Citrus tristeza virus (CTV) poses a severe and economically significant threat to global citrus production. While serological detection offers a valuable tool, existing immunoassays often lack sufficient sensitivity and specificity, and the precise epitope information recognized by antibodies remains inadequately characterized. In this study, we developed an efficient double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA) for CTV detection. Purified CTV particles were used to generate monoclonal antibodies (mAbs) in mice. Among six obtained hybridoma lines, mAbs 10A2 and 10D9 exhibited high titers (up to 3.28 × 10⁷ by indirect ELISA; HRP-conjugated 10D9 reached 1.64 × 10⁷ by direct ELISA). Epitope mapping revealed that both mAbs specifically target linear epitopes (aa 1-15 and aa 166-180) within the major coat protein (CP), corresponding to two surface-exposed loop regions, with high conservation confirmed by phylogenetic analysis. For the DAS-ELISA, mAb 10A2 was selected as the capture antibody, and HRP-10D9 was used as the detection antibody. This antibody combination demonstrated high efficiency and specificity for CP, achieving a detection limit of 15.63 ng/mL for recombinant CP. Field surveys in major citrus-growing regions of China (Guangxi, Jiangxi, Zhejiang) using this DAS-ELISA showed positive detection rates of 40.95%, 52.71%, and 27.5%, respectively, exhibiting strong correlativity with reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) (Kappa = 0.938). The developed mAbs and the sensitive, specific DAS-ELISA provide a powerful tool for CTV surveillance and hold significant promise for both agricultural production and research. KEY POINTS: Two monoclonal antibodies were generated using high-quality CTV particles, which target complementary epitopes on the major coat protein.A double-monoclonal antibody sandwich ELISA was developed based on two antibodies, which target complementary epitopes in the outer loop regions of the viral particle.A large-scale epidemiological survey conducted in citrus groves confirmed the method's effectiveness in identifying CTV-infected citrus.
Shang et al. (Mon,) studied this question.