online Omics Symposium:
Metabolomics, Lipidomics, and Proteomics 2023

Preliminary Program:

12:00 pm Opening
12:10 pm Keynote: Jerzy Adamski (Helmholtz Zentrum München): Contributions of Metabolomics to Understanding of Human Health and Disease
12:40 pm Short talk: Antonia Fecke (ISAS Dortmund): Relative response factor based quantification of plasma samples using high-resolution mass spectrometry
12:55 pm Keynote: Marcus Bantscheff (Cellzome): Chemoproteomics approaches to investigate target engagement, selectivity and mechanism-of-action of bioactive molecules
01:25 pm Short Talk: Vivien Wiltzsch (IZI Fraunhofer Leipzig): Deep proteomic profiling of bone regeneration in a diabetic rat model: Insights into dysregulated molecular mechanisms and implications for personalized PCL-scaffold design

01:40 pm Coffee Break

02:00 pm Keynote: Silke Matysik (University Hospital Regensburg): Stratification of patients regarding faecal metabolites with biological activities
02:30 pm Short Talks: Robin Kosch (Uni Göttingen): PriOmics: network-based data integration for high-throughput omics data by group-wise mixed-graphical modeling

02:45 pm Industry Session – Michael Desor (Waters): Latest developments in Imaging DESI / MALDI and ESI on the same HRMS platform
03:00 pm Industry Session – Arne Behrens (Bruker): Enhancing the information content of MALDI Imaging: SpatialOMx® tools and MALDI HiPLEX-IHC

03:15 pm Keynote : Jennifer van Eyk (Cedars-Sinai Medical Center): The Role of Proteomics to Enable the Two Sides of Precision Medicine
03:45 pm Closing Remarks

03:50 pm Post Symposium Discussion
How to improve the support within e:Med?

This e:Med symposium took place via Zoom.Thank you all for your participation, the interesting talks and the discussion!

Contributions of Metabolomics to Understanding of Human Health and Disease

Jerzy Adamski
 

Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore; Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Slovenia; Metaron Diagnostics i.G., Neuherberg, Germany

Metabolomics as a holistic analysis of metabolites provides functional insights into biological systems. Metabolomics provides dynamic description signatures useful for the risk stratification, early diagnostics, therapy monitoring or theranostics. Both in health and disease metabolomics goes beyond genetic coding further to the impact of life style, environment and interventions on metabolic pathways. Key elements for good metabolomics study will be presented. Examples for the applications of metabolomics in analyses of biomarkers in human phenotypes and drug development will be presented.

CV Jerzy Adamski

Professor Emeritus, Helmholtz Zentrum München and Technical University of München; Professor, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Professor, Institute of Biochemistry, University of Ljubljana, Ljubljana, Slovenia; CSO, Metaron Diagnostics i.G., Neuherberg, Germany

Dr. Jerzy Adamski is a medicinal scientists and worldwide renowned expert in endocrinology and metabolomics. He has been working in the field of endocrine-related cancers and frequent human diseases like diabetes for 20 years. He published 461 papers (e.g. Nature Genetics, 2010; Nature 2011 and 2020; Nature Reviews in Nephrology, 2017; Cell, 2018 and 2021, Nature Biotechnology 2023) holds several patents and has H-index of 77. He acts as an Editor-in-Chief for J. Steroid Biochemistry and Molecular Biology (IF 5.03). He developed prototypes for early diagnosis of endometriosis, diabetes type 2, kidney dysfunction and cardiovascular complications. Recently he edited and co-authored a book “Metabolomics for biomedical research” (ISBN ISBN: 978-0-12-812784-1) published in 2020. He recently co-founded a biotech company Metaron Diagnostics where he acts as CSO. At Metaron Diagnostics he implements validated assays for diagnostics of complex human diseases by metabolomics. His further interests lie in networking and team building for the efficient problem solutions in biomedical discovery and applications in personalized medicine.

