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.
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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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).
Gebhardt, R. Metabolic zonation of the liver: regulation and implications for liver function. Pharmacol. Ther. 53, 275–354 (1992).
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).
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).
Teutsch, H. F. The modular microarchitecture of human liver. Hepatology 42, 317–325 (2005).
Torre, C., Perret, C. & Colnot, S. Molecular determinants of liver zonation. Prog. Mol. Biol. Transl Sci. 97, 127–150 (2010).
Israel, Y. & Orrego, H. Hypermetabolic state and hypoxic liver damage. Recent Dev. Alcohol. 2, 119–133 (1984).
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).
de Groot, H., Littauer, A. & Noll, T. in Oxygen Sensing in Tissues (ed. Acker, H.) 49–64 (Springer-Verlag Berlin Heidelberg, 1988).
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).
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).
Jungermann, K. & Keitzmann, T. Zonation of parenchymal and nonparenchymal metabolism in liver. Annu. Rev. Nutr. 16, 179–203 (1996).
Jungermann, K. & Katz, N. Functional hepatocellular heterogeneity. Hepatology 2, 385S–395S (1982).
Gebhardt, R. & Matz-Soja, M. Liver zonation: novel aspects of its regulation and its impact on homeostasis. World J. Gastroenterol. 20, 8491–8504 (2014).
Colnot, S. & Perret, C. in Molecular Pathology of Liver Diseases (ed. Monga, S. P. S.) 7–16 (Springer US, 2011).
Kater, J. M. Comparative and experimental studies on the cytology of the liver. Z. Für Zellforsch. Mikrosk. Anat. 17, 217–246 (1933).
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).
Chiquoine, A. D. The distribution of glucose-6-phosphatase in the liver and kidney of the mouse. J. Histochem. Cytochem. 1, 429–435 (1953).
Jungermann, K. & Katz, N. Functional specialization of different hepatocyte populations. Physiol. Rev. 69, 708–764 (1989).
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).
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).
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).
Sasse, D., Katz, N. & Jungermann, K. Functional heterogeneity of rat liver parenchyma and of isolated hepatocytes. FEBS Lett. 57, 83–88 (1975).
Feldmann, G., Scoazec, J. Y., Racine, L. & Bernuau, D. Functional hepatocellular heterogeneity for the production of plasma proteins. Enzyme 46, 139–154 (1992).
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).
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).
Gebhardt, R. in Cytochrome P450 Protocols (eds Phillips, I. R. & Shephard, E. A.) 319–328 (Humana Press, 1998).
Lindros, K. O. & Penttilä, K. E. Digitonin-collagenase perfusion for efficient separation of periportal or perivenous hepatocytes. Biochem. J. 228, 757–760 (1985).
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).
Braeuning, A. et al. Differential gene expression in periportal and perivenous mouse hepatocytes. FEBS J. 273, 5051–5061 (2006).
Saito, K., Negishi, M. & Squires, E. J. Sexual dimorphisms in zonal gene expression in mouse liver. Biochem. Biophys. Res. Commun. 436, 730–735 (2013).
Hashimshony, T., Wagner, F., Sher, N. & Yanai, I. CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep. 2, 666–673 (2012).
Jaitin, D. A. et al. Massively parallel single cell RNA-Seq for marker-free decomposition of tissues into cell types. Science 343, 776 (2014).
Zeisel, A. et al. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347, 1138–1142 (2015).
Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).
Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
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).
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).
Kivioja, T. et al. Counting absolute numbers of molecules using unique molecular identifiers. Nat. Methods 9, 72 (2012).
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).
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).
Islam, S. et al. Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. Genome Res. 21, 1160–1167 (2011).
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).
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).
Achim, K. et al. High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nat. Biotechnol. 33, 503–509 (2015).
Itzkovitz, S. & van Oudenaarden, A. Validating transcripts with probes and imaging technology. Nat. Methods 8, S12 (2011).
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).
Bahar Halpern, K. et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 542, 352–356 (2017).
