Integration of semi-empirical MS/MS library with characteristic features for the annotation of novel amino acid-conjugated bile acids

Abstract

Recently, amino acids other than glycine and taurine were found to be conjugated with bile acids by the gut microbiome in mouse and human. As potential diagnostic markers for inflammatory bowel disease and farnesoid X receptor agonists, their physiological effects and mechanisms, however, remain to be elucidated. A tool for the rapid and comprehensive annotation of such new metabolites is required. Thus, we developed a semi-empirical MS/MS library for bile acids conjugated with 18 common amino acids, including alanine, arginine, asparagine, aspartate, glutamine, glutamate, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine. To investigate their fragmentation rules, these amino acids were chemically conjugated with lithocholic acid, deoxycholic acid, and cholic acid, and their accurate-mass MS/MS spectra were acquired. The common fragmentation patterns from the amino acid moieties were combined with 10 general bile acid skeletons to generate a semi-empirical MS/MS library of 180 structures. Software named BAFinder 2.0 was developed to combine the semi-empirical library in negative mode and the characteristic fragments in positive mode for automatic unknown identification. As a proof of concept, this workflow was applied to the LC-MS/MS analysis of the feces of human, beagle dogs, and rats. In total, 171 common amino acid-conjugated bile acids were annotated and 105 of them were confirmed with the retention times of synthesized compounds. To explore other potential bile acid conjugates, user-defined small molecules were in-silico conjugated with bile acids and searched in the fecal dataset. Four novel bile acid conjugates were discovered, including D-Ala-D-Ala, Lys(iso)-Gly, L-2-aminobutyric acid, and ornithine.