An integrated liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflow combining spectral library matching, MetFrag-based in silico fragmentation, SIRIUS fragmentation tree analysis, manual MS/MS interpretation, and molecular networking annotated 124 metabolites in Nardostachys jatamansi. These platforms provided complementary annotations, revealing a rich chemical diversity that included iridoids, lignans, sesquiterpenoids, monoterpenoids, flavonoids, fatty acids, and phenylpropanoids. ABSTRACT Nardostachys jatamansi is an endangered aromatic plant that produces a chemically complex and diverse array of secondary metabolites. In this study, we aimed to comprehensively characterize the chemical diversity of N. jatamansi by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolite annotation. A metabolite annotation workflow combining feature detection, library matching, MetFrag-based in silico fragmentation, SIRIUS fragmentation tree analysis, manual MS/MS interpretation, molecular networking, chemical classification, and structural validation of selected compounds was applied to methanolic extracts of N. jatamansi. Using this integrated strategy, 111 peaks were structurally annotated, and an additional 13 peaks were assigned to tentative structural level annotations based on MS/MS fragment similarity in a molecular network, giving a total of 124 peaks classified at the chemical structural level. The annotated metabolites mainly comprised iridoids, lignans, sesquiterpenoids, sesquiterpenoid hybrids, monoterpenoids, flavonoids, and other constituents such as fatty acids and phenylpropanoids, revealing the remarkable chemical diversity of N. jatamansi. The annotation performance of each metabolite annotation platform was systematically compared in terms of coverage, efficiency, and chemical class level specificity, revealing that these platforms provided complementary annotations whose combined use with molecular networking greatly enhanced metabolite coverage and structural interpretation. This integrated LC-MS/MS and multi-platform workflow extends current knowledge of the chemical diversity of N. jatamansi.

Lipid identification is a major bottleneck in high-throughput lipidomics studies. However, tools for the analysis of lipid tandem MS spectra are rather limited. While the comparison against spectra in...