Proteomics
A.Y. 2025/2026
Learning objectives
Upon completion of the course, students are expected to:
· Understand the fundamental principles of proteomics and selected aspects of metabolomics, with a focus on key technologies such as mass spectrometry, including various instrument types and quantitative proteomics techniques.
· Gain the analytical tools required to assess the strengths and limitations of different experimental approaches, considering factors such as manual workload, cost, sensitivity, and scalability.
· Critically evaluate the entire proteomics workflow, from sample preparation through spectral acquisition to data analysis and biological interpretation.
· Perform basic raw data processing, including conversion to standard formats, quality control, protein identification using search engines, and initial interpretation of MS/MS spectra for peptide sequence reconstruction.
· Recognize the main applications of proteomics and metabolomics in biomedical and biological research.
· Acquire a foundational understanding of statistical methods applicable to the analysis of quantitative omics data.
· Understand the fundamental principles of proteomics and selected aspects of metabolomics, with a focus on key technologies such as mass spectrometry, including various instrument types and quantitative proteomics techniques.
· Gain the analytical tools required to assess the strengths and limitations of different experimental approaches, considering factors such as manual workload, cost, sensitivity, and scalability.
· Critically evaluate the entire proteomics workflow, from sample preparation through spectral acquisition to data analysis and biological interpretation.
· Perform basic raw data processing, including conversion to standard formats, quality control, protein identification using search engines, and initial interpretation of MS/MS spectra for peptide sequence reconstruction.
· Recognize the main applications of proteomics and metabolomics in biomedical and biological research.
· Acquire a foundational understanding of statistical methods applicable to the analysis of quantitative omics data.
Expected learning outcomes
Student learning outcomes will be evaluated through an oral examination conducted by the course instructor. The assessment will focus on the student's understanding of the proteomic and metabolomic methodologies covered in the syllabus, as well as their ability to apply these approaches appropriately.
The oral exam is designed to assess not only the theoretical knowledge and comprehension of key analytical techniques and data interpretation strategies but also the practical skills acquired during the course. Particular attention will be given to the clarity and accuracy of the language used, as well as the student's ability to critically select, justify, and integrate different methodologies to address diverse scientific questions.
The oral exam is designed to assess not only the theoretical knowledge and comprehension of key analytical techniques and data interpretation strategies but also the practical skills acquired during the course. Particular attention will be given to the clarity and accuracy of the language used, as well as the student's ability to critically select, justify, and integrate different methodologies to address diverse scientific questions.
Lesson period: First semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course can be attended as a single course.
Course syllabus and organization
Single session
Course syllabus
· Introduction to proteomics: definition and concepts, history, challenges
· Protein fractionation, separation, purification and quantification
· Protein extraction and sample preparation prior to MS
· Introduction to liquid chromatography (LC) separation prior to MS
· Mass spectrometry (MS) fundamentals I o Soft Ionization techniques (MALDI/ESI) o Concepts of mass accuracy and resolution o An overview on modern Mass Analyser design
· Mass spectrometry (MS) fundamentals II o Tandem mass spectrometry o Peptide fragmentation and MS/MS interpretation for de novo sequencing
· Protein Identification by probability-based scoring through search engines
· Shot-gun proteomics workflows and considerations
· Quantitative proteomics:
o Label-free and isotopic-label-based strategies;
o Targeted proteomics (webinar)
· Protein post-translational modifications, with tailored Strategies (biochemical and analytical) and examples (phospho-proteomics, methyl-proteomics)
· Interaction proteomics: principles and examples (protein-protein, protein-nucleic acid interactions) and proximity-biotinylation approaches
· Structural proteomics and conformational proteomics (External Seminar and webinar)
· Peptidomics and immunopeptidomics (External Seminar)
· Proteomics application in cell biology (case-studies)
· Translational proteomics (External seminars):
o Proteome profiling of clinical samples o Proteomics of body fluids (serum, urine, etc)
o Proteomics in drug development (e.g chemo-proteomics, thermal protein profiling, etc)
· Artificial Intelligence in Proteomics research
· Proteomics and systems biology:
- Feature selection
- Overrepresentation and GeneSet Enrichment Analysis
- Basics of graph theory and application to protein networks
- Classifiers and predictors for clinical applications (biomarkers, prognostic and drug response predictors, surrogate outcomes) (focus seminar)
· Metabolomics:
o definitions and approaches
o Targeted and untargeted metabolomics approach. Typical metabolomic analysis workflows. Identification of metabolites. Metabolite databases.
