Genomic insights into zoonotic transmission and antimicrobial resistance in <i>Campylobacter jejuni</i> from farm to fork: a one health perspective

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Abstract

Background

Campylobacteriosis represents a global public health threat with various socio-economic impacts. Among different Campylobacter species, Campylobacter jejuni ( C. jejuni) is considered to be the foremost Campylobacter species responsible for most of gastrointestinal-related infections. Although these species are reported to primarily inhabit birds, its high genetic and phenotypic diversity allowed their adaptation to other animal reservoirs and to the environment that may impact on human infection.

Main body

A stringent and consistent surveillance program based on high resolution subtyping is crucial. Recently, different epidemiological investigations have implemented high-throughput sequencing technologies and analytical pipelines for higher resolution subtyping, accurate source attribution, and detection of antimicrobial resistance determinants among these species. In this review, we aim to present a comprehensive overview on the epidemiology, clinical presentation, antibiotic resistance, and transmission dynamics of Campylobacter, with specific focus on C. jejuni. This review also summarizes recent attempts of applying whole-genome sequencing (WGS) coupled with bioinformatic algorithms to identify and provide deeper insights into evolutionary and epidemiological dynamics of C. jejuni precisely along the farm-to-fork continuum.

Conclusion

WGS is a valuable addition to traditional surveillance methods for Campylobacter. It enables accurate typing of this pathogen and allows tracking of its transmission sources. It is also advantageous for in silico characterization of antibiotic resistance and virulence determinants, and hence implementation of control measures for containment of infection.

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Most cited references 109

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Inference of Population Structure Using Multilocus Genotype Data

Jonathan Pritchard, Matthew Stephens, Peter Donnelly … (2001)

We describe a model-based clustering method for using multilocus genotype data to infer population structure and assign individuals to populations. We assume a model in which there are K populations (where K may be unknown), each of which is characterized by a set of allele frequencies at each locus. Individuals in the sample are assigned (probabilistically) to populations, or jointly to two or more populations if their genotypes indicate that they are admixed. Our model does not assume a particular mutation process, and it can be applied to most of the commonly used genetic markers, provided that they are not closely linked. Applications of our method include demonstrating the presence of population structure, assigning individuals to populations, studying hybrid zones, and identifying migrants and admixed individuals. We show that the method can produce highly accurate assignments using modest numbers of loci—e.g., seven microsatellite loci in an example using genotype data from an endangered bird species. The software used for this article is available from http://www.stats.ox.ac.uk/~pritch/home.html.

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CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

Brian P. Alcock, Amogelang Raphenya, Tammy Lau … (2019)

Abstract The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.

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ResFinder 4.0 for predictions of phenotypes from genotypes

Valeria Bortolaia, Rolf S. Kaas, Etienne Ruppé … (2020)

Abstract Objectives WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output. Methods The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins. Results Genotype–phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype–phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance. Conclusions WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.

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Author and article information

Contributors

Mohamed Elhadidy: melhadidy@zewailcity.edu.eg

Journal

Journal ID (nlm-ta): Gut Pathog

Journal ID (iso-abbrev): Gut Pathog

Title: Gut Pathogens

Publisher: BioMed Central (London )

ISSN (Electronic): 1757-4749

Publication date (Electronic): 5 December 2022

Publication date PMC-release: 5 December 2022

Publication date Collection: 2022

Volume: 14

Electronic Location Identifier: 44

Affiliations

[1 ]GRID grid.440881.1, ISNI 0000 0004 0576 5483, Biomedical Sciences Program, , University of Science and Technology, Zewail City of Science and Technology, ; Giza, Egypt

[2 ]GRID grid.440881.1, ISNI 0000 0004 0576 5483, Center for Genomics, Helmy Institute for Medical Sciences, , Zewail City of Science and Technology, ; Giza, Egypt

[3 ]GRID grid.7269.a, ISNI 0000 0004 0621 1570, Department of Microbiology and Immunology, Faculty of Pharmacy, , Ain Shams University, ; Cairo, Egypt

[4 ]GRID grid.7776.1, ISNI 0000 0004 0639 9286, Department of Microbiology and Immunology, Faculty of Pharmacy, , Cairo University, ; Cairo, Egypt

[5 ]GRID grid.4807.b, ISNI 0000 0001 2187 3167, Department of Food Hygiene and Technology and Institute of Food Science and Technology, , Universidad de León, ; León, Spain

[6 ]GRID grid.10251.37, ISNI 0000000103426662, Department of Bacteriology, Mycology and Immunology, Faculty of Veterinary Medicine, , Mansoura University, ; Mansoura, Egypt

Article

Publisher ID: 517

DOI: 10.1186/s13099-022-00517-w

PMC ID: 9721040

PubMed ID: 36471447

SO-VID: 80237f58-f904-410f-8703-562d953dc20b

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 19 August 2022

Date accepted : 8 November 2022

Funding

Funded by: Zewail City internal research grant fund

Award ID: ZC 004-2019

Award Recipient : Mohamed Elhadidy

Funded by: joint ASRT/BA research grant

Award ID: Project number 1110

Award Recipient : Mohamed Elhadidy

Funded by: Zewail City of Science & Technology

Open Access :

Open access funding provided by The Science, Technology & Innovation Funding Authority (STDF) in cooperation with The Egyptian Knowledge Bank (EKB).

Custom metadata

ScienceOpen disciplines: Gastroenterology & Hepatology

Keywords: campylobacteriosis,campylobacter jejuni,whole genome sequencing,molecular subtyping,surveillance

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ScienceOpen disciplines: Gastroenterology & Hepatology

Keywords: campylobacteriosis, campylobacter jejuni, whole genome sequencing, molecular subtyping, surveillance

Genomic insights into zoonotic transmission and antimicrobial resistance in Campylobacter jejuni from farm to fork: a one health perspective

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Abstract

Background

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Conclusion

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Karger: Gastroenterology

Most cited references 109

Inference of Population Structure Using Multilocus Genotype Data

CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

ResFinder 4.0 for predictions of phenotypes from genotypes

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