Development of Mass Spectrometry-Based SCFA Analysis Methods in Diverse Samples for Microbiome Research.

With the growing interest in the microbiome, short-chain fatty acids (SCFAs) have emerged as key metabolites due to their critical roles in host physiology, including immune regulation, energy homeostasis, and inflammatory control. As a result, the accurate quantification of SCFAs in various biological samples has become increasingly important. However, reliable and standardized methods for measuring SCFAs across different sample types remain underdeveloped, highlighting the need for methodological refinement. To address this need, we optimized two analytical methods, headspace GC-MS and GC-MS/MS, for SCFA quantification. These techniques were applied to a range of biological matrices, including pure microbial cultures, low-abundance animal liver, animal feces, and standardized simulated human fecal samples. The headspace GC-MS approach enables direct analysis with minimal sample preparation, thereby enhancing throughput and ease of use. In contrast, the GC-MS/MS method, involving methanol extraction, alkaline treatment, and derivatization with MTBSTFA, offers superior sensitivity and precision, making it particularly suitable for small-volume and low-abundance samples. Together, these optimized protocols provide robust, sensitive platforms for profiling SCFAs across diverse biological matrices, facilitating a deeper understanding of microbiome-host interactions and supporting future translational applications.