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

Area of Science:

• Microbiome research
• Metabolomics
• Analytical chemistry

Background:

• Short-chain fatty acids (SCFAs) are key microbial metabolites influencing host physiology.
• Accurate SCFA quantification is vital for microbiome-host interaction studies.
• Standardized methods for SCFA measurement across various biological matrices are lacking.

Purpose of the Study:

• To optimize and validate two analytical methods for SCFA quantification.
• To assess the applicability of these methods to diverse biological samples.
• To provide robust platforms for SCFA profiling in microbiome research.

Main Methods:

• Optimization of headspace Gas Chromatography-Mass Spectrometry (GC-MS) for direct SCFA analysis.
• Development of Gas Chromatography-tandem Mass Spectrometry (GC-MS/MS) involving extraction, alkaline treatment, and derivatization (MTBSTFA).
• Application of both methods to microbial cultures, animal liver, feces, and simulated human fecal samples.

Main Results:

• Headspace GC-MS offers high throughput with minimal sample preparation.
• GC-MS/MS demonstrates superior sensitivity and precision, ideal for low-abundance samples.
• Both methods provide reliable SCFA quantification across tested biological matrices.

Conclusions:

• Optimized headspace GC-MS and GC-MS/MS protocols offer robust and sensitive SCFA profiling.
• These validated methods support deeper understanding of microbiome-host interactions.
• The developed platforms facilitate future translational applications in SCFA research.