Multilevel HierCC typing scheme for global genomic epidemiology and antimicrobial resistance surveillance of Campylobacter jejuni
- 1School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW, Australia
Abstract
Campylobacter jejuni is the most common bacterial cause of human gastroenteritis around the world. A stable, scalable, and standardized typing scheme is essential for epidemiological and antimicrobial resistance (AMR) surveillance for prevention and control of C. jejuni infections. We curated, assembled, and quality-filtered a C. jejuni global whole-genome sequencing (WGS) data set of 63,012 publicly available Illumina short-read genomes. A C. jejuni global cgMLST scheme with 1,161 core loci was developed using a representative subset of 2,587 genomes. We compared the HierCC clustering of the cgMLST profiles at every allelic distance, and identified nine epidemiologically meaningful levels to form a novel multilevel HierCC typing (MHT) scheme. AMR prediction was performed for the global data set using AbritAMR and integrated with the MHT scheme. The multilevel design provides flexible typing resolution for both short- and long-term epidemiological investigations and allows natural and genetically discrete clusters to be described consistently at both global and local scales. We showcased the utility of the scheme with the identification of country- and continent-specific clusters at HC264 to HC19 levels and differentiation of farm-animal-specific (specialist) from human infection (generalist) clusters at HC264 to HC55 levels. In the U.S. dataset from 2016 to 2022, a total of 276 antibiotic-resistant clusters were identified, with 22 resistant clusters increasing in frequency in recent years. An increased prevalence of C. jejuni carrying 50S_L22 mutations in the USA was observed from 2016 to 2022, suggesting continuing selection pressure from macrolide use in farm animals.
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BibTeX
@article{wu2026multilevel,
title = {{Multilevel HierCC typing scheme for global genomic epidemiology and antimicrobial resistance surveillance of Campylobacter jejuni}},
author = {Ruochen Wu and Sandeep Kaur and Michael Payne and Li Zhang and Ruiting Lan},
journal = {Antimicrobial Agents and Chemotherapy},
year = {2026},
month = jul,
doi = {10.1128/aac.00310-26},
url = {https://doi.org/10.1128/aac.00310-26},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Multilevel HierCC typing scheme for global genomic epidemiology and antimicrobial resistance surveillance of Campylobacter jejuni
AU - Ruochen Wu
AU - Sandeep Kaur
AU - Michael Payne
AU - Li Zhang
AU - Ruiting Lan
PY - 2026
DA - 2026/07/28
JO - Antimicrobial Agents and Chemotherapy
DO - 10.1128/aac.00310-26
UR - https://doi.org/10.1128/aac.00310-26
AB - Campylobacter jejuni is the most common bacterial cause of human gastroenteritis around the world. A stable, scalable, and standardized typing scheme is essential for epidemiological and antimicrobial resistance (AMR) surveillance for prevention and control of C. jejuni infections. We curated, assembled, and quality-filtered a C. jejuni global whole-genome sequencing (WGS) data set of 63,012 publicly available Illumina short-read genomes. A C. jejuni global cgMLST scheme with 1,161 core loci was developed using a representative subset of 2,587 genomes. We compared the HierCC clustering of the cgMLST profiles at every allelic distance, and identified nine epidemiologically meaningful levels to form a novel multilevel HierCC typing (MHT) scheme. AMR prediction was performed for the global data set using AbritAMR and integrated with the MHT scheme. The multilevel design provides flexible typing resolution for both short- and long-term epidemiological investigations and allows natural and genetically discrete clusters to be described consistently at both global and local scales. We showcased the utility of the scheme with the identification of country- and continent-specific clusters at HC264 to HC19 levels and differentiation of farm-animal-specific (specialist) from human infection (generalist) clusters at HC264 to HC55 levels. In the U.S. dataset from 2016 to 2022, a total of 276 antibiotic-resistant clusters were identified, with 22 resistant clusters increasing in frequency in recent years. An increased prevalence of C. jejuni carrying 50S_L22 mutations in the USA was observed from 2016 to 2022, suggesting continuing selection pressure from macrolide use in farm animals.
SN - 0066-4804
SN - 1098-6596
ER -