Loss of Serpina1 in Mice Leads to Altered Gene Expression in Inflammatory and Metabolic Pathways

Abstract

The SERPINA1 gene encodes alpha1-antitrypsin (AAT), an acute phase glycoprotein and serine protease inhibitor that is mainly (80-90%) produced in the liver. Point mutations in the SERPINA1 gene can lead to the misfolding, intracellular accumulation, and deficiency of circulating AAT protein, increasing the risk of developing chronic liver diseases or chronic obstructive pulmonary disease. Currently, siRNA technology can knock down the SERPINA1 gene and limit defective AAT production. How this latter affects other liver genes is unknown. Livers were taken from age- and sex-matched C57BL/6 wild-type (WT) and Serpina1 knockout mice (KO) aged from 8 to 14 weeks, all lacking the five serpin A1a-e paralogues. Total RNA was isolated and RNA sequencing, and transcriptome analysis was performed. The knockout of the Serpina1 gene in mice changed inflammatory, lipid metabolism, and cholesterol metabolism-related gene expression in the liver. Independent single-cell sequencing data of WT mice verified the involvement of Serpina1 in cholesterol metabolism. Our results from mice livers suggested that designing therapeutic strategies for the knockout of the SERPINA1 gene in humans must account for potential perturbations of key metabolic pathways and consequent mitigation of side effects.

Keywords: RNA sequencing; SERPINA; alpha1-antitrypsin; data analysis; gene knockout; liver; metabolism; mice; protein misfolding; single-cell; transcriptomics.

Figure 1

Differential gene expression (DEGs) and pathway analysis of Serpina1 KO vs. WT. (a) Principal component analysis of samples selected for RNA-Seq data analysis and DEG exploration with WT labeled blue and KO labeled red. (b) Volcano plot of DEGs where x-axis represents the log₂ fold _change and y-axis represents the significance level wherein p-values have been −log₁₀ transformed. Significantly expressed genes are labeled blue (p-value ≤ 0.05), and non-significant genes are labeled in red. (c) A plot showing the KEGG pathways that were identified from DEGs between KO vs. WT mice using EnrichR. X-axis: odds ratio, Y-axis negative Log₁₀ p-value. (d) Gene ontology analysis using EnrichR: x-axis: odds ratio, y-axis negative Log₁₀ p-value. (e) Protein-protein interaction networks as generated with String-Db: Differentially expressed genes were subjected to k-means clustering (n = 6) with high confidence interaction settings.

Figure 2

Differential expression of gene sets in Serpina1 KO vs. WT mice. Volcano plots depict the fold-change (x-axis) and significance (y-axis) for genes associated with: (a) acute phase response (n = 38); (b) complement pathway (n = 187); (c) cholesterol metabolism (n = 47); (d) bile acid metabolic processes (n = 44); and (e) steroid hormone biosynthesis (n = 30). The ten most highly significant DEGs in each pathway are annotated.

Figure 3

scSEQ data analysis of Serpina1 gene expression. (a): Global expression of Serpina1 isoforms: Serpina1 was broadly expressed in the wild-type mice, with two among thirteen clusters that showed a lower expression. (b): Correlation matrix of Serpina1: Top 100 genes with Serpina1 highly correlated are shown in this plot with highly correlated genes in green and anti-correlated genes in red. (c): Pathway enrichment of correlated genes. (d): Expression changes in the KO dataset of the correlated genes (n = 100). The ten most highly significant DEGs are annotated.