Pangenomic Characterization of Campylobacter Plasmids for Enhanced Molecular Typing, Risk Assessment and Source Attribution

Plasmid-mediated dissemination of antimicrobial resistance (AMR) and virulence genes plays a critical role in enhancing the adaptive potential of <i>Campylobacter</i> spp. While <i>Campylobacter</i> plasmids of concern are commonly classified as pTet, pVir, pCC42 or a large plasmid encoding a T6SS (pT6SS), existing classification systems often lack the resolution to capture intra-group diversity. Here we demonstrate a plasmid typing approach with enhanced discriminatory power that categorizes these major plasmid groups into discrete subgroups and strengthens risk-assessment investigations. Pangenomic analysis of 424 <i>Campylobacter</i> plasmid sequences revealed 30 distinct plasmid groups. The four major groups above accounted for 74.3% of the dataset. Within these major groups, 177 plasmid type-specific loci were used to define 16 subgroups. pTet plasmids were subdivided into 5 subgroups, with subgroup 3 enriched in <i>C. coli</i>. pVir plasmids formed 3 subgroups, with only subgroup 3 harboring the <i>tet(O)</i> genes. The 5 pCC42 subgroups displayed <i>Campylobacter</i> species specificity while the 3 pT6SS subgroups encoded distinct AMR profiles. This high-resolution typing approach provides a unified and scalable method to characterize <i>Campylobacter</i> plasmid diversity and identifies genetic markers critical for pathogen surveillance, source attribution and mitigation strategies employed to safeguard human and animal health.

Authors

Institutions

Publication Details

Journal
Pathogens
Published
2025-09-16
DOI
https://doi.org/10.3390/pathogens14090936
Primary Topic
Salmonella and Campylobacter epidemiology
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Pangenomic Characterization of Campylobacter Plasmids for Enhanced Molecular Typing, Risk Assessment and Source Attribution

Lucas B. Harrison, Cong Li, Shaohua Zhao, Shenia Young et al.
Pathogens
Salmonella and Campylobacter epidemiology
article

Pangenomic Characterization of Campylobacter Plasmids for Enhanced Molecular Typing, Risk Assessment and Source Attribution

Lucas B. Harrison, Cong Li, Shaohua Zhao, Shenia Young, Qijing Zhang, Sampa Mukherjee
article en

Abstract

Plasmid-mediated dissemination of antimicrobial resistance (AMR) and virulence genes plays a critical role in enhancing the adaptive potential of <i>Campylobacter</i> spp. While <i>Campylobacter</i> plasmids of concern are commonly classified as pTet, pVir, pCC42 or a large plasmid encoding a T6SS (pT6SS), existing classification systems often lack the resolution to capture intra-group diversity. Here we demonstrate a plasmid typing approach with enhanced discriminatory power that categorizes these major plasmid groups into discrete subgroups and strengthens risk-assessment investigations. Pangenomic analysis of 424 <i>Campylobacter</i> plasmid sequences revealed 30 distinct plasmid groups. The four major groups above accounted for 74.3% of the dataset. Within these major groups, 177 plasmid type-specific loci were used to define 16 subgroups. pTet plasmids were subdivided into 5 subgroups, with subgroup 3 enriched in <i>C. coli</i>. pVir plasmids formed 3 subgroups, with only subgroup 3 harboring the <i>tet(O)</i> genes. The 5 pCC42 subgroups displayed <i>Campylobacter</i> species specificity while the 3 pT6SS subgroups encoded distinct AMR profiles. This high-resolution typing approach provides a unified and scalable method to characterize <i>Campylobacter</i> plasmid diversity and identifies genetic markers critical for pathogen surveillance, source attribution and mitigation strategies employed to safeguard human and animal health.

PathogensVol. 14(9)
Center for Veterinary Medicine (US), United States Food and Drug Administration (US), Iowa State University (US)
U.S. Department of Agriculture, Centers for Disease Control and Prevention
Openalex Percentile: Top 70%
Salmonella and Campylobacter epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.