Semin Liver Dis 2021; 41(03): 321-330
DOI: 10.1055/s-0041-1729970
Review Article

Toward a Liver Cell Atlas: Understanding Liver Biology in Health and Disease at Single-Cell Resolution

Lichun Ma
1   Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
,
Subreen Khatib
1   Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
,
Amanda J. Craig
1   Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
,
Xin Wei Wang
1   Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
2   Liver Cancer Program, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland
› Author Affiliations
Funding This work was supported by grants (ZIA BC 010877, ZIA BC 010876, ZIA BC 010313, and ZIA BC 011870) from the Intramural Research Program of the Center for Cancer Research, National Cancer Institute of the United States.

Abstract

Single-cell technologies are revolutionizing our understanding of cellular heterogeneity and functional diversity in health and disease. Here, we review the current knowledge and advances in liver biology using single-cell approaches. We focus on the landscape of the composition and the function of cells in a healthy liver in the context of its spatial organization. We also highlight the alterations of the molecular landscape in chronic liver disease and liver cancer, which includes the identification of disease-related cell types, altered cellular functions, dynamic cell–cell interactions, the plasticity of malignant cells, the collective behavior of a cell community, and microenvironmental reprogramming. We anticipate that the uncovered liver cell atlas will help deciphering the molecular and cellular mechanisms driving a healthy liver into a disease state. It also offers insight into the detection of new therapeutic targets and paves the way for effective disease interventions.

Authors' Contributions

L.M. and X.W.W. designed the study. L.M., S.K., A.J.C., and X.W.W. performed literature search and wrote the manuscript. L.M. generated the artwork. All authors read, edited, and approved the manuscript.


Declaration of Interests

The authors declare no competing interests.




Publication History

Article published online:
15 June 2021

© 2021. Thieme. All rights reserved.

