van der Hooft, J. , Ridder, L., Barrett, M. P. and Burgess, K. V. (2015) Enhanced acylcarnitine annotation in high-resolution mass spectrometry data: fragmentation analysis for the classification and annotation of acylcarnitines. Frontiers in Bioengineering and Biotechnology, 3, p. 26. (doi: 10.3389/fbioe.2015.00026) (PMID:25806366) (PMCID:PMC4353373)
|
Text
102957.pdf - Published Version Available under License Creative Commons Attribution. 1MB |
Abstract
Metabolite annotation and identification are primary challenges in untargeted metabolomics experiments. Rigorous workflows for reliable annotation of mass features with chemical structures or compound classes are needed to enhance the power of untargeted mass spectrometry. High-resolution mass spectrometry considerably improves the confidence in assigning elemental formulas to mass features in comparison to nominal mass spectrometry, and embedding of fragmentation methods enables more reliable metabolite annotations and facilitates metabolite classification. However, the analysis of mass fragmentation spectra can be a time-consuming step and requires expert knowledge.<p></p> This study demonstrates how characteristic fragmentations, specific to compound classes, can be used to systematically analyze their presence in complex biological extracts like urine that underwent untargeted mass spectrometry combined with data dependent or targeted fragmentation. Human urine extracts were analyzed using normal phase liquid chromatography (HILIC) coupled to an Ion Trap-Orbitrap hybrid instrument. Subsequently, mass chromatograms and CID and HCD fragments were annotated using the freely available MAGMa software.<p></p> Acylcarnitines play a central role in energy metabolism by transporting fatty acids into the mitochondrial matrix. By filtering on a combination of a mass fragment and neutral loss designed based on the MAGMa fragment annotations, we were able to classify and annotate 50 acylcarnitines in human urine extracts, based on high-resolution mass spectrometry HCD fragmentation spectra at different energies for all of them. Of these annotated acylcarnitines, 31 are not described in HMDB yet and for only 4 annotated acylcarnitines the fragmentation spectra could be matched to reference spectra. Therefore, we conclude that the use of mass fragmentation filters within the context of untargeted metabolomics experiments is a valuable tool to enhance the annotation of small metabolites.<p></p>
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Van Der Hooft, Mr Justin and Burgess, Dr Karl and Barrett, Professor Michael |
| Authors: | van der Hooft, J., Ridder, L., Barrett, M. P., and Burgess, K. V. |
| College/School: | College of Medical Veterinary and Life Sciences > School of Infection & Immunity |
| Journal Name: | Frontiers in Bioengineering and Biotechnology |
| Publisher: | Frontiers |
| ISSN: | 2296-4185 |
| ISSN (Online): | 2296-4185 |
| Published Online: | 19 February 2015 |
| Copyright Holders: | Copyright © 2015 The Authors |
| First Published: | First published in Frontiers in Bioengineering and Biotechnology 3:26 |
| Publisher Policy: | Reproduced under a Creative Commons License |
University Staff: Request a correction | Enlighten Editors: Update this record
Funder and Project Information
Funder and Project Information