Spatial heterogeneity in the mammalian liver
Open accessAbstract
Hepatocytes operate in highly structured repeating anatomical units termed liver lobules. Blood flow along the lobule radial axis creates gradients of oxygen, nutrients and hormones, which, together with morphogenetic fields, give rise to a highly variable microenvironment. In line with this spatial variability, key liver functions are expressed non-uniformly across the lobules, a phenomenon termed zonation. Technologies based on single-cell transcriptomics have constructed a global spatial map of hepatocyte gene expression in mice revealing that ~50% of hepatocyte genes are expressed in a zonated manner. This broad spatial heterogeneity suggests that hepatocytes in different lobule zones might have not only different gene expression profiles but also distinct epigenetic features, regenerative capacities, susceptibilities to damage and other functional aspects. Here, we present genomic approaches for studying liver zonation, describe the principles of liver zonation and discuss the intrinsic and extrinsic factors that dictate zonation patterns. We also explore the challenges and solutions for obtaining zonation maps of liver non-parenchymal cells. These approaches facilitate global characterization of liver function with high spatial resolution along physiological and pathological timescales.
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Hepatocyte function and metabolism varies along the portocentral axis of the liver lobule, a phenomenon known as zonation.
“In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule.”
From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [5]
Blood flow from the portal vein to the central vein in each liver lobule creates a gradient of nutrients, oxygen, hormones and morphogens, resulting in a highly variable environmental axis.
“In each liver lobule, blood flows from the portal vein to the central vein, creating a gradient of nutrients, oxygen, hormones and morphogens that results in a highly variable environmental axis5 (Fig. 1a).”
From Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation (2024) · cites this paper as [5]
During the first 3 weeks of life, the liver transitions from an immature to a mature state as hepatocytes exit the cell cycle, become polyploid, and organize within a zonated lobular structure.
“During this period, the liver transitions from an immature to a mature state as hepatocytes exit the cell cycle, become polyploid, and organize within a zonated lobular structure (Jungermann and Kietzmann 1996; Ben-Moshe and Itzkovitz 2019; Donne et al. 2020).”
From ESRP2–microRNA-122 axis promotes the postnatal onset of liver polyploidization and maturation (2025) · cites this paper as Ben-Moshe and Itzkovitz 2019
Hepatocyte function varies depending on position along the porto-central axis, as hepatocytes are exposed to different microenvironments, a phenomenon known as zonation.
“Hepatocyte function varies depending on the position along this porto-central axis, as they are exposed to different microenvironments, a phenomenon known as zonation7.”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [7]
Periportal hepatocytes are more involved in gluconeogenesis and beta-oxidation, while pericentral hepatocytes are more involved in glycolysis, lipogenesis, and detoxification.
“For example, periportal hepatocytes are more involved in gluconeogenesis and beta-oxidation, while pericentral hepatocytes are more involved in glycolysis, lipogenesis, and detoxification7.”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [7]
The flow along the lobular axis from the portal vein to the central vein creates a gradient of nutrients, oxygen, hormones, and morphogens that results in a highly variable environmental axis.
“The flow along the lobular axis from the portal vein to the central vein, creates a gradient of nutrients, oxygen, hormones, and morphogens that results in a highly variable environmental axis7.”
