A single-nucleus transcriptomic atlas of primate liver aging uncovers the pro-senescence role of SREBP2 in hepatocytes

Abstract

Aging increases the risk of liver diseases and systemic susceptibility to aging-related diseases. However, cell type-specific changes and the underlying mechanism of liver aging in higher vertebrates remain incompletely characterized. Here, we constructed the first single-nucleus transcriptomic landscape of primate liver aging, in which we resolved cell type-specific gene expression fluctuation in hepatocytes across three liver zonations and detected aberrant cell-cell interactions between hepatocytes and niche cells. Upon in-depth dissection of this rich dataset, we identified impaired lipid metabolism and upregulation of chronic inflammation-related genes prominently associated with declined liver functions during aging. In particular, hyperactivated sterol regulatory element-binding protein (SREBP) signaling was a hallmark of the aged liver, and consequently, forced activation of SREBP2 in human primary hepatocytes recapitulated in vivo aging phenotypes, manifesting as impaired detoxification and accelerated cellular senescence. This study expands our knowledge of primate liver aging and informs the development of diagnostics and therapeutic interventions for liver aging and associated diseases.

Keywords: SREBP2; aging; hepatocytes; liver; senescence; single-nucleus RNA sequencing.

Figure 1.

Histological features of liver aging in cynomolgus monkeys. (A) Schematic diagram illustrating sample collection, data analyses and validation. “Young” denotes cynomolgus monkeys 4–6 years old; “Aged” denotes cynomolgus monkeys 18–21 years old. Created with BioRender.com. (B) HE staining in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the area of inflammatory focus are shown on the right. Scale bars, 25 μm. (C) Masson’s trichrome staining in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the positive area of fibrosis are shown on the right. Scale bars, 25 μm. (D) Sudan Black B staining in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the positive area of the Sudan Black B are shown on the right. Scale bars, 25 μm. (E) Immunohistochemistry staining of P21 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of P21-positive cells are shown on the right. Scale bars, 25 μm. (F) Immunofluorescence staining of SPiDER-βGal in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of SPiDER-βGal-positive cells are shown on the right. Scale bars, 20 μm. (G) Immunofluorescence staining of H3K9me3 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the mean fluorescence intensity of H3K9me3 are shown on the right. Scale bars, 20 μm. (H) Immunofluorescence staining of TNFα in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of TNFα-positive cells are shown on the right. Scale bars, 20 μm. (I) Immunofluorescence staining of IL6 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of IL6-positive cells are shown on the right. Scale bars, 20 μm. (I) Immunofluorescence staining of IL1β in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of IL1β-positive cells are shown on the right. Scale bars, 20 μm. (B–J) Data are quantified as fold changes and shown as means ± SEM. Young, n = 8 monkeys; aged, n = 8 monkeys. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

Figure 2.

Transcriptomic features of liver aging in cynomolgus monkeys. (A) Volcano plot shows differentially expressed genes (DEGs) of bulk RNA-seq between aged and young livers (aged/young). Red points represent upregulated DEGs; blue points represent downregulated DEGs; gray points represent unchanged genes. (B) Representative GO terms and pathways of upregulated and downregulated DEGs in aged and young monkey livers. (C) Oil red O staining in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the positive area of the oil red O staining are shown on the right. Scale bars, 25 μm. (D) Immunohistochemistry staining of S100A8 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of S100A8-positive cells are shown on the right. Scale bars, 25 μm. (E) Immunohistochemistry staining of S100A9 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of S100A9-positive cells are shown on the right. Scale bars, 25 μm. (F) Immunohistochemistry staining of MPO in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of MPO-positive cells are shown on the right. Scale bars, 25 μm. (G) Immunofluorescence staining of CD68 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of CD68-positive cells are shown on the right. Scale bars, 20 μm. (H) Immunofluorescence staining of CD45 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of CD45-positive cells are shown on the right. Scale bars, 20 μm. (I) Immunofluorescence staining of MMP9 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of MMP9-positive cells are shown on the right. Scale bars, 20 μm. (J) TUNEL staining in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of TUNEL-positive cells are shown on the right. Scale bars, 20 μm. (C–J) Data are quantified as fold changes and shown as means ± SEM. Young, n = 8 monkeys; aged, n = 8 monkeys. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001.

