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Field Ionization, Field Desorption and Liquid Injection Field Desorption/Ionization: Fundamentals, Techniques, Applications, and Prospects

Sunday, March 10, 2024 | 13:15-16:15 

Mathias H. Linden (mathias@lifdi.com) 1
H. Bernhard Linden (linden@lifdi.com) 1
Raphael Bühler (raphael.buehler@tum.de) 2
Jürgen H. Gross (juergen.gross@oci.uni-heidelberg.de) 3

1 Linden CMS, Auf dem Berge 25, 28844 Weyhe, Germany
2 Catalysis Research Centre, Technical University Munich, Ernst-Otto-Fischer Strasse 1,
85748 Garching, Germany
3 Institute of Organic Chemistry, Heidelberg University, Im Neuenheimer Feld 270,
69120 Heidelberg, Germany

Field ionization (FI), field desorption (FD), and liquid injection field desorption/ionization (LIFDI) are particularly soft ionization methods that can be applied to a wide variety of compound classes. The suitable variant of this family of ionization methods is chosen based on molecular weight, volatility, and polarity of the analyte. LIFDI is especially useful as it combines sample introduction under exclusion of moisture and air and reproducible sample deposition on the emitter with quick operation, and thus, short measurement times. Meanwhile, LIFDI sources can be obtained for a range of instruments including modern TOF and Orbitrap analyzers. Recent work has even demonstrated that, to some extent, FD can be performed at atmospheric pressure (APFD).

This workshop will fully explain the fundamentals of the techniques in both theory and practice. It will demonstrate and compare the specific capabilities of FI, FD, and LIFDI along a range of elaborate examples. Further, it will include instrumental topics such as mass analyzers to combine with and hyphenation of these soft ionization methods with chromatographic separation like GC-FI-MS. One section of the workshop will be dedicated to the handling and analysis of extremely labile compounds in LIFDI while another will provide a glimpse to the opposite setup in APFD.

Registration for the workshop is possible in the registration system

Targeted analysis of proteomics data in Skyline

Sunday, March 10, 2024 | 13:15 – 16:15

Julia Mergner (julia.mergner@tum.de ) 1
Christina Ludwig (tina.ludwig@tum.de) 2
Bavarian Center for Biomolecular Mass Spectrometry at Klinikum rechts der Isar (BayBioMS@MRI), Klinikum rechts der Isar der Technischen Universität München, München
2 Bavarian Center for Biomolecular Mass Spectrometry, School of Life Sciences, Technischen Universität München, München

Proteomics analyses often contain identification and quantification information for thousands of peptides within a single measurement raw file. Skyline (https://skyline.ms) is an open-source software tool for targeted assay development and resulting mass spectrometer data analysis. Among the different software options for data investigation, Skyline is particularly well suited for visually examining chromatographic data from individual peptides and proteins of interest.

In this workshop, we aim to show our participants how to perform targeted data analysis of DIA or PRM data using Skyline and in addition examine different options to build spectral libraries. Attendees will gain hands-on experience evaluating different measurement results based on our guided tutorial and test data set. Participants should install Skyline (version 23.1) on their local system prior to the workshop, ensuring they can efficiently transfer the workshop learnings to their own research data.

Registration for the workshop is possible in the registration system

Prosit, Koina, and Oktoberfest: Deep-learning for proteomics research at your fingertips

Sunday, March 10, 2024 | 13:15 – 16:15

Wassim Gabriel 1, Ludwig Lautenbacher 1, Mario Picciani 1, Mathias Wilhelm 1
1Computational Mass Spectrometry, TUM School of Life Sciences, Technical University of Munich, Freising, 85354 Freising

Over the last year, various deep learning-assisted data analysis pipelines have been developed that boost the performance of mass spectrometry-based proteomics. One such ecosystem of tools consists of three tools, Prosit, Koina, and Oktoberfest, that facilitate the analysis of a variety of challenging datasets (e.g. immunopeptidomics, metaproteomics) acquired under various settings (e.g. data dependent and data independent acquisition). Briefly, Prosit is a deep neuronal network that can accurately predict various peptide properties (e.g. fragment ion intensities, retention time), Koina is a publicly available service that provides access to a variety of deep learning models (e.g. Prosit, DeepLC, AlphaPeptDeep), and Oktoberfest is an open source pipeline for rescoring search engine results and spectral library generation utilizing Koina.
During the workshop, attendees will learn where and how each tool can be used, focusing on 1) predicted spectral library generation, 2) performing data-driven rescoring, and 3) training models on custom data. Each section of the workshop will gradually increase the required skillset starting with web applications requiring no background in bioinformatics reaching basic R and python programming. Participants should bring their own laptop but we will provide the necessary data and examples, focusing on tasks that scientists may encounter when analyzing data.


Registration for the workshop is possible in the registration system

LipiTUM Computational Lipidomics Workshop: In-depth data analysis methods and tools for everyone

Sunday, March 10, 2024 | 13:15-16:15

Josch K. Pauling1
Vivian Würf1
Cemil Can Saylan1
Maria Barranco1

1LipiTUM, Data Science in Systems Biology, Technical University of Munich

Alterations in lipid metabolism have been linked to numerous human diseases, underscoring the importance of lipidomics—an emerging field that explores the study of lipids and their interacting factors. The evaluation of thousands of lipid species across multiple metabolic pathways provides a powerful novel platform for the discovery of lipid biomarkers but also presents new challenges. In this workshop, computational methods to analyze and interpret lipidomics data will be addressed.

