Mouse fecal metabolomics raw data from CTRL, PLN, AmLN, and pAmLN

Description

This dataset contains the raw fecal metabolomics data generated from a study investigating the effects of live Akkermansia muciniphila (AKK) and pasteurized Akkermansia muciniphila (pAKK) on a preeclampsia (PE) mouse model induced by N(G)-nitro-L-arginine methyl ester (L-NAME). The metabolomic profiling was conducted to assess the metabolic changes across four experimental groups: CTRL (control group), PLN (PE model group with L-NAME), AmLN (PE model with live AKK treatment), and pAmLN (PE model with pAKK treatment).

Steps to reproduce

1.Animal Model and Grouping: Pregnant C57BL/6J mice (6–8 weeks old) were randomly assigned to four groups: CTRL, PLN, AmLN, and pAmLN. To induce a preeclampsia (PE) model, L-NAME (NG-nitro-L-arginine methyl ester hydrochloride) was administered at 125 mg/kg/day via gavage starting from embryonic day E8.5 for 10 consecutive days. Mice in the CTRL group received only PBS. PLN group mice were treated with L-NAME , while the AmLN and pAmLN groups received L-NAME in combination with either live Akkermansia muciniphila (AKK) or pasteurized AKK (pAKK). 2.Fecal Sample Collection and Preparation: Fecal samples were collected from each mouse group at E18.5, snap-frozen, and stored at -80°C until further analysis. Fecal metabolomics data were generated for all four groups (CTRL, PLN, AmLN, and pAmLN). 3.Metabolite Extraction: Approximately 100 mg of fecal material from each sample was ground in liquid nitrogen. Prechilled 80% methanol was added for extraction, followed by vortexing and centrifugation at 15,000 g for 20 minutes at 4°C. Supernatants were diluted to a final concentration of 53% methanol in LC-MS grade water. These supernatants were subjected to a second centrifugation (15,000 g, 20 minutes, 4°C) before injection into the LC-MS/MS system. 4.UHPLC-MS/MS Analysis: Fecal metabolite profiling was performed using a Vanquish UHPLC system (Thermo Fisher Scientific) coupled with an Orbitrap Q Exactive™ HF mass spectrometer. Samples were injected onto a Hypersil Gold column (100 × 2.1 mm, 1.9 µm), with a 12-minute linear gradient at a flow rate of 0.2 mL/min. Eluents consisted of 0.1% formic acid in water (eluent A) and methanol (eluent B). The mass spectrometer operated in both positive and negative ion modes. A detailed solvent gradient and instrumentation parameters, including ionization conditions, were followed as per the standard operating procedure. 5.Data Processing and Statistical Analysis: Raw LC-MS/MS data were processed using Compound Discoverer 3.3 software to perform peak alignment, detection, and quantification for each metabolite. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were conducted to identify and visualize metabolic differences across the groups. Differential metabolites were identified using univariate analysis (t-test), with a p-value < 0.05 and VIP score > 1. Pathway enrichment analysis was performed using the KEGG database to identify key metabolic pathways affected in the study.

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