Figure 3.

Single-nucleus transcriptomics identifies major cell types in cynomolgus monkey livers. (A) UMAP plot showing the distribution of different cell types in liver from young and aged monkeys. (B) Feature plots showing the expression profiles of indicated cell-type-specific marker genes in monkey liver. The color key from gray to red indicates low to high gene expression levels. (C) Dot plot showing the expression level of representative marker genes across cell types. The color key from gray to red presents low to high gene expression levels. The size of dots indicates the percentage of cells with gene expression greater than zero. (D) Heatmap showing the expression profiles of the top 50 cell-type-specific marker genes for each cell type in monkey livers, with corresponding functional annotations on the right. The color key from blue to red represents low to high gene expression levels. (E) Sankey plots showing the cell number of each cell type and the proportion in young and aged monkey livers. The length of the bar indicates the cell number of each cell type, and the number was marked above the pie plot. The pie chart at bottom showing the ratios of each cell type in young and aged monkey livers. (F) Immunofluorescence staining of CD163 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of CD163-positive cells are shown on the right. Scale bars, 20 μm. (G) Immunofluorescence staining of CD247 in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of CD247-positive cells are shown on the right. Scale bars, 20 μm. (H) Immunofluorescence staining of CD79B in liver tissues from young and aged monkeys. Representative images are shown on the left; quantitative data for the percentage of CD79B-positive cells are shown on the right. Scale bars, 20 μm. (I) Dot plot showing the log₂ ratio of transcriptional noise between aged and young samples. The color key from gray to red corresponds to Log₁₀ (adjusted P value) of transcriptional noise ratio from low to high. The size of dots indicates the number of genes with aging-related transcriptional noise. (J) Heatmap showing the row scaled expression levels of genes with high Pearson’s correlation coefficients (correlation coefficient > 0.6 and FDR < 0.05) between transcriptional noise and expression profiles in hepatocytes from young and aged monkeys. The bins are arranged based on the transcriptional noise ranking in each group. (K) Bar chart showing the enriched GO terms and pathways of genes with increased transcriptional noise during aging in hepatocytes. (F–H) Data are quantified as fold changes and shown as means ± SEM. Young, n = 8 monkeys; aged, n = 8 monkeys. ^*P < 0.05.

Figure 4.

Characterization of cell-type-specific transcriptomic changes in liver aging. (A) Circos plots showing aging-related upregulated and downregulated DEGs (adjusted P value ≤ 0.05, |Log₂FC | ≥ 0.25) in different cell types from monkey livers. Each connecting curve represents an upregulated or downregulated DEG shared by two cell types. (B) Network visualizing representative GO terms and pathways of aging-related upregulated (left) and downregulated (right) DEGs in each cell type of monkey liver during aging. The nodes representing GO terms or pathways, the pie plots showing the proportion of gene number that hit the certain GO term or pathway across cell types. Any two nodes with similarity score > 0.3 are connected by a line. (C) Radial plots showing upregulated (left) and downregulated (right) DEGs shared by at least three cell types. (D) Network visualizing the aging-related upregulated (left) and downregulated (right) core regulatory transcription factors (TFs) of each cell type. The hexagon nodes and the circle nodes represent cell types and TFs, respectively. Color keys from light to dark indicate the frequency of TFs from low to high. The pie charts in the middle represent TFs that are both upregulated and downregulated in different cell types. (E) Network showing the changes in ligand–receptor interaction events between different cell types in the aged/young comparison group. Cell–cell communication is indicated by the connected line. The thickness of the lines is positively correlated with the number of ligand–receptor interaction events. Red and blue lines represent increased and decreased interaction events between different cell types. (F) Network visualizing the overlap between aging-related DEGs and liver disease-related genes. The hexagon nodes and the circle nodes represent the types and genes of liver disease database, respectively. The size of gene nodes indicates the frequency of occurrences in liver disease database. The pie-donut charts show the number ratio of aging-associated upregulated (red) and downregulated (blue) genes across cell types. Genes in Aging Atlas database are marked with gray background. (G) Ring heatmap showing the co-upregulated and co-downregulated genes between snRNA-seq and aging-related human plasma proteome dataset. The circles represent the aging-related proteins and the size of circles shows the coefficient of aging-related proteins. The colors of circle (red and blue) represent positive and negative correlation with aging, respectively. The color key of heatmap from blue to red indicates the Log₂FC of DEGs in snRNA-seq from low to high.

