Short Courses

General information

On Saturday 27th and Sunday 28th of August we offer 10 different, highly educational Short Courses. These take place between 09:00 and 17:00 on Saturday and between 09:00 and 15:00 on Sunday. Limited seats are available.

Registration for the short courses is closed.

Short Course Registration

There is a maximum of 50 persons for each short course.
Registration for the IMSC 2022 Conference is obligatory in order to be able to register for the short courses.

The registration for the short courses is now closed.


IMSC 2022 Short Courses

Short Course 1
Ion Mobility Spectrometry

Valerie Gabelica & Tim Causon

Duration: 8 hours (Saturday afternoon + Sunday)

Short Course 2
Advanced MS data Analysis

Pratik Jagtap & Tim Griffin

Short Course 3
Imaging Mass Spectrometry

Martina Marchetti-Deschmann & Eva Cuypers

Short Course 4
Tandem Mass Spectrometry

Vicki Wysocki & Ljiljana Pasa-Tolic

Short Course 5
Cross-linking mass spectrometry

Juri Rappsilber & Pascal Albanese

Ion mobility spectrometry (IMS) is complementary to mass spectrometry, as it provides a separation that reflects the ion structure (not only its mass). The ion’s mobility is related to a physical quantity called the collision cross section (CCS). This tutorial course will introduce the fundamental aspects of IMS, the instrumental combination of different types of IMS technologies with MS (i.e., IM-MS), as well as the derivation and interpretation of CCS values. Special focus will be placed on the use of IM-MS for structural assignment in various biological and chemical analysis applications, from small molecules to large biological complexes. We will also include optional hands-on data processing examples.
In this workshop, instructors will cover bioinformatics workflows within the Galaxy platform to analyze mass spectrometry-based proteomics data, and integrate it with other 'omics data. Topics covered will include a) an introduction to the Galaxy platform, b) quantitative proteomics, c) proteogenomics, and d) metaproteomics. MaxQuant and MSstats within Galaxy will be used for quantitative proteomics analysis of mass spectrometry data. Proteogenomics workflows will cover multi-omic tools for the detection and verification of peptides derived from novel proteoforms. The metaproteomics workflows will be used to analyze the taxonomic composition and functional state of microbiomes and generate outputs useful for biological interpretation.
This two-day course will introduce you to the basic concepts involved in running a Imaging Mass Spectrometry experiment, including an introduction to the different types of instrumentation you can use, , instrumental parameters, sample preparation for biological material and other surfaces including matrix application in case of MALDI, imaging acquisitiondata analysis, imaging processing and quantitative aspects. This course will be presented at the beginner to intermediate level, and will be appropriate for mass spectrometrists looking to apply this technology to different kind of samples, but is also suited for e.g. clinicians/pathologists or material scientiest looking to learn more about Imaging Mass Spectrometry. The focus will be on molecular analysis but other mass spectrometry sources and concepts will be touched as well (e.g. elemental imaging by laser ablation inductively-coupled plasma mass spectrometry).
This course is designed for the attendee who wants to understand more about the fundamental, instrumental, and practical aspects of tandem mass spectrometry. Attendees will be new users of MS/MS who have some basic knowledge of mass spectrometry (i.e. familiar with ESI and MALDI, and understand the basic principles of at least one type of mass analyzer). In more detail, the participants will obtain an detailed insight into e.g. fragmentation pathways, collision energy, collision gases, different MS/MS instruments.
This course is designed for experimentalists who want to understand how to perform and interpret crosslinking mass spectrometry (XL-MS) experiments. This exciting structural proteomics technique is the perfect complement to CryoEM experiments and has become a staple in the structural biologists toolbox. In this course you will learn how to properly design XL-MS studies, the different fractionations/enrichment strategies for cross-linked peptides, optimal mass spectrometry data acquisition, data analysis, and protein structural modeling. We will go through several case studies, with practical sessions handling real datasets (please, bring your own laptop) and dedicated Q&A moments. Attendees are expected to have a basic knowledge of standard proteomics sample preparation and mass spectrometry techniques (i.e. familiar with ESI-MS/MS, and understand the basic principles of at least one type of mass analyzer).

