Module 3.3b - Pathogen-wave oriented analyses 2024 (outline)

Outbreaks, typing and AMR


Time

Activity description

ILOs

9.00-9.25

Introduction to the module

Lecture: “Introduction to WGS-based FWD surveillance workflow 


  • Familiarise with an example of FWD surveillance workflow
  • Familiarise with an example of WGS setup for surveillance and outbreak detection of FWD pathogens

9.25-12.00

Outbreak detection and investigation

Lecture: Introduction to 
cgMLST and cluster detection

Practical: “Listeria monocytogenes outbreak detection and investigation”  

  • Explain the background of cgMLST

  • Explain genetic clustering and it’s detection in outbreak context

  • Utilise available command-line tools for cgMLST typing 
  • Detect clusters of closely related isolates using data generated by different sequencing technologies and approaches 
  • Interpret genetic clusters for outbreak investigations

13.00-14.30

Serotyping and virulence typing

Lecture: “Serotyping and virulence typing of Salmonella and E. coli”

Practical: “Serotyping and virulence typing” 

  • Familiarise with Salmonella and E. coliserotypes

  • Familiarise with SeqSero, SerotypeFinder, VirulenceFinder

  • Utilise available command-line tools for serotyping 
  • Utilise available command-line tools for virulence typing 
  • Describe the limitations of the above tools and impact on the typing results
  • Interpret the serotyping and virulence typing results 

14.30-16.00

Antimicrobial resistance genes and point mutations detection

Lecture: Introduction to AMR

Practical: “Antimicrobial resistance genes and point mutations detection in Salmonella” 

  • Explain what is AMR, how it develops and how it spreads

  • Explain the difference between antimicrobial resistance phenotype and genotype

  • Utilise command-line tools to identify AMR genes and point mutations (PMs).
  • Explain why different bioinformatic tools may give different results.
  • Discuss the difference between a tool, a database, and a method.
  • Explain the difference between genotype and phenotype.

 

 

Details

 

The overall aim of this module is to provide participants with the basic theoretical knowledge and practical experience of WGS-based analysis of foodborne pathogens for routine surveillance and outbreak investigations. 

The objective of the morning lecture is to provide the trainees with an example of WGS workflow for FWD surveillance. WGS-based surveillance setup and the major steps of WGS analyses will be demonstrated.  

The objective of the three practical exercises is to dive deeper into different types of WGS-based analyses of FWD pathogens using one or two pathogens as an example/per exercise. Before the training, the participants will be provided with background literature on the tools to be used during the training. This will enable us to understand the bioinformatics data in relation to the biology of FWD pathogens and thus how to interpret and to explain the results. Where relevant, the trainees will have an opportunity to perform the analyses both using Illumina and nanopore sequences and to compare the results generated using each technology or a combination of both. 

In the first practical exercise, participants will identify the relationship between a set of L. monocytogenesisolates by using cgMLST. The main objective of this exercise is to enable the participants to detect clusters of closely related isolates of bacteria, to generate the phylogenetic trees, to visualize and to interpret the results in relation to different approaches and methods used.

In the second practical exercise, the trainees will identify Salmonella and STEC serotypes as well as virulence genes in E. coli for identification and typing of STEC. 

In the third practical exercise, the trainees will learn how to identify AMR genes and point mutations using the two most widely used command-line tools for AMR identification: ResFinder (incl. PointFinder) and AMRFinderPlus. The trainees will be provided with guidance on how to interpret AMR results when different results using different bioinformatics tools are obtained and when there are discrepancies between the genotype and phenotype. 



Last modified: Monday, 25 March 2024, 11:19 AM