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Spatial heterogeneity in the mammalian liver

Abstract

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.

Key points

  • Hepatocytes residing along the lobule porto-central axis are exposed to different microenvironments, resulting in spatial zonation of liver tasks.

  • Single-cell technologies have enabled the reconstruction of zonation patterns for the global hepatocyte transcriptome, revealing principles of liver tissue organization.

  • Examples of optimal features of hepatocyte zonation include the assignment of energetically demanding tasks to highly oxygenated zones, spatial recycling of material and production line patterns.

  • Sequencing pairs of hepatocytes and adjacent non-parenchymal cells enables reconstruction of global zonation patterns of other liver cell types.

  • Liver zonation can give rise to zonated patterns of liver pathologies.

  • Zonation of gene expression is a prominent feature in other metabolic organs such as the intestine and the kidney.

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Fig. 1: Division of labour in the liver lobule.
Fig. 2: Zonation profiles of landmark genes using single-molecule fluorescence in situ hybridization.
Fig. 3: Single-cell spatial reconstruction of hepatocyte transcriptomes using landmark genes.
Fig. 4: Principles of hepatocyte zonation.
Fig. 5: Paired-cell RNA sequencing to infer liver endothelial cell zonation.
Fig. 6: Spatial heterogeneity in other metabolic tissues.

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References

  1. Jungermann, K. Dynamics of zonal hepatocyte heterogeneity. Perinatal development and adaptive alterations during regeneration after partial hepatectomy, starvation and diabetes. Acta Histochem. Suppl. 32, 89–98 (1986).

    CAS  PubMed  Google Scholar 

  2. Gebhardt, R. Metabolic zonation of the liver: regulation and implications for liver function. Pharmacol. Ther. 53, 275–354 (1992).

    CAS  PubMed  Google Scholar 

  3. Godoy, P. et al. Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Arch. Toxicol. 87, 1315–1530 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Hoehme, S. et al. Prediction and validation of cell alignment along microvessels as order principle to restore tissue architecture in liver regeneration. Proc. Natl Acad. Sci. USA 107, 10371–10376 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Teutsch, H. F. The modular microarchitecture of human liver. Hepatology 42, 317–325 (2005).

    PubMed  Google Scholar 

  6. Torre, C., Perret, C. & Colnot, S. Molecular determinants of liver zonation. Prog. Mol. Biol. Transl Sci. 97, 127–150 (2010).

    CAS  PubMed  Google Scholar 

  7. Israel, Y. & Orrego, H. Hypermetabolic state and hypoxic liver damage. Recent Dev. Alcohol. 2, 119–133 (1984).

    CAS  PubMed  Google Scholar 

  8. Kietzmann, T., Dimova, E. Y., Flügel, D. & Scharf, J.-G. Oxygen: modulator of physiological and pathophysiological processes in the liver. Z. Gastroenterol. 44, 67–76 (2006).

    CAS  PubMed  Google Scholar 

  9. de Groot, H., Littauer, A. & Noll, T. in Oxygen Sensing in Tissues (ed. Acker, H.) 49–64 (Springer-Verlag Berlin Heidelberg, 1988).

  10. Arteel, G. E., Iimuro, Y., Yin, M., Raleigh, J. A. & Thurman, R. G. Chronic enteral ethanol treatment causes hypoxia in rat liver tissue in vivo. Hepatology 25, 920–926 (1997).

    CAS  PubMed  Google Scholar 

  11. Matsumura, T. & Thurman, R. G. Measuring rates of O2 uptake in periportal and pericentral regions of liver lobule: stop-flow experiments with perfused liver. Am. J. Physiol. 244, G656–G659 (1983).

    CAS  PubMed  Google Scholar 

  12. Jungermann, K. & Keitzmann, T. Zonation of parenchymal and nonparenchymal metabolism in liver. Annu. Rev. Nutr. 16, 179–203 (1996).

    CAS  PubMed  Google Scholar 

  13. Jungermann, K. & Katz, N. Functional hepatocellular heterogeneity. Hepatology 2, 385S–395S (1982).

    Google Scholar 

  14. Gebhardt, R. & Matz-Soja, M. Liver zonation: novel aspects of its regulation and its impact on homeostasis. World J. Gastroenterol. 20, 8491–8504 (2014).

    PubMed  PubMed Central  Google Scholar 

  15. Colnot, S. & Perret, C. in Molecular Pathology of Liver Diseases (ed. Monga, S. P. S.) 7–16 (Springer US, 2011).

  16. Kater, J. M. Comparative and experimental studies on the cytology of the liver. Z. Für Zellforsch. Mikrosk. Anat. 17, 217–246 (1933).

    Google Scholar 

  17. Deane, H. W. A cytological study of the diurnal cycle of the liver of the mouse in relation to storage and secretion. Anat. Rec. 88, 39–65 (1944).

    CAS  Google Scholar 

  18. Chiquoine, A. D. The distribution of glucose-6-phosphatase in the liver and kidney of the mouse. J. Histochem. Cytochem. 1, 429–435 (1953).

    CAS  PubMed  Google Scholar 

  19. Jungermann, K. & Katz, N. Functional specialization of different hepatocyte populations. Physiol. Rev. 69, 708–764 (1989).

