CdSe/ZnS quantum dot-labeled antibody fluorescent immunoassay strip for swine acute diarrhea syndrome coronavirus S1 protein detection

Abstract

Swine acute diarrhea syndrome coronavirus (SADS-CoV), a porcine enteropathogenic coronavirus, causes acute diarrhea, vomiting, and death in newborn piglets, leading to economic losses in the pig industry. Previous studies have shown that SADS-CoV can infect a variety of mammalian cell lines, including human-derived cells, indicating its potential public health risk of cross-species transmission. In this study, we successfully expressed the SADS-CoV S1 protein using a eukaryotic expression system and screened monoclonal antibodies 1B8 and 3C9. Antibody 1B8 was used as a detection antibody coupled with quantum dots to synthesize a fluorescent probe, while 3C9 was used as a capture antibody. The assembled fluorescent immunochromatographic strip reacted well with SADS-CoV. The detection limit of this test strip for the S1 protein is 0.78 ng mL−1, and the detection limit for SADS-CoV is 102 TCID50 per mL. No cross-reactions were observed with three common porcine enteric coronaviruses, namely porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV), and porcine deltacoronavirus (PDCoV). Moreover, in the detection of newborn piglets' fecal clinical samples, the results of the test strip were highly consistent with those of quantitative fluorescent PCR. The results indicate that the detection method established in this study can be used for the rapid screening and diagnosis of SADS-CoV infection in pig herds.

Graphical abstract: CdSe/ZnS quantum dot-labeled antibody fluorescent immunoassay strip for swine acute diarrhea syndrome coronavirus S1 protein detection

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Article information

Article type
Paper
Submitted
10 Oct 2025
Accepted
25 Nov 2025
First published
16 Mar 2026

Anal. Methods, 2026, Advance Article

CdSe/ZnS quantum dot-labeled antibody fluorescent immunoassay strip for swine acute diarrhea syndrome coronavirus S1 protein detection

B. Zhang, G. Zhang, J. Zhou, H. Wang, H. Liu, Y. Chen, Y. Qi, X. Zhu, E. Liu, S. Wu and A. Wang, Anal. Methods, 2026, Advance Article , DOI: 10.1039/D5AY01694K

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