GenomeGraphR: A user-friendly open-source web application for foodborne pathogen whole genome sequencing data integration, analysis, and visualization

Abstract

Food safety risk assessments and large-scale epidemiological investigations have the potential to provide better and new types of information when whole genome sequence (WGS) data are effectively integrated. Today, the NCBI Pathogen Detection database WGS collections have grown significantly through improvements in technology, coordination, and collaboration, such as the GenomeTrakr and PulseNet networks. However, high-quality genomic data is not often coupled with high-quality epidemiological or food chain metadata. We have created a set of tools for cleaning, curation, integration, analysis and visualization of microbial genome sequencing data. It has been tested using Salmonella enterica and Listeria monocytogenes data sets provided by NCBI Pathogen Detection (160,000 sequenced isolates in 2018). GenomeGraphR presents foodborne pathogen WGS data and associated curated metadata in a user-friendly interface that allows a user to query a variety of research questions such as, transmission sources and dynamics, global reach, and persistence of genotypes associated with contamination in the food supply and foodborne illness across time or space. The application is freely available ( https://fda-riskmodels.foodrisk.org/genomegraphr/ ).

Genetic diversity and profiles of genes associated with virulence and stress resistance among isolates from the 2010-2013 interagency Listeria monocytogenes market basket survey

“…NCBI Pathogen Detection tool (https://www.ncbi.nlm.nih.gov/pathogens) clusters and identifies related genomes that are deposited into GenomeTrakr, which could be used to identify clinical isolates related to the isolate in the 2010-2013 Lm MBS survey. In addition, such clusters and curated metadata can be integrated in GenomeGraphR, a web-based visualization and analytic tool, to investigate routes of transmission, to identify persistence and virulence phenotypes, to assess exposure and to characterize hazard [82]. Indeed, WGS data from food and clinical isolates, together with metadata, could also be used to refine assumptions underlying an existing dose-response model [10].…”

Accurate reconstruction of bacterial pan- and core genomes with PEPPAN

“…The insufficiency of data no longer exists, as bacterial genome assemblies now number in the 100,000s for some genera (Sanaa et al 2019;Zhou et al 2020). However, such large numbers of genomes exacerbate the scalability problem.…”

Whole Genome Sequencing Based Surveillance of L. monocytogenes for Early Detection and Investigations of Listeriosis Outbreaks

“…For two decades, PFGE was the reference method for L. monocytogenes surveillance and outbreak investigation (2, 22). It is still used for screening but is increasingly replaced by WGS based typing methods (7, 14, 21, 23–26). WGS based typing outperforms PFGE with respect to the discriminatory power, information content, throughput, reproducibility, costs and inter-laboratory data exchange.…”

“…All isolates had 98.1–99.8% good targets and a minimum spanning tree (MST) was generated in Ridom SeqSphere+ version 5.1.0 for visualization of strain relatedness. For comparison and data harmonization SeqSphere+ results were compared to the Pasteur cgMLST scheme (7) and GenomeGraphR (14). The sequences have been deposited in DDBJ/EMBL/GenBank under the project number PRJNA434392.…”

“…SNP analysis was done with GenomeGraphR Beta 2.7 [Sanaa et al (14)] using the default settings and a cluster threshold definition of 12 SNPs. All strains were compared with the isolates present in the database.…”