TY - JOUR
T1 - Optimized workflow for on-line derivatization for targeted metabolomics approach by gas chromatography-mass spectrometry
AU - Fritsche-Guenther, Raphaela
AU - Gloaguen, Yoann
AU - Bauer, Anna
AU - Opialla, Tobias
AU - Kempa, Stefan
AU - Fleming, Christina A.
AU - Redmond, Henry Paul
AU - Kirwan, Jennifer A.
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/12
Y1 - 2021/12
N2 - Using manual derivatization in gas chromatography-mass spectrometry samples have varying equilibration times before analysis which increases technical variability and limits the number of potential samples analyzed. By contrast, automated derivatization methods can derivatize and inject each sample in an identical manner. We present a fully automated (on-line) derivatization method used for targeted analysis of different matrices. We describe method optimization and compare results from using off-line and on-line derivatization protocols, including the robustness and reproducibility of the methods. Our final parameters for the derivatization process were 20 µL of methoxyamine (MeOx) in pyridine for 60 min at 30◦ C followed by 80 µL N-Methyl-N-trimethylsilyltrifluoracetamide (MSTFA) for 30 min at 30◦ C combined with 4 h of equilibration time. The repeatability test in plasma and liver revealed a median relative standard deviation (RSD) of 16% and 10%, respectively. Serum samples showed a consistent intra-batch median RSD of 20% with an inter-batch variability of 27% across three batches. The direct comparison of on-line versus off-line demonstrated that on-line was fit for purpose and improves repeatability with a measured median RSD of 11% compared to 17% using the same method off-line. In summary, we recommend that optimized on-line methods may improve results for metabolomics and should be used where available.
AB - Using manual derivatization in gas chromatography-mass spectrometry samples have varying equilibration times before analysis which increases technical variability and limits the number of potential samples analyzed. By contrast, automated derivatization methods can derivatize and inject each sample in an identical manner. We present a fully automated (on-line) derivatization method used for targeted analysis of different matrices. We describe method optimization and compare results from using off-line and on-line derivatization protocols, including the robustness and reproducibility of the methods. Our final parameters for the derivatization process were 20 µL of methoxyamine (MeOx) in pyridine for 60 min at 30◦ C followed by 80 µL N-Methyl-N-trimethylsilyltrifluoracetamide (MSTFA) for 30 min at 30◦ C combined with 4 h of equilibration time. The repeatability test in plasma and liver revealed a median relative standard deviation (RSD) of 16% and 10%, respectively. Serum samples showed a consistent intra-batch median RSD of 20% with an inter-batch variability of 27% across three batches. The direct comparison of on-line versus off-line demonstrated that on-line was fit for purpose and improves repeatability with a measured median RSD of 11% compared to 17% using the same method off-line. In summary, we recommend that optimized on-line methods may improve results for metabolomics and should be used where available.
KW - Automated derivatization
KW - Gas-chromatography mass spectrometry
KW - Metabolomics
KW - On-line derivatization
KW - Optimization
KW - Quality assurance (QA)
KW - Quality control (QC)
KW - Validation
UR - https://www.scopus.com/pages/publications/85121681070
U2 - 10.3390/metabo11120888
DO - 10.3390/metabo11120888
M3 - Article
AN - SCOPUS:85121681070
VL - 11
JO - Metabolites
JF - Metabolites
IS - 12
M1 - 888
ER -