NITCD: A streamlined metabolomics strategy based on bromine isotopes and MS-TDF software

In metabolomics research, derivatization methods, particularly stable isotope derivatization, are commonly employed to enhance the coverage and qualitative and quantitative accuracy of analyte compounds. In our previous work, we adopted a homolog derivatization approach combined with our in-house developed mass spectrometry triple-dimensional derivatization filter (MS-TDF) software to achieve low-cost metabolomics studies. However, differential derivatization efficiencies across homologs led to an increased false positive rate. In this study, we introduce a natural isotope triple-dimensional combinatorial derivatization (NITCD) strategy that overcomes these limitations. The approach employs 4-bromo-2-hydrazinopyridine, which provides a characteristic 1:1 isotopic doublet pattern (⁷⁹Br/⁸¹Br) for intelligent metabolite identification via MS-TDF software. Combined with 2-hydrazinopyridine as a structurally matched internal standard, the system not only reduces false-positive identifications but also enables reliable relative quantification. This strategy was successfully applied to a metabolomics study on rhein treatment in inflammatory bowel disease (IBD). The experimental results demonstrate that, by using NITCD strategy, 564 target compounds can be detected in mouse plasma, with 148 in colon tissue, and 81 in spleen tissue. More importantly, these metabolites were identified, along with their dynamic changes during rhein treatment. It was found that rhein might reverse the IBD-induced alterations in arachidonic acid metabolism, tyrosine metabolism, primary bile acid biosynthesis, and tryptophan metabolism.