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  • References

  • 1 Ben-Moshe S, Itzkovitz S. Spatial heterogeneity in the mammalian liver. Nat Rev Gastroenterol Hepatol 2019; 16 (07) 395-410
  • 2 Gebhardt R, Matz-Soja M. Liver zonation: novel aspects of its regulation and its impact on homeostasis. World J Gastroenterol 2014; 20 (26) 8491-8504
  • 3 Ramachandran P, Matchett KP, Dobie R, Wilson-Kanamori JR, Henderson NC. Single-cell technologies in hepatology: new insights into liver biology and disease pathogenesis. Nat Rev Gastroenterol Hepatol 2020; 17 (08) 457-472
  • 4 Asrani SK, Devarbhavi H, Eaton J, Kamath PS. Burden of liver diseases in the world. J Hepatol 2019; 70 (01) 151-171
  • 5 Zhang C-Y, Yuan W-G, He P, Lei J-H, Wang C-X. Liver fibrosis and hepatic stellate cells: etiology, pathological hallmarks and therapeutic targets. World J Gastroenterol 2016; 22 (48) 10512-10522
  • 6 Bataller R, Gao B. Liver fibrosis in alcoholic liver disease. Semin Liver Dis 2015; 35 (02) 146-156
  • 7 Starr SP, Raines D. Cirrhosis: diagnosis, management, and prevention. Am Fam Physician 2011; 84 (12) 1353-1359
  • 8 Michelotti GA, Machado MV, Diehl AM. NAFLD, NASH and liver cancer. Nat Rev Gastroenterol Hepatol 2013; 10 (11) 656-665
  • 9 Marengo A, Rosso C, Bugianesi E. Liver cancer: connections with obesity, fatty liver, and cirrhosis. Annu Rev Med 2016; 67: 103-117
  • 10 Sun B, Karin M. Obesity, inflammation, and liver cancer. J Hepatol 2012; 56 (03) 704-713
  • 11 Shapiro E, Biezuner T, Linnarsson S. Single-cell sequencing-based technologies will revolutionize whole-organism science. Nat Rev Genet 2013; 14 (09) 618-630
  • 12 Svensson V, Vento-Tormo R, Teichmann SA. Exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc 2018; 13 (04) 599-604
  • 13 Hou Y, Guo H, Cao C. et al. Single-cell triple omics sequencing reveals genetic, epigenetic, and transcriptomic heterogeneity in hepatocellular carcinomas. Cell Res 2016; 26 (03) 304-319
  • 14 Hu Y, Huang K, An Q. et al. Simultaneous profiling of transcriptome and DNA methylome from a single cell. Genome Biol 2016; 17 (01) 88
  • 15 Gu C, Liu S, Wu Q, Zhang L, Guo F. Integrative single-cell analysis of transcriptome, DNA methylome and chromatin accessibility in mouse oocytes. Cell Res 2019; 29 (02) 110-123
  • 16 Chen X, Litzenburger UM, Wei Y. et al. Joint single-cell DNA accessibility and protein epitope profiling reveals environmental regulation of epigenomic heterogeneity. Nat Commun 2018; 9 (01) 4590
  • 17 Angermueller C, Clark SJ, Lee HJ. et al. Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat Methods 2016; 13 (03) 229-232
  • 18 Ku WL, Nakamura K, Gao W. et al. Single-cell chromatin immunocleavage sequencing (scChIC-seq) to profile histone modification. Nat Methods 2019; 16 (04) 323-325
  • 19 Wang YJ, Golson ML, Schug J. et al. Single-cell mass cytometry analysis of the human endocrine pancreas. Cell Metab 2016; 24 (04) 616-626
  • 20 Macaulay IC, Haerty W, Kumar P. et al. G&T-seq: parallel sequencing of single-cell genomes and transcriptomes. Nat Methods 2015; 12 (06) 519-522
  • 21 Gawad C, Koh W, Quake SR. Single-cell genome sequencing: current state of the science. Nat Rev Genet 2016; 17 (03) 175-188
  • 22 Wang Y, Navin NE. Advances and applications of single-cell sequencing technologies. Mol Cell 2015; 58 (04) 598-609
  • 23 Chen W-T, Lu A, Craessaerts K. et al. Spatial transcriptomics and in situ sequencing to study Alzheimer's disease. Cell 2020; 182 (04) 976-991.e19
  • 24 Burgess DJ. Spatial transcriptomics coming of age. Nat Rev Genet 2019; 20 (06) 317-317
  • 25 Lein E, Borm LE, Linnarsson S. The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing. Science 2017; 358 (6359): 64-69
  • 26 Darmanis S, Sloan SA, Zhang Y. et al. A survey of human brain transcriptome diversity at the single cell level. Proc Natl Acad Sci U S A 2015; 112 (23) 7285-7290
