Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/152068
Title: Retrieving and utilizing hypothetical neutral losses from tandem mass spectra for spectral similarity analysis and unknown metabolite annotation
Authors: Xing, Shipei
Hu, Yan
Yin, Zixuan
Liu, Min
Tang, Xiaoyu
Fang, Mingliang
Huan, Tao
Keywords: Engineering::Civil engineering
Issue Date: 2020
Source: Xing, S., Hu, Y., Yin, Z., Liu, M., Tang, X., Fang, M. & Huan, T. (2020). Retrieving and utilizing hypothetical neutral losses from tandem mass spectra for spectral similarity analysis and unknown metabolite annotation. Analytical Chemistry, 92(21), 14476-14483. https://dx.doi.org/10.1021/acs.analchem.0c02521
Journal: Analytical Chemistry
Abstract: Spectral similarity comparison through tandem mass spectrometry (MS²) is a powerful approach to annotate known and unknown metabolic features in mass spectrometry (MS)-based untargeted metabolomics. In this work, we proposed the concept of hypothetical neutral loss (HNL), which is the mass difference between a pair of fragment ions in a MS² spectrum. We demonstrated that HNL values contain core structural information that can be used to accurately assess the structural similarity between two MS² spectra. We then developed the Core Structure-based Search (CSS) algorithm based on HNL values. CSS was validated with sets of hundreds of randomly selected metabolites and their reference MS² spectra, showing significantly improved correlation between spectral and structural similarities. Compared to state-of-the-art spectral similarity algorithms, CSS generates better ranking of structurally relevant chemicals among false positives. Combining CSS, HNL library, and biotransformation database, we further developed Metabolite core structure-based Search (McSearch), a novel computational solution to facilitate the annotation of unknown metabolites using the reference MS² spectra of their structural analogs. McSearch generates better results in the Critical Assessment of Small Molecule Identification (CASMI) 2017 data set than conventional unknown feature annotation programs. McSearch was also tested in experimental MS² data of xenobiotic metabolite derivatives belonging to three different metabolic pathways. Our results confirmed that McSearch can better capture the underlying structural similarity between MS² spectra. Overall, this work provides a novel direction for metabolite annotation via HNL values, paving the way for annotating metabolites using their structurally similar compounds.
URI: https://hdl.handle.net/10356/152068
ISSN: 0003-2700
DOI: 10.1021/acs.analchem.0c02521
Rights: © 2020 American Chemical Society. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:CEE Journal Articles

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