Aims: To determine the reliable combination of protocols for specific detection and identification of R. solanacearum race 3 biovar 2 (R3bv2) through a comprehensive comparison among currently available techniques. Methods and Results: Sensitivity and specificity of the conventional isolation, bioassay, serological assays, conventional and real-time PCR and multiplex PCR were assessed for the detection of 25 strains of R. solanacearum biovars 1, 2 and 3 (Phylotypes I, II, III and IV) in spiked potato saps. Results indicated that all assays evaluated varied in complexity and sensitivity and should be applied strategically in indexing schemes to maximize efficiency of testing without compromising accuracy of the results. Conclusions: The TaqMan PCR assay, with an internal reaction control and confirmation by melting curve and electrophoretic analysis, achieved best sensitivity at 10 2 -10 3 CFU ml À1 for all eighteen strains of R. solanacearumR3bv2. Selective enrichment on mSMSA medium plates enhanced the detection sensitivity up to 10-100 CFU ml À1 for the conventional PCR-based assays.Significance and Impact of the Study: This is the first time nine different assays were compared side by side for their sensitivity and specificity in detection and identification of R. solanacearum R3bv2. The data accumulated here will provide basis for regulatory applications for low level detection and rapid identification of latently infections caused by R. solanacearum R3bv2.

‘Candidatus Liberibacter solanacearum’ was recently described as the causal agent of potato zebra chip disease. This pathogen occurs in North America, New Zealand, and Northern Europe on various crops, and may spread to other potato growing regions. Observation on ‘Ca. L. solanacearum’‐infected tomato and potato plants propagated in growth chambers over 5 years indicated that tomato plants (cvs Moneymaker and Roma) can be a latent carrier of ‘Ca. L. solanacearum’. Tomato plants graft‐inoculated with scions from latently infected tomato plants remained symptomless, but tested positive in a species specific PCR assay. ‘Ca. L. solanacearum’ was consistently detected in the top, middle and bottom portion of the symptomless tomato plants, including stem, petiole, midrib, vein, flowers and fruits. In tomato fruits, ‘Ca. L. solanacearum’ was evenly distributed in the tissues at the peduncle and style ends, as well as in the pericarp, and columella placenta tissues. This is the first report that ‘Ca. L. solanacearum’ is present in a plant reproductive organ. In contrast, potato plants (cvs. Jemseg, Atlantic, Shepody, Frontier Russet, Russet Burbank, Red Pontiac, and Russet Norkotah) grafted with scions from the same latently infected tomato plants resulted in typical symptoms of purple top, leaf scorch, and other disease symptoms in plants and brown discoloration in the vascular ring and medullary rays in tubers.

Bioinformatic approaches for the identification of microorganisms have evolved rapidly, but existing methods are time-consuming, complicated or expensive for massive screening of pathogens and their non-pathogenic relatives. Also, bioinformatic classifiers usually lack automatically generated performance statistics for specific databases. To address this problem, we developed Clasnip (www.clasnip.com), an easy-to-use web-based platform for the classification and similarity evaluation of closely related microorganisms at interspecies and intraspecies levels. Clasnip mainly consists of two modules: database building and sample classification. In database building, labeled nucleotide sequences are mapped to a reference sequence, and then single nucleotide polymorphisms (SNPs) statistics are generated. A probability model of SNPs and classification groups is built using Hidden Markov Models and solved using the maximum likelihood method. Database performance is estimated using three replicates of two-fold cross-validation. Sensitivity (recall), specificity (selectivity), precision, accuracy and other metrics are computed for all samples, training sets, and test sets. In sample classification, Clasnip accepts inputs of genes, short fragments, contigs and even whole genomes. It can report classification probability and a multi-locus sequence typing table for SNPs. The classification performance was tested using short sequences of 16S, 16–23S and 50S rRNA regions for 12 haplotypes of Candidatus Liberibacter solanacearum (CLso), a regulated plant pathogen associated with severe disease in economically important Apiaceous and Solanaceous crops. The program was able to classify CLso samples with even only 1–2 SNPs available, and achieved 97.2%, 98.8% and 100.0% accuracy based on 16S, 16–23S, and 50S rRNA sequences, respectively. In comparison with all existing 12 haplotypes, we proposed that to be classified as a new haplotype, given samples have at least 2 SNPs in the combined region of 16S rRNA (OA2/Lsc2) and 16–23S IGS (Lp Frag 4–1611F/Lp Frag 4–480R) regions, and 2 SNPs in the 50S rplJ/rplL (CL514F/CL514R) regions. Besides, we have included the databases for differentiating Dickeya spp., Pectobacterium spp. and Clavibacter spp. In addition to bacteria, we also tested Clasnip performance on potato virus Y (PVY). 251 PVY genomes were 100% correctly classified into seven groups (PVYC, PVYN, PVYO, PVYNTN, PVYN:O, Poha, and Chile3). In conclusion, Clasnip is a statistically sound and user-friendly bioinformatic application for microorganism classification at the intraspecies level. Clasnip service is freely available at www.clasnip.com.