    CAS  PubMed  Google Scholar 

  20. Jungermann, K., Heilbronn, R., Katz, N. & Sasse, D. The glucose/glucose-6-phosphate cycle in the periportal and perivenous zone of rat liver. Eur. J. Biochem. 123, 429–436 (1982).

    CAS  PubMed  Google Scholar 

  21. Andersen, B., Zierz, S. & Jungermann, K. Alteration in zonation of succinate dehydrogenase, phosphoenolpyruvate carboxykinase and glucose-6-phosphatase in regenerating rat liver. Histochemistry 80, 97–101 (1984).

    CAS  PubMed  Google Scholar 

  22. Nauck, M., Wölfle, D., Katz, N. & Jungermann, K. Modulation of the glucagon-dependent induction of phosphoenolpyruvate carboxykinase and tyrosine aminotransferase by arterial and venous oxygen concentrations in hepatocyte cultures. Eur. J. Biochem. 119, 657–661 (1981).

    CAS  PubMed  Google Scholar 

  23. Sasse, D., Katz, N. & Jungermann, K. Functional heterogeneity of rat liver parenchyma and of isolated hepatocytes. FEBS Lett. 57, 83–88 (1975).

    CAS  PubMed  Google Scholar 

  24. Feldmann, G., Scoazec, J. Y., Racine, L. & Bernuau, D. Functional hepatocellular heterogeneity for the production of plasma proteins. Enzyme 46, 139–154 (1992).

    CAS  PubMed  Google Scholar 

  25. Quistorff, B., Grunnet, N. & Cornell, N. W. Digitonin perfusion of rat liver. A new approach in the study of intra-acinar and intracellular compartmentation in the liver. Biochem. J. 226, 289–297 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Quistorff, B. & Grunnet, N. Dual-digitonin-pulse perfusion. Concurrent sampling of periportal and perivenous cytosol of rat liver for determination of metabolites and enzyme activities. Biochem. J. 243, 87–95 (1987).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Gebhardt, R. in Cytochrome P450 Protocols (eds Phillips, I. R. & Shephard, E. A.) 319–328 (Humana Press, 1998).

  28. Lindros, K. O. & Penttilä, K. E. Digitonin-collagenase perfusion for efficient separation of periportal or perivenous hepatocytes. Biochem. J. 228, 757–760 (1985).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Racine, L. et al. Distribution of albumin, α1-inhibitor 3 and their respective mRNAs in periportal and perivenous rat hepatocytes isolated by the digitonin-collagenase technique. Biochem. J. 305, 263–268 (1995).

    PubMed  PubMed Central  Google Scholar 

  30. Braeuning, A. et al. Differential gene expression in periportal and perivenous mouse hepatocytes. FEBS J. 273, 5051–5061 (2006).

    CAS  PubMed  Google Scholar 

  31. Saito, K., Negishi, M. & Squires, E. J. Sexual dimorphisms in zonal gene expression in mouse liver. Biochem. Biophys. Res. Commun. 436, 730–735 (2013).

    CAS  PubMed  Google Scholar 

  32. Hashimshony, T., Wagner, F., Sher, N. & Yanai, I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2, 666–673 (2012).

    CAS  PubMed  Google Scholar 

  33. Jaitin, D. A. et al. Massively parallel single cell RNA-Seq for marker-free decomposition of tissues into cell types. Science 343, 776 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Zeisel, A. et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).

    CAS  PubMed  Google Scholar 

  35. Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Kolodziejczyk, A. A., Kim, J. K., Svensson, V., Marioni, J. C. & Teichmann, S. A. The technology and biology of single-cell RNA sequencing. Mol. Cell 58, 610–620 (2015).

    CAS  PubMed  Google Scholar 

  38. Fu, G. K., Hu, J., Wang, P.-H. & Fodor, S. P. A. Counting individual DNA molecules by the stochastic attachment of diverse labels. Proc. Natl Acad. Sci. USA 108, 9026–9031 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Kivioja, T. et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72 (2012).

    CAS  Google Scholar 

  40. Casbon, J. A., Osborne, R. J., Brenner, S. & Lichtenstein, C. P. A method for counting PCR template molecules with application to next-generation sequencing. Nucleic Acids Res. 39, e81 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Shiroguchi, K., Jia, T. Z., Sims, P. A. & Xie, X. S. Digital RNA sequencing minimizes sequence-dependent bias and amplification noise with optimized single-molecule barcodes. Proc. Natl Acad. Sci. USA 109, 1347–1352 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Islam, S. et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 21, 1160–1167 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Marinov, G. K. et al. From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing. Genome Res. 24, 496–510 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Achim, K. et al. High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nat. Biotechnol. 33, 503–509 (2015).

    CAS  PubMed  Google Scholar 

  46. Itzkovitz, S. & van Oudenaarden, A. Validating transcripts with probes and imaging technology. Nat. Methods 8, S12 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. Raj, A., van den Bogaard, P., Rifkin, S. A., van Oudenaarden, A. & Tyagi, S. Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 5, 877 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. Bahar Halpern, K. et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 542, 352–356 (2017).

    Google Scholar 

  49. Stouthamer, A. H. A theoretical study on the amount of ATP required for synthesis of microbial cell material. Antonie Van Leeuwenhoek 39, 545–565 (1973).