  • 27 Lake BB, Chen S, Sos BC. et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nat Biotechnol 2018; 36 (01) 70-80
  • 28 Puram SV, Tirosh I, Parikh AS. et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in head and neck cancer. Cell 2017; 171 (07) 1611-1624.e24
  • 29 Suryawanshi H, Clancy R, Morozov P, Halushka MK, Buyon JP, Tuschl T. Cell atlas of the foetal human heart and implications for autoimmune-mediated congenital heart block. Cardiovasc Res 2020; 116 (08) 1446-1457
  • 30 Gladka MM, Molenaar B, de Ruiter H. et al. Single-cell sequencing of the healthy and diseased heart reveals cytoskeleton-associated protein 4 as a new modulator of fibroblasts activation. Circulation 2018; 138 (02) 166-180
  • 31 Lawson DA, Bhakta NR, Kessenbrock K. et al. Single-cell analysis reveals a stem-cell program in human metastatic breast cancer cells. Nature 2015; 526 (7571): 131-135
  • 32 Kim C, Gao R, Sei E. et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell 2018; 173 (04) 879-893.e13
  • 33 Lavin Y, Kobayashi S, Leader A. et al. Innate immune landscape in early lung adenocarcinoma by paired single-cell analyses. Cell 2017; 169 (04) 750-765.e17
  • 34 Ma L, Hernandez MO, Zhao Y. et al. Tumor cell biodiversity drives microenvironmental reprogramming in liver cancer. Cancer Cell 2019; 36 (04) 418-430.e6
  • 35 Ma L, Wang L, Chang CW. et al. Single-cell atlas of tumor clonal evolution in liver cancer. 2020 . Accessed January 25, 2021 at: https://doi.org/10.1101/2020.08.18.254748
  • 36 Zhang L, Li Z, Skrzypczynska KM. et al. Single-cell analyses inform mechanisms of myeloid-targeted therapies in colon cancer. Cell 2020; 181 (02) 442-459.e29
  • 37 Park J, Shrestha R, Qiu C. et al. Single-cell transcriptomics of the mouse kidney reveals potential cellular targets of kidney disease. Science 2018; 360 (6390): 758-763
  • 38 Guo W, Li L, He J. et al. Single-cell transcriptomics identifies a distinct luminal progenitor cell type in distal prostate invagination tips. Nat Genet 2020; 52 (09) 908-918
  • 39 Braet F, Wisse E. Structural and functional aspects of liver sinusoidal endothelial cell fenestrae: a review. Comp Hepatol 2002; 1 (01) 1
  • 40 Crispe IN. The liver as a lymphoid organ. Annu Rev Immunol 2009; 27: 147-163
  • 41 Si-Tayeb K, Lemaigre FP, Duncan SA. Organogenesis and development of the liver. Dev Cell 2010; 18 (02) 175-189
  • 42 Aizarani N, Saviano A. Sagar, et al. A human liver cell atlas reveals heterogeneity and epithelial progenitors. Nature 2019; 572 (7768): 199-204
  • 43 MacParland SA, Liu JC, Ma X-Z. et al. Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun 2018; 9 (01) 4383
  • 44 Torre C, Perret C, Colnot S. Molecular determinants of liver zonation. In: Progress in Molecular Biology and Translational Science. Vol 97. Elsevier; 2010: 127-150
  • 45 Kietzmann T. Metabolic zonation of the liver: the oxygen gradient revisited. Redox Biol 2017; 11: 622-630
  • 46 Jungermann K, Kietzmann T. Oxygen: modulator of metabolic zonation and disease of the liver. Hepatology 2000; 31 (02) 255-260
  • 47 Halpern KB, Shenhav R, Matcovitch-Natan O. et al. Single-cell spatial reconstruction reveals global division of labour in the mammalian liver. Nature 2017; 542 (7641): 352-356
  • 48 Halpern KB, Shenhav R, Massalha H. et al. Paired-cell sequencing enables spatial gene expression mapping of liver endothelial cells. Nat Biotechnol 2018; 36 (10) 962-970
  • 49 Moon AM, Singal AG, Tapper EB. Contemporary epidemiology of chronic liver disease and cirrhosis. Clin Gastroenterol Hepatol 2020; 18 (12) 2650-2666
  • 50 Friedman SL. Mechanisms of hepatic fibrogenesis. Gastroenterology 2008; 134 (06) 1655-1669
  • 51 Kim A, Bellar A, McMullen MR, Li X, Nagy LE. Functionally diverse inflammatory responses in peripheral and liver monocytes in alcohol-associated hepatitis. Hepatol Commun 2020; 4 (10) 1459-1476
