Identification of Novel Gene-Specific Markers for Differentiating Various Pathogenic Campylobacter Species Using a Pangenome Analysis Approach

Abstract

Campylobacter spp. are the causative agents of campylobacteriosis, a major foodborne illness globally, with millions of cases reported annually. These pathogens pose significant risks to both human and animal health. Conventional culture-based diagnostic methods are labor-intensive and time-consuming, underscoring the need for more efficient molecular detection strategies. This study employed a pangenomic analysis to identify novel gene-specific markers for pathogenic Campylobacter species and subspecies, laying the groundwork for their application in diverse diagnostic assays. A curated dataset of 105 high-quality genomes, representing 33 species and 9 subspecies, was analyzed using the Roary ILP Bacterial Annotation Pipeline. The results revealed substantial genomic diversity within the genus, with core gene counts varying across different nucleotide identity thresholds. Ribosomal genes such as rpsL, rpsJ, rpsS, rpmA, rpsK, rpsU, rpsG, rpmH, and rpsZ were consistently identified in the core genome, whereas accessory genes exhibited marked variability. This study uncovered novel and highly specific genetic markers for various Campylobacter species, including petB, clpX, and carB for C. coli; hypothetical proteins for C. jejuni and C. fetus; porA2 for C. lari; and mdtJ for C. upsaliensis. These markers demonstrated a specificity of at least 90% with minimal cross-reactivity with non-target organisms. The findings underscore the genomic heterogeneity within Campylobacter and provide essential genetic targets for the enhanced molecular detection of its pathogenic species, subspecies, and biovars.

Keywords: Campylobacter spp.; foodborne pathogens; molecular detection; pangenome analysis; species-specific markers.

Figure 1

Workflow for target gene identification: from pangenome analysis to BLAST (version 2.1.2) validation and functional testing.

Figure 2

Gene presence/absence matrices at varying average nucleotide identity (ANI) thresholds, as analyzed using Phandango. Subfigures (a–e) correspond to ANI thresholds of 60%, 70%, 80%, 90%, and 95%, respectively. Yellow boxes represent core and soft-core genes, while red boxes indicate accessory genes.

Figure 3

Pangenome distribution of the Campylobacter genus, illustrating the major clades identified within the analyzed dataset. The figure differentiates between pathogenic and non-pathogenic strains, represented by pink and gray bars, respectively.

Figure 4

Functional distribution of the identified genetic targets across various pathogenic Campylobacter species and subspecies. Green rectangles represent hypothetical proteins; blue stars indicate genes involved in DNA synthesis and protective functions; red bullets denote virulence-associated genes; gray symbols represent genes related to transport and metabolism; and pink triangles indicate genes involved in enzymatic activities.