Abstract

Poster Presentations

Day 2, June 23（Mon.）　

Room P (Maesato East, Foyer, Ocean Wing)

2P-PM-05（3C-O3-1645）
PDF

A Streamlined Workflow for Rapid and Accurate Identification of Novel Bioavailable Forms of Microbial Metabolites in vivo by LC-Orbitrap-MSn with Smart Searchable Databases

(¹FSN/POLYU, ²RiFood/POLYU, ³RCMI/POLYU, ⁴CEVR)
^oJianing Liu^1,2, Weipeng Li^1,2, Fanghui Deng^1,2, Man-Kin Wong¹, Danyue Zhao^1,2,3,4

Microbial metabolites, such as urolithins produced from dietary ellagitannins and ellagic acid, have gained substantial attention for their health benefits. However, identifying the existing forms of these metabolites in biosamples is challenging due to complex biotransformation, limited reference databases and interfering bio-matrices. In this study, an untargeted metabolomics workflow was developed to detect urolithin-related metabolites in mouse samples using UHPLC-Orbitrap-IQ-X-MSn. Raw data was preprocessed using R packages to extract relevant features, align retention times, and identify MS2 fragments of urolithin metabolites. Mass defect filtering was applied to uncover metabolites that may be masked by matrix effect. A comprehensive database targeting urolithin-related metabolites was developed, including their precursor and product fragment ions for identification. This database is searchable, enabling quick matching of mass spectra data with known urolithin fragment profiles. Furthermore, its integration within R avoids switching between multiple software platforms, streamlining the data analysis process. With in-house database, we identified >50 urolithin-related metabolites, including new phase II conjugates in mouse samples. In summary, the proposed workflow addresses challenges in identifying microbial metabolites. Our approach paves the way for automated metabolite identification and provides a valuable tool to elucidate the active forms of microbial metabolites and their potential health benefits.