Pathogenomic Insights into Piscirickettsia salmonis with a Focus on Virulence Factors, Single-Nucleotide Polymorphism Identification, and Resistance Dynamics

Abstract

Effective control of bacterial infections remains a significant challenge in aquaculture. The marine bacterium Piscirickettsia salmonis (P. salmonis), responsible for piscirickettsiosis, causes widespread infections in various salmon species, leading to substantial mortality and economic losses. Despite efforts to genetically characterize P. salmonis, critical gaps persist in understanding its virulence factors, antimicrobial resistance genes, and single-nucleotide polymorphisms (SNPs). This study addresses these gaps through a comparative analysis of the pan-genome and core genomes of 80 P. salmonis strains from different geographical regions and genogroups. P. salmonis had an open pan-genome consisting of 14,564 genes, with a core genome of 1257 conserved genes. Eleven virulence-related genes were identified in the pan-genome, categorized into five functional groups, providing new insights into the pathogenicity of P. salmonis. Unique SNPs were detected in four key genes (gyrA, dnaK, rpoB, and ftsZ), serving as robust molecular markers for distinguishing the LF and EM genogroups. Notably, AMR genes identified in four LF strains suggest evolutionary adaptations under selective pressure. Functional annotation of the core genomes using the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases demonstrated conserved gene clusters linked to essential intracellular survival mechanisms and bacterial pathogenicity. These findings suggest a direct association between core genome features and variations in pathogenesis and host-pathogen interactions across genogroups. Phylogenetic reconstruction further highlighted the influence of AMR genes on strain divergence. Collectively, this study enhances the genomic understanding of P. salmonis and lays the groundwork for improved diagnostic tools and targeted therapeutics to manage piscirickettsiosis in aquaculture.

Keywords: SNPs; genomics; pathogenesis; piscirickettsiosis; virulence.

Figure 1

Heat map displays the pairwise average nucleotide identity (ANI) values for 80 genomes of P. salmonis. The utilization of color coding on the x-axis and y-axis was employed to distinguish between the various strains of genomes. The red color indicates a significant level of resemblance, implying that the organisms belong to the same species.

Figure 2

Visualization of the pan-genome of P. salmonis was performed using Roary v3.11.2, including 80 true genomes. The genomes of the strains were grouped based on the presence or absence of genes. The blue color indicates the presence of genes, while the color white indicates the absence of genes.

Figure 3

A rarefaction curve illustrates the total number of novel genes identified by the random incorporation of a single genome. The equation of the power-law fit is γ = 0.1112+/−0.0013.

Figure 4

A reconstructed phylogenetic tree was generated using the gyrA gene and a total of 80 samples. The tree was constructed using maximum likelihood and the Kimura 2-parameter model, which was selected as the most parsimonious model. All positions with less than 95% coverage were removed. The color coding indicates different clades and the genetic variation between the strains. The red box in the LF genogroup indicates the strains which found positive for several antimicrobial resistance genes.

Figure 5

GO enrichment analysis of core genes from the P. salmonis pan-genome using zebrafish as a reference model.

Figure 6

KEGG pathway enrichment analysis of core genes from the P. salmonis pan-genome.