    CAS  PubMed  Google Scholar 

  50. Rolfe, D. F. & Brown, G. C. Cellular energy utilization and molecular origin of standard metabolic rate in mammals. Physiol. Rev. 77, 731–758 (1997).

    CAS  PubMed  Google Scholar 

  51. Bahar Halpern, K. et al. Bursty gene expression in the intact mammalian liver. Mol. Cell 58, 147–156 (2015).

    CAS  PubMed  Google Scholar 

  52. Rappaport, A. M., Borowy, Z. J., Lougheed, W. M. & Lotto, W. N. Subdivision of hexagonal liver lobules into a structural and functional unit. Role in hepatic physiology and pathology. Anat. Rec. 119, 11–33 (1954).

    CAS  PubMed  Google Scholar 

  53. Truksa, J., Lee, P. & Beutler, E. The role of STAT, AP-1, E-box and TIEG motifs in the regulation of hepcidin by IL-6 and BMP-9: lessons from human HAMP and murine Hamp1 and Hamp2 gene promoters. Blood Cells Mol. Dis. 39, 255–262 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. de Aguiar Vallim, T. Q., Tarling, E. J. & Edwards, P. A. Pleiotropic roles of bile acids in metabolism. Cell Metab. 17, 657–669 (2013).

    PubMed  PubMed Central  Google Scholar 

  55. Russell, D. W. The enzymes, regulation, and genetics of bile acid synthesis. Annu. Rev. Biochem. 72, 137–174 (2003).

    CAS  PubMed  Google Scholar 

  56. Dawson, P. A. in Physiology of the Gastrointestinal Tract (ed. Said, H.) 6th edn 931–956 (Academic Press, 2018).

  57. Berndt, N., Horger, M. S., Bulik, S. & Holzhütter, H.-G. A multiscale modelling approach to assess the impact of metabolic zonation and microperfusion on the hepatic carbohydrate metabolism. PLOS Comput. Biol. 14, e1006005 (2018).

    PubMed  PubMed Central  Google Scholar 

  58. Katz, N., Teutsch, H. F., Jungermann, K. & Sasse, D. Heterogeneous reciprocal localization of fructose-1,6-bis-phosphatase and of glucokinase in microdissected periportal and perivenous rat liver tissue. FEBS Lett. 83, 272–276 (1977).

    CAS  PubMed  Google Scholar 

  59. Häussinger, D. Hepatocyte heterogeneity in glutamine and ammonia metabolism and the role of an intercellular glutamine cycle during ureogenesis in perfused rat liver. Eur. J. Biochem. 133, 269–275 (1983).

    PubMed  Google Scholar 

  60. Haüssinger, D. Nitrogen metabolism in liver: structural and functional organization and physiological relevance. Biochem. J. 267, 281 (1990).

    PubMed  PubMed Central  Google Scholar 

  61. Gebhardt, R. & Mecke, D. Heterogeneous distribution of glutamine synthetase among rat liver parenchymal cells in situ and in primary culture. EMBO J. 2, 567–570 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Schliess, F. et al. Integrated metabolic spatial-temporal model for the prediction of ammonia detoxification during liver damage and regeneration. Hepatology 60, 2040–2051 (2014).

    CAS  PubMed  Google Scholar 

  63. Bartl, M. et al. Optimality in the zonation of ammonia detoxification in rodent liver. Arch. Toxicol. 89, 2069–2078 (2015).

    CAS  PubMed  Google Scholar 

  64. Häussinger, D. Glutamine metabolism in the liver: overview and current concepts. Metabolism 38, 14–17 (1989).

    PubMed  Google Scholar 

  65. Schleicher, J. et al. Zonation of hepatic fatty acid metabolism — the diversity of its regulation and the benefit of modeling. Biochim. Biophys. Acta 1851, 641–656 (2015).

    CAS  PubMed  Google Scholar 

  66. Bar-Even, A. et al. The moderately efficient enzyme: evolutionary and physicochemical trends shaping enzyme parameters. Biochemistry 50, 4402–4410 (2011).

    CAS  PubMed  Google Scholar 

  67. Liemburg-Apers, D. C. et al. Quantitative glucose and ATP sensing in mammalian cells. Pharm. Res. 28, 2745–2757 (2011).

    CAS  PubMed  Google Scholar 

  68. Hakvoort, T. B. M. et al. Pivotal role of glutamine synthetase in ammonia detoxification. Hepatology 65, 281–293 (2017).

    CAS  PubMed  Google Scholar 

  69. Augustin, H. G. & Koh, G. Y. Organotypic vasculature: from descriptive heterogeneity to functional pathophysiology. Science 357, eaal2379 (2017).

    PubMed  Google Scholar 

  70. Aird, W. C. Phenotypic heterogeneity of the endothelium: II. Representative vascular beds. Circ. Res. 100, 174–190 (2007).

