Powerful tool for identifying unknown metabolites

An interview with T.Reijmers about Metitree in NBIC's magazine Interface

Contemporary metabolomics research is faced with great challenges. Individual metabolites in complex mixtures need to be analysed and identified. Liquid chromatography combined with multistage mass spectrometry (MSn) appears to be a useful approach, especially since the availability of a promising tool for organising, processing, sharing, visualising and comparing MSn data.

Acknowledgement
NBIC magazine Interface ( - page 17 - )

More about NBIC's Interface magazine can be found and downloaded from: http://www.nbic.nl/about-nbic/news-press/nbic-magazine/

download issue 9 - page 17 | November 2012

An automated Metabolite Identification Pipeline using Mass Spectral Trees

Identifying metabolites has been reported as one of the major bottlenecks in metabolomics. In part, this is due to the absence of good computational tools to automate metabolite identification. To address this issue, we have developed mathematical tools to process and compare multi-stage mass spectrometry data (MSn), in order to extract as much as possible information from the fragmentation trees. In addition, candidate structures are generated computationally and filters are used to reject improbable chemical structures. This poster presents the integrated use of these tools in a pipeline fashion to identify metabolites in human urine.
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Theo Reijmers (1), Julio Peironcely (1,2), Miguel Rojas-Cherto (1), Piotr Kasper (1), Leon Coulier (2), Albert Tas (2), Rob Vreeken (1) and Thomas Hankemeier (1)

1. Analytical Biosciences, Leiden University, 2. TNO Quality of Life, Zeist

MSn spectral tree databases: annotation and identification of plant metabolites

Annotation and identification of metabolites detected in untargeted liquid chromatography coupled to mass spectrometry (LC-MS) profiling techniques is still a major challenge that needs to be overcome in order to interpret the results obtained in a biological context. Protocols for generating MSn and LC-MSn data from metabolites detectable in plants, including Arabidopsis leaves and tomato fruit, have recently been developed, resulting in robust spectral trees [1,2]. Meanwhile, a software tool called MEF has been developed to process the MSn raw data and assign elemental formulas to the detected metabolite MSn signals [3]. Very recently, a web-based program called MetiTree, embedding the MEF tool and algorithms to visualize and compare spectral trees [4] has become available [5].
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Justin J.J. van der Hooft (1,2,3), Miguel Rojas-Cherto (3), Thomas Hankemeier (3), Michael van Vliet (3), Theo Reijmers (3), Robert D. Hall (1,2,3) and Ric C.H. de Vos (1,2,3)

1. Plant Research International, Wageningen-UR, Wageningen, The Netherlands; 2. Centre for BioSystems Genomics, Wageningen, The Netherlands; 3. Netherlands Metabolomics Centre, Leiden, The Netherlands