Assessment of Multilocus Sequence Analysis (MLSA) for Identification of Candidatus Liberibacter Solanacearum from Different Host Plants in Spain

Biology, Ecology, and Management of the Potato Psyllid, Bactericera cockerelli (Hemiptera: Triozidae), and Zebra Chip Disease in Potato

The potato psyllid, Bactericera cockerelli (Šulc) (Hemiptera: Triozidae), transmits the pathogen "Candidatus liberibacter solanacearum" (Lso), the putative causal agent of zebra chip disease (ZC). ZC is a disease of potato that reduces yield and quality and has disrupted integrated pest management programs in parts of the Americas and New Zealand. Advances in our understanding of the ecological factors that influence ZC epidemiology have been accelerated by the relatively recent identification of Lso and motivated by the steady increase in ZC distribution and the potential for devastating economic losses on a global scale. Management of ZC remains heavily reliant upon insecticides, which is not sustainable from the standpoint of insecticide resistance, nontarget effects on natural enemies, and regulations that may limit such tools. This review synthesizes the literature on potato psyllids and ZC, outlining recent progress, identifying knowledge gaps, and proposing avenues for further research on this important pathosystem of potatoes.

Reference-Free Plant Disease Detection Using Machine Learning and Long-Read Metagenomic Sequencing

Surveillance for early disease detection is crucial to reduce the threat of plant diseases to food security. Metagenomic sequencing and taxonomic classification have recently been used to detect and identify plant pathogens. However, for an emerging pathogen, its genome may not be similar enough to any public genome to permit reference-based tools to identify infected samples. Also, in the case of point-of care diagnosis in the field, database access may be limited. Therefore, here we explore reference-free detection of plant pathogens using metagenomic sequencing and machine learning (ML). We used long-read metagenomes from healthy and infected plants as our model system and constructed k-mer frequency tables to test eight different ML models. The accuracy in classifying individual reads as coming from a healthy or infected metagenome were compared. Of all models, random forest (RF) had the best combination of short run-time and high accuracy (over 0.90) using tomato metagenomes. We further evaluated the RF model with a different tomato sample infected with the same pathogen or a different pathogen and a grapevine sample infected with a grapevine pathogen and achieved similar performances. ML models can thus learn features to successfully perform reference-free detection of plant diseases whereby a model trained with one pathogen-host system can also be used to detect different pathogens on different hosts. Potential and challenges of applying ML to metagenomics in plant disease detection are discussed. IMPORTANCE Climate change may lead to the emergence of novel plant diseases caused by yet unknown pathogens. Surveillance for emerging plant diseases is crucial to reduce their threat to food security. However, conventional genomic based methods require knowledge of existing plant pathogens and cannot be applied to detecting newly emerged pathogens. In this work, we explored reference-free, meta-genomic sequencing-based disease detection using machine learning. By sequencing the genomes of all microbial species extracted from an infected plant sample, we were able to train machine learning models to accurately classify individual sequencing reads as coming from a healthy or an infected plant sample. This method has the potential to be integrated into a generic pipeline for a meta-genomic based plant disease surveillance approach but also has limitations that still need to be overcome.

Survey of Candidatus Liberibacter Solanacearum and Its Associated Vectors in Potato Crop in Spain

'Candidatus Liberibacter solanacearum' (CaLsol), the etiological agent of potato zebra chip (ZC), is transmitted to potato plants by the psyllid Bactericera cockerelli (Šulc, 1909) in North and Central America and New Zealand. The risk of the dispersion of ZC in Spain depends on the presence of an efficient vector. This work studies the presence and abundance of ZC symptoms and CaLsol in potato plants, as well as the presence and abundance of psyllid species associated with potato crops in the main producing areas in Spain. Eighty-eight plots were surveyed punctually to detect ZC symptoms and psyllid species in the main potato-producing areas. Furthermore, fourteen potato plots were surveyed by different sampling methods during the cropping season to detect psyllid species from 2016 to 2018. Very few symptomatic and CaLsol-positive plants were detected in Mainland Spain, and any positive plant was detected in the Canary Islands. Most of the adult psyllids captured were identified as Bactericera nigricornis (Foerster, 1848), and some of them as Bactericera trigonica, but no B. cockerelli was detected. B. nigricornis was found widely distributed in the northern half of the Iberian Peninsula; however, this psyllid does not seem sufficient to pose a threat to potato production, due to the scarce number of specimens and because the frequency of B. nigricornis specimens that were CaLsol+ was very low.

Genetic diversity of microsymbionts nodulating Trifolium pratense in subpolar and temperate climate regions

Rhizobia are soil-borne bacteria forming symbiotic associations with legumes and fixing atmospheric dinitrogen. The nitrogen-fixation potential depends on the type of host plants and microsymbionts as well as environmental factors that affect the distribution of rhizobia. In this study, we compared genetic diversity of bacteria isolated from root nodules of Trifolium pratense grown in two geographical regions (Tromsø, Norway and Lublin, Poland) located in distinct climatic (subpolar and temperate) zones. To characterize these isolates genetically, three PCR-based techniques (ERIC, BOX, and RFLP of the 16S-23S rRNA intergenic spacer), 16S rRNA sequencing, and multi-locus sequence analysis of chromosomal house-keeping genes (atpD, recA, rpoB, gyrB, and glnII) were done. Our results indicate that a great majority of the isolates are T. pratense microsymbionts belonging to Rhizobium leguminosarum sv. trifolii. A high diversity among these strains was detected. However, a lower diversity within the population derived from the subpolar region in comparison to that of the temperate region was found. Multi-locus sequence analysis showed that a majority of the strains formed distinct clusters characteristic for the individual climatic regions. The subpolar strains belonged to two (A and B) and the temperate strains to three R. leguminosarum genospecies (B, E, and K), respectively.

Assessment of Psyllid Handling and DNA Extraction Methods in the Detection of ‘Candidatus Liberibacter Solanacearum’ by qPCR

‘Candidatus Liberibacter solanacearum’ (CaLsol) is an uncultured bacterium, transmitted by psyllids and associated with several diseases in Solanaceae and Apiaceae crops. CaLsol detection in psyllids often requires insect destruction, preventing a subsequent morphological identification. In this work, we have assessed the influence on the detection of CaLsol by PCR in Bactericera trigonica (Hemiptera: Psyllidae), of four specimen preparations (entire body, ground, cut-off head, and punctured abdomen) and seven DNA extraction methods (PBS suspension, squashing on membrane, CTAB, Chelex, TRIsureTM, HotSHOT, and DNeasy®). DNA yield and purity ratios, time consumption, cost, and residues generated were also evaluated. Optimum results were obtained through grinding, but it is suggested that destructive procedures are not essential in order to detect CaLsol. Although CaLsol was detected by qPCR with DNA obtained by the different procedures, HotSHOT was the most sensitive method. In terms of time consumption and cost, squashed on membrane, HotSHOT, and PBS were the fastest, while HotSHOT and PBS were the cheapest. In summary, HotSHOT was accurate, fast, simple, and sufficiently sensitive to detect this bacterium within the vector. Additionally, cross-contamination with CaLsol was assessed in the ethanol solutions where B. trigonica specimens were usually collected and preserved. CaLsol-free psyllids were CaLsol-positive after incubation with CaLsol-positive specimens. This work provides a valuable guide when choosing a method to detect CaLsol in vectors according to the purpose of the study.