Vital Surveillances: Genetic and Drug Resistance Characteristics of Campylobacter Isolated — China, 2020–2023

Campylobacter data utilized in this study were obtained from the National Pathogen Identification Network Center database, maintained by the National Institute for Infectious Disease Control and Prevention of the Chinese Center for Disease Control and Prevention. Data collection occurred annually and encompassed isolation location, source, and isolation date. All isolates were collected from 20 provincial-level administrative divisions (PLADs) between January 1, 2020, and December 31, 2023.

A total of 799 Campylobacter isolates were obtained from 9 PLADs and cities during 2020–2023, comprising 634 C. jejuni isolates and 165 C. coli isolates. Minimal inhibitory concentrations (MICs) were determined using the agar dilution method against eleven antimicrobial agents representing seven classes: erythromycin (ERY), azithromycin (AZI), nalidixic acid (NAL), ciprofloxacin (CIP), gentamicin (GEN), streptomycin (STR), chloramphenicol (CHL), florfenicol (FLO), tetracycline (TET), telithromycin (TEL), and clindamycin (CLI).

Genome annotation was performed using the Prokka pipeline v1.14.6 (VicBioinformatics, University of Melbourne, Australia) for gene prediction and functional annotation. Sequence types (STs) and clonal complexes (CCs) were determined using the pubMLST database (https://pubmlst.org/). Antimicrobial resistance genes and point mutations conferring antibiotic resistance were identified using the Resistance Gene Identifier (RGI). Virulence genes were detected across all genomes using the virulence factor database (VFDB). Core genome single nucleotide polymorphisms (cg-SNPs) were extracted using Snippy 4.0 (Wellcome Sanger Institute, Wellcome Genome Campus, UK), with Gubbins 2.4 (Earlham Institute, UK) employed for recombination removal to obtain pure SNP data. Phylogenomic trees were constructed using FastTree 1.6 (Physical Biosciences Division, Lawrence Berkeley National Laboratory, CA, USA) and visualized with iTOL 6.9 (https://itol.embl.de) (5).

Between 2020 and 2023, the National Pathogen Identification Network documented a total of 1,298 Campylobacter isolates (Table 1), comprising 1,077 C. jejuni and 221 C. coli strains. The C. jejuni isolates originated from 20 PLADs, with the highest concentrations observed in Beijing (50.79%, 547/1,077), Shanghai (33.05%, 356/1,077), and Zhejiang PLADs (6.50%, 70/1,077). Clinical isolates from diarrhea patients constituted the predominant source (92.57%, 997/1,077). The 221 C. coli isolates were distributed across 6 PLADs: Beijing (50.68%, 112/221), Shanghai (33.03%, 73/221), Fujian (13.57%, 30/221), Zhejiang (1.35%, 3/221), Guangdong (0.90%, 2/221), and Sichuan (0.45%, 1/221). Among these C. coli isolates, 83.26% (184/221) were recovered from diarrhea patients, while 9.05% (20/221) originated from environmental samples, 4.98% (11/221) from animal sources, and 2.71% (6/221) from food samples.

Among all Campylobacter spp. combined, 7.26% (58/799) of isolates demonstrated susceptibility to all antimicrobial agents tested, though several isolates lacked resistance results for certain antibiotics. The isolates exhibited a high prevalence of resistance to NAL (78.22%), CIP (78.07%), and TET (71.96%), while demonstrating lower resistance rates to CLI (22.45%), GEN (19.92%), AZI (18.30%), FLO (16.77%), TEL (15.01%), STR (13.37%), ERY (12.67%), and CHL (6.14%).

Among the 634 C. jejuni isolates examined over the four-year period, resistance to NAL was most prevalent (77.92%, 494/634), followed by CIP (77.44%, 491/634) and TET (70.98%, 450/634). However, these isolates exhibited considerably lower resistance rates to other tested antibiotics, with CHL resistance reaching only 4.89%. In contrast, the 165 C. coli isolates analyzed demonstrated higher resistance levels than C. jejuni across multiple antimicrobials. Resistance rates for NAL, CIP, and TET exceeded 75.00% in C. coli isolates. Additional antibiotics, including ERY, AZI, GEN, STR, TEL, and CLI, also exhibited higher resistance rates in C. coli compared to C. jejuni. Notably, resistance rates for CHL and FLO remained relatively low, staying below 25.00%. These corresponding results are illustrated in Supplementary Table S1 and Figure 1.

Figure 1. 

Comparison of drug resistance patterns between Campylobacter jejuni and Campylobacter coli. Blue indicates C. jejuni, and orange indicates C. coli.

Abbreviation: ERY=erythromycin; AZI=azithromycin; NAL=nalidixic acid; CIP=ciprofloxacin; GEN=gentamicin; STR=streptomycin; CHL=chloramphenicol; FLO=florfenicol; TET=tetracycline; TEL=telithromycin; CLI=clindamycin.

