ArticleNature metabolism2019
Spatial sorting enables comprehensive characterization of liver zonation.
Article in Nature metabolism, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 127 papers.
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Who cites it
127 citing papers in PubMed.
- Haemodynamic control of zonated liver function via instructive vascular Wnt signalling.Nature communications · 2026Article
- Leveraging IGF signaling to improve the spatial organization and regenerative potential of iPSC-derived vascularized liver organoids.Science advances · 2026Article
- MASLD: Spatial Mechanisms and New Therapeutics.Biomolecules · 2026Review
- Single-cell and spatial omics in liver identify cell-cell communication regulators in aging and insulin resistance.Metabolism: clinical and experimental · 2026Article
- Review
- Dissecting autonomous enzymatic variability in single cells.Nature communications · 2026Article
- Kupffer cells in liver homeostasis and disease: from immune sentinels to metabolic gatekeepers.Nature reviews. Immunology · 2026Review
- Spatial hepatology: Decoding liver zonation for metabolic and regenerative therapeutics (Review).International journal of molecular medicine · 2026Review
- EasySCP unveils extensive liver zonation at single-cell proteomics resolution.Nature communications · 2026Article
- SAA/FPR2 Signaling Between Pericentral Hepatocytes and Macrophages Exacerbates Zonated Liver Transplant Injury.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Joint zonated quantification of multiple parameters in hepatic lobules.Scientific reports · 2026Article
- Article
- Spatial transcriptomics and single-nucleus RNA sequencing reveal rAAV2- and rAAV9-specific transduction signatures in the mouse liver.Gene therapy · 2026Article
- Spatial profiling of gene editing by in situ sequencing in mice and macaques.Nature biomedical engineering · 2026Article
- Scalable discovery of spatial multicellular patterns via neighborhood-to-sequence transformation.Communications biology · 2026Article
- Review
- Single-cell spatial proteomics maps human liver zonation patterns and their vulnerability to disruption in tissue architecture.Nature metabolism · 2026Article
- Single cell multiomic landscape reveals gene programs driving lipid droplet heterogeneity in hepatic steatosis.Scientific reports · 2026Article
- Circadian tryptophan metabolism contributes to systemic aryl hydrocarbon receptor activity.iScience · 2026Article
- Aberrant miR-378 expression promotes hepatic lipid accumulation via hijacking the bile acid-regulated autophagy.Life metabolism · 2026Article
67 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
The mammalian liver is composed of repeating hexagonal units termed lobules. Spatially resolved single-cell transcriptomics revealed that about half of hepatocyte genes are differentially expressed across the lobule, yet technical limitations impeded reconstructing similar global spatial maps of other hepatocyte features. Here, we show how zonated surface markers can be used to sort hepatocytes from defined lobule zones with high spatial resolution. We apply transcriptomics, miRNA array measurements and mass spectrometry proteomics to reconstruct spatial atlases of multiple zonated features. We demonstrate that protein zonation largely overlaps with mRNA zonation, with the periportal HNF4α as an exception. We identify zonation of miRNAs such as miR-122, and inverse zonation of miRNAs and their hepatocyte target genes, highlighting potential regulation of protein levels through zonated mRNA degradation. Among the targets we find the pericentral Wnt receptors Fzd7 and Fzd8 and the periportal Wnt inhibitors Tcf7l1 and Ctnnbip1. Our approach facilitates reconstructing spatial atlases of multiple cellular features in the liver and other structured tissues.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.