Reference : Annotating Nontargeted LC-HRMS/MS Data with Two Complementary Tandem Mass Spectral Li...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
Systems Biomedicine
http://hdl.handle.net/10993/38099
Annotating Nontargeted LC-HRMS/MS Data with Two Complementary Tandem Mass Spectral Libraries
English
Oberacher, Herbert [> >]
Reinstadler, Vera [> >]
Kreidl, Marco [> >]
Stravs, Michael A. [> >]
Hollender, Juliane [> >]
Schymanski, Emma mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) >]
2018
Metabolites
9
1 3
Metabolomics Data Processing and Data Analysis—Current Best Practices
Yes (verified by ORBilu)
International
2218-1989
[en] Tandem mass spectral databases are indispensable for fast and reliable compound identification in nontargeted analysis with liquid chromatography–high resolution tandem mass spectrometry (LC-HRMS/MS), which is applied to a wide range of scientific fields. While many articles now review and compare spectral libraries, in this manuscript we investigate two high-quality and specialized collections from our respective institutes, recorded on different instruments (quadrupole time-of-flight or QqTOF vs. Orbitrap). The optimal range of collision energies for spectral comparison was evaluated using 233 overlapping compounds between the two libraries, revealing that spectra in the range of CE 20–50 eV on the QqTOF and 30–60 nominal collision energy units on the Orbitrap provided optimal matching results for these libraries. Applications to complex samples from the respective institutes revealed that the libraries, combined with a simple data mining approach to retrieve all spectra with precursor and fragment information, could confirm many validated target identifications and yield several new Level 2a (spectral match) identifications. While the results presented are not surprising in many ways, this article adds new results to the debate on the comparability of Orbitrap and QqTOF data and the application of spectral libraries to yield rapid and high-confidence tentative identifications in complex human and environmental samples.
Researchers
http://hdl.handle.net/10993/38099
10.3390/metabo9010003
http://www.mdpi.com/2218-1989/9/1/3
© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
FnR ; FNR12341006 > Emma Schymanski > ECHIDNA > Environmental Cheminformatics to Identify Unknown Chemicals and their Effects > 01/10/2018 > 30/09/2023 > 2018

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