Sevoflurane exposure in early life: mitochondrial dysfunction and neurotoxicity in immature rat brains without long-term memory loss

Figures

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  Fig. 1. The diagram illustrating the flow of the study.

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  Fig. 2. Altered metabolites associated with mitochondrial dysfunction in sevoflurane-induced neurotoxicity. (A) Top 30 metabolites with VIP score > 1 identified using OPLS-DA analysis. These metabolites were the most influential in separating the sevoflurane-treated group from controls. (B, C) Heatmap (B) and violin plot (C) showing significant metabolic variations between sevoflurane-treated and control groups. Metabolites with p < 0.05, VIP > 1, and fold change thresholds (> 1.5 or < 0.6) are highlighted. The heatmap represents relative abundances across the sample groups, while the violin plot illustrates the distributions of key metabolites between groups. D IPA network analysis integrating the key metabolites identified in parts A-C with transcriptomic data. The network highlights interactions between these metabolites, genes, and relevant pathways involved in mitochondrial function and neurotoxicity. Nodes represent metabolites or genes, while edges indicate known interactions. The color coding (orange for predicted activation, blue for predicted inhibition) indicates the predicted effects of sevoflurane exposure on these pathways.

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  Fig. 3. RNA sequencing identified sevoflurane induced alterations linked to mitochondrial function, neuronal development and neurotoxicity. (A) GO and KEGG, p. adj < 0.05; (B) GSEA, (C) GSVA, and (D, E) Top 20 canonical pathways analysis by IPA: (D): inhibited pathways (z score ≤ -2); (E): activated pathways (z score ≥ 2).

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  Fig. 4. Identification of sevoflurane exposure-related modules in WGCNA. (A) Gene-to-gene correlation calculations for soft threshold (β) and scale-free fit assessment (R-squared). (B) Cluster dendrogram construction identifying network modules. (C) Heatmap of module eigengenes correlation with different stages.

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  Fig. 5. Integrated RNAseq and metabolomic analysis: joint pathway enrichment analysis on significantly dysregulated metabolites and genes. (A) The overlapping metabolites-genes pathways determined by integrated pathway enrichment analysis in MetaboAnalyst. Symbols ‘(+)’ and ‘(−)’ represent positive and negative ionization modes, respectively. (B) Mapping of dysregulated metabolites and genes in “Pyruvate Metabolism”; red for up-regulation, blue for down-regulation, gray for non-dysregulated or non-detected.

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  Fig. 6. The learning and memory ability in sevoflurane-induced rats using morris water maze test, which includes 20 samples for the sevoflurane exposure group and 20 samples for control group. The tests conducted at two time points: the first at PND60 (1st time point) and the second at PND90 (2nd time point). Two-way repeated measures ANOVA was used for statistical analysis. (A–C) The total swimming distance, average swimming speed, and average escape latency of the first four training days at PND60. (D–F) The total swimming distance, average swimming speed, and average escape latency of the first four training days at PND90. (G) The morris water maze trajectory maps of two groups of rats at PND60 and PND90. (H–J) The distance travelled and time spent in the target quadrant, as well as the number of crossings between the control group and the sevoflurane exposure group at PND60 and PND90. Cont: control group; Sevo: sevoflurane exposure group.

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  Fig. 7. Cartoon illustration summarizing sevoflurane-induced effects. Exposure to sevoflurane induces abnormalities in DNA repair and RNA metabolism in the nuclei of rat hippocampal neurons, along with an increase in mitochondrial oxidative phosphorylation and TCA cycle activity, ultimately leading to neurodevelopmental impairment and neurotoxicity.