Metabolomics Data Supplementary to: Time-Resolved Multi-Omics Identify Biomarkers of Immediate Reactions to mRNA Vaccination

Metabolite Sample PreparationFor all liquid chromatography mass spectrometry (LCMS) methods LCMS grade solvents were used. Tributylamine and all synthetic molecular references were purchased from Millipore Sigma. LCMS grade water, methanol, isopropanol and acetic acid were purchased through Fisher Scientific. Plasma sample aliquots, each 0.4 mL, were combined with 0.4 mL of methanol and 0.4 mL of chloroform. Samples were shaken for 30 minutes under refrigeration and centrifuged at 16k xg for 20 min. The aqueous (top) layer was diluted 5x in 50 % methanol in water for LCMS analysis of central polar metabolites and oxidized lipid mediators.Liquid Chromatography Mass SpectrometryAqueous metabolites were analyzed using a combination of two analytical methods with opposing ionization polarities (McCloskey)(Groveman). Both methodologies utilized a LD40 XR UHPLC (Shimadzu Co.) system for separation and a 6500+ QTrap mass spectrometer (AB Sciex Pte. Ltd.) for detection. Negative mode samples were separated on a Waters™ Atlantis T3 column (100Å, 3 µm, 3 mm X 100 mm) and eluted using a binary gradient from 5 mM tributylamine, 5 mM acetic acid in 2% isopropanol, 5% methanol, 93% water (v/v) to 100% isopropanol over 13 minutes. Two distinct MRM pairs in negative mode were used for each metabolite. Positive mode method samples were separated across a Phenomenex Kinetex F5 column (100 Å, 2.6 µm, 100 x 2.1 mm) and eluted with a gradient from 0.1 % formic acid in water to 0.1 % formic acid in acetonitrile over 5 minutes. Histamine metabolite targets were added to the positive polarity method based on signals established in previous publications.Metabolomics data processing and bioinformaticsAll signals were integrated using SciexOS 3.1 (AB Sciex Pte. Ltd.). Signals with greater than 50% missing values for a specific tissue set were discarded and remaining missing values were replaced with the lowest registered signal value. Where appropriate, signals with a QC coefficient of variance greater than 30 % were discarded. Metabolites with multiple MRMs were quantified with the higher signal to noise MRM. Filtered datasets of the negative mode aqueous metabolites were total sum normalized after initial filtering. The metabolomics data provided in this submission are the total sum normalized values.