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).
Rolfe, D. F. & Brown, G. C. Cellular energy utilization and molecular origin of standard metabolic rate in mammals. Physiol. Rev. 77, 731–758 (1997).
Bahar Halpern, K. et al. Bursty gene expression in the intact mammalian liver. Mol. Cell 58, 147–156 (2015).
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).
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).
de Aguiar Vallim, T. Q., Tarling, E. J. & Edwards, P. A. Pleiotropic roles of bile acids in metabolism. Cell Metab. 17, 657–669 (2013).
Russell, D. W. The enzymes, regulation, and genetics of bile acid synthesis. Annu. Rev. Biochem. 72, 137–174 (2003).
Dawson, P. A. in Physiology of the Gastrointestinal Tract (ed. Said, H.) 6th edn 931–956 (Academic Press, 2018).
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).
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).
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).
Haüssinger, D. Nitrogen metabolism in liver: structural and functional organization and physiological relevance. Biochem. J. 267, 281 (1990).
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).
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).
Bartl, M. et al. Optimality in the zonation of ammonia detoxification in rodent liver. Arch. Toxicol. 89, 2069–2078 (2015).
Häussinger, D. Glutamine metabolism in the liver: overview and current concepts. Metabolism 38, 14–17 (1989).
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).
Bar-Even, A. et al. The moderately efficient enzyme: evolutionary and physicochemical trends shaping enzyme parameters. Biochemistry 50, 4402–4410 (2011).
Liemburg-Apers, D. C. et al. Quantitative glucose and ATP sensing in mammalian cells. Pharm. Res. 28, 2745–2757 (2011).
Hakvoort, T. B. M. et al. Pivotal role of glutamine synthetase in ammonia detoxification. Hepatology 65, 281–293 (2017).
Augustin, H. G. & Koh, G. Y. Organotypic vasculature: from descriptive heterogeneity to functional pathophysiology. Science 357, eaal2379 (2017).
Aird, W. C. Phenotypic heterogeneity of the endothelium: II. Representative vascular beds. Circ. Res. 100, 174–190 (2007).
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).
Rafii, S., Butler, J. M. & Ding, B.-S. Angiocrine functions of organ-specific endothelial cells. Nature 529, 316 (2016).
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).
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).
Planas-Paz, L. et al. The RSPO–LGR4/5–ZNRF3/RNF43 module controls liver zonation and size. Nat. Cell Biol. 18, 467 (2016).
Halpern, K. et al. Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells. Nat. Biotechnol. 36, 962–970 (2018).
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).
Friedman, S. L. Hepatic stellate cells: protean, multifunctional, and enigmatic cells of the liver. Physiol. Rev. 88, 125–172 (2008).
Friedman, S. L. Molecular regulation of hepatic fibrosis, an integrated cellular response to tissue injury. J. Biol. Chem. 275, 2247–2250 (2000).
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).
Burke, Z. D. & Tosh, D. The Wnt/β-catenin pathway: master regulator of liver zonation? Bioessays 28, 1072–1077 (2006).
Thompson, M. D. & Monga, S. P. S. WNT/β-catenin signaling in liver health and disease. Hepatology 45, 1298–1305 (2007).
Benhamouche, S. et al. Apc tumor suppressor gene is the ‘zonation-keeper’ of mouse liver. Dev. Cell 10, 759–770 (2006).
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).
Rocha, A. S. et al. The angiocrine factor Rspondin3 is a key determinant of liver zonation. Cell Rep. 13, 1757–1764 (2015).
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).
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).
Jungermann, K. & Kietzmann, T. Role of oxygen in the zonation of carbohydrate metabolism and gene expression in liver. Kidney Int. 51, 402–412 (1997).
Kietzmann, T. Metabolic zonation of the liver: the oxygen gradient revisited. Redox Biol. 11, 622–630 (2017).
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).
Lehwald, N. et al. Wnt–β-catenin signaling protects against hepatic ischemia and reperfusion injury in mice. Gastroenterology 141, 707–718 (2011).
