Differential analysis of metabolites in Acorus tatarinowii at different harvesting ages based on widely-targeted metabolomics-raw data

Quality control (QC) samples were prepared by pooling equal volumes of all sample extracts and were used to assess the repeatability and stability of the analytical method. Both QC samples and test samples were analyzed under identical conditions using UPLC-MS/MS.Chromatographic separation was performed on an Agilent SB-C18 column (1.8 μm, 2.1 mm × 100 mm). The mobile phase consisted of 0.1% formic acid in water (solvent A) and 0.1% formic acid in acetonitrile (solvent B).

The gradient elution program was as follows: 0–9 min, 5% B → 95% B; 9–10 min, 95% B; 10–11.1 min, 95% B → 5% B; and 11.1–14 min, 5% B. The flow rate was set to 0.35 mL/min, the column oven temperature was maintained at 40 °C, and the injection volume was 2 μL. For mass spectrometric detection, the electrospray ionization (ESI) source temperature was 500 °C, with ionization voltages of 5,500 V in positive ion mode and −4,500 V in negative ion mode.

The ion source gases (Gas 1, Gas 2) and curtain gas were set to 50, 60, and 25 psi, respectively, and the collision-activated dissociation (CAD) parameter was set to high. Mass spectrometric analysis was carried out on a triple quadrupole mass spectrometer (QQQ) using multiple reaction monitoring (MRM) mode. Nitrogen was used as the collision gas (set to medium).

The declustering potential and collision energy were optimized for each compound, and a specific set of MRM ion pairs was monitored according to the metabolites eluted during each time period.Metabolite identification was performed by matching the acquired MS1 and MS2 spectral data against the in-house MWDB V2.0 database (Metware Biotechnology Co., Ltd.). Quantification of metabolites was achieved using the MRM mode of the QQQ mass spectrometer.

The raw data were processed with MultiQuant software for chromatographic peak detection, integration, and correction. The resulting peak areas were used as the relative abundances of the corresponding metabolites. Subsequent data analysis was conducted using the Metware bioinformatics cloud platform (cloud.metware.cn).