Trends, antimicrobial resistance, and source attribution of Campylobacter jejuni and C. coli in Beijing: An 8-year molecular surveillance study.

OBJECTIVES

Beijing, a large urban center with complex food supply chains, faces increasing challenges from foodborne Campylobacter infections. However, local data on antimicrobial resistance, source attribution, and pathogenic characteristics remain limited. This study aimed to clarify long-term trends, resistance patterns, and likely infection sources of Campylobacter in Beijing to inform prevention and treatment strategies.

METHODS

From 2016 to 2023, 27,691 stool samples were collected from patients with foodborne diseases in 45 hospitals across Beijing. Campylobacter isolates were recovered and identified, followed by antimicrobial susceptibility testing, and whole-genome sequencing. A core-genome MLST-based extreme gradient boosting (XGBoost) model was applied for machine-learning source attribution.

RESULTS

A total of 1204 Campylobacter isolates were identified, including 1005 C. jejuni, 198 C. coli and one C. fetus. The proportion of C. coli increased compared with the early surveillance years and reached its highest level in 2023. Both C. jejuni and C. coli showed >90% resistance to fluoroquinolones and tetracyclines, and C. coli has a much higher resistance rate to macrolide. Machine-learning analysis identified chicken as the major source for C. coli infections, accounting for 75.76% cases.

CONCLUSIONS

This 8-year genomic surveillance highlights the sustained and increasing contribution of C. coli and extensive resistance in Beijing, supporting targeted control measures and antibiotic stewardship in foodborne disease management.