ArticleEuropean journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology2021
Prediction of antimicrobial resistance in clinical Campylobacter jejuni isolates from whole-genome sequencing data.
Article in European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 48 citations in OpenAlex.
- Genomic association of Campylobacter concisus for colonization advantages and virulence in children and adolescents with inflammatory bowel disease.BMC microbiology · 2026Article
- WGS-based surveillance for Campylobacter spp. in human infections and chicken meat production in Italy (2023).BMC microbiology · 2025Article
- Distribution of Antimicrobial Resistance and Biofilm Production Genes in the Genomic Sequences ofAntibiotics (Basel, Switzerland) · 2025Article
- Antimicrobial susceptibility profiles of thermophilicFrontiers in microbiology · 2025Article
- Neural network-based predictions of antimicrobial resistance phenotypes in multidrug-resistantAntimicrobial agents and chemotherapy · 2024Article
- Genotypic characterization and antimicrobial susceptibility of humanMicrobiology spectrum · 2024Article
- Genomic resistant determinants of multidrug-resistant Campylobacter spp. isolates in Peru.Journal of global antimicrobial resistance · 2024Article
- Gene expression profile of Campylobacter jejuni in response to macrolide antibiotics.Archives of microbiology · 2024Article
- Identification of knowledge gaps in whole-genome sequence analysis of multi-resistant thermotolerant Campylobacter spp.BMC genomics · 2024Article
- Epidemiological Data and Antimicrobial Resistance ofPathogens (Basel, Switzerland) · 2024Article
- Genotyping of Campylobacter jejuni and prediction tools of its antimicrobial resistance.Folia microbiologica · 2024Article
- Cellulitis with bacteremia due to multidrug-resistantIDCases · 2024Article
- Quantitative assessment and genomic profiling ofFrontiers in microbiology · 2024Article
- Rapid metagenomic sequencing for diagnosis and antimicrobial sensitivity prediction of canine bacterial infections.Microbial genomics · 2023Article
- Reservoirs of antimicrobial resistance in the context of One Health.Current opinion in microbiology · 2023Review
- Clinical Diagnostics of Bacterial Infections and Their Resistance to Antibiotics-Current State and Whole Genome Sequencing Implementation Perspectives.Antibiotics (Basel, Switzerland) · 2023Review
- Low-Level Tetracycline Resistance GeneAntibiotics (Basel, Switzerland) · 2023Article
- Genomic characterization of molecular markers associated with antimicrobial resistance and virulence of the prevalentCurrent research in food science · 2023Article
- Genomic insight intoFrontiers in veterinary science · 2023Article
- Comparative genomics of Campylobacter jejuni from clinical campylobacteriosis stool specimens.Gut pathogens · 2022Article
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Campylobacter jejuni is recognised as the leading cause of bacterial gastroenteritis in industrialised countries. Although the majority of Campylobacter infections are self-limiting, antimicrobial treatment is necessary in severe cases. Therefore, the development of antimicrobial resistance (AMR) in Campylobacter is a growing public health challenge and surveillance of AMR is important for bacterial disease control. The aim of this study was to predict antimicrobial resistance in C. jejuni from whole-genome sequencing data. A total of 516 clinical C. jejuni isolates collected between 2014 and 2017 were subjected to WGS. Resistance phenotypes were determined by standard broth dilution, categorising isolates as either susceptible or resistant based on epidemiological cutoffs for six antimicrobials: ciprofloxacin, nalidixic acid, erythromycin, gentamicin, streptomycin, and tetracycline. Resistance genotypes were identified using an in-house database containing reference genes with known point mutations and the presence of resistance genes was determined using the ResFinder database and four bioinformatical methods (modified KMA, ABRicate, ARIBA, and ResFinder Batch Upload). We identified seven resistance genes including tet(O), tet(O/32/O), ant(6)-Ia, aph(2″)-If, blaOXA, aph(3')-III, and cat as well as mutations in three genes: gyrA, 23S rRNA, and rpsL. There was a high correlation between phenotypic resistance and the presence of known resistance genes and/or point mutations. A correlation above 98% was seen for all antimicrobials except streptomycin with a correlation of 92%. In conclusion, we found that WGS can predict antimicrobial resistance with a high degree of accuracy and have the potential to be a powerful tool for AMR surveillance.
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