Improved detection of rice yellow mottle virus with a polyclonal antibody xMAP assay: A high-throughput alternative...

Rice yellow mottle virus (RYMV) is one of the most destructive viral pathogens affecting rice production in sub-Saharan Africa, where its extensive genetic diversity and high evolutionary rate complicate reliable diagnosis. Current serological methods, notably double-antibody sandwich enzyme-linked immunosorbent assay (DAS-ELISA), are widely used for routine detection but may lack sensitivity when viral loads are low or samples are degraded. In this study, we developed and evaluated a high-throughput microsphere immunoassay (MIA) based on Luminex xMAP technology as an alternative serological tool for RYMV detection. A panel of three monoclonal antibodies (mABs) and one polyclonal antibody (pAB), all raised against a RYMV isolate from Madagascar, was assessed using greenhouse-propagated and field-collected rice samples representing all six known RYMV genetic groups. Assay performance was evaluated in terms of sensitivity, specificity, and accuracy using receiver operating characteristic (ROC) curve analysis, and results were compared with those obtained by DAS-ELISA. While mABs failed to retain their expected serotype specificity in the xMAP format, the polyclonal antibody enabled robust and strain-independent detection of RYMV. The pAB-based xMAP assay showed excellent diagnostic performance, with 100% specificity, sensitivity exceeding 97%, and an area under the ROC curve of 0.99. Importantly, the pAB-based xMAP assay demonstrated a 100- to 500-fold increase in sensitivity compared with DAS-ELISA, allowing reliable detection of RYMV in samples with low viral loads or compromised integrity. No cross-reactivity was observed with other co-circulating rice viruses, including maize streak virus and rice stripe necrosis virus. This study demonstrates that a polyclonal antibody-based xMAP immunoassay provides a highly sensitive, specific, and scalable alternative to conventional ELISA for RYMV diagnosis. This approach represents a promising tool for large-scale epidemiological surveys and improved management of rice viral diseases in Africa.