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Lateral Flow Immunochromatographic Assay for Adenovirus Antibody Detection in Human Serum Using Gold Nanoparticles and Quantum Dots

Submitted:

14 July 2026

Posted:

15 July 2026

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Abstract
Background/Objectives: Human adenoviruses (HAdVs) are widely used as vectors for vaccines and gene therapy; however, pre-existing immunity can reduce their efficacy. Therefore, rapid and accessible serological methods are required to assess antibody levels against adenoviruses. Lateral flow immunochromatographic assay (LFIA) sensitivity depends on the label and antigen. In this study, we aimed to develop and evaluate LFIA systems based on gold nanoparticles (GNPs) and quantum dots (QDs) using a recombinant HAdV hexon protein. Methods: A recombinant HAdV hexon protein fragment (rhHAdV, 35 kDa; amino acids A120–R316) was expressed in Escherichia coli and purified using Ni2+ affinity chromatography. Protein identity was confirmed using sodium dodecyl sulfate-polyacrylamide gel electrophoresis, western blotting, and liquid chromatography–tandem mass spectrometry analyses. Two LFIA formats were developed using Protein G-conjugated GNPs (GNP-G) and QDs (QD-G). Analytical sensitivity was evaluated using serial dilutions of positive serum samples. Diagnostic performance was assessed using 90 human serum samples and compared with that of a commercial enzyme-linked immunosorbent assay (ELISA). Results: The rhHAdV antigen demonstrated high immunoreactivity in ELISA. Antibody detection was achieved at serum dilutions of up to 1:300 and 1:1000 for the GNP- and QD-based LFIA, respectively. Both LFIA formats showed high specificity (98.2%). Sensitivity was 96.9% and 100% for GNP-G and QD-G, respectively; ROC analysis demonstrated excellent diagnostic accuracy, with AUC values of 0.976 and 0.991, respectively. Conclusions: The findings of this study highlight the potential of QD-based LFIA as an advanced tool for rapid serodiagnostics and large-scale immunological monitoring.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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