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Introduction to Nutritional Metabolomics
Provider: Faculty of Science

Activity no.: 5472-22-06-31There are no available seats 
Enrollment deadline: 20/04/2022
PlaceDepartment of Nutrition Exercise and Sports
Date and time27.06.2022, at: 09:00 - 01.07.2022, at: 16:00
Regular seats17
ECTS credits3.00
Contact personNicola Procházková    E-mail address: np@nexs.ku.dk
Enrolment Handling/Course OrganiserJan Stanstrup    E-mail address: JST@NEXS.KU.DK
Written languageEnglish
Teaching languageEnglish
Semester/BlockBlock 5
Block noteDuration: 4½ days
Exam formOral defence, presentation of the Group Work, Critical questions from lecturers
Exam detailsPresentation of group work
Course workload
Course workload categoryHours
Project work14.00
Theory exercises6.00



The course will be conducted as an in-person course.

The course will provide a general overview of LC-MS based untargeted metabolomics from study design to results and will be exemplified with its specific application in nutrition. It will be delivered using a mixture of lectures, hands-on data preparation and analysis, computer-based practical sessions, and discussions. Visits to wet labs and instructions on human sample preparation procedures is included but there is no practical lab work.

The students will go through common steps in a typical metabolomics study using a real-life case. This case study includes plasma (or urine) samples from a nutritional intervention. The sample preparation and analysis on UPLC-QTOF has been conducted and the students will further process and analyze the acquired data with various freeware tools (e.g. R, XCMS, MZmine etc). They will finally work on identification of relevant metabolites using manual analysis assisted by several web-based databases and structure elucidation tools. The course will conclude by presentations of reports generated by the students based on the case study.

The students should expect a fairly technical course with a strong focus on the hands-on data analysis abilities and data interpretation skills. Programming skills are not a prerequisite for entering the course and students are guided through the exercises. However, for students that are not familiar with R we expect them to explore the self-study curriculum based on short videos and texts that cover essential programming concepts.
The project work has a high workload and hence evening work can be expected during the course week.

Learning outcome
The aim of this course is to introduce the students to all phases in a nutritional metabolomics study, to instruct the student on sample handling, and to train the student in data analysis and in the use of freely available tools for the metabolomics data flow.

After completing the course the students should be able to:

• Describe the handling of urine, plasma and other samples collected from humans for metabolomics analysis
• Understand the basic principles of UPLC-QTOF technology
• Suggest which sample type to analyze for a specific research question and propose the relevant sample collection and preparation procedure
• Carry out data preprocessing using freely available tools (R/XCMS)
• Perform basic univariate and multivariate analysis (e.g. R)
• Interpret the MS/MS spectra by manual interpretation and by utilizing available tools (e.g. MetFusion, MetFrag) and databases (e.g. HMDB, METLIN and MassBank)

Teaching and learning methods
Lectures, hands-on exercises, group discussions.

Professor Lars Ove Dragsted
Assistant Professor Jan Stanstrup
Associate Professor Morten Arendt Rasmussen
Associate Professor Henrik Munch Roager
Assistant Professor Giorgia La Barbera
Post doc Natalia Vazquez Manjarrez
PhD student Nicola Procházková
PhD student Tu Hu
PhD student Kristina Pigsborg

No fee for the PhD students under the Open Market in Denmark and NOVA partners (Nordic Countries).
Other participants are to pay a course fee of 500 EUR. Each student must pay and arrange their own travel and accommodation in Copenhagen during the course.

The program can be downloaded here.

For more information please contact Nicola Procházková: np@nexs.ku.dk

Date of the exam is Friday 1 July 2022 from 09:00 to 12:00.

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