Scientific Task Groups
Computational Mass Spectrometry Task Group
The Computational Mass Spectrometry task group represents the Metabolomics interests in the www.CompMS.org initiative, which promotes the efficient, high quality analysis of mass spectrometry data with state-of-the art computational tools and algorithms through dissemination and training in existing, and coordination of new, innovative approaches. The CompMS initiative aims to exploit synergies between different application domains, in particular proteomics and metabolomics. The scientific remit of the group will include all aspects of computational method development from signal processing, feature alignment and grouping, to development of metabolite identification algorithms and metabolic network reconstruction. For discussions and announcements, please join Metabolomics Society Forum. Members from the CompMS community participating in the Task Group are: Corey Broeckling, David Grant, Emma Schymanski, Etienne Thevenot, Federico Taverna, Jermaine Goveia, Johannes Rainer, Kris Morreel, Lee Ferguson, Michael Witting, Ming Wang, Nicola Zamboni, Pieter Dorrestein, Rainer Breitling, Shawez Khan, Simon Rogers, Tomas Pluskal.
Data Analysis Task Group
It has been well document that there is a reproducibility crisis in science in general. Closer to home, there are areas of ambiguity within the data analysis pipeline for metabolomics. This is often not deliberate and can be, but not limited to, a lack of transparency in the reporting of the data analysis process, or the employment of push-button ‘black box’ automated approaches, compounded with a lack of user knowledge.
The Metabolomics Society has therefore started this task group to help establish best practice and recommendations for what needs to be reported in order to ensure reproducibility of metabolomics data analysis science. We believe this will have a positive impact and improve data analysis practices more broadly.
Data Standards Task Group
Data Standards Task Group aims to foster and coordinate efforts in enabling efficient data formats for storage, exchange and verification of information within metabolomics datasets. The Data Standards Task Group will engage with producers or users of data formats such as; database providers, software engineers and instrument vendors working towards standardization and agreements set by metabolomics MSI, HUPO-PSI, COSMOS and other similar community-wide accepted initiatives. We actively work on open-data standards formats and its compliance with minimum information guidelines.
Lipidomics Task Group
LipidMetThe field of lipidomics has grown considerably over the past years and judging by the high number of lipidomics presentations at the meetings of the Metabolomics Society, large number of members are pursuing lipidomics as part of their research as well. Research on lipid biology is a very broad field, and lipidomics has become an essential tool of interest to many scientific societies and initiatives related to lipids. Metabolomics field has dealt with analyses of lipids since its inception (e.g. bile acids, endocannabinoids, steroids, fatty acids, structural lipids, various acylglycerols), while ‘lipidomics’ as a subfield has mainly focused from analytical perspective on comprehensive analysis of major classes of complex lipids such as phospholipids, sphingolipids, triacylglycerols etc.
Given this, it is important to engage the lipidomics community to the degree possible also from within the Metabolomics Society and to contribute to the growth of the lipidomics community. This is also important if we are to significantly impact data harmonization and quality control in this subfield of metabolomics via relevant task groups from Metabolomics Society. LipidMet is a lipidomics task group within the Metabolomics Society, which aims to connect the relevant initiatives in the field, including other related task groups in the Metabolomics Society, International Lipidomics Society, and major international lipidomics networks such as EpiLipidNet (https://www.epilipid.net/).
Specific tasks and activities of the LipidMet:
- Closing the gap between metabolomics and lipidomics analytical solutions
- Optimization and harmonization of workflows for comprehensive coverage of metabolites and lipids, including MS imaging
- Bioactive lipids – from discovery to functions
- Facilitate integration of bioinformatics tools for lipidomics and metabolomics
- Online tutorials and workshops on lipidomics analysis
- Organization of satellite workshops at MetSoc-associated meetings Via early career member network from EpiLipidNET, support MetSoc EMN on questions of lipidomics
- Engagement with industry
Metabolomic Epidemiology Task Group
The Metabolomic Epidemiology task group has outlined the objectives that will support its mission to promote the growth and understanding of metabolomic epidemiology as an independent research discipline. These objectives are:
- Establish a network of collaborations to enable the development of the required infrastructure, resources, and funding opportunities that will ensure the sustained growth of metabolomic epidemiology in the 21st century.
- Accelerate scientific discovery by addressing the unique challenges faced by metabolomic epidemiology researchers.
- Promote education to enable epidemiologists to work effectively with metabolomics data, and for fundamental metabolomics researchers to collaborate with epidemiologists.
- Provide a unified voice for the views and concerns of the metabolomic epidemiology community, assuring that they help drive the future direction of the Metabolomics Society.
Metabolite Identification Task Group
The Metabolite Identification task group is working with the community to build consensus on metabolite identification reporting standards, to educate the community on best practices and current tools and resources and to provide the opportunity for inter-laboratory comparisons. The objectives are:
- To build consensus on metabolite identification reporting standard
- To educate the community on best practices and current tools and resources
- Provide the opportunity for inter-laboratory comparisons
MetFAIR – Reproducible Reporting and Metabolite Annotation Task Group
MetFAIR Task Group focuses on the practices related to the reproducible reporting and use of metabolite annotation data across biological studies and research groups globally. In particular, four distinct areas require improvements to enhance the reporting and use of metabolite annotation data:
- The reporting of metabolite annotations in publications, data repositories and other databases presently does not rely on a controlled vocabulary (name or structural identifier) and best practice recommendations are currently not available to assist the metabolomics community.
- Linkage with databases and publishing metabolomics data in (open access) repositories – how to submit data and how to integrate information from different repositories and databases.
- Reporting of metabolomics raw data in publications including but not limited to the multiplicity of signals detected for a single metabolite and how to handle them in statistical analysis.
- Metabolomics data in the context of multi-omics studies – how to handle network and pathway databases with naming and identifier conventions that don’t fit metabolite and lipid identifiers used in our community.
Model Organism Metabolomes Task Group
The remit of this newly forming Task Group is to leverage upon the critical mass of research activity that surrounds established model organisms, i.e., to focus metabolite identification efforts on the identification of Model Organism Metabolomes (MOMs). Such activity would complement the work conducted by the Metabolite Identification Task Group, and parallels the approach used by the proteomics community, specifically HUPO and their Initiative on Model Organism Proteomes (iMOP). We aim to (1) integrate disparate model organism-focused research groups into a Model Organism Metabolomes community and promote interactions between these groups; (2) share, discuss and coordinate analytical and bioinformatics strategies to progress the annotation and identification of Model Organism Metabolomes (including polar metabolites and lipids), ideally resulting in best practice strategies. This will be achieved through targeted publications, dissemination of information through MetaboNews, and a discussion group on the Metabolomics Society’s new Metabolomics Forum.
Precision Medicine and Pharmacometabolomics Task Group
The Precision Medicine and Pharmacometabolomics Task Group seeks to catalyze the engagement of our metabolomics community in global initiatives in precision medicine. We will create communication channels to facilitate the incorporation of metabolomics data as a compliment to genomics data in informing about disease heterogeneity and treatment outcomes. We seek to facilitate advancements in the field of Pharmacometabolomics and as enabling tool for Precision Medicine.
