Abstract
Metabolomics has become a crucial phenotyping technique in a range of research fields including medicine, the life sciences, biotechnology and the environmental sciences. This necessitates the transfer of experimental information between research groups, as well as potentially to publishers and funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative ‘coordination of standards in metabolomics’ (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities’ participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.
Highlights
Metabolomics (Bundy et al 2009; Clayton et al 2006; Eckhart et al 2012; Holmes et al 2008)1 and fluxomics (metabolic flux analysis, Zamboni, Nicola et al ‘‘13C-based metabolic flux analysis.’’ Nature protocols 4.6 (2009): 878–892) measurements mark the end point closest to the phenotype of organisms, reflecting changes in organisms influenced by external parameters such as nutritional, environmental or toxicological interactions
We aim to extend the open standards for mass spectrometry (MS) data exchange initiated by proteomics standards initiative (PSI), such as mzML (Martens et al 2011), mzIdentML (Jones et al 2012) and mzQuantML (Walzer et al 2013) to meet the requirement of metabolomics experiments for reporting MS experiments
coordination of standards in metabolomics’ (COSMOS) developing the missing XML exchange formats for nuclear magnetic resonance (NMR) spectroscopy such as nmrML, nmrIdentML, nmrQuantML and nmrTab needed by databases and open source software such as NMRLab/MetaboLab (Ludwig and Gunther 2011) Bayesian AuTomated Metabolite Analyser for NMR spectra (BATMAN) (Hao et al 2012) and rNMR (Lewis et al 2009)
Summary
Metabolomics (Bundy et al 2009; Clayton et al 2006; Eckhart et al 2012; Holmes et al 2008) and fluxomics (metabolic flux analysis, Zamboni, Nicola et al ‘‘13C-based metabolic flux analysis.’’ Nature protocols 4.6 (2009): 878–892) measurements mark the end point closest to the phenotype of organisms, reflecting changes in organisms influenced by external parameters such as nutritional, environmental or toxicological interactions In this context, due to its dynamic nature, metabolomics is of considerable value for examples in personalised medicine, especially as it captures rapid responses close to the phenotype and in concert with the genome, transcriptome and epigenome (van der Greef et al 2006, Nicholson et al 2011). Considering the diversity and breadth of metabolomics applications, not forgetting complexity and diversity of the analytical technologies in use, there is a clearly identified need for standardisation that evolves with the technologies and is sufficiently inclusive to cover all metabolomics applications
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