MetClassNet: new approaches to bridge the gap between genome-scale metabolic networks and untargeted metabolomics

• Applicants: Privatdozent Dr. Steffen Neumann; Privatdozent Dr. Michael Witting
• Subject Area: Bioinformatics and Theoretical Biology ; Analytical Chemistry
• Term: from 2019 to 2023
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 431572533

• Final Report Year: 2024

Final Report Abstract

Metabolism is a complex phenomenon and a key biological process, which is modulated in living organisms in response to environmental exposure, genetic variations, diet and many other factors. Understanding metabolism is essential to improve plant performance (e.g. yield), nutritional content and health effects of foods and to understand human health. The metabolome, the entire complement of small molecules or metabolites in a given organism or system, is highly dynamic and chemically diverse. Individual metabolites are connected by (enzymatic) reactions forming a dense network. The German-French project “MetClassNet: new approaches to bridge the gap between genome-scale metabolic networks and untargeted metabolomics” developed methods to combine several experimental and knowledge into a multilayer network for improved data analysis, visualisation and metabolite identification. Different organisms were anticipated to be used as model systems and test cases for the data analytical approaches developed within MetClassNet. The focus in the Munich group was the nematode Caenorhabditis elegans, a widely used model organism in biomedical research, while the group in Halle focused on plant applications. All software was developed and published under an Open Source License. Several datasets were annotated according to the FAIR criteria and published in Open Access metabolomics ressources. The results were disseminated in several Open Access publications, and presented to a larger audience at the annual conference of the international Metabolomics Society,

Publications

• Spectra consolidation of high-resolution tandem mass spectrometry data in LC-MS based nontargeted metabolomics and lipidomics. Metabolomics Society conference (virtual, 2020). Poster + flash talk
  L. Salzer & M. Witting
  
• Suggestions for Standardized Identifiers for Fatty Acyl Compounds in Genome Scale Metabolic Models and Their Application to the WormJam Caenorhabditis elegans Model. Metabolites, 10(4), 130.
  Witting, Michael
  
• GNPS ecosystem use case: Finding new molecules in Caenorhabditis elegans. SGMS School 2021
  Michael Witting
  
• Quo Vadis Caenorhabditis elegans Metabolomics—A Review of Current Methods and Applications to Explore Metabolism in the Nematode. Metabolites, 11(5), 284.
  Salzer, Liesa & Witting, Michael
  
• A Modular and Expandable Ecosystem for Metabolomics Data Annotation in R. Metabolites, 12(2), 173.
  Rainer, Johannes; Vicini, Andrea; Salzer, Liesa; Stanstrup, Jan; Badia, Josep M.; Neumann, Steffen; Stravs, Michael A.; Verri, Hernandes Vinicius; Gatto, Laurent; Gibb, Sebastian & Witting, Michael
  
• Description of FAHFAs in Caenorhabditis elegans. Metabolomics Society ConferenceCoference 2022. Poster
  Michael Witting, Ansgar Korf, Aiko Barsch & Sven Meyer
  
• Metabolite mapping strategies for untargeted metabolomics. Metabolomics 2022, Poster
  Sarah Scharfenberg, Clément Frainay, Elva Novoa, Michael Witting & Steffen Neumann
  
• MobilityTransformR: an R package for effective mobility transformation of CE-MS data. Bioinformatics, 38(16), 4044-4045.
  Salzer, Liesa; Witting, Michael & Schmitt-Kopplin, Philippe
  
• Multi-network integration to analyze non-targeted LC-MS metabolomics data from Caenorhabditis elegans, Metabolomics Society Conference 2022 Talk
  Liesa Salzer, Michael Witting, Elva Novoa, Clément Frainay & Fabien Jourdan
  
• Networks and Graphs Discovery in Metabolomics Data Analysis and Interpretation. Frontiers in Molecular Biosciences, 9.
  Amara, Adam; Frainay, Clément; Jourdan, Fabien; Naake, Thomas; Neumann, Steffen; Novoa-del-Toro, Elva María; Salek, Reza M.; Salzer, Liesa; Scharfenberg, Sarah & Witting, Michael
  
• APEX: an Annotation Propagation Workflow through Multiple Experimental Networks to Improve the Annotation of New Metabolite Classes in Caenorhabditis elegans. Analytical Chemistry, 95(48), 17550-17558.
  Salzer, Liesa; Novoa-del-Toro, Elva María; Frainay, Clément; Kissoyan, Kohar Annie B.; Jourdan, Fabien; Dierking, Katja & Witting, Michael
  
• Capillary electrophoresis-mass spectrometry as a tool for Caenorhabditis elegans metabolomics research. Metabolomics, 19(7).
  Salzer, Liesa; Schmitt-Kopplin, Philippe & Witting, Michael