Genome-Guided TaqMan qPCR for Detection of Xanthomonas albilineans and Quantitative Interpretation of Pathogen Abundance in Sugarcane Leaf Scald.

Abstract

Sugarcane leaf scald, caused by Xanthomonas albilineans, is difficult to diagnose because latent infections often precede symptom development, allowing infected planting material to disseminate the pathogen unnoticed. Although quantitative PCR (qPCR) has substantially improved pathogen detection, most available assays target conserved ribosomal regions, which can limit species-level discrimination and offer little guidance for interpreting pathogen abundance. Comparative genomic analysis identified Xal_000736 as a candidate species-specific target for assay development. A TaqMan qPCR assay targeting this locus was developed and evaluated using purified genomic DNA, bacterial suspensions, plant matrix-matched standards, six X. albilineans isolates, 21 non-target bacterial strains, and naturally or artificially infected sugarcane samples. Assay performance was directly compared with that of the previously described 16S rRNA-based xal-FR assay. The biological significance of pathogen abundance was further examined using correlation analysis, logistic regression, receiver operating characteristic (ROC) analysis, and generalized linear mixed-effects models (GLMMs). The 0736 assay showed high amplification efficiency, excellent linearity, and reproducible quantification throughout the validated dynamic range. Quantitative performance was comparable between the two assays, whereas the 0736 assay achieved substantially greater analytical specificity against the bacterial panel examined. ROC analysis also produced a higher area under the curve for the 0736 assay, although the difference between assays was not statistically significant. Pathogen abundance increased with disease severity but overlapped considerably among adjacent symptom classes, indicating that bacterial abundance alone could not fully distinguish disease status. Logistic regression identified quantitative reference values associated with symptom transition and diagnostic classification, while mixed-effects modelling confirmed that the relationship between pathogen abundance and disease status remained significant after accounting for cultivar-related variation. Together, these results show that genome-guided target selection can improve analytical specificity without compromising quantitative performance. They also provide a quantitative basis for interpreting qPCR-derived pathogen abundance in sugarcane leaf scald. Because the proposed reference values were derived from the populations and sampling conditions included in this study, independent validation across additional cultivars, environments, and pathogen populations will be required before routine diagnostic or regulatory use.