Dataset Information

Liver zonation patterns and cell size variability in isolated human hepatocytes

ABSTRACT: Human hepatocytes differ in gene expression and function across the hexagonal lobules of the tissue microarchitecture, a phenomenon referred to as liver zonation. Hepatocytes also display intra-lobular differences in cell size, but to what extent zonal expression and function correlate with cell size in isolated human hepatocytes is not entirely clear. Here, we first used our accumulated experience of nearly 100 hepatocyte isolations to assess the impact of donor background and process parameters on hepatocyte quality. We observed substantial inter-batch variability in cell size distributions and a tendency for overall cell size to affect the outcome of hepatocyte isolation and cryopreservation. We further separated cells into different size fractions and analyzed them with label-free quantitative proteomics. This showed that protein abundances in different hepatocyte size fractions recapitulated the in vivo expression patterns of well-known zonal markers. We also found that proteins with sequential enrichment across fractions largely represented biological processes with known zonal specificity. This was confirmed by differences in the metabolic activity of zonated CYP enzymes. Altogether, our results show that hepatocyte size corresponds to zonal origin, and that our size fractionation approach can be used to study zone-specific liver functions in vitro.

INSTRUMENT(S):

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Hepatocyte, Liver

SUBMITTER: Christine Wegler

LAB HEAD: Per Artursson

PROVIDER: PXD013142 | Pride | 2021-01-26

REPOSITORIES: Pride

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			Action	DRS
	Christine_TPA_180404_LysC_B2.raw	Raw
	Christine_TPA_180404_LysC_B3.raw	Raw
	Christine_TPA_180404_LysC_B4.raw	Raw
	Christine_TPA_180404_LysC_B5.raw	Raw
	Christine_TPA_180404_LysC_B6.raw	Raw

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Publications

Hepatocyte size fractionation allows dissection of human liver zonation.

Ölander Magnus M Wegler Christine C Flörkemeier Inken I Treyer Andrea A Handin Niklas N Pedersen Jenny M JM Vildhede Anna A Mateus André A LeCluyse Edward L EL Urdzik Jozef J Artursson Per P

Journal of cellular physiology 20210116 8

Human hepatocytes show marked differences in cell size, gene expression, and function throughout the liver lobules, an arrangement termed liver zonation. However, it is not clear if these zonal size differences, and the associated phenotypic differences, are retained in isolated human hepatocytes, the "gold standard" for in vitro studies of human liver function. Here, we therefore explored size differences among isolated human hepatocytes and investigated whether separation by size can be used t ...[more]

PMID: 33452735

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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.