Evaluation of the taxonomic accuracy and pathogenicity prediction power of 16 primer sets amplifying single copy marker genes in the Pseudomonas syringae species complex

Naïve Bayes Classifiers and accompanying dataset for Pseudomonas syringae isolate characterization

The Pseudomonas syringae species complex (PSSC) is a diverse group of plant pathogens with a collective host range encompassing almost every food crop grown today. As a threat to global food security, rapid detection and characterization of epidemic and emerging pathogenic lineages is essential. However, phylogenetic identification is often complicated by an unclarified and ever-changing taxonomy, making practical use of available databases and the proper training of classifiers difficult. As such, while amplicon sequencing is a common method for routine identification of PSSC isolates, there is no efficient method for accurate classification based on this data. Here we present a suite of five Naïve bayes classifiers for PCR primer sets widely used for PSSC identification, trained on in-silico amplicon data from 2,161 published PSSC genomes using the life identification number (LIN) hierarchical clustering algorithm in place of traditional Linnaean taxonomy. Additionally, we include a dataset for translating classification results back into traditional taxonomic nomenclature (i.e. species, phylogroup, pathovar), and for predicting virulence factor repertoires.

Diversity of Culture Microorganisms from Portuguese Sweet Cherries

Consumers today seek safe functional foods with proven health-promoting properties. Current evidence shows that a healthy diet can effectively alleviate oxidative stress levels and reduce inflammatory markers, thereby preventing the occurrence of many types of cancer, hypertension, and cardiovascular and neurological pathologies. Nevertheless, as fruits and vegetables are mainly consumed fresh, they can serve as vectors for the transmission of pathogenic microorganisms associated with various disease outbreaks. As a result, there has been a surge in interest in the microbiome of fruits and vegetables. Therefore, given the growing interest in sweet cherries, and since their microbial communities have been largely ignored, the primary purpose of this study is to investigate their culturome at various maturity stages for the first time. A total of 55 microorganisms were isolated from sweet cherry fruit, comprising 23 bacteria and 32 fungi species. Subsequently, the selected isolates were molecularly identified by amplifying the 16S rRNA gene and ITS region. Furthermore, it was observed that the communities became more diverse as the fruit matured. The most abundant taxa included Pseudomonas and Ralstonia among the bacteria, and Metschnikowia, Aureobasidium, and Hanseniaspora among the fungi.

Evaluation of the taxonomic accuracy and pathogenicity prediction power of 16 primer sets amplifying single copy marker genes in the Pseudomonas syringae species complex

The Pseudomonas syringae species complex is composed of several closely related species of bacterial plant pathogens. Here, we used in silico methods to assess 16 PCR primer sets designed for broad identification of isolates throughout the species complex. We evaluated their in silico amplification rate in 2161 publicly available genomes, the correlation between pairwise amplicon sequence distance and whole genome average nucleotide identity, and trained naive Bayes classification models to quantify classification resolution. Furthermore, we show the potential for using single amplicon sequence data to predict type III effector protein repertoires, which are important determinants of host specificity and range.