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Clavibacter is an agriculturally important genus comprising a single species, Clavibacter michiganensis, and multiple subspecies, including, C. michiganensis subsp. nebraskensis which causes Goss's wilt/blight of corn, accounts for high yield losses and is listed among the five most significant diseases of corn in the United States of America. Our research objective was to develop a robust and rapid multiplex TaqMan real-time PCR (qPCR) to detect C. michiganensis in general and C. michiganensis subsp. nebraskensis with enhanced reliability and accuracy by adding non-complementary AT sequences to the 5' end of the forward and reverse primers. Comparative genomic analyses were performed to identify unique and conserved gene regions for primer and probe design. The unique genomic regions, ABC transporter ATP-binding protein CDS/ABC-transporter permease and MFS transporter were determined for specific detection of C. michiganensis and C. m. subsp. nebraskensis, respectively. The AT-rich sequences at the 5' position of the primers enhanced the reaction efficiency and sensitivity of rapid qPCR cycling; the reliability, accuracy and high efficiency of the developed assay was confirmed after testing with 59 strains from inclusivity and exclusivity panels-no false positives or false negatives were detected. The assays were also validated through naturally and artificially infected corn plant samples; all samples were detected for C. michiganensis and C. m. subsp. nebraskensis with 100% accuracy. The assay with 5' AT-rich sequences detected up to 10- and 100-fg of C. michiganensis and C. michiganensis subsp. nebraskensis genome targets, respectively. No adverse effect was observed when sensitivity assays were spiked with host genomic DNA. Addition of 5' AT-rich sequences enhanced the qPCR reaction efficiency from 0.82 (M = -3.83) and 0.91 (M = -3.54) to 1.04 (with optimum slope value; M = -3.23) for both C. michiganensis and C. michiganensis subsp. nebraskensis, respectively; an increase of 10-fold sensitivity was also obtained with C. michiganensis primer set. The methodology proposed here can be used to optimize reaction efficiency and to harmonize diagnostic protocols which have prodigious applications in routine diagnostics, biosecurity and microbial forensics.

A DNA marker that distinguishes plant associated bacteria at the species level and below was derived by comparing six sequenced genomes of Xanthomonas, a genus that contains many important phytopathogens. This DNA marker comprises a portion of the dnaA replication initiation factor (RIF). Unlike the rRNA genes, dnaA is a single copy gene in the vast majority of sequenced bacterial genomes, and amplification of RIF requires genus-specific primers. In silico analysis revealed that RIF has equal or greater ability to differentiate closely related species of Xanthomonas than the widely used ribosomal intergenic spacer region (ITS). Furthermore, in a set of 263 Xanthomonas, Ralstonia and Clavibacter strains, the RIF marker was directly sequenced in both directions with a success rate approximately 16% higher than that for ITS. RIF frameworks for Xanthomonas, Ralstonia and Clavibacter were constructed using 682 reference strains representing different species, subspecies, pathovars, races, hosts and geographic regions, and contain a total of 109 different RIF sequences. RIF sequences showed subspecific groupings but did not place strains of X. campestris or X. axonopodis into currently named pathovars nor R. solanacearum strains into their respective races, confirming previous conclusions that pathovar and race designations do not necessarily reflect genetic relationships. The RIF marker also was sequenced for 24 reference strains from three genera in the Enterobacteriaceae: Pectobacterium, Pantoea and Dickeya. RIF sequences of 70 previously uncharacterized strains of Ralstonia, Clavibacter, Pectobacterium and Dickeya matched, or were similar to, those of known reference strains, illustrating the utility of the frameworks to classify bacteria below the species level and rapidly match unknown isolates to reference strains. The RIF sequence frameworks are available at the online RIF database, RIFdb, and can be queried for diagnostic purposes with RIF sequences obtained from unknown strains in both chromatogram and FASTA format.