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Spatiotemporal liver dynamics shapes hepatocellular heterogeneity and impacts in vivo gene engineering [MERFISH]

ABSTRACT: Hepatocytes are the main liver cells, pivotal for metabolism and relevant in vivo gene therapy targets. While prior research has explored liver homeostasis and regeneration, growth and maturation are not fully elucidated. Here, by single-cell and spatial transcriptomics, and clonal analysis we discovered that a subset of clonogenic hepatocytes (15-20%) in newborns generates >90% of the adult tissue and co-localizes with hematopoietic islands in a spatial niche. Gene editing of these clonogenic hepatocytes resulted in an expansion of the gene-engineered area, a finding supporting their role in liver growth. Age-dependent hepatocellular heterogeneity also influenced the efficiency of lentiviral gene delivery in vivo and its distribution within the liver lobule. Progressive establishment of metabolic zonation post-weaning and high proteasome activity in the peri-central area in adults determined the observed age-related outcomes. These insights into the spatiotemporal hepatocyte dynamics advance our understanding of liver biology and have implications for therapeutic strategies.

ORGANISM(S): Mus musculus synthetic construct

PROVIDER: GSE274042 | GEO | 2025/10/10

REPOSITORIES: GEO

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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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Spatiotemporal liver dynamics shapes hepatocellular heterogeneity and impacts in vivo gene engineering [MERFISH]

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