    CAS  PubMed  Google Scholar 

  71. Strauss, O., Phillips, A., Ruggiero, K., Bartlett, A. & Dunbar, P. R. Immunofluorescence identifies distinct subsets of endothelial cells in the human liver. Sci. Rep. 7, 44356 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  72. Rafii, S., Butler, J. M. & Ding, B.-S. Angiocrine functions of organ-specific endothelial cells. Nature 529, 316 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  73. Wang, B., Zhao, L., Fish, M., Logan, C. Y. & Nusse, R. Self-renewing diploid Axin2+ cells fuel homeostatic renewal of the liver. Nature 524, 180–185 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Carmon, K. S., Gong, X., Lin, Q., Thomas, A. & Liu, Q. R-Spondins function as ligands of the orphan receptors LGR4 and LGR5 to regulate Wnt/β-catenin signaling. Proc. Natl Acad. Sci. USA 108, 11452–11457 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. Planas-Paz, L. et al. The RSPO–LGR4/5–ZNRF3/RNF43 module controls liver zonation and size. Nat. Cell Biol. 18, 467 (2016).

    CAS  PubMed  Google Scholar 

  76. Halpern, K. et al. Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells. Nat. Biotechnol. 36, 962–970 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Bykov, I., Ylipaasto, P., Eerola, L. & Lindros, K. O. Functional differences between periportal and perivenous kupffer cells isolated by digitonin-collagenase perfusion. Comp. Hepatol. 3, S34 (2004).

    PubMed  PubMed Central  Google Scholar 

  78. Friedman, S. L. Hepatic stellate cells: protean, multifunctional, and enigmatic cells of the liver. Physiol. Rev. 88, 125–172 (2008).

    CAS  PubMed  Google Scholar 

  79. Friedman, S. L. Molecular regulation of hepatic fibrosis, an integrated cellular response to tissue injury. J. Biol. Chem. 275, 2247–2250 (2000).

    CAS  PubMed  Google Scholar 

  80. Preziosi, M., Okabe, H., Poddar, M., Singh, S. & Monga, S. P. Endothelial Wnts regulate β-catenin signaling in murine liver zonation and regeneration: a sequel to the Wnt–Wnt situation. Hepatol. Commun. 2, 845 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Burke, Z. D. & Tosh, D. The Wnt/β-catenin pathway: master regulator of liver zonation? Bioessays 28, 1072–1077 (2006).

    CAS  PubMed  Google Scholar 

  82. Thompson, M. D. & Monga, S. P. S. WNT/β-catenin signaling in liver health and disease. Hepatology 45, 1298–1305 (2007).

    CAS  PubMed  Google Scholar 

  83. Benhamouche, S. et al. Apc tumor suppressor gene is the ‘zonation-keeper’ of mouse liver. Dev. Cell 10, 759–770 (2006).

    CAS  PubMed  Google Scholar 

  84. Sekine, S., Lan, B. Y.-A., Bedolli, M., Feng, S. & Hebrok, M. Liver-specific loss of β-catenin blocks glutamine synthesis pathway activity and cytochrome p450 expression in mice. Hepatology 43, 817–825 (2006).

    CAS  PubMed  Google Scholar 

  85. Rocha, A. S. et al. The angiocrine factor Rspondin3 is a key determinant of liver zonation. Cell Rep. 13, 1757–1764 (2015).

    CAS  PubMed  Google Scholar 

  86. Matz-Soja, M. et al. Hedgehog signaling is a potent regulator of liver lipid metabolism and reveals a GLI-code associated with steatosis. eLife 5, e13308 (2016).

    PubMed  PubMed Central  Google Scholar 

  87. Wölfle, D., Schmidt, H. & Jungermann, K. Short-term modulation of glycogen metabolism, glycolysis and gluconeogenesis by physiological oxygen concentrations in hepatocyte cultures. Eur. J. Biochem. 135, 405–412 (2005).

    Google Scholar 

  88. Jungermann, K. & Kietzmann, T. Role of oxygen in the zonation of carbohydrate metabolism and gene expression in liver. Kidney Int. 51, 402–412 (1997).

    CAS  PubMed  Google Scholar 

  89. Kietzmann, T. Metabolic zonation of the liver: the oxygen gradient revisited. Redox Biol. 11, 622–630 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Kaidi, A., Williams, A. C. & Paraskeva, C. Interaction between β-catenin and HIF-1 promotes cellular adaptation to hypoxia. Nat. Cell Biol. 9, 210 (2007).

    CAS  PubMed  Google Scholar 

  91. Lehwald, N. et al. Wnt–β-catenin signaling protects against hepatic ischemia and reperfusion injury in mice. Gastroenterology 141, 707–718 (2011).

    CAS  PubMed  Google Scholar 

  92. Cheng, X. et al. Glucagon contributes to liver zonation. Proc. Natl Acad. Sci. USA 115, E4111–E4119 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  93. Waxman, D. J. & Chang, T. K. H. in Cytochrome P450: Structure, Mechanism, and Biology (ed. Ortiz de Montellano, P. R.) 2nd edn 391–417 (Springer US, 1995).

  94. Oinonen, T. & Lindros, K. O. Zonation of hepatic cytochrome P-450 expression and regulation. Biochem. J. 329, 17–35 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. Bird, A. DNA methylation patterns and epigenetic memory. Genes Dev. 16, 6–21 (2002).

