Establishment of a novel large-scale targeted metabolomics method based on NFSWI-DDA mode utilizing HRMS and TQ-MS.

Metabolites identification is the major bottleneck in untargeted LC-MS metabolomics, primarily due to the limited availability of MS information for most detected metabolites in data dependent acquisition (DDA) mode. To solve this problem, we have integrated the iterative, interval, and segmented window acquisition concepts to develop an innovative non-fixed segmented window interval data dependency acquisition (NFSWI-DDA) mode, which achieves comparable MS coverage to data independent acquisition (DIA) mode. This acquisition strategy harnesses the strengths of both DDA and DIA, which could provide extensive coverage and excellent reproducibility of MS spectra. Furthermore, utilizing the NFSWI-DDA data, we successfully acquired and identified a large-scale of multiple reaction monitoring (MRM) ion pairs, and transitioned them from high-resolution mass spectrometry (HRMS) to triple quadrupole mass spectrometry (TQ-MS). At last, a large-scale targeted metabolomics method was established practically. This method enables targeted analysis of 475 endogenous metabolites encompassing amino acids, nucleotides, bile acids, fatty acids, and carnitines, which could cover 9 major metabolic pathways as well as 65 secondary metabolic pathways. The established targeted method allows for semi-quantitative assessment of 475 metabolites while enabling quantitative analysis of 327 specific metabolites in biological samples. The method demonstrates immense potential in the detection of various biological samples, offering robust technical support and generating extensive data to advance applications in precision medicine and life sciences.