Longitudinal comparison of susceptibility testing results revealed an overall declining trend in resistance rates across all 11 antibiotics. Significant temporal trends in antibiotic resistance were observed throughout the three-year study period, including FLO resistance in C. jejuni and ERY, STR, FLO, and TEL resistance in C. coli. However, the limited sample size in 2020 may not accurately represent the resistance patterns for that year.

Between 2020 and 2023, we obtained whole-genome sequencing data for 665 Campylobacter isolates from 12 different provinces and cities, comprising 540 C. jejuni and 125 C. coli isolates. The majority of these isolates originated from human patients (91.88%, 611/665), while the remaining specimens were derived from poultry (3.46%, 23/665), environmental samples (3.16%, 21/665), and food samples (1.50%, 10/665).

We identified a total of 53 resistance genes in C. jejuni and C. coli, predominantly associated with gyrA mutations (T86I), cmeABC efflux systems, and tet genes. More than 99% (99.07%, 535/540) of the analyzed C. jejuni isolates harbored genes linked to the multidrug efflux systems cmeR and cmeC, demonstrating a higher carriage rate than the cmeB gene (77.60%, 97/125) detected in C. coli isolates. Nearly all C. coli isolates possessed the gyrA mutation (T86I) (98.40%, 123/125), which occurred more frequently than in C. jejuni (95.56%, 516/540). These findings align with the elevated resistance levels observed against ciprofloxacin and nalidixic acid in both species. Additional antibiotic-resistant genes and mutations were detected across isolates, as illustrated in (Supplementary Figure S1).

We identified numerous virulence genes associated with Campylobacter adherence, colonization, immune evasion, invasion, motility, export apparatus, secretion systems, and toxin production. All categories of virulence genes were detected, with certain genes related to motility and export apparatus present in all isolates, including flgB, flgC, and fliE in C. jejuni, and cheY, flgP, fliR, and fliW in C. coli. Three genes — cdtA, cdtB, and cdtC — encoding the A, B, and C subunits of cytolethal distending toxin (CDT), respectively, were confirmed in C. jejuni isolates. However, only cdtB and cdtC genes were detectable in C. coli isolates. The virulence gene wlaN, associated with Guillain-Barré syndrome, was detected exclusively in C. jejuni but not in C. coli. Additionally, 71 C. jejuni isolates harbored a cluster of virulence genes related to capsule formation, including Cj1421c, Cj1422c, Cj1426c, Cj1427c, Cj1429c, Cj1432c, Cj1433c, Cj1435c, Cj1436c, Cj1437c, and Cj1440c. Genes associated with adhesion, invasion, and motility were present in nearly all isolates, while genes linked to the type IV secretion system were detected less frequently (Supplementary Figure S1).

Multilocus sequence typing (MLST) identified 159 distinct sequence types (STs) among 420 C. jejuni isolates, while 44 different multilocus sequence typing locus combinations were identified in the remaining 120 isolates (Figure 2). Among these, 23 STs were characterized, with the most prevalent clonal complexes being ST-21 (33.81%, 142/420), ST-45 (9.29%, 39/420), ST-464 (6.19%, 26/420), ST-354 (5.48%, 23/420), and ST-443 (5.24%, 22/420). For C. coli, all detected isolates belonged to the clonal complex ST-828, and one unclassified clonal complex (Figure 2). Among C. jejuni isolates, ST-403 exhibited exceptionally high resistance gene carriage rates, with 78.57% (11/14) simultaneously harboring aac(6')-Ie-aph(2'')-Ia, ant(6)-Ia, aph(3')-IIIa, and aad(6) (aminoglycoside resistance genes), sat-4 (streptomycin resistance), and InuC (lincosamide resistance), while tet(O/M/O) demonstrated an even higher carriage rate of 85.71% (12/14). In contrast, specific β-lactam resistance genes (OXA-583, OXA-591) were exclusively identified in ST-21. Unlike the resistance gene patterns, C. jejuni ST-464 demonstrated the most diverse virulence gene profile, particularly showing enriched carriage of capsular polysaccharide (CPS) cluster genes Cj1413c-Cj1448c compared to other sequence types (Supplementary Figure S2).

Figure 2. 

Phylogenomic tree based on cg-SNPs in (A) C. jejuni and (B) C. coli.

Note: The first ring represents the strains and sources, the second ring represents the CCs, the third ring represents the isolated location, and the fourth ring represents the isolated date.

Abbreviation: cg-SNP=core genome single nucleotide polymorphism; CC=clonal complex.

This study leveraged genetic and drug resistance surveillance data to examine trends in Campylobacter infections across China from 2020 to 2023. The number of Campylobacter isolates reported through the National Pathogen Identification Network Center database increased substantially during this period. This upward trend likely reflects enhanced surveillance focus on Campylobacter infections combined with improved detection methodologies that have increased pathogen identification rates. Notably, fewer Campylobacter isolates were collected in 2020 and 2022 compared to 2021 and 2023, which may be attributed to disruptions caused by the COVID-19 pandemic (6).

