B-172 Correlation of Microbiome Sequencing Data and Quantified Short-Chain Fatty Acids by LC-MS/MS in IBD and Non-IBD Stool Samples
Authors: Diesner M , Bock A , Dieterich W , Zopf Y , Armbruster F 
Published: October 2024

Background

SCFAs are the primary metabolites produced by bacterial fermentation of dietary fiber and undigested proteins. They play a crucial role in various metabolic pathways, such as regulating the host’s energy balance and anti-inflammatory processes. The most studied SCFAs are acetic acid, propionic acid and butyric acid, with an approximate molecular ratio of 60:20:20 in healthy adults. A significantly different distribution may indicate a bacterial dysbiosis. While most SCFAs have a positive impact on the host’s health, the impact of branched short-chain fatty acids (bSCFAs), such as isobutyric acid and isovaleric acid, are less well-known. In order to evaluate whether the determination of a broader SCFA panel holds additional diagnostic value, we have developed a sensitive and robust LC-MS/MS method to determine 11 C2 - C7 SCFAs in human fecal samples.

Methods

The LC-MS/MS method includes acetic acid (AA), propionic acid (PA), butyric acid (BA), valeric acid (VA), caproic acid (CA) and heptanoic acid (HA), as well as the isomers isobutyric acid (iBA), 2-methylbutyric acid (2-MBA), isovaleric acid (iVA), isocaproic acid (iCA) and 2-methylhexanoic acid (2-MHA). After suspending the stool samples in a stabilizing buffer, the tubes were centrifuged and 25 µl of the supernatant was mixed with an internal standard solution (10 isotopically labeled internal standards) and subsequently derivatized. After one hour, the reaction was quenched and samples were injected into an ACQUITY UPLC H-Class (Waters) with an injection cycle of 9.5 min. Analytes were measured in positive mode by ESI-MS/MS on a Xevo TQ-MS (Waters). For quantification, six calibrators and three controls covering the anticipated physiological ranges were used.

Results

Microbiome sequencing data identified a total of 193 species, most of which belong to the Firmicutes phylum. Next, Actinobacteria and Proteobacteria are in descending order of abundance. In our IBD samples, we see a significant dysbiosis of these ratios and orders in comparison to the screening patients. E.g. in one sample, no Bacteroidetes were found, but a high amount of Actinobacteria (40 %) were sequenced. Corresponding SCFA data detected an AA:PA:BA ratio of 76:11:10, as well as no VA, iCA, CA, 2-MHA and HA, whereas SCFA data from most screening patients showed an AA:PA:BA ratio of 60:20:20 (± 10:10:10).

Conclusions

After a fast and simple sample preparation and derivatization, the LC MS/MS method allows robust and sensitive measurement of all presented SCFAs from human feces samples. The preliminary analysis of the combined microbiome and SCFA data showed that the detected AA:PA:BA ratio difference could be a valid indicator for a dysbiosis or an altered microbiome, corroborating data from previous studies. While we could detect differences on bSCFAs and longer SCFAs between IBD and non-IBD patient samples in this pilot study, larger patient and control cohorts are needed in order to substantiate our initial promising findings and finally allow a robust evaluation of these parameters as diagnostic tool to monitor and determine the state of the patient microbiome.