Whole Genome Sequencing Applied to Pathogen Source Tracking in Food Industry: Key Considerations for Robust Bioinformatics Data Analysis and Reliable Results Interpretation

Abstract

Whole genome sequencing (WGS) has arisen as a powerful tool to perform pathogen source tracking in the food industry thanks to several developments in recent years. However, the cost associated to this technology and the degree of expertise required to accurately process and understand the data has limited its adoption at a wider scale. Additionally, the time needed to obtain actionable information is often seen as an impairment for the application and use of the information generated via WGS. Ongoing work towards standardization of wet lab including sequencing protocols, following guidelines from the regulatory authorities and international standardization efforts make the technology more and more accessible. However, data analysis and results interpretation guidelines are still subject to initiatives coming from distinct groups and institutions. There are multiple bioinformatics software and pipelines developed to handle such information. Nevertheless, little consensus exists on a standard way to process the data and interpret the results. Here, we want to present the constraints we face in an industrial setting and the steps we consider necessary to obtain high quality data, reproducible results and a robust interpretation of the obtained information. All of this, in a time frame allowing for data-driven actions supporting factories and their needs.

Surveillance of Listeria monocytogenes: Early Detection, Population Dynamics, and Quasimetagenomic Sequencing during Selective Enrichment

“…WGS is predominantly applied in outbreak situations by food authorities or researchers but is becoming more important as a surveillance tool for source tracking of pathogens in the food industry ( 16 , 54 ). While other studies have shown the potential of Illumina MiSeq and Oxford Nanopore MinION sequencing ( 26 , 28 , 29 ), we wanted to test Nanopore Flongle flow cells as a low-cost, real-time sequencing alternative.…”

“…In order to move toward a situation where the management of L. monocytogenes is not based only on the presence or absence of the pathogen in a sample and where genetic typing information is analyzed retrospectively, food manufacturers and quality managers need a methodological pipeline to rapidly distinguish between sporadic contamination, reoccurring contamination from raw materials or other sources, and persistence of certain clones. To enable better pathogen source tracking and quality surveillance, the food industry needs to test and implement new methods and approaches to increase the speed and resolution of pathogen detection and microbiome surveillance ( 16 ).…”

The power, potential, benefits, and challenges of implementing high-throughput sequencing in food safety systems

“…Research and development (R&D) is an active area where these companies are testing and evaluating the multifaceted use of this technology. Such evaluations are conducted, for example, to compare the accuracy of different sequencing platforms for serotype predictions, to investigate laboratory cross-contaminations 53 , to validate sequence workflows, to understand pathogenic genetic responses to heat stress and source tracking 54 , 55 , and to catalog, characterize and quantify foodborne pathogenic bacteria and the related bacterial communities along the food supply chain 56 .…”

Phylogenomic Analysis of Salmonella enterica subsp. enterica Serovar Bovismorbificans from Clinical and Food Samples Using Whole Genome Wide Core Genes and kmer Binning Methods to Identify Two Distinct Polyphyletic Genome Pathotypes

“…Genome-wide and core genome analysis of Salmonella serovars using WGS datasets has been proven to be capable of profiling underlying evolutionary processes contributing to the genome backbone differences among different lineages constituting a conventionally typed serovar [19][20][21][22]46,47]. The application of WGS technology for sequence-based serotyping [25,48], characterization of outbreak isolates [49,50], source-tracking in the epidemiological investigation of foodborne outbreaks, and phylogenetic relationships [51][52][53][54][55] have been well documented. The robust bioinformatic workflow from this study utilizes an ad hoc set of complete genome assemblies for high-resolution phylogenetic analysis and adds to the existing S. enterica core-genes (cgMLST) and whole genome MLST (wgMLST) typing schema hosted on public resources such as EnteroBase and SISTR [46,48].…”