Isoniazid derivatization strategy of carboxyl-containing metabolites for LC-MS/MS-based targeted metabolomics

Metabolomics is a biochemical analysis tool for identifying metabolic phenotypes and used to reveal the pathogenic mechanisms of disease and to inform drug-targeted therapies. Carboxyl-containing metabolites (CCMs) account for an important proportion of the metabolome, but because of the diversity of physical and chemical properties of CCMs in biological samples, traditional liquid chromatography-mass spectrometry (LC-MS) targeted metabolome analysis methods cannot achieve simultaneous quantification of multiple types of CCMs. Therefore, we proposed for the first time a targeted metabolomics strategy using isoniazid derivatization combined with LC-MS/MS to simultaneously quantify 39 CCMs of 5 different types (short-chain fatty acids, amino acids, bile acids, phenylalanine and tryptophan metabolic pathway acids) with large polarity differences associated with Alzheimer's disease (AD) and significantly improve the detection coverage and sensitivity. The yields of isoniazid derivative CCMs were high and could guarantee the accuracy of CCM quantification. The LODs of CCMs increased significantly (1.25-2000-fold) after derivatization. The method showed good selectivity, intra-day and inter-day accuracies and precisions, and repeatability. There was no significant effect on the determination of CCMs in terms of matrix effect and recovery. CCMs showed good stability. And CCMs showed good stability under short-term storage and freeze-thaw cycles. At the same time, the regulatory effects of Schisandrae chinensis Fructus and Ginseng Radix et Rhizoma (SG) herb pair on CCM metabolic disorders in feces, urine, serum, and the brain of AD rats were elucidated from the perspective of targeted metabolomics. In combination with pharmacodynamic evaluation and gut microbiota analysis, the mechanism of SG herb pair on AD rats was comprehensively understood. In summary, this innovative isoniazid derivatization combined with a targeted metabolomics method has great potential for trace biological lineage analysis.