    CAS  PubMed  Google Scholar 

  96. Kaplan, S., Bren, A., Zaslaver, A., Dekel, E. & Alon, U. Diverse two-dimensional input functions control bacterial sugar genes. Mol. Cell 29, 786–792 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  97. Brosch, M. et al. Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control. Nat. Commun. 9, 4150 (2018).

    PubMed  PubMed Central  Google Scholar 

  98. Tujios, S. & Fontana, R. J. Mechanisms of drug-induced liver injury: from bedside to bench. Nat. Rev. Gastroenterol. Hepatol. 8, 202 (2011).

    CAS  PubMed  Google Scholar 

  99. Nelson, S. D. Molecular mechanisms of the hepatotoxicity caused by acetaminophen. Semin. Liver Dis. 10, 267–278 (1990).

    CAS  PubMed  Google Scholar 

  100. Makin, A. J., Wendon, J. & Williams, R. A. 7-year experience of severe acetaminophen-induced hepatotoxicity (1987–1993). Gastroenterology 109, 1907–1916 (1995).

    CAS  PubMed  Google Scholar 

  101. Anundi, I., Lähteenmäki, T., Rundgren, M., Moldeus, P. & Lindros, K. O. Zonation of acetaminophen metabolism and cytochrome P450 2E1-mediated toxicity studied in isolated periportal and perivenous hepatocytes. Biochem. Pharmacol. 45, 1251–1259 (1993).

    CAS  PubMed  Google Scholar 

  102. Ganey, P. E., Kauffman, F. C. & Thurman, R. G. Oxygen-dependent hepatotoxicity due to doxorubicin: role of reducing equivalent supply in perfused rat liver. Mol. Pharmacol. 34, 695–701 (1988).

    CAS  PubMed  Google Scholar 

  103. Badger, D. A., Sauer, J. M., Hoglen, N. C., Jolley, C. S. & Sipes, I. G. The role of inflammatory cells and cytochrome P450 in the potentiation of CCl4-induced liver injury by a single dose of retinol. Toxicol. Appl. Pharmacol. 141, 507–519 (1996).

    CAS  PubMed  Google Scholar 

  104. Keegan, A., Martini, R. & Batey, R. Ethanol-related liver injury in the rat: a model of steatosis, inflammation and pericentral fibrosis. J. Hepatol. 23, 591–600 (1995).

    CAS  PubMed  Google Scholar 

  105. Zieve, L., Anderson, W. R. & Dozeman, R. Hepatic regenerative enzyme activity after diffuse injury with galactosamine: relationship to histologic alterations. J. Lab. Clin. Med. 112, 575–582 (1988).

    CAS  PubMed  Google Scholar 

  106. Reid, W. D. Mechanism of allyl alcohol-induced hepatic necrosis. Experientia 28, 1058–1061 (1972).

    CAS  PubMed  Google Scholar 

  107. Brunt, E. M. Pathology of fatty liver disease. Mod. Pathol. 20, S40 (2007).

    CAS  PubMed  Google Scholar 

  108. Iseri, O. A., Lieber, C. S. & Gottlieb, L. S. The ultrastructure of fatty liver induced by prolonged ethanol ingestion. Am. J. Pathol. 48, 535–555 (1966).

    CAS  PubMed  PubMed Central  Google Scholar 

  109. Farrell, G. C., Teoh, N. C. & Mccuskey, R. S. Hepatic microcirculation in fatty liver disease. Anat. Rec. 291, 684–692 (2008).

    Google Scholar 

  110. Chalasani, N. et al. Relationship of steatosis grade and zonal location to histological features of steatohepatitis in adult patients with non-alcoholic fatty liver disease. J. Hepatol. 48, 829 (2008).

    PubMed  PubMed Central  Google Scholar 

  111. Schwen, L. O. et al. Zonated quantification of steatosis in an entire mouse liver. Comput. Biol. Med. 73, 108–118 (2016).

    PubMed  Google Scholar 

  112. Hijmans, B. S., Grefhorst, A., Oosterveer, M. H. & Groen, A. K. Zonation of glucose and fatty acid metabolism in the liver: mechanism and metabolic consequences. Biochimie 96, 121–129 (2014).

    CAS  PubMed  Google Scholar 

  113. Prudêncio, M., Rodriguez, A. & Mota, M. M. The silent path to thousands of merozoites: the Plasmodium liver stage. Nat. Rev. Microbiol. 4, 849 (2006).

    PubMed  Google Scholar 

  114. Ng, S. et al. Hypoxia promotes liver stage malaria infection in primary human hepatocytes in vitro. Dis. Model. Mech. 7, 215–224 (2013).

    PubMed  PubMed Central  Google Scholar 

  115. Seeger, C. & Mason, W. S. Hepatitis B virus biology. Microbiol. Mol. Biol. Rev. 64, 51–68 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. Chisari, F. V. Unscrambling hepatitis C virus–host interactions. Nature 436, 930–932 (2005).

    CAS  PubMed  Google Scholar 

  117. Bedossa, P., Dargère, D. & Paradis, V. Sampling variability of liver fibrosis in chronic hepatitis C. Hepatology 38, 1449–1457 (2003).