From Enhancer grammar of liver cell types and hepatocyte zonation states (2022) · cites this paper as [7]
Cites
Spatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · see citing works
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829 · see citing works
Hepatic Stellate Cells: Protean, Multifunctional, and Enigmatic Cells of the Liver
Friedman, S. L. (2008) · Physiological Reviews · doi:10.1152/physrev.00013.2007 · Cited by 2,842 · see citing works
Imaging individual mRNA molecules using multiple singly labeled probes
Raj, A., van den Bogaard, P., Rifkin, S. A., van Oudenaarden, A., & Tyagi, S. (2008) · Nature Methods · doi:10.1038/nmeth.1253 · Cited by 2,028 · see citing works
Godoy, P., Hewitt, N. J., Albrecht, U., Andersen, M. E., Ansari, N., Bhattacharya, S., Bode, J. G., Bolleyn, J., Borner, C., Böttger, J., et al. (2013) · Archives of Toxicology · doi:10.1007/s00204-013-1078-5 · Cited by 1,280 · see citing works
Counting absolute numbers of molecules using unique molecular identifiers
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010 · see citing works
A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility
Cusanovich, D. A., Hill, A. J., Aghamirzaie, D., Daza, R. M., Pliner, H. A., Berletch, J. B., Filippova, G. N., Huang, X., Christiansen, L., DeWitt, W. S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.052 · Cited by 759 · see citing works
Self-renewing diploid Axin2+ cells fuel homeostatic renewal of the liver
Wang, B., Zhao, L., Fish, M., Logan, C. Y., & Nusse, R. (2015) · Nature · doi:10.1038/nature14863 · Cited by 674 · see citing works
Metabolic zonation of the liver: Regulation and implications for liver function
Gebhardt, R. (1992) · Pharmacology & Therapeutics · doi:10.1016/0163-7258(92)90055-5 · Cited by 607 · see citing works
Design and Analysis of Single-Cell Sequencing Experiments
Grün, D., & van Oudenaarden, A. (2015) · Cell · doi:10.1016/j.cell.2015.10.039 · Cited by 536 · see citing works
Bipotential Adult Liver Progenitors Are Derived from Chronically Injured Mature Hepatocytes
Tarlow, B. D., Pelz, C., Naugler, W. E., Wakefield, L., Wilson, E. M., Finegold, M. J., & Grompe, M. (2014) · Cell Stem Cell · doi:10.1016/j.stem.2014.09.008 · Cited by 533 · see citing works
Single-cell epigenomics: Recording the past and predicting the future
Kelsey, G., Stegle, O., & Reik, W. (2017) · Science · doi:10.1126/science.aan6826 · Cited by 415 · see citing works
Nakamura, M., Kondo, H., Mori, T., Komori, A., Matsuyama, M., Ito, M., Takii, Y., Koyabu, M., Yokoyama, T., Migita, K., et al. (2007) · Hepatology · doi:10.1002/hep.21472 · Cited by 365 · see citing works
The RSPO–LGR4/5–ZNRF3/RNF43 module controls liver zonation and size
Planas-Paz, L., Orsini, V., Boulter, L., Calabrese, D., Pikiolek, M., Nigsch, F., Xie, Y., Roma, G., Donovan, A., Marti, P., et al. (2016) · Nature Cell Biology · doi:10.1038/ncb3337 · Cited by 359 · see citing works
Mauvoisin, D., Wang, J., Jouffe, C., Martin, E., Atger, F., Waridel, P., Quadroni, M., Gachon, F., & Naef, F. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1314066111 · Cited by 329 · see citing works
Liver zonation: Novel aspects of its regulation and its impact on homeostasis
Gebhardt, R. (2014) · World Journal of Gastroenterology · doi:10.3748/wjg.v20.i26.8491 · Cited by 275 · see citing works
Differential gene expression in periportal and perivenous mouse hepatocytes
