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Introduction to Environmental Metabolomics (2021)

ECTS credits: 5


Course parameters:

Language: English

Level of course: PhD and early career researcher course

Time of year: Q3, 2021. The course will take place as a 6-day summer school during 15-22 September 2021.

No. of contact hours/hours in total incl. preparation, assignment(s) or the like:

6 days of lectures, exercises and workshops (48 h)

Preparation by reading book chapters, articles and preparing data for analysis (50 h)

Capacity limits: max. 25, min. 10 participants. PhD students and early career researchers have highest priority.

Course fee: €400 (3,000 DKK) which covers materials and food.


Objectives of the course:

Untargeted metabolomics is the comprehensive characterization of metabolites present in organisms and it is the closest measure of the phenotype at the molecular level. Application of metabolomics within the environmental sciences is known as environmental metabolomics and allows for studying interactions between organisms and the surrounding environment. Moreover, it involves the study of (secondary) metabolites and interaction between host organisms and microbiomes, the exo- and endometabolomes, and it includes exposome characterization and non-targeted chemical screening to study the environmental occurrence, fate and impact of chemicals released from anthropogenic activities.  

The aim of the summer school is to introduce state-of-the-art environmental metabolomics based on high-resolution mass spectrometry including its possibilities and shortcomings. The course will introduce analytical hardware (e.g. Orbitrap mass spectrometry) and acquisition strategies, study design and sample preparation in an environmental context. The course will place its main focus (day 2-6) on working with state-of-the-art informatic tools for data (pre-)processing and statistical analysis, e.g. MZmine, XCMS, GNPS, Compound Discoverer, MatLab and R. Participants can bring own untargeted metabolomic data for use in the workshops.


Learning outcomes and competences:

At the end of the course, the student should be able to:

  • Understand types of chromatography and high-resolution mass spectrometry used for acquiring data
  • Discuss the strengths and weaknesses of various sample preparation strategies for untargeted metabolomics
  • Evaluate best suitable acquisition strategy for untargeted metabolomics
  • Assess quality of untargeted metabolomics studies
  • Carry out data pre-processing using MZmine and XCMS
  • Build and apply pre-processing and data analysis pipeline in Compound Discoverer
  • Understand and use advanced statistical methods, e.g. PCA, PLS-DA and differential analysis
  • Understand and apply metabolite identification confidence levels
  • Apply GNPS for molecular network analysis

Compulsory programme:

The summer school takes place as a six days intensive course. Prior to the course, the participants are expected to have read the listed literature. It is expected that all participants are highly active in the workshops. On the final day the participants will present their (workshop) processed data to have their performance assessed.


Course contents:

The teaching will be carried out as lectures, exercises, workshops and participant presentations. During the workshops, participants will form small groups and carry out various data analyses with their own data set or provided study data sets. On the final day each participant will present their analyses and findings. Furthermore, a number of visiting expert researchers and companies are intensively involved in the course to communicate the most recent advances in the field of metabolomics.

Day 1:
Environmental metabolomics is introduced and the used scientific equipment (high-resolution mass spectrometry) and its acquisition strategy to record untargeted metabolomic data is discussed. Sample preparation for untargeted environmental metabolomics is presented. Furthermore, study design, quality assurance and quality control for metabolomic studies are discussed. Day 1 is concluded with a lab tour.

Day 2:
We will focus on data pre-processing and an overview of various pre-processing methods is presented and discussed. The participants will be introduced to MZmine and XCMS and work on own or study data at a nearly full day workshop. The day will conclude with a social event.

Day 3:
Compound Discoverer is introduced together with its advantages and shortcomings for data pre-processing and analysis. A special focus is given on processing strategies, data visualization, metabolite annotation, normalization algorithms and scripting nodes. The participants will be introduced to Compound Discoverer and work on own or study data at a nearly full day workshop.