Cheng, X. et al. Glucagon contributes to liver zonation. Proc. Natl Acad. Sci. USA 115, E4111–E4119 (2018).
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).
Oinonen, T. & Lindros, K. O. Zonation of hepatic cytochrome P-450 expression and regulation. Biochem. J. 329, 17–35 (1998).
Bird, A. DNA methylation patterns and epigenetic memory. Genes Dev. 16, 6–21 (2002).
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).
Brosch, M. et al. Epigenomic map of human liver reveals principles of zonated morphogenic and metabolic control. Nat. Commun. 9, 4150 (2018).
Tujios, S. & Fontana, R. J. Mechanisms of drug-induced liver injury: from bedside to bench. Nat. Rev. Gastroenterol. Hepatol. 8, 202 (2011).
Nelson, S. D. Molecular mechanisms of the hepatotoxicity caused by acetaminophen. Semin. Liver Dis. 10, 267–278 (1990).
Makin, A. J., Wendon, J. & Williams, R. A. 7-year experience of severe acetaminophen-induced hepatotoxicity (1987–1993). Gastroenterology 109, 1907–1916 (1995).
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).
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).
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).
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).
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).
Reid, W. D. Mechanism of allyl alcohol-induced hepatic necrosis. Experientia 28, 1058–1061 (1972).
Brunt, E. M. Pathology of fatty liver disease. Mod. Pathol. 20, S40 (2007).
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).
Farrell, G. C., Teoh, N. C. & Mccuskey, R. S. Hepatic microcirculation in fatty liver disease. Anat. Rec. 291, 684–692 (2008).
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).
Schwen, L. O. et al. Zonated quantification of steatosis in an entire mouse liver. Comput. Biol. Med. 73, 108–118 (2016).
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).
Prudêncio, M., Rodriguez, A. & Mota, M. M. The silent path to thousands of merozoites: the Plasmodium liver stage. Nat. Rev. Microbiol. 4, 849 (2006).
Ng, S. et al. Hypoxia promotes liver stage malaria infection in primary human hepatocytes in vitro. Dis. Model. Mech. 7, 215–224 (2013).
Seeger, C. & Mason, W. S. Hepatitis B virus biology. Microbiol. Mol. Biol. Rev. 64, 51–68 (2000).
Chisari, F. V. Unscrambling hepatitis C virus–host interactions. Nature 436, 930–932 (2005).
Bedossa, P., Dargère, D. & Paradis, V. Sampling variability of liver fibrosis in chronic hepatitis C. Hepatology 38, 1449–1457 (2003).
Diamantis, I. & Boumpas, D. T. Autoimmune hepatitis: evolving concepts. Autoimmun. Rev. 3, 207–214 (2004).
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).
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).
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).
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).
Llovet, J. M. et al. Hepatocellular carcinoma. Nat. Rev. Dis. Primers 2, 16018 (2016).
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).
Zucman-Rossi, J., Villanueva, A., Nault, J. C. & Llovet, J. M. Genetic landscape and biomarkers of hepatocellular carcinoma. Gastroenterology 149, 1226–1239 (2015).
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).
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).
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).
Celton-Morizur, S. & Desdouets, C. Polyploidization of liver cells. Adv. Exp. Med. Biol. 676, 123–135 (2010).
Duncan, A. W. Aneuploidy, polyploidy and ploidy reversal in the liver. Semin. Cell Dev. Biol. 24, 347–356 (2013).
Tanami, S. et al. Dynamic zonation of liver polyploidy. Cell Tissue Res. 368, 405–410 (2017).
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).
Yanger, K. & Stanger, B. Z. Facultative stem cells in liver and pancreas: fact and fancy. Dev. Dyn. 240, 521–529 (2011).
Michalopoulos, G. K. & DeFrances, M. C. Liver regeneration. Science 276, 60–66 (1997).
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).
