Genomic Variation between Campylobacter jejuni Isolates Associated with Milk-Borne-Disease Outbreaks

Revez, Joana; Zhang, Ji; Schott, Thomas; Kivistö, Rauni; Rossi, Mirko; Hänninen, Marja‐Liisa

doi:10.1128/jcm.00931-14

Cited by 47 publications

(46 citation statements)

References 27 publications

(45 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This work has clearly shown that, regardless of the methodology used, the genomic diversity among epidemiologically linked isolates within an outbreak investigation is limited to a few changes, which mainly affect homopolymeric runs. Revez et al, analyzing a milk-borne outbreak, observed up to 3 SNVs and phase variations in 12 loci between the milk-and patient-derived isolates, using a PubMLST-hosted whole-genome multilocus sequence typing (wgMLST) schema featuring 1,738 loci (15). A similar number of genomic differences (3 SNVs) was observed between one human isolate and the assumed source isolate in a waterborne outbreak (7).…”

Section: Application Of Wgs Of C Jejuni In Point-source Outbreak Invmentioning

confidence: 94%

“…Due to their intrinsic genetic instability, variations observed in these genomic regions cannot be used to infer epidemiological relationships between isolates. Therefore, to ensure that the genetic signals used for tracing and source attribution of isolates are independent of genomic changes introduced by the host, such homopolymeric tracts should be excluded from genome comparisons in the context of public health investigations (7,8,15,16).…”

Section: Genomic Diversity During C Jejuni Infection and Colonizationmentioning

confidence: 99%

See 1 more Smart Citation

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

2017

Self Cite

View full text Add to dashboard Cite

This review describes the current state of knowledge regarding the application of whole-genome sequencing (WGS) in the epidemiology of Campylobacter jejuni, the leading cause of bacterial gastroenteritis worldwide. We describe how WGS has increased our understanding of the evolutionary and epidemiological dynamics of this pathogen and how WGS has the potential to improve surveillance and outbreak detection. We have identified hurdles to the full implementation of WGS in public health settings. Despite these challenges, we think that ample evidence is available to support the benefits of integrating WGS into the routine monitoring of C. jejuni infections and outbreak investigations.KEYWORDS foodborne pathogens, genome analysis, molecular subtyping, surveillance studies T he ability to conduct epidemiological investigations and to intervene to control and to prevent foodborne and environmentally transmitted diseases is a major task of public health authorities. The identification, over a short period of time, of a sudden increase in the number of expected cases of a disease in a population in a limited geographical area (point-source outbreak) or clusters of cases with a presumptive common source not necessarily clustered geographically (diffuse outbreak) depends on knowledge of the baseline infectious state of the population regarding that disease, which is usually acquired through surveillance. In this regard, identifying epidemiologically linked cases and differentiating them from concurrent sporadic incidences are essential for risk assessment, outbreak investigations, and source attribution for foodborne pathogens. These processes have relied increasingly on traditional epidemiological investigations supplemented with molecular subtyping of the etiological agent, and no method offers a higher degree of resolution than whole-genome sequencing (WGS). The recent development of high-throughput sequencing technologies for WGS (i.e., next-generation sequencing [NGS]) has resulted in large-scale sequencing of various pathogens. Allowing the detection of all possible epidemiologically significant variations between strains (1), WGS is progressively replacing traditional typing methods (serotyping, phenotyping, pulsed-field gel electrophoresis [PFGE], and amplified fragment length polymorphism [AFLP] analysis) and sequence-based investigations (PCR-based methods). Moreover, the declining costs of NGS and the availability of benchtop analyzers are increasingly facilitating the application of WGS for routine surveillance and outbreak investigations of bacterial and viral infectious diseases by public health authorities (2). As a result, WGS analysis is currently being used in several countries for real-time surveillance of Listeria monocytogenes and Salmonella enterica (http://www.fda.gov/Food/FoodScience Research/WholeGenomeSequencingProgramWGS) (3), and similar approaches for other foodborne pathogens are expected to come into use shortly. Campylobacter jejuni is one of the most frequent causes of bacterial g...

show abstract

Section: Application Of Wgs Of C Jejuni In Point-source Outbreak Invmentioning

confidence: 94%

Section: Genomic Diversity During C Jejuni Infection and Colonizationmentioning

confidence: 99%

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

2017

Self Cite

View full text Add to dashboard Cite

show abstract

“…Recently, whole genome sequencing has offered that discriminatory power with the potential to enhance epidemiological investigations and elucidate transmission pathways (Phillips et al, 2016). The use of next-generation sequencing technology for WGS allows for the sequencing of large numbers of isolates, and novel bioinformatics tools can be used for comparative genomics and analysis of the phylogeny of the isolates (Revez et al, 2014). WGS has been a very useful and powerful tool for establishing potential links between clinical, food and environmental isolates of pathogens, which could allow the identification of the source of contamination and remove contaminated foods from markets (Deng et al, 2016).…”