While Campylobacter infections typically resolve without intervention, antimicrobial treatment becomes essential in severe or prolonged cases. Fluoroquinolones and macrolides serve as first-line therapeutic agents for human Campylobacter infections in clinical practice (7). Previous investigations of antibiotic resistance in Campylobacter-associated gastroenteritis have documented variable resistance patterns (8). Our analysis of resistance trends from 2020 to 2023 revealed persistent high-level resistance to multiple antibiotics, particularly nalidixic acid, ciprofloxacin, and tetracycline. Although overall resistance trends showed a declining pattern over the four-year period, the decreases for most antibiotics lacked statistical significance, indicating that multidrug resistance in Campylobacter remained consistently elevated. These findings underscore the continued need for more stringent antibiotic stewardship measures. Consistent with previous research, C. coli demonstrated higher resistance rates than C. jejuni (9). Given the emergence and dissemination of novel resistance mechanisms in Campylobacter, China must strengthen antimicrobial regulation while maintaining robust pathogen resistance surveillance programs.

Previous investigations have established strong correlations between antibiotic resistance phenotypes in Campylobacter and specific resistance genes or genetic mutations, with antimicrobial resistance genotypes serving as reliable predictors of resistance phenotypes (10). Our findings align with this principle, as the gyrA (T86I) mutation conferring quinolone resistance, the tet(O) gene responsible for tetracycline resistance, and the cme and OXA genes associated with β-lactam resistance were detected in most isolates, corresponding to the observed high resistance rates against nalidixic acid, ciprofloxacin, and tetracycline. C. coli exhibited more severe antibiotic resistance compared to C. jejuni. Recent studies have consistently identified various resistance genes in C. coli, including the erm gene associated with macrolide resistance and the fexA and optrA genes linked to phenicol resistance (11). These genes were also detected in our study, resulting in C. coli resistance to erythromycin, azithromycin, chloramphenicol, and florfenicol. Consequently, antimicrobial resistance in C. coli represents an increasingly significant public health threat, necessitating coordinated surveillance and management strategies to prevent the emergence and spread of resistant C. coli strains through food supply chains. The mechanisms underlying Campylobacter-induced diarrhea remain incompletely understood. Our analysis identified numerous Campylobacter isolates harboring genes associated with adhesion, colonization, motility, and invasion — factors critical for Campylobacter pathogenesis. Genes related to adherence, colonization, and invasion (including cadF, ciaC, flgB, flgC, fliE, fliR, fliW, flgP, jlpA, cheY, Cj1279c, and pebA) demonstrated high conservation among Campylobacter isolates and were present in the majority of clinical specimens. This conservation pattern highlights the substantial virulence potential of these Campylobacter isolates in human infections. Capsular polysaccharide plays a crucial role in Campylobacter pathogenicity (12). We identified a distinct cluster of isolates carrying virulence genes associated with capsular polysaccharide expression. Among the 26 isolates classified as ST-464, which represents the predominant sequence type in poultry reservoirs (13), 21 isolates (80.77%) clustered within this group. This finding indicates a strong phylogenetic association between ST-464 and capsular polysaccharide virulence determinants, potentially contributing to the pathogenicity and host adaptation characteristics of this sequence type. Additional research is needed to elucidate the specific genetic and evolutionary relationships involved.

The correlation between clonal complexes and factors such as sample sources and collection timeframes was relatively weak in this study. However, the predominance of human-derived samples introduces potential analytical bias. To address this limitation, future investigations should incorporate continuous, systematic surveillance of Campylobacter from diverse sources, which would strengthen epidemiological insights and inform more effective public health interventions.

As a critical foodborne pathogen affecting both developed and developing nations, systematic surveillance of Campylobacter remains essential for effective disease control and comprehensive food safety risk assessment. Our comprehensive analysis of the genetic characteristics and antibiotic resistance profiles of Campylobacter isolates collected across China from 2020 to 2023 provides crucial baseline data encompassing virulence gene distributions, antimicrobial resistance phenotypes and associated genetic markers, phylogenetic relationships, and the circulation patterns of resistance determinants. These findings reveal persistently high resistance rates to fluoroquinolones and tetracyclines, with C. coli demonstrating more extensive multidrug resistance compared to C. jejuni. The identification of specific sequence types associated with distinct virulence and resistance profiles, particularly the concentration of capsular polysaccharide genes in ST-464 isolates, highlights important epidemiological patterns that warrant continued monitoring. However, a notable limitation of this investigation is that antimicrobial susceptibility testing and whole-genome sequencing were performed on only a subset of available isolates, which may not fully capture the complete epidemiological landscape of Campylobacter infections in China. Future surveillance efforts should incorporate more comprehensive sampling strategies to enhance the representativeness of resistance and genetic diversity assessments.

We thank the colleagues from the National Pathogen Identification Network Center and the provincial and municipal Pathogen Identification Network Center.