Data analysis v3

LC-MS chromatograms were transformed into the netCDF format using the Bruker Daltonics Esquire v5.2 and Data Analysis v3.2 software (Bruker Daltonik GmbH, Bremen, Germany).
The open-source software MZmine v2.2 (http://mzmine.sourceforge.net) was used to extract the data, which was processed by median fold change normalization before log transformation and mean centering. The matrix effect did not substantially affect the relative quantification of secondary metabolites under our analytical conditions (data not shown) as we have previously shown [15 (link)]. In order to further evaluate the performances of HPLC-ESI-MS for relative quantitation, the HPLC-ESI-MS relative quantitation of the more abundant metabolites were compared with those with obtained by HPLC-DAD, which is a quantitative techniques (Additional file 3).
GC-MS chromatograms were analyzed using Agilent C1701 Chemstation software. Peaks were automatically integrated and the results were checked manually. The data representing 63 samples × 48 identified molecules were normalized by internal standard peak areas to avoid differences in detection efficiencies. Monoterpene and sesquiterpene compounds were normalized to the α-copaene peak area, norisoprenoids to the d₃-β-ionone peak area, and remaining compounds to the d₁₃-hexanol peak area. The resulting data set was autoscaled before analysis.

Chromatograms and mass spectra were processed using Data Analysis v3.2 (Bruker, Billerica, United States) and metabolites were identified based on m/z, retention time and MS/MS fragmentation pattern. The chromatograms were converted to netCDf files for peak alignment and area extraction using MZmine.³ The resulting feature matrix was analyzed using SIMCA v13.0 (Umetrics, Umea, Sweden). Pareto scaling was applied to all analytical methods. Unsupervised principal component analysis (PCA) was used to identify the major clusters defined by the samples before supervised orthogonal partial least squares discriminant analysis (OPLS-DA/O2PLS-DA). OPLS-DA/O2PLS-DA models were cross-validated by ANOVA with a threshold of p < 0.01.