    PubMed  Google Scholar 

  118. Diamantis, I. & Boumpas, D. T. Autoimmune hepatitis: evolving concepts. Autoimmun. Rev. 3, 207–214 (2004).

    CAS  PubMed  Google Scholar 

  119. Lohse, A. W., Manns, M., Dienes, H.-P., Büschenfelde, K.-H. M. Z. & Cohen, I. R. Experimental autoimmune hepatitis: disease induction, time course and T-cell reactivity. Hepatology 11, 24–30 (2005).

    Google Scholar 

  120. Lettmann, K. A. & Hardtke-Wolenski, M. The importance of liver microcirculation in promoting autoimmune hepatitis via maintaining an inflammatory cytokine milieu – a mathematical model study. J. Theor. Biol. 348, 33–46 (2014).

    CAS  PubMed  Google Scholar 

  121. Nakamura, M. et al. Anti-gp210 and anti-centromere antibodies are different risk factors for the progression of primary biliary cirrhosis. Hepatology 45, 118–127 (2007).

    CAS  PubMed  Google Scholar 

  122. Selmi, C., Coppel, R. L. & Gershwin, M. E. in The Autoimmune Diseases (eds Mackay, I. R. & Rose, N. R.) 4th edn 749–765 (Academic Press, 2006).

  123. Llovet, J. M. et al. Hepatocellular carcinoma. Nat. Rev. Dis. Primers 2, 16018 (2016).

    PubMed  Google Scholar 

  124. Nault, J. C. et al. High frequency of telomerase reverse-transcriptase promoter somatic mutations in hepatocellular carcinoma and preneoplastic lesions. Nat. Commun. 4, 2218 (2013).

    PubMed  Google Scholar 

  125. Zucman-Rossi, J., Villanueva, A., Nault, J. C. & Llovet, J. M. Genetic landscape and biomarkers of hepatocellular carcinoma. Gastroenterology 149, 1226–1239 (2015).

    CAS  PubMed  Google Scholar 

  126. Sia, D., Villanueva, A., Friedman, S. L. & Llovet, J. M. Liver cancer cell of origin, molecular class, and effects on patient prognosis. Gastroenterology 152, 745–761 (2017).

    CAS  PubMed  Google Scholar 

  127. Vaupel, P., Kallinowski, F. & Okunieff, P. Blood flow, oxygen and nutrient supply, and metabolic microenvironment of human tumors: a review. Cancer Res. 49, 6449–6465 (1989).

    CAS  PubMed  Google Scholar 

  128. Adler, M., Kohanim, Y. K., Tendler, A., Mayo, A. & Alon, U. Continuum of gene-expression profiles provides spatial division of labor within a differentiated cell type. Cell Syst. 8, 43–52 (2019).

    CAS  PubMed  Google Scholar 

  129. Celton-Morizur, S. & Desdouets, C. Polyploidization of liver cells. Adv. Exp. Med. Biol. 676, 123–135 (2010).

    CAS  PubMed  Google Scholar 

  130. Duncan, A. W. Aneuploidy, polyploidy and ploidy reversal in the liver. Semin. Cell Dev. Biol. 24, 347–356 (2013).

    PubMed  Google Scholar 

  131. Tanami, S. et al. Dynamic zonation of liver polyploidy. Cell Tissue Res. 368, 405–410 (2017).

    CAS  PubMed  Google Scholar 

  132. Morales-Navarrete, H. et al. A versatile pipeline for the multi-scale digital reconstruction and quantitative analysis of 3D tissue architecture. eLife 4, e11214 (2015).

    PubMed  PubMed Central  Google Scholar 

  133. Yanger, K. & Stanger, B. Z. Facultative stem cells in liver and pancreas: fact and fancy. Dev. Dyn. 240, 521–529 (2011).

    PubMed  PubMed Central  Google Scholar 

  134. Michalopoulos, G. K. & DeFrances, M. C. Liver regeneration. Science 276, 60–66 (1997).

    CAS  PubMed  Google Scholar 

  135. Alwahsh, S. M., Rashidi, H. & Hay, D. C. Liver cell therapy: is this the end of the beginning? Cell. Mol. Life Sci. 75, 1307–1324 (2018).

    CAS  PubMed  Google Scholar 

  136. Tarlow, B. D. et al. Bipotential adult liver progenitors are derived from chronically injured mature hepatocytes. Cell Stem Cell 15, 605–618 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  137. Font-Burgada, J. et al. Hybrid periportal hepatocytes regenerate the injured liver without giving rise to cancer. Cell 162, 766–779 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  138. Forbes, S. J., Gupta, S. & Dhawan, A. Cell therapy for liver disease: from liver transplantation to cell factory. J. Hepatol. 62, S157–S169 (2015).

    CAS  PubMed  Google Scholar 

  139. Bilzer, M., Roggel, F. & Gerbes, A. L. Role of Kupffer cells in host defense and liver disease. Liver Int. 26, 1175–1186 (2006).

    CAS  PubMed  Google Scholar 

  140. Kelsey, G., Stegle, O. & Reik, W. Single-cell epigenomics: recording the past and predicting the future. Science 358, 69–75 (2017).

    CAS  PubMed  Google Scholar 

  141. Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  142. Furlan-Magaril, M., Várnai, C., Nagano, T. & Fraser, P. 3D genome architecture from populations to single cells. Curr. Opin. Genet. Dev. 31, 36–41 (2015).