Tarlow, B. D. et al. Bipotential adult liver progenitors are derived from chronically injured mature hepatocytes. Cell Stem Cell 15, 605–618 (2014).
Font-Burgada, J. et al. Hybrid periportal hepatocytes regenerate the injured liver without giving rise to cancer. Cell 162, 766–779 (2015).
Forbes, S. J., Gupta, S. & Dhawan, A. Cell therapy for liver disease: from liver transplantation to cell factory. J. Hepatol. 62, S157–S169 (2015).
Bilzer, M., Roggel, F. & Gerbes, A. L. Role of Kupffer cells in host defense and liver disease. Liver Int. 26, 1175–1186 (2006).
Kelsey, G., Stegle, O. & Reik, W. Single-cell epigenomics: recording the past and predicting the future. Science 358, 69–75 (2017).
Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486 (2015).
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).
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).
Cusanovich, D. A. et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell 174, 1309–1324 (2018).
Moor, A. E. et al. Global mRNA polarization regulates translation efficiency in the intestinal epithelium. Science 357, 1299–1303 (2017).
Moor, A. E. et al. Spatial reconstruction of single enterocytes uncovers broad zonation along the intestinal villus axis. Cell 175, 1156–1167 (2018).
McEnerney, L. et al. Dual modulation of human hepatic zonation via canonical and non-canonical Wnt pathways. Exp. Mol. Med. 49, e413 (2017).
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).
Aebersold, R. & Mann, M. Mass spectrometry-based proteomics. Nature 422, 198–207 (2003).
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).
Meissner, A. et al. Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res. 33, 5868–5877 (2005).
Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376 (2012).
Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).
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).
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).
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).
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).
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).
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).
Angelo, M. et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20, 436 (2014).
Bodenmiller, B. Multiplexed epitope-based tissue imaging for discovery and healthcare applications. Cell Syst. 2, 225–238 (2016).
Chang, Q. et al. Imaging mass cytometry. Cytometry A 91, 160–169 (2017).
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).
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).
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).
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).
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).
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).
Storch, K.-F. et al. Extensive and divergent circadian gene expression in liver and heart. Nature 417, 78–83 (2002).
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).
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).
Dingemanse, M. A. et al. Development of the ornithine cycle in rat liver: zonation of a metabolic pathway. Hepatology 24, 407–411 (1996).
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).
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).
MacParland, S. A. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat. Commun. 9, 4383 (2018).
Chen, M. et al. Drug-induced liver injury: Interactions between drug properties and host factors. J. Hepatol. 63, 503–514 (2015).
Albenberg, L. et al. Correlation between intraluminal oxygen gradient and radial partitioning of intestinal microbiota. Gastroenterology 147, 1055–1063 (2014).
Belzer, C. & de Vos, W. M. Microbes inside—from diversity to function: the case of Akkermansia. ISME J. 6, 1449–1458 (2012).
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).
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).
Schmidt, U. & Guder, W. G. Sites of enzyme activity along the nephron. Kidney Int. 9, 233–242 (1976).
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).
Guder, W. G. & Ross, B. D. Enzyme distribution along the nephron. Kidney Int. 26, 101–111 (1984).
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).
Der, E. et al. Single cell RNA sequencing to dissect the molecular heterogeneity in lupus nephritis. JCI Insight 2, 93009 (2017).
Park, J. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 360, 758–763 (2018).
Shoval, O. et al. Evolutionary trade-offs, Pareto optimality, and the geometry of phenotype space. Science 336, 1157–1160 (2012).
Hart, Y. et al. Inferring biological tasks using Pareto analysis of high-dimensional data. Nat. Methods 12, 233 (2015).
Nagrath, D. et al. Integrated energy and flux balance based multiobjective framework for large-scale metabolic networks. Ann. Biomed. Eng. 35, 863–885 (2007).
Grün, D. & van Oudenaarden, A. Design and analysis of single-cell sequencing experiments. Cell 163, 799–810 (2015).
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.
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.
The authors declare no competing interests.
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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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