Participants of this workshop gain insights into analyzing and exploring lipidomics data using biclustering and lipid metabolic networks. Together we will stratify lipidomics samples and draw conclusions based on functional associations between lipids. This will allow us to biologically interpret the results. We will utilize the respective software tools for different experimental settings and choose the appropriate settings based on the research question. We will also go through possible visualizations and how to analyze and interpret quantitative lipid data in the context of lipid reaction networks. Moreover, participants have a chance to deep dive into new methods in lipidomics data analysis such as the electron-activated dissociation (EAD) lipidomics data for double-bond identification.

Basic knowledge of lipidomics, biochemistry, and statistics is recommended but not required. The course will start with an introductory presentation on the theoretical background, providing you with the necessary information. This is followed by a hands-on application, which will be performed using web-based tools and only requires a modern internet browser (Chrome or Firefox recommended), so please bring your laptop. We suggest a spreadsheet program (Excel, LibreOffice or OpenOffice) to be able to view the example data. Course materials and example data will be provided at the workshop or shortly before.

Registration for the workshop is possible in the registration system

High Resolution Mass Spectrometry

Sunday, March 10, 2024 | 13:15 – 16:15

Wolfgang Schrader (wschrader@kofo.mpg.de)
Marianne Engeser (Marianne.Engeser@uni-bonn.de)
(FG Fourier Transform & High Resolution MS)

Arnd Ingendoh, Bruker Daltonics:
FTICR-MS Fourier Transform Ion Cyclotron Resonance Mass Spectrometry - An Introduction 

Hamish Stewart, Thermo Fisher Scientific:
On the Orbitrap Analyzer

David Heywood, Waters Corporation:
Enhancing resolving power using multiple passes of a multi-reflecting time-of-fight mass analyser

Alessandro Vetere:
Data interpretation in complex systems

Bente Siebels, Universitätsklinikum Hamburg-Eppendorf:
High resolution Mass Spectrometry from large molecules

What is the difference between standard mass spectrometry and high resolution mass spectrometry? How can it be done and what are the techniques used to acquire and handle high resolution data? 

These are some of the questions we want to answer in our workshop about high resolution mass spectrometry. Experienced users will talk about the different techniques that are available to do high resolution mass spectrometry. Details about Fourier Transform Ion Cyclotron Resonance MS will be shown, as well as how an Orbitrap analyzer functions and can be operated. The details of multi-reflectron Time-of-Flight analyzers will be discussed and we can then see the different characteristics that each of these techniques provide. 

Additional topics will be how do deal with the high data load that can be gained in different applications when using high resolution mass spectrometry.

This workshop is of interest to everybody who wants to understand and master the intricacies of using high resolution methods and applications in mass spectrometry.

Registration for the workshop is possible in the registration system

MS Imaging

Wednesday, March 13, 2024 | 14:00 - 17:00

High-resolution Imaging of Biological Samples Using Nanospray Desorption Electrospray Ionization (nano-DESI) Mass Spectrometry

This year’s DGMS annual meeting will take place in Freising between the 10.03.2024 and 13.03.2024, and the focus group ‘MS imaging’ will offer an annual workshop on Wednesday, 13.3.2024, directly after the main program. The goal is to educate newcomers and to encourage discussion with experienced users in the field of mass spectrometry imaging. This year’s workshop will be focused on giving an overview of state-of-the-art capabilities of different MSI modalities. Confirmed senior speakers for this event are Julia Laskin (ASMS president, Purdue University, USA) and Jens Soltwisch (University of Muenster, Germany). Most importantly, we also would like to encourage young and advanced researchers in the field to highlight the capabilities of their MSI method, workflow, or data analysis strategy. Therefore, we invite all MS imaging researchers to submit short abstracts (max. 450 words) of the intended contribution to Carsten Hopf (c.hopf@hs-mannheim.de) and Sven Heiles (Sven.Heiles@isas.de). We are looking forward to discussing with you in Freising.

Registration for the workshop is possible in the registration system

AI-powered analysis of bottom-up proteomics data with CHIMERYS

Wednesday, March 13, 2024 | 14:00 – 17:00

Tobias Schmidt (tobias.schmidt@msaid.de) 1
Florian Seefried (florian.seefried@msaid.de) 1
Layla Eljagh (layla.eljagh@msaid.de) 1
MSAID GmbH, Lichtenbergstr. 8, 85748 Garching b.München

The core concept of proteomic data analysis is matching experimental spectra to a peptide representation derived from a protein sequence database. CHIMERYS is an intelligent, AI-powered search algorithm for bottom-up proteomic data analysis that leverages the power of accurately predicted peptide properties through deep learning to facilitate this process.

Join us for an immersive workshop on harnessing the power of artificial intelligence powered software for proteomic analysis. This workshop aims to equip participants with the necessary skills to proficiently use Thermo Scientific Proteome Discoverer 3.1 (PD) and maximize the capabilities of CHIMERYS 2.0 for in-depth data exploration in DDA, DIA, and PRM datasets.

During the workshop, attendees will learn how to install and set up PD 3.1 on their local system. Participants will be given access to CHIMERYS through a complimentary demo license, enabling them to start analyzing a sample dataset. The workshop will provide hands-on training, guiding participants through the intricacies of data analysis within Proteome Discoverer, ensuring they can effectively utilize these tools for their research and data analysis needs.

Registration for the workshop is possible in the registration system