Chemoproteomics approaches to investigate target engagement, selectivity and mechanism-of-action of bioactive molecules

Markus Bantscheff
 

Cellzome, Germany

MS-based proteomics uniquely allows the direct and hypothesis-free analysis of small molecule interactions within the proteome. Chemoproteomics approaches classically rely on enrichment of drug targets from cell extracts or live cell systems by chemical probes derived from the bioactive compound under investigation. However, chemical probes can be challenging and time consuming to generate. Recently, several proteomics methods emerged that detect small molecule protein binding my measuring ligand-induced effects on biophysical properties of target proteins, e.g. thermal stability, resistance to proteolysis, and surface exposure of amino acid side chains. Combination of these methods with quantitative MS enable proteome-wide measurements. For example, thermal proteome profiling (TPP) or cellular thermal shift assay (CETSA)-MS deciphers a drug’s MoA by the hypothesis-free profiling of drug-induced protein thermal stability changes across the proteome. Whilst initial protocols only allowed detection of soluble intracellular targets; recent improvements demonstrated engagement of intra- and extracellular membrane proteins. The recently introduced cell surface thermal proteome profiling approach combines cell surface biotinylation with thermal shift assays and allows for the comprehensive characterization of ligand-induced changes in protein abundances and thermal stabilities. We present drug binding to extracellular receptors, complexes and transporters and describe stimulation-dependent remodeling of T-cell receptor complexes. In addition to cell surface proteins, protein secretion is an important factor with which cells interact with their environment. Using a panel of liver toxic compounds, we demonstrate that the secretome of liver cell models allows clustering compounds with similar adverse mechanisms and when combined with thermal proteome profiling allows tracking dysregulated pathways and mechanism of action.

Enhancing the information content of MALDI Imaging: SpatialOMx® tools and MALDI HiPLEX-IHC

Arne Behrens

Bruker Daltonics GmbH & Co. KG, Bremen, Germany

Latest developments in Imaging DESI / MALDI and ESI on the same HRMS platform

Michael Desor

Waters

Relative response factor based quantification of plasma samples using high-resolution mass spectrometry

Presenting Author: Antonia Fecke

Bioanalytics Department, Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. Dortmund Germany

PriOmics: network-based data integration for high-throughput omics data by group-wise mixed-graphical modeling
 

Robin Kosch
 

Department of Medical Bioinformatics, University Medical Center Göttingen, Göttingen, Germany

Integrating biomedical data from different sources remains a challenging task in systems biology. While many promising strategies for modeling complex systems exist, graphical models, e.g., Gaussian Graphical Models (GGMs) have the advantage that they can distinguish direct from indirect statistical relationships between variables. Further, Mixed Graphical Models (MGMs) allow to incorporate discrete variables, e.g., phenotypical or clinical data. In this work, we extend the concept of MGMs by incorporating prior knowledge into the model estimates, which is achieved by a novel regularization strategy based on a group-wise LASSO penalization.
The suggested regularization scheme is particularly suited for the analysis of state-of-the-art proteomics data, such as SWATH-MS. Established analysis strategies rely on the aggregation of peptide abundances to protein abundances. Consequently, they ignore information on direct peptide-peptide associations. Other methods perform analyses on peptide-level but ignore their respective protein affiliations. PriOmics incorporates the protein affiliation via group group-wise LASSO penalization.
We could demonstrate the superior performance of the PriOmics algorithm in contrast to standard MGMs, both, in simulation and real biological data. We investigated a dataset from the German High-Grade Lymphoma Study Group (DSHNHL) containing SWATH-MS proteomics data, including post-translational modifications, from 344 patients with Diffuse Large B-Cell Lymphoma (DLBCL) and additional transcriptomics, clinical and phenotypical features. We were able to identify key proteins for the cell-of-origin classification of DLBCL patients into Activated B-cell (ABC) like and Germinal B-Cell (GCB) like DLBCLs. Moreover, we show that PriOmics is able to disentangle effects from post translational modifications from those of protein abundances.

Stratification of patients regarding faecal metabolites with biological activities

Presenting Author: Silke Matysik

Silke Matysik1*, Sabrina Krautbauer1, Gerhard Liebisch1, Hans-Frieder Schött2
 
1 Institute of Clinical Chemistry and Laboratory Medicine, University Hospital Regensburg, Franz-Josef-Strauss-Allee 11, 93053 Regensburg, Germany
2 Singapore Lipidomics Incubator (SLING), Life Sciences Institute, National University of Singapore, Singapore

