Experimental hepatic encephalopathy causes early but sustained glial transcriptional changes

Abstract

Hepatic encephalopathy (HE) is a common complication of liver cirrhosis, associated with high morbidity and mortality, for which no brain-targeted therapies exist at present. The interplay between hyperammonemia and inflammation is thought to drive HE development. As such, astrocytes, the most important ammonia-metabolizing cells in the brain, and microglia, the main immunomodulatory cells in the brain, have been heavily implicated in HE development. As insight into cellular perturbations driving brain pathology remains largely elusive, we aimed to investigate cell-type specific transcriptomic changes in the HE brain. In the recently established mouse bile duct ligation (BDL) model of HE, we performed RNA-Seq of sorted astrocytes and microglia at 14 and 28 days after induction. This revealed a marked transcriptional response in both cell types which was most pronounced in microglia. In both cell types, pathways related to inflammation and hypoxia, mechanisms commonly implicated in HE, were enriched. Additionally, astrocytes exhibited increased corticoid receptor and oxidative stress signaling, whereas microglial transcriptome changes were linked to immune cell attraction. Accordingly, both monocytes and neutrophils accumulated in the BDL mouse brain. Time-dependent changes were limited in both cell types, suggesting early establishment of a pathological phenotype. While HE is often considered a unique form of encephalopathy, astrocytic and microglial transcriptomes showed significant overlap with previously established gene expression signatures in other neuroinflammatory diseases like septic encephalopathy and stroke, suggesting common pathophysiological mechanisms. Our dataset identifies key molecular mechanisms involved in preclinical HE and provides a valuable resource for development of novel glial-directed therapeutic strategies.

Fig. 1

Isolation of astrocytes and microglia using FACS yields enriched astrocyte and microglial fractions. A Experimental set-up. B Representative flow cytometry plots indicating gating strategy used to identify microglia and astrocytes in all mice. C Relative abundance of microglia and astrocytes in sham and BDL mouse brains 14 and 28 days after induction. Data are pooled from 2 experiments with n = 12–18. D Heatmap visualizing log₂TPM expression levels of cell-type specific markers of microglia, astrocytes, neurons, oligodendrocytes, oligodendrocyte precursor cells, pericytes and endothelial cells in isolated microglia and astrocytes. Heatmaps represent an average of n = 4–12 samples per group

Fig. 2

Glial cells show a distinct but sustained response after BDL compared to sham controls. A–H Volcano plots and heatmaps showing microglial (A–D) and astrocytic (E–H) gene expression changes 14 days (A, B, E, F) and 28 days (C, D, G, H) after BDL. In volcano plots (A, C, E, G), dotted lines indicate adjusted p-value (y-axis) and log₂FC (x-axis) cut-offs for differential expression (red: DEG; green: failed p-value cut-off; blue: failed |log2FC| cut-off; gray: failed both cut-offs). Selected genes are manually labeled. Heatmaps (B, D, F, H) detail the top 25 DEGs ranked on |log2FC|. I Venn diagram showing overlapping DEGs based on cell type and time after induction

Fig. 3

Validation of gene expression changes in microglia and astrocytes following BDL. A Gene expression of selected genes in isolated microglia in the RNA-Seq experiment (top) and the qPCR validation cohort (bottom). Asterisks denote DE compared to sham controls. B Gene expression of selected genes in isolated astrocytes in the RNA-Seq experiment (top) and the qPCR validation cohort (bottom). *p < 0.05, **p < 0.01, ***p < 0.001, ****p < 0.0001

Fig. 4

Glial gene expression is enriched for inflammatory signaling. A, B, E, F Dot plots featuring the top 10 enriched biological pathways in BDL microglia after (A) 14 or (B) 28 days and astrocytes after (E) 14 and (F) 28 days. Biological pathways are ordered according to the ratio of the input DEG set annotated in the respective GO terms (geneRatio). Dot color corresponds to the adjusted p-value and dot size corresponds to the number of DEGs annotated in the respective GO term. C, D, G, H IPA analysis with identified upstream regulators of microglial signaling 14 (C) and 28 days (D) after BDL induction and of astrocytic signaling 14 (G) and 28 days (H) after BDL induction. Upstream regulators are ranked based on z-score. Bars represent z-score (orange: activation; blue: inhibition) and dots represent − log10 (P-value). Dotted lines indicate the p-value cut-off (p < 0.05) and dashed lines indicate the z-score cut-off (|z-score| > 2)

Fig. 5

Immune phenotyping reveals progressive influx of monocytes and neutrophils in BDL mouse brains. A Representative flow cytometry plots indicating gating strategy used to identify monocytes and neutrophils. B Relative abundance of neutrophils, monocytes, T cells, B cells and DCs in sham/BDL mouse brains 14 and 28 days after induction. Data are derived from a single experiment with n = 6–8/group. Representative images showing C CCR2-positive monocytes, D Ly6G-positive neutrophils and concanavalin A positive blood vessels in cortex and hippocampus of sham and BDL mice, 14 days after surgery. Scale bar represents 20 µm

Fig. 6

Gene set enrichment analysis reveals significant overlap between the glial transcriptome in BDL mice and neuroinflammatory disorders. Comparison of BDL microglia (at A 14 and B 28 days after induction) and astrocytes (at C 14 and D 28 days after induction) with published gene signatures. GSEA plots include the RES, NES, adjusted p-value, placement of the member genes and ranked list metric plot for that full gene distribution