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Spatial sorting enables comprehensive characterization of liver zonation
Open accessPublished version of a preprint
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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“Blood flow from the periportal to the perivenous zones along the lobular axis creates spatial gradients of oxygen, metabolites, and nutrients, which benefit hepatocytes and other cells (Tsukada et al., 2013;Ben-Moshe and Itzkovitz, 2019).”
From Fast formation and maturation enhancement of human liver organoids using a liver-organoid-on-a-chip (2024) · cites this paper as Ben-Moshe and Itzkovitz, 2019
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“The liver is a spatially and functionally heterogeneous organ that contains branches of the hepatic portal vein, hepatic artery, and biliary tree across its lobules (Ben-Moshe et al., 2019;Inverso et al., 2021).”
From Fast formation and maturation enhancement of human liver organoids using a liver-organoid-on-a-chip (2024) · cites this paper as Ben-Moshe et al., 2019
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“while it has been previously reported that Tcf7l1 and Tbx3 expression is zonated in the adult mouse liver43,53”
From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [43]
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“In contrast, expression of perivenous markers was significantly elevated close to the outlet where oxygenation is lower.”
From 3D microperfusion of mesoscale human microphysiological liver models improves functionality and recapitulates hepatic zonation (2023) · cites this paper as [33]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“Close to the inlet, where oxygen concentrations are highest, we observed increased levels of the periportal marker proteins ARG1, BAAT, PYGL, FBP1 and ASL ( Fig. 6 a).”
From 3D microperfusion of mesoscale human microphysiological liver models improves functionality and recapitulates hepatic zonation (2023) · cites this paper as [33]
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“Spatial and functional hepatic zonation, established by the heterogeneous tissue along the portal-central axis of the liver, is important for ensuring optimal liver function.”
From Fast formation and maturation enhancement of human liver organoids using a liver-organoid-on-a-chip (2024) · cites this paper as Ben-Moshe and Itzkovitz, 2019
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Enhancer grammar of liver cell types and hepatocyte zonation states
González-Blas, C. B., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2022) · doi:10.1101/2022.12.08.519575 · Cited by 5
Zonated mechanosensing by PIEZO1 controls liver regeneration
Zhang, Y., Sun, Y., Xu, G., Wu, Y., Shi, Z., Chang, Z., Liu, J., Pang, K., Liu, S., Wang, H., et al. (2026) · Science · doi:10.1126/science.aef0825 · Cited by 5
Metadata
- Authors
- Ben-Moshe, S., Shapira, Y., Moor, A. E., Manco, R., Veg, T., Bahar Halpern, K., & Itzkovitz, S.
- Affiliations
- Weizmann Institute of Science (IL)
- University of Zurich (CH)
- Corresponding author
- Itzkovitz, Shalev
- Venue
- Nature Metabolism
- Published
- 2019-09-16
- Volume
- 1
- Issue
- 9
- Pages
- 899-911
- ISSN
- 2522-5812 (ISSN-L)
- PMC
- PMC6751089
- OpenAlex
- W2974173934
- Cited by
- 205
- References
- 82
- Citations by year
- 2026: 31 · 2025: 29 · 2024: 42 · 2023: 31 · 2022: 26 · 2021: 26 · 2020: 16 · 2019: 4
- FWCI
- 5.95
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature Metabolism (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- Digital Access to Libraries (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Funders
- Howard Hughes Medical Institute (55008734)
- Vallee Foundation
- European Commission (2007–2013, FP7 2007-2013, FP7/2007)
- Weizmann Institute of Science
- Israel Science Foundation (FP7/2007-2013, 1486/16, 1796/12)
- Israeli Centers for Research Excellence (1796/12)
- Planning and Budgeting Committee of the Council for Higher Education of Israel
- FP7 Ideas: European Research Council (335122)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Health Sciences › Medicine › Hepatology › Liver physiology and pathology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- liver zonation, lobules, spatial sorting, HNF4α, miR-122, mRNA degradation, Wnt signaling, FZD7, FZD8, TCF7L1
- MeSH terms
- Animals, Humans, Liver, RNA, Messenger, Gene Expression Profiling, Protein Transport, Hepatocytes, MicroRNAs, Single-Cell Analysis
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