Foreword

The Inter EURLs Working Group (WG) has been established by the European Commission to promote the use of NGS across the EURLs' networks, build NGS capacity within the EU, and ensure liaison with the work of the EURLs and the work of EFSA and ECDC on the NGS mandate sent by the Commission. The WG includes all the EURLs operating in the field of microbiological contamination of food and feed.

Course Objectives

ONLINE
• Explain the principles of raw-read QC and contamination assessment, and their relevance for downstream analyses.
• Introduce the main approaches for WGS-based typing (including virulotyping and serotyping), allele-based relatedness assessment, and SNP-based analysis.
• Clarify the interpretation of genomic clustering results.
• Share relevant guidance, good practices, and interpretation principles developed within the Inter-EURLs framework.

ONSITE
• Apply the concepts covered online to the analysis and interpretation of WGS data in a hands-on setting.
• Work through QC, contamination assessment, typing, and cluster analysis using user-friendly approaches.
• Interpret results from participant datasets and trainer-provided example datasets.
• Discuss quality criteria, analytical limitations, and the use of stepwise approaches in cluster investigation.
• Promote exchange of experience and harmonized interpretation across laboratories.

Main Covered Topics

The training course will focus on the main features and interpretation principles of WGS-based microbial genomic data analysis at a basic and practice-oriented level, including:

• Raw-read QC, including key QC metrics, sequence quality indicators, estimated depth of coverage, common quality issues, and their impact on downstream analyses.
• Contamination assessment, including inter-species contamination and within-species mixed-strain contamination, detection approaches, interpretation of contamination metrics and action thresholds, and consequences for sample inclusion, exclusion, and troubleshooting.
• Genomic characterization of bacterial isolates, including serotyping, virulotyping, and AMR detection.
• WGS-based typing and genomic relatedness, including cgMLST principles, allele calling, generation of cgMLST/wgMLST allelic profiles, and quality, interpretation, and reporting considerations.
• Allele-based relatedness analysis and cluster detection, including allelic distance matrices, minimum spanning trees (MSTs), context-dependent thresholds, and integration with available epidemiological metadata.
• SNP-based relatedness analysis and phylogenetic inference, including basic SNP-based analysis, phylogenetic tree interpretation, analytical robustness, and key limitations such as reference choice, missing data, and recombination handling where relevant.
• Dedicated lectures on parasites sequencing and amplicon sequencing of viruses.

Expected Learning Outcomes

At the end of the course, participants are expected to be able to:

• Assess raw-read quality and identify potential contamination issues.
• Understand the principles and outputs of WGS-based typing and cluster analysis.
• Distinguish between allele-based cluster analysis and SNP-based phylogenetic analysis.
• Interpret genomic results in the context of surveillance and outbreak investigation.
• Use scientifically accurate terminology when discussing and reporting results.