Using a Genome-Based PCR Primer Prediction Pipeline to Develop Molecular Diagnostics for the Turfgrass Pathogen Acidovorax avenae

Abstract

Acidovorax avenae is the causal agent of bacterial etiolation and decline (BED) of creeping bentgrass, a poorly understood and often misdiagnosed disease that can result in considerable aesthetic and functional damage to golf course putting greens. Current diagnostics of BED are based on laborious culture-based methods. In this work, we employed a novel alignment-free primer prediction pipeline to design diagnostic primers for turfgrass-pathogenic A. avenae using 15 draft genomes of closely related target and nontarget Acidovorax spp. as input. Twenty candidate primer sets specific to turfgrass-pathogenic A. avenae were designed. The specificity and sensitivity of these primer sets were validated via a traditional polymerase chain reaction (PCR) and a real-time PCR assay. Primer sets 0017 and 0019 coupled with an internal oligo probe showed optimal sensitivity and specificity when evaluated with the target pathogen, closely related bacterial species, and microorganisms that inhabit the same host and soil environment. Finally, the accuracy of the newly developed real-time PCR assay was evaluated to detect BED pathogens from BED-symptomatic and asymptomatic turfgrass samples. The diagnostic results produced by the real-time PCR assay were consistent with results of a cultural-based method. This assay will allow quicker and more effective detection of the BED pathogen, thus potentially reducing misdiagnoses and unnecessary usage of fungicides.