Integrating Whole-Genome Sequencing Data Into Quantitative Risk Assessment of Foodborne Antimicrobial Resistance: A Review of Opportunities and Challenges

Abstract

Whole-genome sequencing (WGS) will soon replace traditional phenotypic methods for routine testing of foodborne antimicrobial resistance (AMR). WGS is expected to improve AMR surveillance by providing a greater understanding of the transmission of resistant bacteria and AMR genes throughout the food chain, and therefore support risk assessment activities. At this stage, it is unclear how WGS data can be integrated into quantitative microbial risk assessment (QMRA) models and whether their integration will impact final risk estimates or the assessment of risk mitigation measures. This review explores opportunities and challenges of integrating WGS data into QMRA models that follow the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR. We describe how WGS offers an opportunity to enhance the next-generation of foodborne AMR QMRA modeling. Instead of considering all hazard strains as equally likely to cause disease, WGS data can improve hazard identification by focusing on those strains of highest public health relevance. WGS results can be used to stratify hazards into strains with similar genetic profiles that are expected to behave similarly, e.g., in terms of growth, survival, virulence or response to antimicrobial treatment. The QMRA input distributions can be tailored to each strain accordingly, making it possible to capture the variability in the strains of interest while decreasing the uncertainty in the model. WGS also allows for a more meaningful approach to explore genetic similarity among bacterial populations found at successive stages of the food chain, improving the estimation of the probability and magnitude of exposure to AMR hazards at point of consumption. WGS therefore has the potential to substantially improve the utility of foodborne AMR QMRA models. However, some degree of uncertainty remains in relation to the thresholds of genetic similarity to be used, as well as the degree of correlation between genotypic and phenotypic profiles. The latter could be improved using a functional approach based on prediction of microbial behavior from a combination of ‘omics’ techniques (e.g., transcriptomics, proteomics and metabolomics). We strongly recommend that methodologies to incorporate WGS data in risk assessment be included in any future revision of the Codex Alimentarius Guidelines for Risk Analysis of Foodborne AMR.

High-resolution characterisation of ESBL/pAmpC-producing Escherichia coli isolated from the broiler production pyramid

“…Another study suggested that pathogenicity may be linked to genome reduction rather than the acquisition of certain VGs 40 . It is therefore likely that traditional pathotyping schemes will be modified in the future and that multi-omic pathogenicity predictive models that consider the presence and expression of all genes rather than small sets will gain more ground as genome databases grow 11 . Nevertheless, the virulence gene repertoire of ESBL/pAmpC-EC reported here and in other studies, may explain their adaptation to and persistence in various niches, such as the poultry environment 41 .…”

“…However, our study has limitations. Quantitative estimates on transmission pathways as well as statistical associations between the identified genotypes, which are essential for QMRAs, cannot be inferred with our analysis since this would require the www.nature.com/scientificreports/ sequencing of a larger and more representative part of our initial collection of isolates 11 . Such approaches are hampered by the decreasing but still significant cost of WGS.…”

“…These results contribute to the growing amount of available high throughput data that will serve as the baseline for future food chain QMRA models. For example, the AMR profile, the genetic context of resistance genes and the virulence potential of isolates described in this study are relevant for guiding the risk identification and characterisation steps 11 . Given the key role of plasmids in the dissemination of ESBL/pAmpC genes elucidated here and in other studies 9 , exposure assessment modelling should definitely include, if not prioritise on, the transfer probability of ESBL/pAmpC plasmids, especially of those with a wide host-spectrum.…”

“…However, the connection between human exposure and presence of ESBL/pAmpC-EC in broilers was supported by circumstantial evidences showing the presence of identical ESBL/pAmpC genes in closely related E. coli of both hosts inferred by low-resolution typing methods 9,10 . The importance of high-resolution, whole genome sequencing (WGS) studies in informing and reducing the uncertainty of quantitative microbial risk assessment (QMRA) models employed in the risk analysis of foodborne antimicrobial resistance was recently stressed 11,12 . Such an assessment for the broiler chain would require the thorough characterisation of ESBL/pAmpC-EC and their transmission patterns across the production pyramid 5 .…”

First and broad detection of three typical carbapenemase genes on the surfaces of commercially available spices worldwide and isolation of complete NDM-1 genes from black pepper, cumin, and clove

“…Antimicrobial resistance (AMR) has become great concern worldwide in the clinical field as well as in the field of food production and distribution, or the food chain (1)(2)(3)(4)(5)(6)(7). Carbapenem resistance is one of the most severe forms of AMR (1,8), and carbapenemase [a subgroup of β-lactamase (bla)]-producing bacteria, such as carbapenemase-producing Enterobacteriaceae, are spreading worldwide (9,10).…”