Short Course 6

Stephen Blanksby & Michal Holcapek

Duration: Saturday 09.00-16.00

Short Course 7
Biopharma & native MS

Sarah Cianferani & Valentina D'Atri

Short Course 8

Guinevere Lageveen-Kammeijer & Noortje de Haan

Short Course 9
Clinical Proteomics

Sander Piersma, Irene Bijnsdorp, Connie Jimenez & Tamar Geiger

Duration: 8 hours (Saturday afternoon + Sunday)

Short Course 10
Computational Proteomics
Quality Control for Biological Mass Spectrometry

David Tabb & Quentin Giai Gianetto

Duration: Sunday 09.00-15.00
This short course provides a basic introduction into lipidomic analysis by mass spectrometry (MS) using both MS-only approaches and MS-hyphenation with separation techniques (including ultrahigh-performance liquid chromatography and ultrahigh-performance supercritical fluid chromatography). The course starts with the basic introduction into lipid nomenclature and biological consideration of lipid functions. The whole process of lipidomic analysis is briefly described, such as sample preparation, MS analysis, data processing, and reporting: consistent with the recommendations of International Lipidomics Society. The main focus of the short course is the acquisition and analysis of MS-based lipidomics data including (i) lipid identification and annotation and (ii) quantitation. Examples, including the application of lipidomic quantitation in early cancer detection will be shown, highlighting the importance of carefully selected of internal standards, analytical validation, and the use of quality control samples. Finally, an example is presented showing how chemical derivatization improves the lipidomic coverage of low-abundant lipid classes with unfavorable physicochemical properties.
A two-days course on the fundamentals and principles of native MS and its application to the biopharma industry. The course will start at the introductory level by providing a series of basic knowledge about native MS (ESI, analyzers, data treatment, and history) and non-denaturing liquid chromatography (LC) techniques. Then, the state-of-art of native MS will be explored both as standalone technique and in combination with LC or ion mobility, with an emphasis on the analysis of biopharmaceutical proteins. Finally, applications of native MS for protein/ligand, oligonucleotides, membrane proteins and viral vectors will be exemplified in different case studies, highlighting the combination of native MS approaches with other structural MS techniques.
Did you ever encounter glycans, but you -kind of- neglected them as they seemed too complicated to characterize? Or did you just perform a glycan release to make the analysis of your protein a lot easier? You have no idea how to interpret your data when a glycan is present? Fear no more! We are here to provide you with the basics in the field of mass spectrometric glycomics and glycoproteomics. The course will start with a historical overview on glycan research (i.e. how did glycans work their way up to being acknowledged as important study objects) and we will guide you through the maze of different nomenclatures. Moreover, although glycans are well known for their complexity, we will reveal to you the “rules of glycan structures” based on known biosynthetic pathways. This will be followed by an in-depth discussion on glyco(proteo)mic mass spectrometric technologies and workflows. In addition, different sample preparation steps and data analysis approaches will be covered. We will close-up with a session about glycomic biomarker discovery. The course will run over two days and time will be split between lectures and workshops (e.g. how do you recognize a glycan in a mass spectrum and how do you assign it). While not everything can be covered within these two days we will ensure that you will know your “glyco-basics” in the end. Moreover, participants are encouraged to submit any specific glyco-questions they have prior to the course and we will try to discuss them during the course.
Clinical proteomics experiments are aimed at uncovering differences in proteins or phosphosites between clinical groups. These groups can include clinically and/or molecularly distinct disease subtypes, differences in response to treatment or differences in prognosis. In order to detect these differential proteins or phosphosites, experimental bias between groups needs to be minimized. Especially, in label-free experiments where the comparison is many vs. many and each sample needs to me measured individually, proper experimental design is important since samples are not pooled prior to data acquisition. Complete (block) randomization or alternation of samples across groups in addition to QA/QC samples is advised for large-scale clinical proteomics experiments to minimize bias and ensure high data quality. Different experiment strategies will be discussed.
This short course illustrates methods used to assess repeatability and reproducibility in projects. The program starts with an overview of a core facility's implementation of the seven basic tools of quality. The three hands-on sessions will demonstrate and dissect scripts in the R statistical environment; participants would benefit from prior knowledge of R, but the training will include description of how each section of code works. The challenges to be addressed in these hands-on sessions will include recognition of outlier experiments in shotgun proteomics, assessing repeatability within cohorts and including sufficient biological replicates, and tracking the longitudinal drift in instrument performance.