The Metabolomics Standards Initiative (MSI) and Core Information for Metabolomics Reporting (CIMR)

History: The Metabolomics Standards Initiative (MSI) was conceived in 2005 following earlier work by the Standard Metabolic Reporting Structure initiative and the Architecture for Metabolomics consortium. The early efforts of MSI were focused on community-agreed reporting standards, which provided a clear description of the biological system studied and all components of metabolomics studies.

The aim was to allow data to be efficiently applied, shared and reused. There were five working groups and the chemical analysis group proposed minimum information for reporting chemical analysis, including minimum metadata to report related to metabolite identification

Working Groups: The MSI WGs worked towards developing the following standards:

1. Core Information for Metabolomics Reporting (CIMR): This document will specify the minimal guidelines reporting metabolomics work. It will do so in a textual form and will seek in the long term to cover all application areas and analysis technologies. This document will be developed by the biological context metadata WG, the chemical analysis WG, the data processing WG, the exchange format WG and the ontology WG.
2. Ontology: The CV and ontology will be developed iteratively by the ontology WG on the basis of CIMR. This will be done in collaboration with: HUPO-PSI, FGED (MGED) and OBI ontology (former FuGO).
3. Exchange format: A data model and exchange format will be developed by the exchange format WG on the basis of CIMR, making use of the MSI ontology. This will be done in a collaborative and iterative approach, including HUPO-PSI and FUGE.

• Biological context metadata WG
  • In vivo / mammalian biologuy context
  • Plant biology context
  • In vitro biology/microbiology context
  • Environmental analysis context
• Chemical analysis WG
• Data processing/analysis WG
• Ontology WG
• Exchange format WG

Historical links to original sourceforge site:

Metabolite identification: The chemical analysis working group defined four different levels of metabolite identification observed in the scientific literature. These included:

• Level 1 -Identified metabolites
• Level 2 - Putatively annotated compounds
• Level 3 - Putatively characterised compound classes
• Level 4 - Unknown compounds

Important differences: Level 1 identification necessitates that 2 or more orthogonal properties of an authentic chemical standard analysed in the researcher’s laboratory are compared to experimental data acquired in the same laboratory with the same analytical methods.

By contrast, level 2 and 3 annotation does not require matching to data for authentic chemical standards acquired within the same laboratory. Many studies do not compare experimental data to data acquired for authentic chemical standards, and therefore annotations and not identifications are achieved.

Defining metabolites as identified or annotated is hugely important to provide clarity. It is recommended that all researchers define the level of identification, common name and structural code (e.g., InChI or SMILES) in their publications and when submitting data to repositories. However, the current use of these standards is low in peer-reviewed publications. As a community we need to robustly apply these reporting standards routinely.

More informations see:

The role of reporting standards for metabolite annotation and identification in metabolomic studies

Reza M Salek, Christoph Steinbeck, Mark R Viant, Royston Goodacre, Warwick B Dunn GigaScience 2013, 2:13 (16 October 2013)

List of MSI related and standards publication

Bundy, J., Davey, M., & Viant, M. (2009). Environmental metabolomics: a critical review and future perspectives. Metabolomics : Official journal of the Metabolomic Society, 5(1), 3-21, doi:10.1007/s11306-008-0152-0.

Castle, A. L., Fiehn, O., Kaddurah-Daouk, R., & Lindon, J. C. (2006). Metabolomics Standards Workshop and the development of international standards for reporting metabolomics experimental results. [Consensus Development Conference, NIH]. Briefings in Bioinformatics, 7(2), 159-165, doi:10.1093/bib/bbl008.