Abstract：Sugarcane mosaic virus (SCMV), one of the most important maize viruses, causes annually serious yield loss in maize (Zea mays) industry. Establishment of sensitive and specific virus detection technique is critical for preventing and controlling SCMV. For this purpose, 8 hybridoma lines (12A10, 10B11, 6A1, 19F3, 15C12, 22A2, 21H3, and 21C12) secreting monoclonal antibodies (MAbs) against SCMV were obtained using the purified virions of SCMV Yunnan isolate (SCMV-YN) as the immunogen and the hybridoma technology. With the obtained hybridomas, the ascitic fluids containing MAbs were produced. Using an indirect-enzyme-linked immunosorbent assay (indirect-ELISA), the titers of 8 ascitic fluids containing MAbs were detected to be 10-6 or 10-7, and all 8 MAbs belonged to IgG1, κ light chain. Western blot assay demonstrated that 3 MAbs (22A2, 21H3 and 6A1) recognized common epitopes on capsid protein (CP) of SCMV Beijing isolates (SCMV-BJ) and SCMV-YN. MAbs 12A10, 15C12, 10B11, 21C12 and 19F3 could only recognize the specific epitopes on SCMV-YN. The dot enzyme-linked immunosorbent assay (dot-ELISA) was established by these prepared MAbs as the first antibody. Results of the specificity analyses of the developed dot-ELISAs indicated that 3 MAbs (22A2, 21H3 and 6A1) and their dot-ELISAs had a positive response when detected SCMV-BJ and SCMV-YN isolates, while other prepared 5 MAbs (12A10, 19F3, 10B11, 21C12 and 15C12) and their dot-ELISAs only had a positive response with SCMV-YN isolate, manifesting that those 5 MAbs could be used to detect and identify SCMV-YN isolate. Sensitivity analyses indicated that the dot-ELISAs based respectively on MAbs 15C12, 10B11, 21H3 or 6A1 were the most sensitive, and their sensitivities were up to 1∶10 240 (W/V, g/mL) dilution for SCMV-infected maize leaf crude extract. Detection sensitivity of the MAbs 19F3 or 12A10 was 1∶5 120 dilution, and 22A2 or 21C12 was 1∶2 560 dilution. The anti-SCMV MAbs and the developed dot-ELISA serological detection assay in present study will provide technology support for detecting and diagnosing SCMV, identifying viral strains, breeding for disease resistance and establishing scientific prevention and control for this viral disease.
