Faculty of Science

Introduction to Nutritional Metabolomics
Provider: Faculty of Science

Activity no.: 5472-25-06-31	There are no available seats
	Enrollment deadline: 06/06/2025

Place

Department of Nutrition Exercise and Sports

Date and time

30.06.2025, at: 08:00 - 04.07.2025, at: 16:00

Regular seats

ECTS credits

2.50

Contact person

Jan Stanstrup E-mail address: JST@NEXS.KU.DK

Enrolment Handling/Course Organiser

Francesca Bucci E-mail address: fb@nexs.ku.dk

Written language

English

Teaching language

English

Semester/Block

Block 5

Block note

Duration: 5 days

Exam requirements

Active participation in the group work and final presentation.

Exam form

Continuous assessment

Course workload

Course workload category	Hours
Preparation	30.75
Lectures	18.00
Practical exercises	14.00
Theory exercises	6.00

Sum	68.75

Enrolment guidelines

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

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 be concluded 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

Knowledge:
• Analyze different types of study designs commonly used in metabolomics (e.g., interventional study, case-control, cohort, cross-sectional) and evaluate their strengths and weaknesses in terms of validity, bias, and applicability.
• Explain each step of the metabolomics pipeline, including sample collection, data acquisition, preprocessing, statistical analysis, and interpretation, and identify appropriate tools and methods to perform each step effectively.

Skills:
• 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. MetFrag, SIRIUS) and databases (e.g. HMDB, METLIN and MassBank)

Competences:
• 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

Teaching and learning methods

Basic principles and an overview are given by mostly frontal lectures that include small tasks and quizzes.
Each practical step is then explained, and the students work in groups to perform the tasks on the dataset provided.
The course culminates in a presentation where the students describe the steps they took and the conclusions they reached.

Lecturers

Assistant Professor Jan Stanstrup, NEXS
Associate Professor Henrik Munch Roager, NEXS
Associate Professor Giorgia La Barbera, NEXS
Associate Professor Carl Brunius, Chalmers University of Technology, Sweden
PhD student Francesca Bucci, NEXS

Remarks

Breakfast (light), snacks, lunch and dinner will be provided during the course.

Fee
There is no fee for the PhD students under the Open Market in Denmark.
Other participants are to pay a course fee of 700 EUR.
Your registration is considered binding and the following rules apply:
3 weeks before the start of the course, it is possible to opt out, without having to pay participation fees. If you opt out beyond this date or do not show up on the course you will be charged the full participation fee, unless another participant are able to sign up for the course instead.
The fee must be paid no later than the 6th of June 2025.
Each student must pay and arrange their own travel and accommodation in Copenhagen during the course.

The preliminary program can be downloaded here.

For more information please contact Jan Stanstrup - jst@nexs.ku.dk

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