  • 52 Neuveut C, Wei Y, Buendia MA. Mechanisms of HBV-related hepatocarcinogenesis. J Hepatol 2010; 52 (04) 594-604
  • 53 Suhail M, Abdel-Hafiz H, Ali A. et al. Potential mechanisms of hepatitis B virus induced liver injury. World J Gastroenterol 2014; 20 (35) 12462-12472
  • 54 Duan M, Hao J, Cui S. et al. Diverse modes of clonal evolution in HBV-related hepatocellular carcinoma revealed by single-cell genome sequencing. Cell Res 2018; 28 (03) 359-373
  • 55 Xiong X, Kuang H, Ansari S. et al. Landscape of intercellular crosstalk in healthy and NASH liver revealed by single-cell secretome gene analysis. Mol Cell 2019; 75 (03) 644-660.e5
  • 56 Ægidius HM, Veidal SS, Feigh M. et al. Multi-omics characterization of a diet-induced obese model of non-alcoholic steatohepatitis. Sci Rep 2020; 10 (01) 1148
  • 57 Ramachandran P, Dobie R, Wilson-Kanamori JR. et al. Resolving the fibrotic niche of human liver cirrhosis at single-cell level. Nature 2019; 575 (7783): 512-518
  • 58 Dobie R, Wilson-Kanamori JR, Henderson BEP. et al. Single-cell transcriptomics uncovers zonation of function in the mesenchyme during liver fibrosis. Cell Rep 2019; 29 (07) 1832-1847.e8
  • 59 Zhang Q, Lou Y, Yang J. et al. Integrated multiomic analysis reveals comprehensive tumour heterogeneity and novel immunophenotypic classification in hepatocellular carcinomas. Gut 2019; 68 (11) 2019-2031
  • 60 Zhang M, Yang H, Wan L. et al. Single-cell transcriptomic architecture and intercellular crosstalk of human intrahepatic cholangiocarcinoma. J Hepatol 2020; 73 (05) 1118-1130
  • 61 Chaisaingmongkol J, Budhu A, Dang H. et al; TIGER-LC Consortium. Common molecular subtypes among Asian hepatocellular carcinoma and cholangiocarcinoma. Cancer Cell 2017; 32 (01) 57-70.e3
  • 62 Losic B, Craig AJ, Villacorta-Martin C. et al. Intratumoral heterogeneity and clonal evolution in liver cancer. Nat Commun 2020; 11 (01) 291
  • 63 Nowell PC. The clonal evolution of tumor cell populations. Science 1976; 194 (4260): 23-28
  • 64 Lipinski KA, Barber LJ, Davies MN, Ashenden M, Sottoriva A, Gerlinger M. Cancer evolution and the limits of predictability in precision cancer medicine. Trends Cancer 2016; 2 (01) 49-63
  • 65 Greaves M, Maley CC. Clonal evolution in cancer. Nature 2012; 481 (7381): 306-313
  • 66 Reya T, Morrison SJ, Clarke MF, Weissman IL. Stem cells, cancer, and cancer stem cells. Nature 2001; 414 (6859): 105-111
  • 67 Batlle E, Clevers H. Cancer stem cells revisited. Nat Med 2017; 23 (10) 1124-1134
  • 68 Zheng H, Pomyen Y, Hernandez MO. et al. Single-cell analysis reveals cancer stem cell heterogeneity in hepatocellular carcinoma. Hepatology 2018; 68 (01) 127-140
  • 69 Ho DW-H, Tsui Y-M, Sze KM-F. et al. Single-cell transcriptomics reveals the landscape of intra-tumoral heterogeneity and stemness-related subpopulations in liver cancer. Cancer Lett 2019; 459: 176-185
  • 70 Whiteside TL. The tumor microenvironment and its role in promoting tumor growth. Oncogene 2008; 27 (45) 5904-5912
  • 71 Zheng C, Zheng L, Yoo JK. et al. Landscape of infiltrating T cells in liver cancer revealed by single-cell sequencing. Cell 2017; 169 (07) 1342-1356.e16
  • 72 Zhang Q, He Y, Luo N. et al. Landscape and dynamics of single immune cells in hepatocellular carcinoma. Cell 2019; 179 (04) 829-845.e20
  • 73 Krenkel O, Tacke F. Liver macrophages in tissue homeostasis and disease. Nat Rev Immunol 2017; 17 (05) 306-321
  • 74 Kalluri R, Zeisberg M. Fibroblasts in cancer. Nat Rev Cancer 2006; 6 (05) 392-401
  • 75 Hida K, Maishi N, Annan DA, Hida Y. Contribution of tumor endothelial cells in cancer progression. Int J Mol Sci 2018; 19 (05) 1272
  • 76 Sharma A, Seow JJW, Dutertre C-A. et al. Onco-fetal reprogramming of endothelial cells drives immunosuppressive macrophages in hepatocellular carcinoma. Cell 2020; 183 (02) 377-394.e21