Braeuning, A., Ittrich, C., Köhle, C., Hailfinger, S., Bonin, M., Buchmann, A., & Schwarz, M. (2006) · The FEBS Journal · doi:10.1111/j.1742-4658.2006.05503.x · Cited by 240 · see citing works
Spatial sorting enables comprehensive characterization of liver zonation
Ben-Moshe, S., Shapira, Y., Moor, A. E., Halpern, K. B., & Itzkovitz, S. (2019) · doi:10.1101/529784 · Cited by 205 · see citing works
Self-citationSpatial sorting enables comprehensive characterization of liver zonation
Ben-Moshe, S., Shapira, Y., Moor, A. E., Manco, R., Veg, T., Bahar Halpern, K., & Itzkovitz, S. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0109-9 · Cited by 205 · see citing works
Self-citationPreziosi, M., Okabe, H., Poddar, M., Singh, S., & Monga, S. P. (2018) · Hepatology Communications · doi:10.1002/hep4.1196 · Cited by 135 · see citing works
Glucagon contributes to liver zonation
Cheng, X., Kim, S. Y., Okamoto, H., Xin, Y., Yancopoulos, G. D., Murphy, A. J., & Gromada, J. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1721403115 · Cited by 90 · see citing works
Flagged first, then by citations
Cited by
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Microscopic examination of spatial transcriptome using Seq-Scope
Cho, C.-S., Xi, J., Si, Y., Park, S.-R., Hsu, J.-E., Kim, M., Jun, G., Kang, H. M., & Lee, J. H. (2021) · Cell · doi:10.1016/j.cell.2021.05.010 · Cited by 520 · see citing works
Liver homeostasis is maintained by midlobular zone 2 hepatocytes
Wei, Y., Wang, Y. G., Jia, Y., Li, L., Yoon, J., Zhang, S., Wang, Z., Zhang, Y., Zhu, M., Sharma, T., et al. (2021) · Science · doi:10.1126/science.abb1625 · Cited by 292 · see citing works
Single-cell technologies in hepatology: new insights into liver biology and disease pathogenesis
Ramachandran, P., Matchett, K. P., Dobie, R., Wilson-Kanamori, J. R., & Henderson, N. C. (2020) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-020-0304-x · Cited by 253 · see citing works
The spatiotemporal program of zonal liver regeneration following acute injury
Ben-Moshe, S., Veg, T., Manco, R., Dan, S., Papinutti, D., Lifshitz, A., Kolodziejczyk, A. A., Bahar Halpern, K., Elinav, E., & Itzkovitz, S. (2022) · Cell Stem Cell · doi:10.1016/j.stem.2022.04.008 · Cited by 224 · see citing works
Self-citationSpatial sorting enables comprehensive characterization of liver zonation
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Self-citationSpatial sorting enables comprehensive characterization of liver zonation
Ben-Moshe, S., Shapira, Y., Moor, A. E., Manco, R., Veg, T., Bahar Halpern, K., & Itzkovitz, S. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0109-9 · Cited by 205 · see citing works
Self-citationSpace-time logic of liver gene expression at sub-lobular scale
Droin, C., Kholtei, J. E., Bahar Halpern, K., Hurni, C., Rozenberg, M., Muvkadi, S., Itzkovitz, S., & Naef, F. (2021) · Nature Metabolism · doi:10.1038/s42255-020-00323-1 · Cited by 148 · see citing works
Self-citationMolecular mechanisms in liver repair and regeneration: from physiology to therapeutics
Ma, X., Huang, T., Chen, X., Li, Q., Liao, M., Fu, L., Huang, J., Yuan, K., Wang, Z., & Zeng, Y. (2025) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-02104-8 · Cited by 133 · see citing works
Scalable production of tissue-like vascularized liver organoids from human PSCs
Harrison, S. P., Siller, R., Tanaka, Y., Chollet, M. E., de la Morena-Barrio, M. E., Xiang, Y., Patterson, B., Andersen, E., Bravo-Pérez, C., Kempf, H., et al. (2023) · Experimental & Molecular Medicine · doi:10.1038/s12276-023-01074-1 · Cited by 119 · see citing works
