TY - JOUR
T1 - MS2 and LC libraries for untargeted metabolomics: Enhancing method development and identification confidence
AU - Folberth, Julica
AU - Begemann, Kimberly
AU - Jöhren, Olaf
AU - Schwaninger, Markus
AU - Othman, Alaa
N1 - Copyright © 2020 Elsevier B.V. All rights reserved.
PY - 2020/5/15
Y1 - 2020/5/15
N2 - As part of the “omics” technologies in the life sciences, metabolomics is becoming increasingly important. In untargeted metabolomics, unambiguous metabolite identification and the inevitable coverage bias that comes with the selection of analytical conditions present major challenges. Reliable compound annotation is essential for translating metabolomics data into meaningful biological information. Here, we developed a fast and transferable method for generating in-house MS2 libraries to improve metabolite identification. Using the new method we established an in-house MS2 library that includes over 4,000 fragmentation spectra of 506 standard compounds for 6 different normalized collision energies (NCEs). Additionally, we generated a comprehensive liquid chromatography (LC) library by testing 57 different LC-MS conditions for 294 compounds. We used the library information to develop an untargeted metabolomics screen with maximum coverage of the metabolome that was successfully tested in a study of 360 human serum samples. The current work demonstrates a workflow for LC–MS/MS-based metabolomics, with enhanced metabolite identification confidence and the possibility to select suitable analysis conditions according to the specific research interest.
AB - As part of the “omics” technologies in the life sciences, metabolomics is becoming increasingly important. In untargeted metabolomics, unambiguous metabolite identification and the inevitable coverage bias that comes with the selection of analytical conditions present major challenges. Reliable compound annotation is essential for translating metabolomics data into meaningful biological information. Here, we developed a fast and transferable method for generating in-house MS2 libraries to improve metabolite identification. Using the new method we established an in-house MS2 library that includes over 4,000 fragmentation spectra of 506 standard compounds for 6 different normalized collision energies (NCEs). Additionally, we generated a comprehensive liquid chromatography (LC) library by testing 57 different LC-MS conditions for 294 compounds. We used the library information to develop an untargeted metabolomics screen with maximum coverage of the metabolome that was successfully tested in a study of 360 human serum samples. The current work demonstrates a workflow for LC–MS/MS-based metabolomics, with enhanced metabolite identification confidence and the possibility to select suitable analysis conditions according to the specific research interest.
UR - http://www.scopus.com/inward/record.url?scp=85083308001&partnerID=8YFLogxK
U2 - 10.1016/j.jchromb.2020.122105
DO - 10.1016/j.jchromb.2020.122105
M3 - Journal articles
C2 - 32305706
AN - SCOPUS:85083308001
SN - 1570-0232
VL - 1145
SP - 122105
JO - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
JF - Journal of Chromatography B: Analytical Technologies in the Biomedical and Life Sciences
M1 - 122105
ER -