Česká společnost pro hmotnostní spektrometrii

(13. ročník České konference hmotnostní spektrometrie a 11. Neformální proteomické setkání - FrO-18)
Advancing Gut Microbiome Metabolomics: A Derivatization-Based Approach

Tommaso Stefani ^1 *, Anna Michl ², Ondrej Hrebicek ¹, Martin Schwarzer ², Zdeněk Kameník ³

1. Laboratory of Antibiotic Resistance and Microbial Metabolomics, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic
2. Laboratory of Gnotobiology, Institute of Microbiology of the Czech Academy of Sciences, Novy Hradek, Czech Republic
3. Laboratory of Antibiotic Resistance and Microbial Metabolomics, Institute of Microbiology of the CzeLaboratory of Antibiotic Resistance and Microbial Metabolomics, Institute of Microbiology of the Czech Academy of Sciences, Prague, Czech Republic

Abstrakt

Microbiota-associated metabolites play a crucial role in host physiology and disease by mediating host-microbiota communication, providing essential nutrients, and regulating metabolism and immune functions. Understanding these interactions requires comprehensive chemical analysis of the metabolites. However, their low abundance, diverse physicochemical properties, and analysis in complex matrices present significant challenges, leaving us with no universal method to analyze them all. Chemical derivatization is a powerful approach, particularly for polar metabolites. Modifying the analyte structure decreases their polarity and makes them compatible with conventional reverse-phase liquid chromatography.

3-nitrophenylhydrazine (3NPH) is a widely used derivatization agent, which was previously employed in studies targeting well-known microbial metabolites such as Short Chain Fatty Acids (SCFA).[1] However, the potential of its applicability can be extended and go beyond to larger datasets, covering the majority of polar primary metabolites as well as known products of microbial metabolism.

Here, we present a large-scale analysis of nearly 600 gut microbiome-related chemical standards, derivatized using 3NPH. Standards were systematically classified based on structural similarities, biological relevance, and metabolic pathway associations using a Python-based automated categorization pipeline and public metabolomic databases. For streamlined identification, the recently introduced in-silico Derivatization Tool in MetaboScape by Bruker was employed for an automated targeted search.

To validate the applicability of this derivatization strategy, we utilized the library of derivatized standards for the targeted analysis of microbiota-associated metabolites in stool samples from mice with different statuses of microbial colonization, including germ-free models. Our results demonstrate the utility of this approach in providing valuable insights into host-microbiota metabolic interactions.

* Korespondující autor: tommaso.stefani@biomed.cas.cz

Literatura

1. Han J, Lin K, Sequeira C, Borchers CH. An isotope-labeled chemical derivatization method for the quantitation of short-chain fatty acids in human feces by liquid chromatography-tandem mass spectrometry. Anal Chim Acta. 2015 Jan 7;854:86-94.