Acute-phase protein synthesis: a key feature of innate immune functions of the liver
Ehlting, C., Wolf, S. D., & Bode, J. G. (2021) · Biological Chemistry · doi:10.1515/hsz-2021-0209 · Cited by 115 · see citing works
Neuregulin 4 suppresses NASH-HCC development by restraining tumor-prone liver microenvironment
Zhang, P., Chen, Z., Kuang, H., Liu, T., Zhu, J., Zhou, L., Wang, Q., Xiong, X., Meng, Z., Qiu, X., et al. (2022) · Cell Metabolism · doi:10.1016/j.cmet.2022.07.010 · Cited by 105 · see citing works
Single-cell and bulk transcriptomics of the liver reveals potential targets of NASH with fibrosis
Wang, Z.-Y., Keogh, A., Waldt, A., Cuttat, R., Neri, M., Zhu, S., Schuierer, S., Ruchti, A., Crochemore, C., Knehr, J., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-98806-y · Cited by 103 · see citing works
Bravo González-Blas, C., Matetovici, I., Hillen, H., Taskiran, I. I., Vandepoel, R., Christiaens, V., Sansores-García, L., Verboven, E., Hulselmans, G., Poovathingal, S., et al. (2024) · Nature Cell Biology · doi:10.1038/s41556-023-01316-4 · Cited by 85 · see citing works
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Gao, J., Lan, T., Kostallari, E., Guo, Y., Lai, E., Guillot, A., Ding, B., Tacke, F., Tang, C., & Shah, V. H. (2024) · Journal of Hepatology · doi:10.1016/j.jhep.2024.05.014 · Cited by 90 · see citing works
Nicheformer: a foundation model for single-cell and spatial omics
Tejada-Lapuerta, A., Schaar, A. C., Gutgesell, R., Palla, G., Halle, L., Minaeva, M., Vornholz, L., Dony, L., Drummer, F., Richter, T., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02814-z · Cited by 100 · see citing works
Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy
Richter, M. L., Deligiannis, I. K., Yin, K., Danese, A., Lleshi, E., Coupland, P., Vallejos, C. A., Matchett, K. P., Henderson, N. C., Colome-Tatche, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-24543-5 · Cited by 75 · see citing works
Multi-zonal liver organoids from human pluripotent stem cells
Reza, H. A., Santangelo, C., Iwasawa, K., Reza, A. A., Sekiya, S., Glaser, K., Bondoc, A., Merola, J., & Takebe, T. (2025) · Nature · doi:10.1038/s41586-025-08850-1 · Cited by 71 · see citing works
A framework for ultra-low-input spatial tissue proteomics
Makhmut, A., Qin, D., Fritzsche, S., Nimo, J., König, J., & Coscia, F. (2023) · Cell Systems · doi:10.1016/j.cels.2023.10.003 · Cited by 67 · see citing works
Guillot, A., Kohlhepp, M., Bruneau, A., Heymann, F., & Tacke, F. (2020) · Cancers · doi:10.3390/cancers12092449 · Cited by 46 · see citing works
Fetal liver development and implications for liver disease pathogenesis
Lotto, J., Stephan, T. L., & Hoodless, P. A. (2023) · Nature Reviews Gastroenterology & Hepatology · doi:10.1038/s41575-023-00775-2 · Cited by 47 · see citing works
Liver macrophages: development, dynamics, and functions
Nusse, Y., & Kubes, P. (2025) · Cellular & Molecular Immunology · doi:10.1038/s41423-025-01298-3 · Cited by 50 · see citing works
Constructing biomimetic liver models through biomaterials and vasculature engineering
Lv, W., Zhou, H., Aazmi, A., Yu, M., Xu, X., Yang, H., Huang, Y. Y. S., & Ma, L. (2022) · Regenerative Biomaterials · doi:10.1093/rb/rbac079 · Cited by 45 · see citing works
Region-specific cellular and molecular basis of liver regeneration after acute pericentral injury.
