Epithelial zonation along the mammalian small intestine defines five discrete metabolic domains [Mouse_bulkRNA-seq]
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE201858 | GEO | 2023/11/28
REPOSITORIES: GEO
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Project description:Liver zonation characterizes the separation of metabolic pathways along the lobules and is required for optimal function. Wnt/beta-catenin signaling controls metabolic zonation by activating genes in the perivenous hepatocytes, while suppressing genes in the periportal counterparts. We now demonstrate that glucagon opposes the actions of Wnt/beta-catenin signaling on gene expression and metabolic zonation pattern. The effects were more pronounced in the periportal hepatocytes where 28% of all genes were activated by glucagon and inhibited by Wnt/beta-catenin. The glucagon and Wnt/beta-catenin receptors and their signaling pathways are uniformly distributed in periportal and perivenous hepatocytes and the expression is not regulated by the opposing signal. Collectively, our results show that glucagon controls gene expression and metabolic zonation in the liver through a counter play with the Wnt/beta-catenin signaling pathway.
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Project description:Liver zonation characterizes the separation of metabolic pathways along the lobules and is required for optimal function. Wnt/beta-catenin signaling controls metabolic zonation by activating genes in the perivenous hepatocytes, while suppressing genes in the periportal counterparts. We now demonstrate that glucagon opposes the actions of Wnt/beta-catenin signaling on gene expression and metabolic zonation pattern. The effects were more pronounced in the periportal hepatocytes where 28% of all genes were activated by glucagon and inhibited by Wnt/beta-catenin. The glucagon and Wnt/beta-catenin receptors and their signaling pathways are uniformly distributed in periportal and perivenous hepatocytes and the expression is not regulated by the opposing signal. Collectively, our results show that glucagon controls gene expression and metabolic zonation in the liver through a counter play with the Wnt/beta-catenin signaling pathway.
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Project description:Small intestinal villi are highly specialized structural and functional units uniquely adapted to the absorption of nutrients in higher vertebrates. Intestinal villus enterocytes are organized in spatially resolved “zones” dedicated to specialized tasks, such as anti-bacterial protection, and absorption of amino-acids, carbohydrates and lipids. However, the molecular mechanisms for the establishment and maintenance of villus intestinal epithelial zonation are incompletely understood. Here, we show that transcription factor C-Maf is highly expressed in mature lower and mid-villus small intestinal enterocytes, where it is induced in response to BMP signaling. In vivo depletion of C-Maf in the adult enterocytes perturbed the villus epithelial zonation transcriptional program and enhanced the expression of genes involved in carbohydrate metabolism and bile acid regulation and transport, while suppressing genes related to amino acid transport and lipid metabolism. Loss of C-Maf under homeostatic conditions had no effect on body weight due to compensatory small intestinal remodeling, accompanied by increased generation of tuft cells and goblet cell hyperplasia. However, upon challenge with anti-metabolite therapy, C-Maf inactivation impaired body weight recovery, resulting in reduced survival, due to delayed enterocyte maturation. Our results identify a novel role for C-Maf in maintaining the zonation program of differentiated intestinal epithelium, by balancing absorptive versus secretory cell differentiation in the small intestine, while highlighting the importance of coordination between stem/progenitor cell and enterocyte differentiation programs for intestinal regeneration.
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Project description:Cell type identity is encoded by gene regulatory networks (GRN), in which transcription factors (TFs) bind to enhancers to regulate target gene expression. In the mammalian liver, lineage TFs have been characterized for the main cell types, including hepatocytes. Hepatocytes cover a relatively broad cellular state space, as they differ significantly in their metabolic state, and function, depending on their position with respect to the central or portal vein in a liver lobule. It is unclear whether this spatially defined cellular state space, called zonation, is also governed by a well-defined gene regulatory code. To address this challenge, we have mapped enhancer-GRNs (eGRNs) across liver cell types at high resolution, using a combination of single-cell multi-omics, spatial omics, GRN inference, and deep learning. We found that zonated variation in gene expression in hepatocytes, liver sinusoidal endothelial cells and hepatocellular stellate cells corroborate cell state changes in transcription and chromatin accessibility with spatial transcriptomics. eGRN mapping suggests that zonation states in hepatocytes are driven by the repressors Tcf7l1 and Tbx3, that modulate the core hepatocyte GRN, controlled by Hnf4a, Cebpa, Hnf1a, Onecut1 and Foxa1, among others. To investigate how these TFs cooperate with cell type TFs, we performed an in vivo Massively Parallel Reporter Assay (MPRA) on 12,000 hepatocyte enhancers and used these data to train a hierarchical deep learning model (called DeepLiver) that exploits both enhancer accessibility and activity. DeepLiver confirms Cebpa, Onecut, Foxa1, Hnf1a and Hnf4a as drivers of enhancer specificity in hepatocytes; Tcf7l1/2 and Tbx3 as regulators of the zonation state; and Hnf4a, Hnf1a, AP-1 and Ets as activators. Finally, taking advantage of in silico mutagenesis predictions from DeepLiver and MPRA, we confirmed that the destruction of Tcf7l1/2 or Tbx3 motifs in zonated enhancers abrogates their zonation bias. Our study provides a multi-modal explanation of the regulatory code underlying hepatocyte identity and their zonation state, that can be exploited to engineer enhancers with desired activity levels and zonation patterns.
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Project description:Cell type identity is encoded by gene regulatory networks (GRN), in which transcription factors (TFs) bind to enhancers to regulate target gene expression. In the mammalian liver, lineage TFs have been characterized for the main cell types, including hepatocytes. Hepatocytes cover a relatively broad cellular state space, as they differ significantly in their metabolic state, and function, depending on their position with respect to the central or portal vein in a liver lobule. It is unclear whether this spatially defined cellular state space, called zonation, is also governed by a well-defined gene regulatory code. To address this challenge, we have mapped enhancer-GRNs (eGRNs) across liver cell types at high resolution, using a combination of single-cell multi-omics, spatial omics, GRN inference, and deep learning. We found that zonated variation in gene expression in hepatocytes, liver sinusoidal endothelial cells and hepatocellular stellate cells corroborate cell state changes in transcription and chromatin accessibility with spatial transcriptomics. eGRN mapping suggests that zonation states in hepatocytes are driven by the repressors Tcf7l1 and Tbx3, that modulate the core hepatocyte GRN, controlled by Hnf4a, Cebpa, Hnf1a, Onecut1 and Foxa1, among others. To investigate how these TFs cooperate with cell type TFs, we performed an in vivo Massively Parallel Reporter Assay (MPRA) on 12,000 hepatocyte enhancers and used these data to train a hierarchical deep learning model (called DeepLiver) that exploits both enhancer accessibility and activity. DeepLiver confirms Cebpa, Onecut, Foxa1, Hnf1a and Hnf4a as drivers of enhancer specificity in hepatocytes; Tcf7l1/2 and Tbx3 as regulators of the zonation state; and Hnf4a, Hnf1a, AP-1 and Ets as activators. Finally, taking advantage of in silico mutagenesis predictions from DeepLiver and MPRA, we confirmed that the destruction of Tcf7l1/2 or Tbx3 motifs in zonated enhancers abrogates their zonation bias. Our study provides a multi-modal explanation of the regulatory code underlying hepatocyte identity and their zonation state, that can be exploited to engineer enhancers with desired activity levels and zonation patterns.
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