» Articles » PMID: 36409434

The Critical Role That Spectral Libraries Play in Capturing the Metabolomics Community Knowledge

Overview
Journal Metabolomics
Publisher Springer
Specialty Endocrinology
Date 2022 Nov 21
PMID 36409434
Authors
Affiliations
Soon will be listed here.
Abstract

Background: Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of thousands of compounds, forming an essential knowledge base for the interpretation of metabolomics experiments.

Aim Of Review: We describe existing spectral library resources, highlight different strategies for compiling spectral libraries, and discuss quality considerations that should be taken into account when interpreting spectral library searching results. Finally, we describe how spectral libraries are empowering the next generation of machine learning tools in computational metabolomics, and discuss several opportunities for using increasingly accessible large spectral libraries.

Key Scientific Concepts Of Review: This review focuses on the current state of spectral libraries for untargeted LC-MS/MS based metabolomics. We show how the number of entries in publicly accessible spectral libraries has increased more than 60-fold in the past eight years to aid molecular interpretation and we discuss how the role of spectral libraries in untargeted metabolomics will evolve in the near future.

Citing Articles

Computational metabolomics reveals overlooked chemodiversity of alkaloid scaffolds in Piper fimbriulatum.

Damiani T, Smith J, Hebra T, Perkovic M, cicak M, Kadlecova A Plant J. 2025; 121(5):e70086.

PMID: 40052447 PMC: 11886945. DOI: 10.1111/tpj.70086.


SimMS: a GPU-accelerated cosine similarity implementation for tandem mass spectrometry.

Onoprishvili T, Yuan J, Petrov K, Ingalalli V, Khederlarian L, Leuchtenmuller N Bioinformatics. 2025; 41(3).

PMID: 39977359 PMC: 11886821. DOI: 10.1093/bioinformatics/btaf081.


Molecular Structure Discovery for Untargeted Metabolomics Using Biotransformation Rules and Global Molecular Networking.

Martin M, Bittremieux W, Hassoun S Anal Chem. 2025; 97(6):3213-3219.

PMID: 39903752 PMC: 11841678. DOI: 10.1021/acs.analchem.4c01565.


A complementary approach for detecting biological signals through a semi-automated feature selection tool.

Arini G, Mencucini L, de Felicio R, Feitosa L, Rezende-Teixeira P, de Oliveira Tsuji H Front Chem. 2024; 12:1477492.

PMID: 39525959 PMC: 11543558. DOI: 10.3389/fchem.2024.1477492.


The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF.

Klein J, Lam H, Mak T, Bittremieux W, Perez-Riverol Y, Gabriels R Anal Chem. 2024; 96(46):18491-18501.

PMID: 39514576 PMC: 11579979. DOI: 10.1021/acs.analchem.4c04091.


References
1.
Schymanski E, Neumann S . The Critical Assessment of Small Molecule Identification (CASMI): Challenges and Solutions. Metabolites. 2014; 3(3):517-38. PMC: 3901296. DOI: 10.3390/metabo3030517. View

2.
Pedrioli P, Eng J, Hubley R, Vogelzang M, Deutsch E, Raught B . A common open representation of mass spectrometry data and its application to proteomics research. Nat Biotechnol. 2004; 22(11):1459-66. DOI: 10.1038/nbt1031. View

3.
Gessulat S, Schmidt T, Zolg D, Samaras P, Schnatbaum K, Zerweck J . Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning. Nat Methods. 2019; 16(6):509-518. DOI: 10.1038/s41592-019-0426-7. View

4.
Kelchtermans P, Bittremieux W, De Grave K, Degroeve S, Ramon J, Laukens K . Machine learning applications in proteomics research: how the past can boost the future. Proteomics. 2013; 14(4-5):353-66. DOI: 10.1002/pmic.201300289. View

5.
Ducati A, Ruskic D, Sosnowski P, Baba T, Bonner R, Hopfgartner G . Improved metabolite characterization by liquid chromatography - Tandem mass spectrometry through electron impact type fragments from adduct ions. Anal Chim Acta. 2021; 1150:338207. DOI: 10.1016/j.aca.2021.338207. View