18 research outputs found
Towards automated identification of metabolites using mass spectral trees
The detailed description of the chemical compounds present in organisms, organs/tissues, biofluids and cells is the key to understand the complexity of biological systems. The small molecules (metabolites) are known to be very diverse in structure and function. However, the identification of the chemical structure of metabolites is one of the major bottlenecks in metabolomics research. Hence, the annotation and the structure elucidation of the metabolites are essential to understand the biological system under study. Actually, no single analytical platform exists that can measure and identify all existing metabolites. Multistage mass spectrometry (MSn) is a powerful analytical technique that helps identifying all these metabolites. This technique provides detailed structural information of the unknown metabolite by fragmenting the metabolite and its fragments recursively. However, only computational tools can provide a fast and straightforward analysis of the large amount of complex data that is generated by using MSn spectrometry. The aim of this thesis was to develop a novel semi-automatic approach for the identification of metabolites using MS n data. Furthermore, these tools were to be integrated into a pipeline to assign identities to unknown metabolites present in databases but especially to unknown metabolites not present in a databaseUBL - phd migration 201
Fragmentation trees for the structural characterisation of metabolites
Analytical BioScience
MS2Analyzer: A Software for Small Molecule Substructure Annotations from Accurate Tandem Mass Spectra
Systematic
analysis and interpretation of the large number of tandem
mass spectra (MS/MS) obtained in metabolomics experiments is a bottleneck
in discovery-driven research. MS/MS mass spectral libraries are small
compared to all known small molecule structures and are often not
freely available. MS2Analyzer was therefore developed to enable user-defined
searches of thousands of spectra for mass spectral features such as
neutral losses, <i>m</i>/<i>z</i> differences,
and product and precursor ions from MS/MS spectra in MSP/MGF files.
The software is freely available at http://fiehnlab.ucdavis.edu/projects/MS2Analyzer/. As the reference query set, 147 literature-reported neutral losses
and their corresponding substructures were collected. This set was
tested for accuracy of linking neutral loss analysis to substructure
annotations using 19 329 accurate mass tandem mass spectra
of structurally known compounds from the NIST11 MS/MS library. Validation
studies showed that 92.1 ± 6.4% of 13 typical neutral losses
such as acetylations, cysteine conjugates, or glycosylations are correct
annotating the associated substructures, while the absence of mass
spectra features does not necessarily imply the absence of such substructures.
Use of this tool has been successfully demonstrated for complex lipids
in microalgae