  • 77 Massalha H, Bahar Halpern K, Abu-Gazala S. et al. A single cell atlas of the human liver tumor microenvironment. Mol Syst Biol 2020; 16 (12) e9682
  • 78 Miles LA, Bowman RL, Merlinsky TR. et al. Single-cell mutation analysis of clonal evolution in myeloid malignancies. Nature 2020; 587 (7834): 477-482
  • 79 Pellegrino M, Sciambi A, Treusch S. et al. High-throughput single-cell DNA sequencing of acute myeloid leukemia tumors with droplet microfluidics. Genome Res 2018; 28 (09) 1345-1352
  • 80 Durante MA, Rodriguez DA, Kurtenbach S. et al. Single-cell analysis reveals new evolutionary complexity in uveal melanoma. Nat Commun 2020; 11 (01) 496
  • 81 Marjanovic ND, Hofree M, Chan JE. et al. Emergence of a high-plasticity cell state during lung cancer evolution. Cancer Cell 2020; 38 (02) 229-246.e13
  • 82 Zhu P, Guo H, Ren Y. et al. Single-cell DNA methylome sequencing of human preimplantation embryos. Nat Genet 2018; 50 (01) 12-19
  • 83 Luo C, Rivkin A, Zhou J. et al. Robust single-cell DNA methylome profiling with snmC-seq2. Nat Commun 2018; 9 (01) 3824
  • 84 Jia G, Preussner J, Chen X. et al. Single cell RNA-seq and ATAC-seq analysis of cardiac progenitor cell transition states and lineage settlement. Nat Commun 2018; 9 (01) 4877
  • 85 Cusanovich DA, Hill AJ, Aghamirzaie D. et al. A single-cell atlas of in vivo mammalian chromatin accessibility. Cell 2018; 174 (05) 1309-1324.e18
  • 86 Cao J, Cusanovich DA, Ramani V. et al. Joint profiling of chromatin accessibility and gene expression in thousands of single cells. Science 2018; 361 (6409): 1380-1385
  • 87 Palii CG, Cheng Q, Gillespie MA. et al. Single-cell proteomics reveal that quantitative changes in co-expressed lineage-specific transcription factors determine cell fate. Cell Stem Cell 2019; 24 (05) 812-820.e5
  • 88 Orecchioni M, Bedognetti D, Newman L. et al. Single-cell mass cytometry and transcriptome profiling reveal the impact of graphene on human immune cells. Nat Commun 2017; 8 (01) 1109
  • 89 Clark SJ, Argelaguet R, Kapourani C-A. et al. scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells. Nat Commun 2018; 9 (01) 781
  • 90 Maniatis S, Äijö T, Vickovic S. et al. Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis. Science 2019; 364 (6435): 89-93
  • 91 Ståhl PL, Salmén F, Vickovic S. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 2016; 353 (6294): 78-82
  • 92 van Dijk D, Sharma R, Nainys J. et al. Recovering gene interactions from single-cell data using data diffusion. Cell 2018; 174 (03) 716-729.e27
  • 93 McGinnis CS, Murrow LM, Gartner ZJ. DoubletFinder: doublet detection in single-cell RNA sequencing data using artificial nearest neighbors. Cell Syst 2019; 8 (04) 329-337.e4
  • 94 Aran D, Looney AP, Liu L. et al. Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage. Nat Immunol 2019; 20 (02) 163-172
  • 95 Zhang AW, O'Flanagan C, Chavez E. et al. Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers. Nat Methods 2019; 16 (10) 1007-1015
  • 96 Patel AP, Tirosh I, Trombetta JJ. et al. Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma. Science 2014; 344 (6190): 1396-1401
  • 97 Singer J, Kuipers J, Jahn K, Beerenwinkel N. Single-cell mutation identification via phylogenetic inference. Nat Commun 2018; 9 (01) 5144
  • 98 La Manno G, Soldatov R, Zeisel A. et al. RNA velocity of single cells. Nature 2018; 560 (7719): 494-498
  • 99 Qiu X, Mao Q, Tang Y. et al. Reversed graph embedding resolves complex single-cell trajectories. Nat Methods 2017; 14 (10) 979-982
  • 100 Vento-Tormo R, Efremova M, Botting RA. et al. Single-cell reconstruction of the early maternal-fetal interface in humans. Nature 2018; 563 (7731): 347-353
  • 101 Satija R, Farrell JA, Gennert D, Schier AF, Regev A. Spatial reconstruction of single-cell gene expression data. Nat Biotechnol 2015; 33 (05) 495-502