Ms dial

Data pre-processing and processing relied on the Automated Mass Spectral Deconvolution and Identification System v.2.66 (www.amdis.net, accessed on 10 March 2023), Xcalibur v.2.0.7 and LCquan v.2.5.6 (Thermo Fisher Scientific), MSDial v.3.12 (prime.psc.riken.jp/Metabolomics_Software/MS-DIAL/, accessed on 10 March 2023). For interpretation of the LC-MS data LabSolution (Shimadzu, Kyoto, Japan) and MSDial (prime.psc.riken.jp/compms/MSDial/, accessed on 10 March 2023) were used. Metabolite identification relied on a broad panel of available spectral libraries: National Institute of Standards and Technology (NIST), Golm Metabolome Database (GMD), Human Metabolome Database (HMDB), MS/MS and electron ionization (EI)-MS spectra curated by RIKEN Center for Sustainable Resource Science (prime.psc.riken.jp/Metabolomics Software/MS-DIAL/, accessed on 10 March 2023), and an in-house library (partially with Kovats retention time indices, calculated by the retention times of alkane standards). The post-processing and statistical interpretation of the acquired data relied on MetaboAnalyst 5.0 (www.metaboanalyst.ca, accessed on 10 March 2023) [94 (link)].

GC-MS/MS analysis was performed as previously described [49 (link)], using a GCMS-TQ8050 (Shimadzu Corporation, Kyoto, Japan). A 30 m × 0.25 mm (internal diameter) BPX-5 column (SGE, Melbourne, Australia) with a 0.25 µm film thickness was used, according to the method described in the Smart Metabolites Database (Shimadzu, Kyoto, Japan).
Data processing was performed using the Smart Metabolites Database (Shimadzu, Kyoto, Japan), MS-DIAL version 3.08 [50 (link)], and the MRMPROBS program version 2.42 [51 (link)]. Peaks were recorded for the 45−600 m/z mass range, and were automatically detected via MS-DIAL using the peak detection option of a minimum peak height of 2000. A data quality check was conducted using the thresholds of −10 < RI < 10, dot production > 0.8, and presence > 0.6, and the remaining data was then manually checked. Ultimately, 172 metabolites were identified in the plasma samples. The relative quantities of the metabolites were calculated using the peak areas of each metabolite relative to that of the internal standard (2-isopropylmalic acid), and expressed as a percentage of an arbitrary control set to 100%.

To explain how foliar infection of P. notoginseng changes plant metabolism, the aboveground parts and fibrous roots of uninoculated and inoculated plants were analyzed by gas chromatography-mass spectrometry (GC-MS). Derivatization of the sample was performed according to a previous method (90 (link)), and 80 μL of the supernatant transferred to vials was detected by GC-MS (91 (link)). Briefly, detection was performed using a gas chromatograph-mass spectrometer (GCMS-QP2010 Ultra, Shimadzu, Japan) with an SH-Rxi-5Sil MS column (30.0 m by 0.25 mm by 0.25 μm). An Abf Converter, MS-DIAL (92 (link)), Shimadzu offline software, and the NIST 14 library were used for peak identification and related data generation. Data were normalized on MetaboAnalyst 4.0 (93 (link)). SIMCA-P 14.1 (Umetrics, Umea, Sweden) was used for orthogonal projection to latent structures-discriminant analysis (OPLS-DA). The differential metabolites were screened based on their variable importance in the projection (VIP) and P value (VIP >1; P < 0.05).