Transcriptome analysis of the HepG2 cells expressing hepatic transcription factors
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE115423 | GEO | 2018/10/02
REPOSITORIES: GEO
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Project description:Plasticity of differentiated cells has been proved by nuclear transfer, induced pluripotent cells and transdifferentiation. Here we show that by transduction of 3 factors (FOXA3, HNF1A and HNF4A), human fetal fibroblasts can be converted to hepatocyte-like cells (hiHep cells), expressing hepatic marker genes, and acquiring many mature hepatocyte functions in vitro and in vivo. Human fetal fibroblasts (HFF) were tranfected with 3 liver enriched transcription factors (FOXA3, HNF1A, HNF4A), and converted to hepatocyte-like cells (hiHep cells). HFF and primary human hepatocytes (PHH) serve as control.
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Project description:Here, we chemically induced liver progenitor cells (CLiPs) from mouse hepatocytes using a previously established protocol. To identify central protein kinases (PKs) that potentially promote the maturation of lpc-Hep cells, we profiled the transcriptomes and phosphoproteomes of freshly isolated primary mouse hepatocytes (MHs) and ALBUMIN+ hepatocytes (CLiP-Heps) cells. Based on the algorithm developed by us and experiment verification, we validated three PKs that promote mouse hepatocyte maturation. Then, we use RNA sequencing technology to identify potential regulators during hepatic reprogramming with samples from HDFs 2.25 days (FHH-2.25d) and 5 days (FHH-5d) after FOXA3, HNF1A, and HNF4A (FHH) transduction, as well as HDFs transduced with GFP for 2.25 days (GFP) as the control group. After combined analysis with phosphoproteomic data with the algorithm and experiment verification, we identified 2 PKs that may be involved in hepatic reprogramming regulation. One of the five potential regulator candidates is PIM1, which can promote the progress remarkably with overexpression. Therefore, we next perform another RNA-seq to drive the molecular mechanisms under undergoing the regulation by PIM1. Finally, we revealed that cell cycle and ferroptosis pathways are involved in the regulation via PIM1.
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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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