Fig. 7: 3kDa filtration in high water content AMW extracts improves metabolite recovery and prevents unwanted protein-mediated effects.
From: A diverse proteome is present and enzymatically active in metabolite extracts
a Heatmap depicting relative abundance of murine liver metabolites across AMW20 ± Filter and AMW50 ± Filter extraction conditions. All significantly different metabolites are shown. Significance was calculated by One-way ANOVA (alpha=0.05, two-sided, F-stat) with Fisher posthoc testing using MetaboAnalyst 5.0, and row hierarchical clustering was performed using Morpheus (Broad; metric = 1 minus Pearson correlation; linkage method = average; cluster = rows). b Relative abundance of Cluster 2-related murine liver metabolites across AMW20 ± Filter and AMW50 ± Filter extraction conditions. Significance calculated by One-way Welch’s ANOVA (t-stat, two-sided) with a Dunnett’s T3 multiple comparisons (mean ± SD, n = 3 technical replicates per group). c Relative abundance of Cluster 3-related murine liver metabolites across AMW20 ± Filter and AMW50 ± Filter extraction conditions. Significance calculated by One-way Welch’s ANOVA (t-stat, two-sided) with a Dunnett’s T3 multiple comparisons (mean ± SD, n = 3 technical replicates per group). d Volcano plot of relative abundance of murine liver metabolites between AMW50 + F and AMW20. All metabolites are shown, metabolites are colored based on cluster and metabolite class, as defined in Fig. 1a. Significance was calculated by t-test with FDR correction (two-tailed, parametric, cutoff = 0.05) using MetaboAnalyst 6.0 (n = 3 technical replicates per group). e Volcano plot of relative abundance of murine liver metabolites between AMW50 + F and AMW50. All metabolites are shown, metabolites are colored based on cluster and metabolite class. Significance was calculated by t-test with FDR correction (two-tailed, parametric, cutoff = 0.05) using MetaboAnalyst 6.0 (n = 3 technical replicates per group).