Section: Whole Genome Sequencingmentioning

confidence: 99%

Foodborne bacteria in dairy products: Detection by molecular techniques

Cancino‐Padilla

Fellenberg

Franco

et al. 2017

Ciencia e investigación agraria

View full text Add to dashboard Cite

Staphylococcus aureus, Salmonella spp., Listeria monocytogenes and Escherichia coli O157:H7 are the most frequent potential pathogens associated with milk or dairy products in industrialized countries and are therefore the main microbiological hazards linked to raw milk and raw cheese. This review summarizes the scientific information about outbreaks related to foodborne pathogens in dairy products and highlights the increasing application of molecular approaches to detect and identify the bacteria responsible for these outbreaks. Molecular techniques have facilitated the rapid detection and identification of foodborne pathogens, which has been crucial for current surveillance and outbreak control.

show abstract

“…The cgMLST methods address this problem by comparing only genes common to a set of bacterial isolates (2). These methods are now mature and have been applied successfully to the analysis of a number of bacterial outbreaks (8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21).Given the developments in WGS-based strain typing described above, there is much excitement about applying these methods to real-time hospital epidemiology, but the actual cost-benefit equation, the feasibility of achieving results on an actionable time scale, and the technical requirements for implementation in a "real world" clinical microbiology laboratory are difficult to study. In work published in this issue of the Journal of Clinical Microbiology, …”

mentioning

confidence: 99%

mentioning

confidence: 99%

Commentary: Next-Generation Epidemiology: Using Real-Time Core Genome Multilocus Sequence Typing To Support Infection Control Policy

Dekker

Frank

2016

J Clin Microbiol

View full text Add to dashboard Cite

M ultilocus sequencing typing (MLST), introduced by Maiden and colleagues in 1998, has come to represent one of the most widely used and successful molecular methods for strainlevel classification of bacterial isolates (1). MLST schemes work by indexing sequence variation in a small set of housekeeping genes to a numerical classification system. Each novel sequence occurring at any of the selected loci is named as a unique numbered allele, and the profile of a given isolate is specified by the numbers representing the allelic composition. Each combination of alleles is assigned a unique sequence type (ST), and STs, in turn, can be grouped into higher levels of classification (2, 3). The ability of MLST to resolve closely related strains is limited in principle by the absolute sequence diversity present in the loci covered by the scheme and by the manner in which this sequence diversity distributes across the population to be classified. As MLST schemes require conserved PCR primer binding sites, the targets must also be sufficiently conserved so that the method works robustly, and this puts limits on the resolution of classical MLST (3). MLST schemes have now been developed for Ͼ100 genera and species, and continuously updated databases are maintained by the University of Oxford, United Kingdom (pubmlst.org), Imperial College London, London, United Kingdom (http://www.mlst.net/), and others.Classical MLST analysis, developed to be compatible with Sanger sequencing methods, is based on 400-to-500-nucleotide segments of (usually) seven genes, encompassing Ͻ0.2% of the bacterial genome in many cases (3). Advances in whole-genome sequencing (WGS) and the availability of a large number of assembled bacterial genomes have made possible new approaches to strain-and clone-level epidemiologic tracking of isolates, including the ability to apply MLST schemes on a genome-wide scale. Inference of clonal relationships from the comparison of wholegenome sequences for the purpose of epidemiologic investigations can involve a bit more subtlety than classical MLST analysis, however, and there are abundant opportunities for drawing incorrect conclusions. Perhaps the simplest of the many available approaches is that of direct-alignment-based (single nucleotide polymorphism [SNP]-based) phylogenetic analysis, often built on the underlying statistical assumptions of independent individual substitution events. Direct-alignment-based phylogenetic analyses have been used to study the population structures of bacterial outbreaks and to construct transmission maps in a variety of epidemiologic investigations (4-6). However, single recombination events, mobile genetic element insertions, or other horizontal genetic transfer events can result in multiple SNPs or more-complex rearrangements over a contiguously exchanged or interrupted region. Consequently, genome-wide direct-alignment methods, in addition to being computationally expensive, may result in the generation of incorrect tree topologies due to such rearrangements (7). Alternative...

show abstract

Genomic Variation between Campylobacter jejuni Isolates Associated with Milk-Borne-Disease Outbreaks

Cited by 47 publications

References 27 publications

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

Whole-Genome Sequencing in Epidemiology of Campylobacter jejuni Infections

Foodborne bacteria in dairy products: Detection by molecular techniques

Commentary: Next-Generation Epidemiology: Using Real-Time Core Genome Multilocus Sequence Typing To Support Infection Control Policy

Contact Info

Product

Resources

About