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Fautt, C.

Publications and source records attributed to Fautt, C..

3 recordsLinked to original sources

Genomic evidence for widespread reciprocal recognition and killing among Pseudomonas syringae strains

Community assembly dynamics are in part driven by competition between community members. Diverse bacteria antagonize competitors through the production of toxic compounds, such as bacteriophage-derived tailocins. These toxins are highly specific in their targeting, which is determined by interactions between the tailocins tail fiber and competitors lipopolysaccharide O-antigen moieties. Tailocins play a pivotal role in mediating microbial interactions among the economically significant plant pathogens within the Pseudomonas syringae species complex, with the potential to alter community structure and disease progression in host plants. Previous work looking at 45 P. syringae strains has demonstrated that at least two phylogenetic clades of tail fibers are encoded in the conserved tailocin region across the species complex, which roughly corresponds to two clusters of targeting activity. To better understand the full diversity of tail fibers associated with tailocins in the species complex, we screened 2,161 publicly available genomes for their tailocin tail fiber content, predicted protein structures that represent the diversity of fibers, and investigated forces possibly driving the distribution of fibers throughout the species complex. Here we present evidence that while the two previously described tail fiber clades are indeed widespread among virulent P. syringae strains, their distribution is largely uncorrelated with phylogeny. Instead, we found that the presence of one tail fiber or the other is strongly correlated with the allelic diversity of another gene, associated with lipopolysaccharide O-antigen structure, dTDP-4-dehydrorhamnose reductase. Our findings suggest the presence of two reciprocally targeting groups of strains distributed throughout the P. syringae species complex that transcend phylogenetic relationships.

genomics↗

SYRINGAE: A web-based application 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 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, naive 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.

microbiology↗

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 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 naive 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.

microbiology↗