Development of an immunodiagnostic assay for the detection of .

BACKGROUND/AIM: (SCMV; genus and family ), poses a significant threat to global sugarcane cultivars, including those in Pakistan. The aim of this study was to develop a rapid and effective diagnostic tool for detection of SCMV, enabling timely implementation of control measures to mitigate potential yield losses.

MATERIALS AND METHODS

The study focused on the in silico analysis, physicochemical properties, immunogenicity, and subcellular localization of the SCMV coat protein (CP). The SCMV CP gene was synthesized, cloned, and expressed in . The recombinant fusion CP (rFCP-SCMV) was purified and used to generate polyclonal antibodies (pABs) in mice. The immunogenicity of the antibodies was evaluated through indirect ELISA and RT-PCR.

RESULTS

Epitope prediction using tools like the OptimumAntigen design tool from GenScript, BepiPred, and IEDB identified key B-cell epitopes on the SCMV CP, enhancing the specificity of the antibodies. Structural modeling with SWISS-MODEL and PyMOL provided insights into the 3D structures of viral proteins and their epitopes, aiding in the design of high-affinity antibodies. Molecular docking studies simulated the interaction between antibodies and viral epitopes, enabling the selection of optimal antibody candidates. The synthesized recombinant fusion CP (rFCP-SCMV) was used to produce pAbs in mice. These antibodies exhibited high sensitivity, detecting as low as 100 pg of SCMV protein in indirect ELISA. They also effectively identified SCMV in infected sugarcane field samples, confirmed by RT-PCR. The antibodies maintained high specificity and sensitivity even at a 1:10,000 dilution, proving their efficacy in recognizing both the recombinant protein and virus particles in plant sap.

CONCLUSION

The study reveals a rapid, effective immunodiagnostic technique for detecting SCMV in sugarcane cultivars, offering an accurate alternative to conventional virology methods, reducing contamination risk, and providing a valuable tool for mitigating yield losses.