Introduction to Whole Genome Sequencing in AMR surveillance​

Recordings and Course material

This course is now freely available for self-learning. Presentations, Zoom recordings from the original course and course material to conduct the exercises have been combined and are available through the PDF file found below. Please note that since this course is self-learning, we are not able to provide feedback on work submitted for the exercises beyond the automated response to certain questions.

 

Course information
Title:

Introduction to Whole Genome Sequencing (WGS) in Antimicrobial Resistance (AMR).

Language of instruction:

English.

Offered as:

Webinar with lectures, exercises and panel discussion.

Duration of course:

6 x ½ days.

Responsible:

Rene S. Hendriksen (DTU), rshe@food.dtu.dk

Course co-responsible:

Pernille Nilsson (DTU), Anthony Smith (NICD, South Africa), Jinal Bhiman (NICD, South Africa), Marco van Zwetselaar (KCRI, Tanzania), Beverly Eygir (NMIMR, Ghana), Iruka N. Okeke (UI, Nigeria).

General course objectives:

The course provides an introduction to Whole Genome Sequencing (WGS) and its use in Antimicrobial resistance (AMR) surveillance.

The participant will upon completion of the course i) know what WGS is and how it can be used and ii) be able to use freely available online tools to perform simple bioinformatics analysis and interpret results.

Learning objectives:

A participant who has met the objectives of the course will be able to:

• Describe the potential uses of WGS in public health microbiology
• Describe the different sequencing platforms and the technology behind using the correct terminology
• Plan sampling/surveillance appropriate for with WGS studies with epidemiology in mind
• Perform drag-and-drop bioinformatics using online analysis tools and interpret the results

Content:

The course covers sampling strategies for doing WGS in AMR, sequencing terminology, detailing state-of-the art technology including technical specifics of whole genome sequencing to give the participants a thorough understanding. Furthermore the course covers what the output data looks like, the importance of quality control and the use of online tools to analyse the data for species identification and AMR detection.

The course will comprise of lectures and hands-on exercises that the participants will have to complete and submit answers to in between course days.

Course literature:

No literature required.

Audience:

None and novel users.