Broad-range and effective detection of human noroviruses by colloidal gold immunochromatographic assay based on the shell domain of the major capsid protein

Autor: Meng Xu, Feifeng Lu, Chenang Lyu, Qingping Wu, Jumei Zhang, Peng Tian, Liang Xue, Ting Xu, Dapeng Wang
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: BMC Microbiology, Vol 21, Iss 1, Pp 1-10 (2021)
Druh dokumentu: article
ISSN: 1471-2180
DOI: 10.1186/s12866-020-02084-z
Popis: Abstract Background Human noroviruses (HuNoVs) are a major cause of nonbacterial gastroenteritis in all age groups worldwide. HuNoVs can be detected in vitro using molecular assays such as RT-PCR and RT-qPCR. However, these molecular-based techniques require special equipment, unique reagents, experienced personnel, and extended time to obtain results. Besides, the diversity of viral genotypes is high. Therefore, methods that are rapid, broad-range and effective in the detection of HuNoVs are desiderated for screening the feces or vomit of infected people during outbreaks. Results In this study, a colloidal-gold-based immunochromatographic assay (ICA) was developed for effective detection of HuNoVs in clinical samples. Monoclonal antibodies (MAbs) against the shell (S) domain in the major capsid protein of HuNoVs were used in the ICA. The limitations of detection for HuNoVs in clinical samples were 1.2 × 106 genomic copies per gram of stool sample (gc/g) and 4.4 × 105 gc/g for genogroup I and II (GI and GII) HuNoVs, respectively. A total of 122 clinical samples were tested for HuNoVs by ICA and compared against RT-qPCR. The relative sensitivity, specificity and agreement of ICA was 84.2% (95% CI: 83.6–84.8%), 100.0% (95% CI: 98.5–100.0%) and 87.7% (95% CI: 85.6–89.8%), respectively. No cross-reaction with other common enteric viruses or bacteria was observed. The ICA detected a broad range of genotypes, including GI.1, GI.3, GI.4, GI.6, GI.14, GII.2, GII.3, GII.4, GII.6, GII.13, and GII.17 HuNoVs. Conclusions This study demonstrates that ICA targeting the S domain of VP1 is a promising candidate for effectively identifying the different genotypes of HuNoVs in clinical samples with high sensitivity and specificity.
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