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Agrodiag PorCoV: A Multiplex Immunoassay for the Differential Diagnosis of Porcine Enteric Coronaviruses

Three different porcine enteric coronaviruses (PECs), i.e., porcine epidemic diarrhea virus (PEDV), transmissible gastroenteritis virus (TGEV) and porcine Deltacoronavirus (PDCoV) are currently circulating in U.S. commercial swine herds. Differential diagnosis of PECs relies on laboratory methods. This study describes the development of an ELISA-like multiplex planar immunoassay based on virus-specific recombinant S1 proteins printed in an array of spots at the bottom of a 96-well microplate for simultaneous detection differential serodiagnosis of PEDV, TGEV, PDCoV in a single sample. The technology overall format and working principle is similar to the solid-phase standard ELISA. After the three typical incubation steps, the reaction was visualized as blue spots which intensity correlated with antibody levels to specific viral antigen target in the array. The diagnostic performance of the assay was evaluated on known status serum samples (n = 480) collected over time (day post-inoculation -7, 0, 7, 14, 21, 28, 35, and 42) from pigs inoculated with PEDV, TGEV Purdue, TGEV Miller, PDCoV (USA/IL/2014), or mock inoculated with culture media under experimental conditions. Antigen-specific cut-offs were selected to ensure 100% diagnostic and analytical specificity for each given antigen target. The overall diagnostic sensitivity was 92% (44/48 positives, 95% confidence interval (CI) 98,100) for PEDV S1, 100% (95/95 positives, 95% CI 98, 100) for TGEV S1, and 98% (47/48 positives, 95% CI 97, 100) for PDCoV S1. The results of this study demonstrate that the AgroDiag PEC multiplex immunoassay is an efficient and reliable test for differential detection and serodiagnosis of PEDV, TGEV and PDCoV.

Malbec R, Kimpston-Burkgren K, Vandenkoornhuyse E, Olivier C, Souplet V, Audebert C, Carrilo-Ávila J, Baum D, Giménez-Lirola L. Agrodiag PorCoV: a multiplex immunoassay for the differential diagnosis of porcine enteric coronaviruses. J Immunol Methods. 2020 June. https://doi.org/10.1016/j.jim.2020.112808