Bacterial toxin-antitoxin (TA) systems consist of two or more adjacent genes, encoding a toxin and an antitoxin. TA systems are implicated in evolutionary and physiological functions including genome maintenance, antibiotics persistence, phage defense, and virulence. Eight classes of TA systems have been described, based on the mechanism of toxin neutralization by the antitoxin. Although studied well in model species of clinical significance, little is known about the TA system abundance and diversity, and their potential roles in stress tolerance and virulence of plant pathogens. In this study, we screened the genomes of 339 strains representing the genetic and lifestyle diversity of the Pseudomonas syringae species complex for TA systems. Using bioinformatic search and prediction tools, including SLING, BLAST, HMMER, TADB2.0, and T1TAdb, we show that P. syringae strains encode 26 different families of TA systems targeting diverse cellular functions. TA systems in this species are almost exclusively type II. We predicted a median of 15 TA systems per genome, and we identified six type II TA families that are found in more than 80% of strains, while others are more sporadic. The majority of predicted TA genes are chromosomally encoded. Further functional characterization of the predicted TA systems could reveal how these widely prevalent gene modules potentially impact P. syringae ecology, virulence, and disease management practices.

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.

The Pseudomonas syringae species complex (PSSC) is a diverse group of plant pathogens with a collective host range encompassing almost every food crop grown throughout the world. As a threat to global food security, rapid detection and characterization of epidemic and emerging pathogenic lineages is essential. However, phylogenetic identification and prediction of virulence is often complicated by an unclarified taxonomy and the diversity of virulence factor repertoires carried by PSSC isolates. To address these issues, we have built SYRINGAE (www.syringae.org), a web-based phylogenetic placement and functional inference pipeline for PSSC. SYRINGAE contains a comprehensive phylogeny of 2,161 quality-checked genome assemblies annotated with 120 virulence genes. From this dataset, naïve Baye classification models trained from life identification numbers (LINs) and common marker gene sequences can be used for accurate identification of isolates. SYRINGAE efficiently articulates taxonomical and functional data generated over the last several decades on PSSC and constitutes a unique tool tailored towards the rapid characterization of PSSC emerging strains of concern.

The Pseudomonas syringae species complex is comprised of several closely related species of bacterial plant pathogens. Here, we use in-silico methods to assess 16 PCR primer sets designed for broad identification of isolates throughout the species complex. We evaluate their in-silico amplification rate in 2,161 publicly available genomes, the correlation between pairwise amplicon sequence distance and whole genome average nucleotide identity (ANI), and we train naïve Bayes classification models to quantify classification resolution. Further, we show the potential for using single amplicon sequence data to predict an important determinant of host specificity and range, type III effector protein repertoires.