o The dynamic study of metabolism: Fluxomics
o Applications of metabolomics in pre-clinical and research
· Protein fractionation, separation, purification and quantification
· Protein extraction and sample preparation prior to MS
· Introduction to liquid chromatography (LC) separation prior to MS
· Mass spectrometry (MS) fundamentals I o Soft Ionization techniques (MALDI/ESI) o Concepts of mass accuracy and resolution o An overview on modern Mass Analyser design
· Mass spectrometry (MS) fundamentals II o Tandem mass spectrometry o Peptide fragmentation and MS/MS interpretation for de novo sequencing
· Protein Identification by probability-based scoring through search engines
· Shot-gun proteomics workflows and considerations
· Quantitative proteomics:
o Label-free and isotopic-label-based strategies;
o Targeted proteomics (webinar)
· Protein post-translational modifications, with tailored Strategies (biochemical and analytical) and examples (phospho-proteomics, methyl-proteomics)
· Interaction proteomics: principles and examples (protein-protein, protein-nucleic acid interactions) and proximity-biotinylation approaches
· Structural proteomics and conformational proteomics (External Seminar and webinar)
· Peptidomics and immunopeptidomics (External Seminar)
· Proteomics application in cell biology (case-studies)
· Translational proteomics (External seminars):
o Proteome profiling of clinical samples o Proteomics of body fluids (serum, urine, etc)
o Proteomics in drug development (e.g chemo-proteomics, thermal protein profiling, etc)
· Artificial Intelligence in Proteomics research
· Proteomics and systems biology:
- Feature selection
- Overrepresentation and GeneSet Enrichment Analysis
- Basics of graph theory and application to protein networks
- Classifiers and predictors for clinical applications (biomarkers, prognostic and drug response predictors, surrogate outcomes) (focus seminar)
· Metabolomics:
o definitions and approaches
o Targeted and untargeted metabolomics approach. Typical metabolomic analysis workflows. Identification of metabolites. Metabolite databases.
o The dynamic study of metabolism: Fluxomics
o Applications of metabolomics in pre-clinical and research
Prerequisites for admission
Basic knowledge of chemistry and biochemistry. Notions on the nature and structure of proteins. Basic knowledge of principle protein separation techniques (e.g. chromatography, electrophoresis, etc)
Teaching methods
The course combines traditional lectures with hands-on laboratory sessions designed to reinforce key concepts through practical experience. Laboratory activities include both bench experiments and computational tutorials, conducted in small groups. These tutorials will involve:
· interpretation of mass spectra for peptide sequence reconstruction;
· use of protein identification search engines and critical discussion of the output data;
· statistical and functional analysis of quantitative proteomics datasets using MaxQuant and Perseus.
In addition, students will engage in class discussions based on real-world case studies in proteomics and metabolomics, where active participation is expected. Selected lectures will be delivered by invited scientists currently leading proteomics research projects. These sessions will be moderated by the course instructor, who will facilitate discussion and provide synthesis.
Interactive participation, including questions and contributions during lectures and tutorials, is strongly encouraged throughout the course.
· interpretation of mass spectra for peptide sequence reconstruction;
· use of protein identification search engines and critical discussion of the output data;
· statistical and functional analysis of quantitative proteomics datasets using MaxQuant and Perseus.
In addition, students will engage in class discussions based on real-world case studies in proteomics and metabolomics, where active participation is expected. Selected lectures will be delivered by invited scientists currently leading proteomics research projects. These sessions will be moderated by the course instructor, who will facilitate discussion and provide synthesis.
