van Der Hooft, J. J. J. , Wandy, J. , Barrett, M. P. , Burgess, K. E.V. and Rogers, S. (2016) Topic modeling for untargeted substructure exploration in metabolomics. Proceedings of the National Academy of Sciences of the United States of America, 113(48), pp. 13738-13743. (doi: 10.1073/pnas.1608041113) (PMID:27856765) (PMCID:PMC5137707)
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Abstract
The potential of untargeted metabolomics to answer important questions across the life sciences is hindered due to a paucity of computational tools that enable extraction of key biochemically relevant information. Available tools focus on using mass spectrometry fragmentation spectra to identify molecules whose behavior suggests they are relevant to the system under study. Unfortunately, fragmentation spectra cannot identify molecules in isolation, but require authentic standards or databases of known fragmented molecules. Fragmentation spectra are, however, replete with information pertaining to the biochemical processes present; much of which is currently neglected. Here we present an analytical workflow that exploits all fragmentation data from a given experiment to extract biochemically-relevant features in an unsupervised manner. We demonstrate that an algorithm originally utilized for text-mining, Latent Dirichlet Allocation, can be adapted to handle metabolomics datasets. Our approach extracts biochemically-relevant molecular substructures (‘Mass2Motifs’) from spectra as sets of co-occurring molecular fragments and neutral losses. The analysis allows us to isolate molecular substructures, whose presence allows molecules to be grouped based on shared substructures regardless of classical spectral similarity. These substructures in turn support putative de novo structural annotation of molecules. Combining this spectral connectivity to orthogonal correlations (e.g. common abundance changes under system perturbation) significantly enhances our ability to provide mechanistic explanations for biological behavior.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Rogers, Dr Simon and Wandy, Dr Joe and Van Der Hooft, Mr Justin and Burgess, Dr Karl and Barrett, Professor Michael |
| Authors: | van Der Hooft, J. J. J., Wandy, J., Barrett, M. P., Burgess, K. E.V., and Rogers, S. |
| College/School: | College of Medical Veterinary and Life Sciences College of Medical Veterinary and Life Sciences > School of Infection & Immunity College of Science and Engineering > School of Computing Science |
| Journal Name: | Proceedings of the National Academy of Sciences of the United States of America |
| Publisher: | National Academy of Sciences |
| ISSN: | 0027-8424 |
| ISSN (Online): | 1091-6490 |
| Published Online: | 16 November 2016 |
| Copyright Holders: | Copyright © 2016 National Academy of Sciences |
| First Published: | First published in Proceedings of the National Academy of Sciences of the United States of America 2016 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
| Related URLs: | |
| Data DOI: | 10.5525/gla.researchdata.313 |
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