Foodborne outbreak investigation

ABSTRACT Recall inaccuracies are a key limitation in a foodborne outbreak investigation. Misclassifications in self-reported exposure status reduce the power of epidemiological studies to detect meaningful associations between exposures and the development of illness. The purpose of this study was to investigate the effect of recall inaccuracies on the validity of food history data in a context comparable to outbreak investigations. The food consumption of 96 university students was collected using Ethica, a smartphone-based data acquisition system. Comprehensive food histories were captured for 10 days through a combination of digital images, meal descriptions, and short food exposure surveys. These real-time data were used as a reference to measure the sensitivity and specificity of food history questionnaires administered 7 or 18 days (2.5 weeks) after consumption (n = 86). The questionnaires and time intervals used in this study were designed to resemble a range of plausible local, provincial, and national enteric outbreak investigations conducted by public health officials in Canada. Comparably low accuracy of dietary memory after both time intervals suggests there is a substantial potential for bias for most food types following the first week after consumption. The magnitude of recall inaccuracies was not uniform across food types. This study serves as a first step in quantifying recall inaccuracies in a context comparable to how cases and controls might be questioned for outbreak investigations so that recall inaccuracies can be accounted for and mitigated in public health practice. HIGHLIGHTS

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Global Food-source Identifier (GFI): Collaborative virtual research environment and shared data catalogue for the foodborne outbreak investigation international community

Food Control ◽

10.1016/j.foodcont.2020.107623 ◽

2021 ◽

Vol 121 ◽

pp. 107623

Author(s):

Ana Sofia Ribeiro Duarte ◽

Cecilie Liv Nielsen ◽

Leonardo Candela ◽

Lars Valentin ◽

Frank M. Aarestrup ◽

...

Keyword(s):

Food Source ◽

International Community ◽

Outbreak Investigation ◽

Foodborne Outbreak ◽

Research Environment ◽

Shared Data ◽

Virtual Research Environment ◽

Global Food

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Strain-Level Metagenomic Data Analysis of Enriched In Vitro and In Silico Spiked Food Samples: Paving the Way towards a Culture-Free Foodborne Outbreak Investigation Using STEC as a Case Study

International Journal of Molecular Sciences ◽

10.3390/ijms21165688 ◽

2020 ◽

Vol 21 (16) ◽

pp. 5688

Author(s):

Assia Saltykova ◽

Florence E. Buytaers ◽

Sarah Denayer ◽

Bavo Verhaegen ◽

Denis Piérard ◽

...

Keyword(s):

Data Analysis ◽

In Silico ◽

Food Samples ◽

Strain Level ◽

Outbreak Investigation ◽

Metagenomic Data ◽

Analysis Approach ◽

Foodborne Outbreak ◽

Metagenomic Approach

Culture-independent diagnostics, such as metagenomic shotgun sequencing of food samples, could not only reduce the turnaround time of samples in an outbreak investigation, but also allow the detection of multi-species and multi-strain outbreaks. For successful foodborne outbreak investigation using a metagenomic approach, it is, however, necessary to bioinformatically separate the genomes of individual strains, including strains belonging to the same species, present in a microbial community, which has up until now not been demonstrated for this application. The current work shows the feasibility of strain-level metagenomics of enriched food matrix samples making use of data analysis tools that classify reads against a sequence database. It includes a brief comparison of two database-based read classification tools, Sigma and Sparse, using a mock community obtained by in vitro spiking minced meat with a Shiga toxin-producing Escherichia coli (STEC) isolate originating from a described outbreak. The more optimal tool Sigma was further evaluated using in silico simulated metagenomic data to explore the possibilities and limitations of this data analysis approach. The performed analysis allowed us to link the pathogenic strains from food samples to human isolates previously collected during the same outbreak, demonstrating that the metagenomic approach could be applied for the rapid source tracking of foodborne outbreaks. To our knowledge, this is the first study demonstrating a data analysis approach for detailed characterization and phylogenetic placement of multiple bacterial strains of one species from shotgun metagenomic WGS data of an enriched food sample.