The analysis of human faecal metabolites can provide an insight into metabolic interactions between gut microbiota and host organism. Metabolic profiles in faeces have received little attention until now and reference values are missing, especially in the context of dietary and therapeutic interventions. The aim of the present study is to give concomitant concentration ranges of faecal sterol species, bile acids and short chain fatty acids based on a large cohort.
Sterol species, bile acids and short chain fatty acids in human faeces from 165 study participants were quantified by LC-MS/MS. For standardization, we refer all values to dry weight of faeces. Based on the individual intestinal sterol conversion we classified participants into low and high converters according to their coprostanol/cholesterol ratio.
Based on a large number of study participants we give a general quantitative overview of several metabolites in human faeces that can be used as reference values. The intestinal cholesterol conversion is a distinctive feature to evaluate SCFA and bile acid concentrations. Patient stratification into high or low sterol converter groups is associated with significant differences in faecal metabolites with biological activities. Such stratification could then allow assessing faecal metabolites better, e.g. before therapeutic interventions. Low converters excrete significantly more straight chain fatty acids and bile acids than high converters. 5th, 95th percentile and median of bile acids and short chain fatty acids were calculated for both groups.
The strength of our calculation is that our data base on i) a large cohort, ii) an uncontrolled diet which should reflect the behaviour of the normal population and iii) a comprehensive data set from various countries in Europe.

The Role of Proteomics to Enable the Two Sides of Precision Medicine

Jennifer van Eyk

(Cedars-Sinai Medical Center, California USA)

Underlying precision medicine is the concept that an individual’s Omic signature (including the proteome) will provide a physician with clinically actionable diagnosis and a subsequent mechanistic therapeutic route. This requires i) having an array of mechanistic therapies for each disease and ii) a means to diagnosis (identify) which therapy (or combination) will be appropriate for a particular person. Proteomics has played a role in discovery and defining potential mechanistic routes, but it is now time to move into implementation. This will, we hope, drive democratize of precision medicine.

Deep proteomic profiling of bone regeneration in a diabetic rat model: Insights into dysregulated molecular mechanisms and implications for personalized PCL-scaffold design

Presenting Author: Vivien Wiltzsch

Wiltzsch, Vivien*,1,5; Schmidt, Johannes R.1,5; Dias, Daniela2,5; Adamowicz, Klaudia3,5; Arend, Lis3,5; Lehmann, Jörg1,5; Lingner, Thomas4,5; Laske, Tanja3,5; Baumbach, Jan3,5; Poh, Patrina S.P.2,5; Kalkhof, Stefan1,5

1Department of Preclinical Development and Validation, Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig, Germany; 2Julius Wolff Institute, BIH at Charité – Universitätsmedizin Berlin, Berlin, Germany; 3Institute for Computational Systems Biology, University of Hamburg, Hamburg, Germany; 4Genevention GmbH, Göttingen, Germany; 5 e:Med consortium SyMBoD

Even though bone has a remarkable self-healing capacity, patients comorbid with type 2 diabetes mellitus (T2DM) can suffer from compromised bone healing. Therefore, research in regenerative medicine is currently investigating personalizable materials such as polycaprolactone (PCL) for their ability to promote intrinsic bone healing.
Within the scope of the interdisciplinary e:Med consortium SyMBoD, PCL scaffold-guided bone regeneration of a critical-size femur defect was investigated in a diabetic rat model. Longitudinal sampling of blood plasma (for proteomics and metabolomics) and µCT imaging was performed on diabetic and non-diabetic animals over either 21 or 42 days post-surgery. Finally, bone tissue was explanted for successive metabolite and proteome extraction. LC-MS/MS proteomic analyses were carried out on a Q-Exactive HF Quadrupole-Orbitrap mass spectrometer and processed by MaxQuant. Proteins altered during bone regeneration were identified by pairwise correlations of disease conditions and time points.
Multiplexed proteomics screening of bone tissue enabled the quantification of more than 4,000 proteins, thus providing novel insights into dysregulated bone regeneration in diabetic conditions at molecular level. Functional annotation analysis of differentially expressed proteins in the non-diabetic group identified enriched clusters involving GO terms “ECM organization” and “circulatory system development”. No such terms were found in the diabetic group, indicating a delayed onset of bone healing which was further confirmed histologically.
In conclusion, deep proteomics profiling revealed altered pathways at diabetic conditions, that may serve as targets for functionalization of PCL scaffold that address the needs of diabetic patients in impaired bone healing. Furthermore, integrative plasma and tissue proteomics allow for the identification of potential liquid biopsy-accessible indicative biomarkers for impaired fracture healing in T2DM.