signal separation, and signal analysis, to enhance its detection capabilities for Hp nucleic acid. The optimized UCNPs-LFA platform features a significantly decreased detection limit, a broadened detection range, and high reliability. Results demonstrate that the limit of detection (LOD) is 25 fM, a 105-fold improvement over the initial platform. This systematic optimization strategy is versatile and can be applied to optimize other nanoparticle-based LFAs.