IntroductionBovine viral diarrhea virus (BVDV), a positive-sense single-stranded RNA virus, causes significant economic losses in the cattle industry. Current diagnostic methods for BVDV exhibit variable sensitivity and specificity, underscoring the need for more rapid and accurate detection approaches. Here, we developed a novel competitive ELISA (cELISA) to detect antibodies against the BVDV E2 protein.Methods and resultsWe generated three monoclonal antibodies (mAbs)—3E6, 2D5, and 5B9—by immunizing mice with purified BVDV E2 protein expressed in Expi293F cells. Among these, mAb 3E6 displayed superior competitive binding abilities to the E2 protein, enabling effective differentiation between BVDV positive and negative sera. Remarkably, mAb 3E6 exhibited pan-genotypic recognition of various BVDV strains, including BVDV-1a, -1b, -1c, -1m, -1p, -1v, and -2a, while showing no cross-reactivity with the classical swine fever virus (CSFV). Computational modeling using AlphaFold 3 identified domain B of the E2 protein as the primary binding site for mAb 3E6. Building upon these findings, we established a cELISA employing mAb 3E6 and recombinant E2 protein. Receiver-operating characteristic (ROC) analysis revealed outstanding diagnostic performance, achieving a sensitivity of 99.26% and specificity of 98.99%. Further tests confirmed the cELISA's specificity for detecting BVDV-specific antibodies, with no cross-reactivity with antisera from animals infected or immunized against BCoV, BHV-1, BRV, AKAV, LSDV, BLV, and CSFV. Consistency was observed between results from the BVDV E2 cELISA and traditional virus neutralization test (VNT), demonstrating high sensitivity for monitoring antibody dynamics. In performance evaluations, the established cELISA exhibited high concordance with VNT in assessing 160 vaccinated sera and 190 clinical samples.DiscussionThe BVDV E2 cELISA, utilizing mAb 3E6 to target domain B of the BVDV E2 protein, represents a reliable and effective serological diagnostic tool for the detection of antibodies against both BVDV-1 and BVDV-2. This methodology holds significant promise for applications in clinical diagnosis and the evaluation of vaccine efficacy.