Postrun analysis

Prior to statistical analysis, mzXML files, which were converted using Shimadzu LabSolutions Postrun Analysis, were imported into Mzmine 2.31⁶³ and processed as previously described^{29 (link)}. The aligned peak list was exported as a comma-separated file for statistical analysis. Statistical analysis was performed using MetaboAnalyst^{64 (link)}, where log transformation and pareto scaling was initially applied to the data. The normalized data were subjected to principal components analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The quality of the models was evaluated with the relevant R² and Q². To identify the difference in intensity of a single mass feature among multiple growth conditions, one-way ANOVA was performed, followed by a post hoc Tukey’s honest significant difference (HSD) test.

MS data, including a deconvolution of mass spectra, data collection, alignment, and normalization, were analyzed using GC-MS and processed using a PostRun analysis (Shimadzu, Tokyo, Japan). Metabolite peaks were deconvoluted and collected using an area threshold of 4000. To normalize all MS data, an internal standard of dicyclohexyl phthalate was used. Identification of metabolites was carried out by comparing their mass spectra and retention indices (RI), which were obtained using a number of n-alkanes (C8–C40) with the Wiley and NIST mass spectral databases, the published RIs, and authentic standards.