Back

SYRINGAE: A web-based application for Pseudomonas syringae isolate characterization

Fautt, C.; Couradeau, E.; Hockett, K. L.

2022-11-04 microbiology
10.1101/2022.11.04.515192 bioRxiv
Show abstract

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.

Matching journals

The top 4 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.