A sensitive GC/MS detection method for analyzing microbial metabolites short chain fatty acids in fecal and serum samples

Publication date: 1 May 2019

Source: Talanta, Volume 196

Author(s): Shuming Zhang, Hongbin Wang, Mei-Jun Zhu

Abstract

Gut microbiota and their major metabolites, short-chain fatty acids (SCFAs), are recognized as important players in gut homeostasis and metabolic disease occurance. A convenient and sensitive detection method is needed to profile SCFAs in limited and complex biological samples. The gas chromatography/mass spectrometry (GC/MS) is the most common method for SCFAs profiling in biological samples. Trimethylsilyl (TMS) derivatization reagents such as N, O-bis(trimethyl-silyl)-trifluoroacetamide (BSTFA) are commonly used in GC/MS analysis to improve sensitivity and accuracy, but they were barely used in SCFA analysis due to their sensitivity to moisture and the volatility of SCFAs. Here, we developed a rapid, convenient and reliable method for SCFAs profiling in small amounts of fecal and serum samples by GC/MS using BSTFA in combination with sodium sulfate dehydration pretreatment. SCFAs were extracted with anhydrous ether from acidified fecal water extract or serum samples, followed by dehydration with sodium sulfate and BSTFA derivatization at a reduced temperature. Select ion monitoring mode was used for highly sensitive quantification of SCFAs by GC/MS. The derivation with BSTFA at 37 °C or 22 °C showed an excellent linearity (R² > 0.999), good recoveries (81.27–128.42%), high repeatability (RSD < 2%) and low limit of detections (LODs) of different SCFAs ranging from 0.064 to 0.067 µM. All major SCFAs including acetic acid, propionic acid, isobutyric acid, butyric acid, isovaleric acid and valeric acid were identified and quantified accurately in fecal and serum samples. In conclusions, a reliable, convenient and sensitive method wasdeveloped for the measurement of SCFA and other volatile compounds in small biological samples using sodium sulfate dehydration pretreatment and BSTFA derivatization-based GC/MS analyses.

Graphical abstract

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