Interactive participation, including questions and contributions during lectures and tutorials, is strongly encouraged throughout the course.
Teaching Resources
Students will be provided with the slides of the course, which must be suitably integrated with lecture notes. With regard to the proteomics and metabolomics parts, mainly due to the rapid evolution that characterizes these disciplines, there are few texts on the market that include all the topics covered, adequately up-to-date. Possible reference textbooks for proteomics and metabolomics are:
· Proteomica T. Alberio, M. Fasano, P. Roncada, 2021 EdiSES (in Italian)
· Proteomics for Biological Discovery, Second Edition Timothy D. Veenstra, John R. Yates III Print ISBN:9781118279243 |Online ISBN:9781119081661 |DOI:10.1002/9781119081661 © 2019 John Wiley & Sons, Inc.
· Introducing Proteomics, from concepts to sample preparation, mass spectrometry and data analysis by J. Lovric (2011), Wiley-Blackwell Publishers
· Introduction to proteomics, Principles and Applications (2010) N. Mishra, John Wiley & Sons, Inc., Publication.
· Metabolomics: From Fundamentals to Clinical Applications (2017) A. Sussulini, Springer.
· Metabolomics in Practice: Successful Strategies to Generate and Analyze Metabolic Data (2013). M. Lämmerhofer and W. Weckwerth, Wiley‐VCH Verlag GmbH & Co. KGaA.
These textbooks will be then integrated with relevant recent reviews/articles on the topics covered during the lectures. Video lectures and tutorials from past International Schools/Courses of proteomics and freely available online will also be indicated to the students
· Proteomica T. Alberio, M. Fasano, P. Roncada, 2021 EdiSES (in Italian)
· Proteomics for Biological Discovery, Second Edition Timothy D. Veenstra, John R. Yates III Print ISBN:9781118279243 |Online ISBN:9781119081661 |DOI:10.1002/9781119081661 © 2019 John Wiley & Sons, Inc.
· Introducing Proteomics, from concepts to sample preparation, mass spectrometry and data analysis by J. Lovric (2011), Wiley-Blackwell Publishers
· Introduction to proteomics, Principles and Applications (2010) N. Mishra, John Wiley & Sons, Inc., Publication.
· Metabolomics: From Fundamentals to Clinical Applications (2017) A. Sussulini, Springer.
· Metabolomics in Practice: Successful Strategies to Generate and Analyze Metabolic Data (2013). M. Lämmerhofer and W. Weckwerth, Wiley‐VCH Verlag GmbH & Co. KGaA.
These textbooks will be then integrated with relevant recent reviews/articles on the topics covered during the lectures. Video lectures and tutorials from past International Schools/Courses of proteomics and freely available online will also be indicated to the students
Assessment methods and Criteria
Given the highly interactive nature of the course, which includes practical and bioinformatics exercises and group work, it is essential to attend lessons regularly. Students who have followed at least 80% of the course are considered attending. The overall assessment of the students will be based on their performance in a compulsory oral test, consisting of questions aiming at verifying the overall understanding of the basic principles of the analytical methods ion applied in MS-based proteomics and metabolomics, the major challenges of these disciplines and the solutions developed to tackled them. Special attention will will be given to assess the understating of the different approaches and strategies in proteomics and metabolomics that are linked to the simulation of real-life scientific situations that embody what has been discussed in the course. The exam will also verify the students' understating of the most important data analysis approachess, including statistical analysis of large-scale, quantitative -omics data.
BIO/10 - BIOCHEMISTRY - University credits: 6
Practicals: 16 hours
Lessons: 40 hours
Lessons: 40 hours
Professor:
Bonaldi Tiziana
Professor(s)
Reception:
to be defined by appointment, via email or telephone
Building 13, Floor 1 of the Department of Experimental Oncology of the European Institute of Oncology, Via Adamello 16, Milan