Metabolomic data were converted from .d (Bruker, Bremen, Germany) format into .mzdata format. Metabolomic data processing was performed using the XCMS online platform (36) that also performed initial quality controls and multivariate analysis of the data, including principal components analysis, as well as isotope removal and adduct annotation. Primary annotation levels were obtained using the MISA annotation, an in-source fragment annotation algorithm (9). Features were considered for multigroup analysis if q < 0.05 and maximal intensity was larger than 10,000. Metabolites were identified after obtaining MS2 spectra using the following criteria: Accurate masses, authentic standards, and comparison with spectral databases [primarily METLIN (37)] were used to identify compounds. A maximum of 2 ppm (parts per million) of mass error was tolerated. Authentic standard compounds were used for every identified metabolite to determine its identity and to confirm its MS2 spectrum in positive and negative ion mode, as well as its retention time. Data were processed using peak alignment software XCMS online. Hierarchical clustering was performed using Euclidean distance without K-means preprocessing. Chemicals and reagents were obtained from Sigma.

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