Journal: bioRxiv

Article Title: Metabolomics of Mouse Embryonic CSF Following Maternal Immune Activation

doi: 10.1101/2023.12.06.570507

Figure Lengend Snippet: An approach to generate an embryonic CSF (eCSF) compound database as a tool for future developmental and neurological research. A Schematic depicting experimental workflow for embryonic CSF sample preparation. CSF from embryos (eCSF) from a single pregnant mouse was pooled and 3-7 µl extracted for analysis. Each pregnant mouse was considered a replicate. B Schematic depicting the analytical workflow in generating an eCSF polar compound database. Polar chromatography was performed in HILIC mode (ZIC-HILIC: zwitterionic hydrophilic interaction column) and metabolites were detected using a high-resolution (HiRes) mass spectrometer (Thermo Orbitrap QEactive). Data was processed using two separate approaches depending on compound identification strategy. Contaminants were filtered either based on an extensive set of mock samples or on labeled metabolome correspondence (“IROA” credentialing, see also Fig EV1). Signals (features) passing filtration and quality control were then used to generate compound databases at MS 1 and MS 2 level. C Representative results from untargeted polar metabolomics on eCSF from CD-1 mice (N=7) for mock-filtered dataset outlined in B. Positive- and negative-mode analysis is shown separately. Raw data for polar metabolomics was processed using CompoundDiscoverer (CD) 3.3. Mock and eCSF samples are compared using a volcano plot. Signal was normalized based on targeted analysis of polar metabolites and mean-centering per sample (see methods for details). Metabolites highlighted in orange are >2-fold significantly higher in eCSF than in mock samples. D Representative results from untargeted polar metabolomics on eCSF from CD-1 mice (N=7) for IROA credentialed dataset as outlined in B. Relevant biological features were identified using IROA-“LTRS” – a 1/1 mix of 95:5/5:95 unlabeled ( 12 C) and 13 C-labeled reference yeast metabolome ( 12 C/ 13 C reference, IROA® TruQuant Yeast Extract Semi-targeted QC Workflow). IROA-credentialed features were identified from eCSF ( 12 C, unlabeled) mixed with a reference internal standard (“IS”) that was a mix of 5:95 unlabeled ( 12 C) and 13 C-labeled metabolome. Non- credentialed 12 C signals ( 12 C reference or 12 C eCSF), with no matching IROA 13 C signals, are depicted as indicated on legend. E Strategy for the implementation of the eCSF library into an untargeted analysis workflow combining in-house and online databases at MS 1 and MS 2 levels. Levels of identification certainty (1 through 4) are depicted following recommendations from the metabolomics community. G Breakdown of the composition of the eCSF-specific filtered features from the mock- filtered CD-1 untargeted dataset for which we have obtained MS 2 level information. Negative and positive mode are presented independently. Matches to in-house (House MS 2 DB) and external (mzCloud TM MS 2 ) libraries are depicted. The remaining spectra were manually quality controlled and consolidated into the CD-1 MS 2 database.

Article Snippet: All steps for sample preparation for IROA-assisted metabolomics were identical as described above except for the final resuspension step, which was performed using the IROA provided Internal Standard (IS) (95% 13 C-labeled, IROA® TruQuant Yeast Extract Semi-targeted QC Workflow, IROA Technologies™).

Techniques: Sample Prep, Chromatography, Hydrophilic Interaction Liquid Chromatography, Mass Spectrometry, Labeling, Filtration, Control