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A Practical Method to Implement Strain-Level Metagenomics-Based Foodborne Outbreak Investigation and Source Tracking in Routine

Microorganisms ◽

10.3390/microorganisms8081191 ◽

2020 ◽

Vol 8 (8) ◽

pp. 1191

Author(s):

Florence E. Buytaers ◽

Assia Saltykova ◽

Sarah Denayer ◽

Bavo Verhaegen ◽

Kevin Vanneste ◽

...

Keyword(s):

Food Product ◽

Practical Method ◽

Outbreak Investigation ◽

Source Tracking ◽

Foodborne Outbreak ◽

Accurate Identification ◽

Shotgun Metagenomics ◽

Chain Reactions ◽

Food Isolate ◽

Food Matrices

The management of a foodborne outbreak depends on the rapid and accurate identification of the responsible food source. Conventional methods based on isolation of the pathogen from the food matrix and target-specific real-time polymerase chain reactions (qPCRs) are used in routine. In recent years, the use of whole genome sequencing (WGS) of bacterial isolates has proven its value to collect relevant information for strain characterization as well as tracing the origin of the contamination by linking the food isolate with the patient’s isolate with high resolution. However, the isolation of a bacterial pathogen from food matrices is often time-consuming and not always successful. Therefore, we aimed to improve outbreak investigation by developing a method that can be implemented in reference laboratories to characterize the pathogen in the food vehicle without its prior isolation and link it back to human cases. We tested and validated a shotgun metagenomics approach by spiking food pathogens in specific food matrices using the Shiga toxin-producing Escherichia coli (STEC) as a case study. Different DNA extraction kits and enrichment procedures were investigated to obtain the most practical workflow. We demonstrated the feasibility of shotgun metagenomics to obtain the same information as in ISO/TS 13136:2012 and WGS of the isolate in parallel by inferring the genome of the contaminant and characterizing it in a shorter timeframe. This was achieved in food samples containing different E. coli strains, including a combination of different STEC strains. For the first time, we also managed to link individual strains from a food product to isolates from human cases, demonstrating the power of shotgun metagenomics for rapid outbreak investigation and source tracking.

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Whole Genome Sequencing Provides an Added Value to the Investigation of Staphylococcal Food Poisoning Outbreaks

Frontiers in Microbiology ◽

10.3389/fmicb.2021.750278 ◽

2021 ◽

Vol 12 ◽

Author(s):

Stéphanie Nouws ◽

Bert Bogaerts ◽

Bavo Verhaegen ◽

Sarah Denayer ◽

Lasse Laeremans ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Protein A ◽

Food Poisoning ◽

Gene Profiling ◽

Added Value ◽

Outbreak Investigation ◽

Whole Genome ◽

Foodborne Outbreak ◽

Chain Reactions

Through staphylococcal enterotoxin (SE) production, Staphylococcus aureus is a common cause of food poisoning. Detection of staphylococcal food poisoning (SFP) is mostly performed using immunoassays, which, however, only detect five of 27 SEs described to date. Polymerase chain reactions are, therefore, frequently used in complement to identify a bigger arsenal of SE at the gene level (se) but are labor-intensive. Complete se profiling of isolates from different sources, i.e., food and human cases, is, however, important to provide an indication of their potential link within foodborne outbreak investigation. In addition to complete se gene profiling, relatedness between isolates is determined with more certainty using pulsed-field gel electrophoresis, Staphylococcus protein A gene typing and other methods, but these are shown to lack resolution. We evaluated how whole genome sequencing (WGS) can offer a solution to these shortcomings. By WGS analysis of a selection of S. aureus isolates, including some belonging to a confirmed foodborne outbreak, its added value as the ultimate multiplexing method was demonstrated. In contrast to PCR-based se gene detection for which primers are sometimes shown to be non-specific, WGS enabled complete se gene profiling with high performance, provided that a database containing reference sequences for all se genes was constructed and employed. The custom compiled database and applied parameters were made publicly available in an online user-friendly interface. As an all-in-one approach with high resolution, WGS additionally allowed inferring correct isolate relationships. The different DNA extraction kits that were tested affected neither se gene profiling nor relatedness determination, which is interesting for data sharing during SFP outbreak investigation. Although confirming the production of enterotoxins remains important for SFP investigation, we delivered a proof-of-concept that WGS is a valid alternative and/or complementary tool for outbreak investigation.

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