Day 4:
The participants will continue the workshop on Compound Discoverer and improvement of data acquisition is discussed in connection to the processed data. We will focus on using more advanced statistics, e.g. hierarchical cluster analysis and principal component analysis, in Compound Discoverer.

Day 5:
This day will focus on using advanced statistics in environmental metabolomics, e.g. differential analysis and PLS-DA. Matlab and R will be introduced for advanced statistics in environmental metabolomics. The participants will get hands on experience from working on own or study data in a nearly full day workshop on Matlab and R. The day will conclude with a social event.

Day 6:
We will focus on informatics tools for metabolite annotation, introduce molecular network analysis and GNPS. The participants will analyze own or study data at a GNPS workshop. Furthermore, semi-quantitative approaches in environmental metabolomics are introduced and discussed. The participants performance is evaluated at a presentation seminar, where each participant will present their experiences and findings from the workshops.



The participants need to have a background in natural science at MSc level. Experience in Matlab, R,

Compound Discoverer, MZmine, XCMS or GNPS is an advantage.


Name of lecturers: Martin Hansen (Aarhus University), Xiaomin Zhou (Aarhus University), Rikke Poulsen (Aarhus University) and several guest researchers, experts and companies.


Type of course/teaching methods:

Lecture, seminars, conference talks, exercises, workshops, and participant presentations.



A total of ca. 15 scientific papers and book chapters will be distributed to the participants no later than September 7, 2021. A tentative list is provided below.

  • Bundy, J. G., Davey, M. P. & Viant, M. R. Environmental metabolomics: A critical review and future perspectives. Metabolomics 5, 3–21 (2009).
  • Viant, M. R. et al. Use cases, best practice and reporting standards for metabolomics in regulatory toxicology. Nat. Commun. 10, (2019).
  • Sorokina, M. & Steinbeck, C. Review on natural products databases: Where to find data in 2020. J. Cheminform. 12, 1–51 (2020).
  • Domingo-Almenara X., Siuzdak G. (2020) Metabolomics Data Processing Using XCMS. In: Computational Methods and Data Analysis for Metabolomics. doi.org/10.1007/978-1-0716-0239-3_2
  • Hodgson, J. Mass spectrometry searches using MASST. Nat. Biotechnol. 38, 19–22 (2020).
  • Nothias, L. F. et al. Feature-based molecular networking in the GNPS analysis environment. Nat. Methods 17, 905–908 (2020).
  • Koelmel, J. P. et al. Expanding Lipidome Coverage Using LC-MS/MS Data-Dependent Acquisition with Automated Exclusion List Generation. J. Am. Soc. Mass Spectrom. 28, 908–917 (2017).
  • Nash, W. J. & Dunn, W. B. From mass to metabolite in human untargeted metabolomics: Recent advances in annotation of metabolites applying liquid chromatography-mass spectrometry data. TrAC - Trends Anal. Chem. 120, 115324 (2019).
  • Suggested book: Alvarez-Munoz, D and Farre, M. Environmental Metabolomics, 1st ed. Elsevier (2020).


Course homepage:



Course assessment:

The participants will present their (workshop) generated data to have their performance assessed. The participants will receive a diploma, after active participation, completing the PhD and early career researcher summer school.



Department of Environmental Science, Aarhus University


Time: 15-22 September 2021


Place: Department of Environmental Science, Aarhus University, Frederiksborgvej 399, 4000 Roskilde, Denmark. https://envs.au.dk/en/ominstituttet/directions-map/



Send e-mail to Associate Professor Martin Hansen (martin.hansen@envs.au.dk), include your CV with a publication list, and in the message clearly stating your current experience within untargeted metabolomics (e.g. data acquisition, data analysis and informatic tools) and if you will bring your own study data for the workshops.

Please note that there are a course fee, €400 (3,000 DKK), which covers materials and food.

Deadline for registration is 5 September 2021. Information regarding admission will be sent out no later than 7 September 2021.

If you have any questions, please contact Associate Professor Martin Hansen, martin.hansen@envs.au.dk

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