    CAS  PubMed  Google Scholar 

  143. Budnik, B., Levy, E., Harmange, G. & Slavov, N. SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneity during cell differentiation. Genome Biol. 19, 161 (2018).

    PubMed  PubMed Central  Google Scholar 

  144. Cusanovich, D. A. et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell 174, 1309–1324 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  145. Moor, A. E. et al. Global mRNA polarization regulates translation efficiency in the intestinal epithelium. Science 357, 1299–1303 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  146. Moor, A. E. et al. Spatial reconstruction of single enterocytes uncovers broad zonation along the intestinal villus axis. Cell 175, 1156–1167 (2018).

    CAS  PubMed  Google Scholar 

  147. McEnerney, L. et al. Dual modulation of human hepatic zonation via canonical and non-canonical Wnt pathways. Exp. Mol. Med. 49, e413 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  148. Ben-Moshe, S., Shapira, Y., Moor, A. E., Halpern, K. B. & Itzkovitz, S. Spatial sorting enables comprehensive characterization of liver zonation. Preprint at bioRxiv https://doi.org/10.1101/529784 (2019).

    Article  Google Scholar 

  149. Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198–207 (2003).

    CAS  PubMed  Google Scholar 

  150. Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21.29.1–21.29.9 (2015).

    Google Scholar 

  151. Meissner, A. et al. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res. 33, 5868–5877 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  152. Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  153. Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  154. Caprioli, R. M., Farmer, T. B. & Gile, J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal. Chem. 69, 4751–4760 (1997).

    CAS  PubMed  Google Scholar 

  155. Cornett, D. S., Reyzer, M. L., Chaurand, P. & Caprioli, R. M. MALDI imaging mass spectrometry: molecular snapshots of biochemical systems. Nat. Methods 4, 828 (2007).

    CAS  PubMed  Google Scholar 

  156. Stoeckli, M., Staab, D. & Schweitzer, A. Compound and metabolite distribution measured by MALDI mass spectrometric imaging in whole-body tissue sections. Int. J. Mass Spectrom. 260, 195–202 (2007).

    CAS  Google Scholar 

  157. Shrivas, K. et al. Ionic matrix for enhanced MALDI imaging mass spectrometry for identification of phospholipids in mouse liver and cerebellum tissue sections. Anal. Chem. 82, 8800–8806 (2010).

    CAS  PubMed  Google Scholar 

  158. Shimma, S. et al. MALDI-based imaging mass spectrometry revealed abnormal distribution of phospholipids in colon cancer liver metastasis. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 855, 98–103 (2007).

    CAS  PubMed  Google Scholar 

  159. Chaurand, P., Cornett, D. S., Angel, P. M. & Caprioli, R. M. From whole-body sections down to cellular level, multiscale imaging of phospholipids by MALDI mass spectrometry. Mol. Cell. Proteomics 10, O110.004259 (2011).

    PubMed  Google Scholar 

  160. Angelo, M. et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20, 436 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  161. Bodenmiller, B. Multiplexed epitope-based tissue imaging for discovery and healthcare applications. Cell Syst. 2, 225–238 (2016).

    CAS  PubMed  Google Scholar 

  162. Chang, Q. et al. Imaging mass cytometry. Cytometry A 91, 160–169 (2017).

    PubMed  Google Scholar 

  163. Holzhütter, H.-G. The principle of flux minimization and its application to estimate stationary fluxes in metabolic networks. Eur. J. Biochem. 271, 2905–2922 (2004).

    PubMed  Google Scholar 

  164. Holzhütter, H.-G., Drasdo, D., Preusser, T., Lippert, J. & Henney, A. M. The virtual liver: a multidisciplinary, multilevel challenge for systems biology. Wiley Interdiscip. Rev. Syst. Biol. Med. 4, 221–235 (2012).

    PubMed  Google Scholar 

  165. Ricken, T. et al. Modeling function–perfusion behavior in liver lobules including tissue, blood, glucose, lactate and glycogen by use of a coupled two-scale PDE–ODE approach. Biomech. Model. Mechanobiol. 14, 515–536 (2015).

    CAS  PubMed  Google Scholar 

  166. Atger, F. et al. Circadian and feeding rhythms differentially affect rhythmic mRNA transcription and translation in mouse liver. Proc. Natl Acad. Sci. USA 112, E6579–E6588 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  167. Mauvoisin, D. et al. Circadian clock-dependent and -independent rhythmic proteomes implement distinct diurnal functions in mouse liver. Proc. Natl Acad. Sci. USA 111, 167–172 (2014).

    CAS  PubMed  Google Scholar 

  168. Robles, M. S., Cox, J. & Mann, M. In-vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism. PLOS Genet. 10, e1004047 (2014).

    PubMed  PubMed Central  Google Scholar 

  169. Storch, K.-F. et al. Extensive and divergent circadian gene expression in liver and heart. Nature 417, 78–83 (2002).

    CAS  PubMed  Google Scholar 

  170. Akhtar, R. A. et al. Circadian cycling of the mouse liver transcriptome, as revealed by cDNA microarray, is driven by the suprachiasmatic nucleus. Curr. Biol. 12, 540–550 (2002).