Figure 5.

Zonation-specific transcriptional alterations in aged cynomolgus monkey livers. (A) Arc plot showing prioritization of the cell types responsive to aging. (B) Schematic diagram showing the structure and functions of liver lobules. (C) tSNE plot showing the distribution of hepatocyte subtypes (left) and the expression levels for cell-type-specific marker genes of each subtype (right). The color key from gray to blue indicates low to high gene expression levels. (D) Violin plots showing the score of gene sets related to zonation-specific functions across three hepatocyte subtypes. (E) Heatmap (left) showing the aging-related DEGs across three hepatocyte subtypes. DEGs are classified into 14 modules according to the overlap among three subtypes. Heatmap (right) showing the GO terms and pathways of modules. (F) Network visualizing aging-related upregulated and downregulated core regulatory TFs (nodes) and their target genes (points) among three hepatocyte subtypes, with TFs arranging in the middle and target genes arranging on the outer ring. The size of the node indicates the number of target genes regulated by the TFs. The colors of node represent the average Log₂FC of TFs during aging in different hepatocyte subtypes. Red and blue points represent upregulated and downregulated target genes during aging respectively. The pie-donut chart shows the number ratio of target genes regulated by the TFs across allhepatocyte subtypes. (G) Network visualizing the enriched GO terms and pathways of upregulated SREBP2 target genes among three hepatocyte subtypes. The nodes representing GO terms and pathways, the pie plots showing the proportion of gene number that hit the certain term or pathway across three hepatocyte subtypes. Any two terms with similarity score > 0.3 are connected by a line.

Figure 6.

SREBP2 mediates senescence and metabolic dysfunction in hepatocytes. (A) RT-qPCR analysis of SREBP2 mRNA level in liver tissues from young and aged monkeys. (B) RT-qPCR analysis for mRNA levels of classical target genes of SREBP2 in liver tissues from young and aged monkeys. (C) Western blot for protein level of SREBP2 (N) in liver tissues from young and aged monkeys. SREBP2 (P), precursor SREBP2 protein; SREBP2 (N), nuclear SREBP2 protein. Representative images are shown on the left; quantitative data for the SREBP2 (N) protein level are shown on the right. (D) SA-β-gal staining was performed on human primary hepatocytes cultured in vitro on Day 1 and Day 15 respectively. Representative images are shown on the left; quantitative data for the percentage of SA-β-gal positive cells are shown on the right. Scale bars, 100 μm. (E) RT-qPCR analysis of SREBP2 mRNA level in human primary hepatocytes cultured in vitro on Day 1 and Day 15, respectively. (F) Schematic of experiments in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or luciferase (Luc, used as control). Created with BioRender.com. (G) RT-qPCR analysis of SREBP2 mRNA level in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or Luc. (H) Western blot for protein level of SREBP2 (N) in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or Luc. SREBP2 (P), precursor SREBP2 protein; SREBP2 (N), nuclear SREBP2 protein. Representative images are shown on the left; quantitative data for the protein level of SREBP2 (N) are shown on the right. (I) SA-β-gal staining in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or Luc. Representative images are shown on the left; quantitative data for the percentage of SA-β-gal-positive cells are shown on the right. Scale bars, 100 μm. (J) RT-qPCR analysis for mRNA levels of liver function-related genes in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or Luc. (K) Western blot of CYP1A2 protein level in human primary hepatocytes transduced with lentiviruses expressing SREBP2 or Luc. Representative images are shown on the left; quantitative data for the protein level of CYP1A2 are shown on the right. (L) Schematic diagram showing the signatures of primate liver aging. Created with BioRender.com. Data are quantified as fold changes (excluding D and I) and shown as means ± SEM. For (A–C), young, n = 8 monkeys; aged, n = 8 monkeys. For (D, E and G–K), n = 3 biological replicates. ^*P < 0.05, ^**P < 0.01, ^***P < 0.001