Research output: Contribution to journal › Article › peer-review
Matrix Effects in GC-MS Profiling of Common Metabolites after Trimethylsilyl Derivatization. / Tarakhovskaya, Elena; Marcillo, Andrea; Davis, Caroline; Milkovska-Stamenova, Sanja; Hutschenreuther, Antje; Birkemeyer, Claudia.
In: Molecules (Basel, Switzerland), Vol. 28, No. 6, 2653, 15.03.2023.Research output: Contribution to journal › Article › peer-review
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TY - JOUR
T1 - Matrix Effects in GC-MS Profiling of Common Metabolites after Trimethylsilyl Derivatization
AU - Tarakhovskaya, Elena
AU - Marcillo, Andrea
AU - Davis, Caroline
AU - Milkovska-Stamenova, Sanja
AU - Hutschenreuther, Antje
AU - Birkemeyer, Claudia
PY - 2023/3/15
Y1 - 2023/3/15
N2 - Metabolite profiling using gas chromatography coupled to mass spectrometry (GC-MS) is one of the most frequently applied and standardized methods in research projects using metabolomics to analyze complex samples. However, more than 20 years after the introduction of non-targeted approaches using GC-MS, there are still unsolved challenges to accurate quantification in such investigations. One particularly difficult aspect in this respect is the occurrence of sample-dependent matrix effects. In this project, we used model compound mixtures of different compositions to simplify the study of the complex interactions between common constituents of biological samples in more detail and subjected those to a frequently applied derivatization protocol for GC-MS analysis, namely trimethylsilylation. We found matrix effects as signal suppression and enhancement of carbohydrates and organic acids not to exceed a factor of ~2, while amino acids can be more affected. Our results suggest that the main reason for our observations may be an incomplete transfer of carbohydrate and organic acid derivatives during the injection process and compound interaction at the start of the separation process. The observed effects were reduced at higher target compound concentrations and by using a more suitable injection-liner geometry.
AB - Metabolite profiling using gas chromatography coupled to mass spectrometry (GC-MS) is one of the most frequently applied and standardized methods in research projects using metabolomics to analyze complex samples. However, more than 20 years after the introduction of non-targeted approaches using GC-MS, there are still unsolved challenges to accurate quantification in such investigations. One particularly difficult aspect in this respect is the occurrence of sample-dependent matrix effects. In this project, we used model compound mixtures of different compositions to simplify the study of the complex interactions between common constituents of biological samples in more detail and subjected those to a frequently applied derivatization protocol for GC-MS analysis, namely trimethylsilylation. We found matrix effects as signal suppression and enhancement of carbohydrates and organic acids not to exceed a factor of ~2, while amino acids can be more affected. Our results suggest that the main reason for our observations may be an incomplete transfer of carbohydrate and organic acid derivatives during the injection process and compound interaction at the start of the separation process. The observed effects were reduced at higher target compound concentrations and by using a more suitable injection-liner geometry.
KW - Gas Chromatography-Mass Spectrometry/methods
KW - Metabolomics/methods
KW - Amino Acids/chemistry
KW - Carbohydrates/chemistry
KW - Trimethylsilyl Compounds/chemistry
KW - compound saturation
KW - quantification
KW - metabolomics
KW - gas chromatography–mass spectrometry
KW - signal suppression
KW - signal enhancement
UR - https://www.mendeley.com/catalogue/279b8cb8-2efe-31cc-8fd9-2e4bed51168f/
U2 - 10.3390/molecules28062653
DO - 10.3390/molecules28062653
M3 - Article
C2 - 36985624
VL - 28
JO - Molecules
JF - Molecules
SN - 1420-3049
IS - 6
M1 - 2653
ER -
ID: 107413421