Wang, S., Wang, X., Shan, Y., Tan, Z., Su, Y., Cao, Y., Wang, S., Dong, J., Gu, J., & Wang, Y. (2024) · Cell Stem Cell · doi:10.1016/j.stem.2024.01.013 · Cited by 40 · see citing works
IL6 supports long-term expansion of hepatocytes in vitro
Guo, R., Jiang, M., Wang, G., Li, B., Jia, X., Ai, Y., Chen, S., Tang, P., Liu, A., Yuan, Q., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35167-8 · Cited by 36 · see citing works
Distinct hepatocyte identities in liver homeostasis and regeneration
Chen, F., Schönberger, K., & Tchorz, J. S. (2023) · JHEP Reports · doi:10.1016/j.jhepr.2023.100779 · Cited by 30 · see citing works
The origin of hepatocellular carcinoma depends on metabolic zonation
Guo, J., Liang, R., Chung, A., Li, Z., Li, B., Chen, E., Li, L., Wang, J., Hsieh, M.-H., Fang, I. X., et al. (2026) · Science · doi:10.1126/science.adv7129 · Cited by 24 · see citing works
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Zhou, Y., Zhao, Y., Carbonaro, M., Chen, H., Germino, M., Adler, C., Ni, M., Zhu, Y. O., Kim, S. Y., Altarejos, J., et al. (2024) · Metabolism · doi:10.1016/j.metabol.2024.155830 · Cited by 24 · see citing works
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Campbell, S. A., Stephan, T. L., Lotto, J., Cullum, R., Drissler, S., & Hoodless, P. A. (2021) · Development · doi:10.1242/dev.199814 · Cited by 22 · see citing works
Chen, X., Zhang, L., Zheng, L., & Tuo, B. (2022) · International Journal of Molecular Medicine · doi:10.3892/ijmm.2022.5169 · Cited by 22 · see citing works
Fast formation and maturation enhancement of human liver organoids using a liver-organoid-on-a-chip
Byeon, J. H., Jung, D. J., Han, H.-J., Son, W.-C., & Jeong, G. S. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1452485 · Cited by 12 · see citing works
Enhancer grammar of liver cell types and hepatocyte zonation states
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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 · see citing works
ESRP2–microRNA-122 axis promotes the postnatal onset of liver polyploidization and maturation
Bangru, S., Chen, J., Baker, N., Das, D., Chembazhi, U. V., Derham, J. M., Chorghade, S., Arif, W., Alencastro, F., Duncan, A. W., et al. (2025) · Genes & Development · doi:10.1101/gad.352129.124 · Cited by 4 · see citing works
Targeting macrophages in liver fibrosis
González del Barrio, L., Ipsen, D. H., Pfister, D. R., Hancz, D., & Scott, C. L. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1835489 · Cited by 3 · see citing works
- Authors
- Ben-Moshe, S., & Itzkovitz, S.
- Affiliations
- Weizmann Institute of Science (IL)
- Corresponding author
- Itzkovitz, Shalev
- ORCID
- Itzkovitz, Shalev
- Venue
- Nature Reviews Gastroenterology & Hepatology
- Published
- 2019-04-01
- Volume
- 16
- Issue
- 7
- Pages
- 395-410
- ISSN
- 1759-5045 (ISSN-L)
- 1759-5053
- OpenAlex
- W2932965638
- Cited by
- 485
- References
- 21
- Citations by year
- 2026: 76 · 2025: 71 · 2024: 82 · 2023: 82 · 2022: 78 · 2021: 50 · 2020: 30 · 2019: 15 · 2016: 1
- FWCI
- 5.68
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Gastroenterology & Hepatology (publishedVersion)
- PubMed (publishedVersion)
- Weizmann Institute of Science Institutional Repository
- Topics
- Health Sciences › Medicine › Hepatology › Liver physiology and pathology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- liver zonation, spatial heterogeneity, liver lobule, hepatocyte gene expression, hepatic microenvironment, morphogenetic fields, non-parenchymal liver cells, liver regeneration, single-cell transcriptomics, epigenetic heterogeneity
- MeSH terms
- Single Molecule Imaging, Animals, Humans, Liver, Genome, Gene Expression Profiling, Hepatocytes, Single-Cell Analysis, Transcriptome
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