Proteomics with an Introduction to Metabolomics   (MF3PUMB)

Academic year:

2026/2027.

Attendance requirements:

There are no requirements.

ECTS:

5

Study level:

Study program:

Teachers:

Tanja D. Ćirković Veličković

Tatjana Simić

Ivanka Marković

Katarina T. Smiljanić

Vesna Ćorić

Aleksandra Stanojević

Hours of instruction:

Weekly: two hours of lectures + two hours of exercises (2+2+0)

Goals:

The course is intended for students of various profiles who wish to acquire knowledge and practical training in the IT processing of measurement results obtained using analytical methods of proteomics and metabolomics, as well as examples of the application of these methods in biomedical sciences for the purpose of discovering biomarkers, determining the structure and modifications of proteins, discovering immunologically relevant proteins (antigens and allergens), as well as how the results of these analyses are used to understand biological processes at the molecular level, which are skills necessary for work in research laboratories and biotechnology companies.

Outcome:

Upon completion of the course, students will be able to:

• understand the goal of proteomics and metabolomics as multidisciplinary sciences;
• understand the basic concept of analytical platforms (chromatography, mass spectrometry, two-dimensional electrophoresis) used for proteomics and metabolomics;
• process the results obtained by applying proteomics methods using informatics;
• understand the basics of multivariate data analysis in metabolomics;
• become familiar with the basic applications of proteomics and metabolomics in biomarker research in biomedical sciences;
• design and conduct experiments in the field of proteomics and metabolomics and correctly interpret the obtained data.

Teaching methods:

Lectures, practical classes, colloquium.

Extracurricular activities:

—

Coursebooks:

• ¨. Throck Watson, O. D. Sparkman: Introduction to mass spectrometry, Wiley 2007.
• J. Lovric: Introducing Proteomics: From concepts to sample separation, mass spectrometry and data analysis, Wiley, 2011.
• Pedrioli et al.: Nature Biotechnology 22, 1459-66, 2004.
• A. I. Nesvizhskii, O. Vitek, R. Aebersold: Analysis and validation of proteomic data generated by tandem mass spectrometry, Nature Methods 4, 787-97, 2007.
• Silas G. Villas-Boas, Ute Roessner, Michael A. E. Hansen, Jorn Smedsgaard, Jens Nielsen: Metabolome analysis - an introduction, John Wiley & Sons, Inc.
• Multi- and Megavariate Data Analysis, Part I: Basic Principles and Applications, Umetrics AB
• FDA-NIH Biomarker Working Group: BEST (Biomarkers, EndpointS, and other Tools) Resource, Food and Drug Administration (US) 2016. https://www.ncbi.nlm.nih.gov/books/NBK326791/
• Course material provided from theoretical and practical classes.

Additional material:

—

Lectures:

10 points (2 hours a week)

Syllabus:

1. Introduction to proteomics and metabolomics techniques.
2. Preparation of biological samples for further analysis using proteomics and metabolomics methods.
3. Methods coupled with mass spectrometry in proteomics: two-dimensional electrophoresis.
4. Methods coupled with mass spectrometry in proteomics: liquid chromatography (HPLC) at the nanoscale and capillary electrophoresis.
5. "Bottom up proteomics": identification and characterization of proteins by peptide mapping. Selection of a database for analysis.
6. De novo protein sequencing by mass spectrometry and analysis of post-translational modifications by global proteomic analysis of post-translational modifications of proteins.
7. Disulfide mapping and redox proteomics, protein quantification (SILAC, iTRAQ, label-free quantification).
8. Analysis of multiprotein complexes and cellular organelles.
9. Immunoproteomics methods – application in antigen and allergen detection.
10. "Top down protomics": determination of the exact mass of proteins and peptides, analysis of post-translational modifications (glycosylation, phosphorylation).
11. Application of mass spectrometry for protein quantification in complex samples and biological fluids.
12. Application of proteomics: nanozymes (artificial enzymes) for “middle down” application in proteomics, application in veterinary medicine, glycomics and glycoproteomics. (Invited lecturers from abroad - Tatjana Parac-Vogt, Paola Roncada, Gordan Lauc).
13. Mass spectrometry methods in metabolomics and small molecule analysis.
14. Metabolic modifications of small molecules.
15. Examples of applications of metabolomics in pharmacodynamic studies.
16. Application of proteomics in biomarker research of various human diseases.
17. Application of metabolomics in neuroinflammation and cell signaling: Pathways to new therapeutic targets (Invited lecturers from abroad - D. Milovanović, E. Manolakos).

The literature study will be conducted according to the Journal Club model, or rather a discussion forum, where students, together with teachers, analyze current scientific publications relevant to the topic.

Exercises:

20 points (2 hours a week)

Syllabus:

1. Data formats in proteomics and their conversion (mzML, mzXML, pepXML, protXML).
2. Determination of the exact mass of proteins by mass spectrometry - processing of spectra in order to determine the exact mass.
3. Preparation and management of databases for proteomic analysis. In-house databases and contaminant databases (cRAP). PeptideAtlas, SBEAMS, SRMAtlas.
4. Peptide mapping (PMF) of proteins and proteomics - analysis of mass spectra using various "open" software and algorithms: Mascot, Sequest, X!tandem.
5. Peptide mapping (PMF) of proteins and proteomics - analysis of mass spectra using MS Fragger, Proteome Discoverer 4.2 and Peaks Studio X Pro software.
6. De novo sequencing and mutation detection in proteins using Peaks Studio software.
7. Global proteomic profiling of post-translational modifications using Peaks Studio X Pro software.
8. Determination of post-translational modifications of proteins. Hydroxylation and phosphorylation.
9. Determination of the position of disulfide bridges in proteins and redox proteomics by spectral analysis.
10. Quantitative proteomics - LFQ protein quantification using Peaks Studio software.
11. Analysis of proteomic data obtained by shotgun proteomics methods (protein classification by function, GO...).
12. Proteomic data repositories (ProteomeExchange, Pride). Deposit of spectra into data repositories.
13. Processing of metabolomics results by multivariate data analysis. Basic methods of multivariate data analysis in metabolomics - PCA, OPLS, OPLS-DA.
14. Functional analyses in proteomic biomarker research using Reactome and Metscape software ("enrichment" analysis, functional annotation and functional classification).
15. Processing of biomarker quality determination results using Receiver Operating Curve (ROC) analysis.
16. Graphical presentation of proteomic and metabolomic analysis results.

Colloquia:

20 points

Written exam:

50 points