Miguel Rojas-Cherto

Peironcely Julio E

PT Kasper

RJ Vreeken

T Hankemeier

T Reijmers

Journal of Cheminformatics

PubMed

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The pipelined metabolite identification based on MS fragmentation

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POSTER PRESENTATION Open Access
The pipelined metabolite identification based on
MS fragmentation
Miguel Rojas-Cherto*, PT Kasper, Peironcely Julio E, T Reijmers, RJ Vreeken, T Hankemeier
From 5th German Conference on Cheminformatics: 23. CIC-Workshop
Goslar, Germany. 8-10 November 2009
Structural characterization and identification of com-
ponents of complex biological mixtures constitutes one
of the central aspects of metabolomics. Metabolite
identification is a challenging but essential task in stu-
dies of biological samples. Mass spectrometry, because
of its high sensitivity and specificity, is widely and suc-
cessfully used in analysis of biological samples. Identifi-
cation of metabolites can be in principle achieved
using high resolution multistage mass spectrometry
(MSn) because it provides a feature rich fingerprint of
the precursor structure. However, neither general
methodology for the identification nor extensive
databases of metabolites with multistage mass spectro-
metric data are available at the moment. We demon-
strate in this poster the feasibility of the strategy for
metabolite identification based on analysis of fragmen-
tation trees.
High resolution multi stage MS experiments were per-
formed on LTQ-Orbitrap (Thermo) equipped with Tri-
versa nanoMate (Advion) nanoelectrospray ion source
using defined protocol. An in-house developed software,
integrating among others: Chemistry Development Kit
(CDK) and XCMS libraries, was used for spectral data
processing. Resulting fragmentation trees were stored in
a local database.
Multi-stage Molecular Formula (MMF) tool, which
uses a method to resolve the elemental composition of
the compound and fragment ions derived from MSn
data using a cyclic constraining process has been
developed. The process of elemental formula assign-
ment and fitting within elemental formula paths
removes artefacts of the spectra. Background signals,
spikes, contaminations, side peaks, etc., are rejected in
this stage and are not included in the fragmentation
tree. The resulting fragmentation trees are stored in
XML format.
Repeatability, reproducibility and robustness of frag-
mentation tree acquisitions were tested by changing
experimental conditions and varying the concentration
of the metabolite of interest. An acquisition protocol
was established for the reliable and reproducible acquisi-
tion of mass spectral trees. It was investigated to which
extent the variation of conditions such as fragmentation
energy, isolation width etc. did change the fragmenta-
tion pattern or topology of hierarchical relations
between fragments.
We demonstrate how the developed analytical strategy
based on analysis of fragmentation trees can be used to
discriminate between metabolite isomers with the same
elemental composition and an only slightly different
structure, but with a significantly different biological
function.
Our results provide firm basis for developing a gen-
eric, multi stage mass spectrometry based platform for
efficient identification of metabolites.
Published: 4 May 2010
doi:10.1186/1758-2946-2-S1-P53
Cite this article as: Rojas-Cherto et al.: The pipelined metabolite
identification based on MS fragmentation. Journal of Cheminformatics
2010 2(Suppl 1):P53.
Leiden, The Netherlands
Rojas-Cherto et al. Journal of Cheminformatics 2010, 2(Suppl 1):P53
http://www.jcheminf.com/content/2/S1/P53
© 2010 Rojas-Cherto et al; licensee BioMed Central Ltd.


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The pipelined metabolite identification based on MS fragmentation

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