    CAS  PubMed  Google Scholar 

  171. Moorman, A. F. M., Vermeulen, J. L. M., Charles, R. & Lamers, W. H. Localization of ammonia-metabolizing enzymes in human liver: ontogenesis of heterogeneity. Hepatology 9, 367–372 (2005).

    Google Scholar 

  172. Dingemanse, M. A. et al. Development of the ornithine cycle in rat liver: zonation of a metabolic pathway. Hepatology 24, 407–411 (1996).

    CAS  PubMed  Google Scholar 

  173. Agius, L. & Tosh, D. Acinar zonation of cytosolic but not organelle-bound activities of phosphoenolpyruvate carboxykinase and aspartate aminotransferase in guinea-pig liver. Biochem. J. 271, 387–391 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  174. Wimmer, M., Luttringer, C. & Colombi, M. Enzyme activity patterns of phosphoenolpyruvate carboxykinase, pyruvate kinase, glucose-6-phosphate-dehydrogenase and malic enzyme in human liver. Histochemistry 93, 409–415 (1990).

    CAS  PubMed  Google Scholar 

  175. MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).

    PubMed  PubMed Central  Google Scholar 

  176. Chen, M. et al. Drug-induced liver injury: Interactions between drug properties and host factors. J. Hepatol. 63, 503–514 (2015).

    CAS  PubMed  Google Scholar 

  177. Albenberg, L. et al. Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota. Gastroenterology 147, 1055–1063 (2014).

    PubMed  Google Scholar 

  178. Belzer, C. & de Vos, W. M. Microbes inside—from diversity to function: the case of Akkermansia. ISME J. 6, 1449–1458 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  179. White, J. W. & Swartz, F. J. Changes in polyploidization of exocrine pancreas in db/db diabetic and normal mice. Eur. J. Endocrinol. 94, 523–528 (1980).

    CAS  Google Scholar 

  180. Lawrence, G. M., Jepson, M. A., Trayer, I. P. & Walker, D. G. The compartmentation of glycolytic and gluconeogenic enzymes in rat kidney and liver and its significance to renal and hepatic metabolism. Histochem. J. 18, 45–53 (1986).

    CAS  PubMed  Google Scholar 

  181. Schmidt, U. & Guder, W. G. Sites of enzyme activity along the nephron. Kidney Int. 9, 233–242 (1976).

    CAS  PubMed  Google Scholar 

  182. Burch, H. B. et al. Distribution along the rat nephron of three enzymes of gluconeogenesis in acidosis and starvation. Am. J. Physiol. 235, F246–F253 (1978).

    CAS  PubMed  Google Scholar 

  183. Guder, W. G. & Ross, B. D. Enzyme distribution along the nephron. Kidney Int. 26, 101–111 (1984).

    CAS  PubMed  Google Scholar 

  184. Lee, J. W., Chou, C.-L. & Knepper, M. A. Deep sequencing in microdissected renal tubules identifies nephron segment–specific transcriptomes. J. Am. Soc. Nephrol. 26, 2669–2677 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  185. Der, E. et al. Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis. JCI Insight 2, 93009 (2017).

    PubMed  Google Scholar 

  186. Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, 758–763 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  187. Shoval, O. et al. Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space. Science 336, 1157–1160 (2012).

    CAS  PubMed  Google Scholar 

  188. Hart, Y. et al. Inferring biological tasks using Pareto analysis of high-dimensional data. Nat. Methods 12, 233 (2015).

    CAS  PubMed  Google Scholar 

  189. Nagrath, D. et al. Integrated energy and flux balance based multiobjective framework for large-scale metabolic networks. Ann. Biomed. Eng. 35, 863–885 (2007).

    PubMed  Google Scholar 

  190. Grün, D. & van Oudenaarden, A. Design and analysis of single-cell sequencing experiments. Cell 163, 799–810 (2015).

    PubMed  Google Scholar 

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Acknowledgements

The authors thank K. Bahar Halpern, Y. Shapira and A. Afriat for valuable comments. S.I. is supported by the Henry Chanoch Krenter Institute for Biomedical Imaging and Genomics, the Leir Charitable Foundations, the Richard Jakubskind Laboratory of Systems Biology, the Cymerman-Jakubskind Prize, the Lord Sieff of Brimpton Memorial Fund, the I-CORE programme of the Planning and Budgeting Committee and the Israel Science Foundation (grants 1902/ 12 and 1796/12), Israel Science Foundation grant number 1486/16, the European Molecular Biology Organization (EMBO) Young Investigator Program, the European Research Council (ERC) under the European Union’s Seventh Framework Programme (FP7/2007-2013 and ERC grant agreement number 335122), the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement number 768956), the Bert L. and N. Kuggie Vallee Foundation and the Howard Hughes Medical Institute (HHMI) international research scholar award.

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Nature Reviews Gastroenterology & Hepatology thanks S. Colnot, R. Gebhart and the other anonymous reviewer(s), for their contribution to the peer review of this work.

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Ben-Moshe, S., Itzkovitz, S. Spatial heterogeneity in the mammalian liver. Nat Rev Gastroenterol Hepatol 16, 395–410 (2019). https://doi.org/10.1038/s41575-019-0134-x

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