Development and evaluation of a monoclonal antibody-based competitive ELISA for detecting porcine deltacoronavirus antibodies

Abstract Porcine deltacoronavirus (PDCoV) is an emerging swine enteropathogenic coronavirus that can cause acute diarrhea and vomiting in newborn piglets and poses a potential risk for cross-species transmission. It is necessary to develop an effective serological diagnostic tool for the surveillance of PDCoV infection and vaccine immunity effects. In this study, we developed a monoclonal antibody-based competitive ELISA (cELISA) that selected the purified recombinant PDCoV nucleocapsid (N) protein as the coating antigen to detect PDCoV antibodies. To evaluate the diagnostic performance of the cELISA, 122 swine serum samples (39 positive and 83 negative) were tested and the results were compared with an indirect immunofluorescence assay (IFA) as the reference method. By receiver operating characteristic (ROC) curve analysis, the optimum cutoff value of percent inhibition (PI) was determined to be 26.8%, which showed excellent diagnostic performance, with an area under the curve (AUC) of 0.9919, a diagnostic sensitivity of 97.44% and a diagnostic specificity of 96.34%. Furthermore, there was good agreement between the cELISA and virus neutralization test (VNT) for the detection of PDCoV antibodies, with a coincidence rate of 92.7%, and the κ analysis showed almost perfect agreement (κ = 0.851). Overall, the established cELISA showed good diagnostic performance, including sensitivity, specificity and repeatability, and can be used for diagnostic assistance, evaluating the response to vaccination and assessing swine herd immunity.

Authors

Institutions

Publication Details

Journal
Animal Diseases
Published
2024-09-13
DOI
https://doi.org/10.1186/s44149-024-00137-8
Citations
2
Primary Topic
Animal Virus Infections Studies
Type
article
Field-Weighted Citation Impact
0.68

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Development and evaluation of a monoclonal antibody-based competitive ELISA for detecting porcine deltacoronavirus antibodies

Jizong Li, Baochao Fan, Bin Li, Shanshan Yang et al.
2 citations
Animal Diseases
Animal Virus Infections Studies
0.68
article

Development and evaluation of a monoclonal antibody-based competitive ELISA for detecting porcine deltacoronavirus antibodies

Jizong Li, Baochao Fan, Bin Li, Shanshan Yang, Xuehan Zhang, Jinzhu Zhou, Wei Wang, Yongxiang Zhao, Junming Zhou, Rongli Guo
article en
2 citations

Abstract

Abstract Porcine deltacoronavirus (PDCoV) is an emerging swine enteropathogenic coronavirus that can cause acute diarrhea and vomiting in newborn piglets and poses a potential risk for cross-species transmission. It is necessary to develop an effective serological diagnostic tool for the surveillance of PDCoV infection and vaccine immunity effects. In this study, we developed a monoclonal antibody-based competitive ELISA (cELISA) that selected the purified recombinant PDCoV nucleocapsid (N) protein as the coating antigen to detect PDCoV antibodies. To evaluate the diagnostic performance of the cELISA, 122 swine serum samples (39 positive and 83 negative) were tested and the results were compared with an indirect immunofluorescence assay (IFA) as the reference method. By receiver operating characteristic (ROC) curve analysis, the optimum cutoff value of percent inhibition (PI) was determined to be 26.8%, which showed excellent diagnostic performance, with an area under the curve (AUC) of 0.9919, a diagnostic sensitivity of 97.44% and a diagnostic specificity of 96.34%. Furthermore, there was good agreement between the cELISA and virus neutralization test (VNT) for the detection of PDCoV antibodies, with a coincidence rate of 92.7%, and the κ analysis showed almost perfect agreement (κ = 0.851). Overall, the established cELISA showed good diagnostic performance, including sensitivity, specificity and repeatability, and can be used for diagnostic assistance, evaluating the response to vaccination and assessing swine herd immunity.

Animal DiseasesVol. 4(1)
Ministry of Science and Technology (BA), Shaoxing University (CN), Jiangsu Academy of Agricultural Sciences (CN), Ministry of Agriculture (CA), Ministry of Agriculture and Rural Affairs (CN), Yangzhou University (CN)
Jiangsu Agricultural Science and Technology Innovation Fund, National Natural Science Foundation of China, Government of Jiangsu Province, Zhejiang Sci-Tech University, National Key Research and Development Program of China
Openalex Percentile: Top 32%
Animal Virus Infections Studies
0.68
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.