Unraveling the Complexity of Liver Disease One Cell at a Time

Abstract

The human liver is a complex organ made up of multiple specialized cell types that carry out key physiological functions. An incomplete understanding of liver biology limits our ability to develop therapeutics to prevent chronic liver diseases, liver cancers, and death as a result of organ failure. Recently, single-cell modalities have expanded our understanding of the cellular phenotypic heterogeneity and intercellular cross-talk in liver health and disease. This review summarizes these findings and looks forward to highlighting new avenues for the application of single-cell genomics to unravel unknown pathogenic pathways and disease mechanisms for the development of new therapeutics targeting liver pathology. As these technologies mature, their integration into clinical data analysis will aid in patient stratification and in developing treatment plans for patients suffering from liver disease.

Fig. 1

Single-cell experimental and analysis workflow. (A) Spatial transcriptomics: liver tissue samples are sectioned, and transcripts are barcoded according to their location based on a matrix of spots. These barcodes are then used to spatially resolve gene signatures across the tissue section. (B) Droplet-based experimental workflow: dissected tissues are dissociated into either single-cell or single-nucleus suspensions. CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing): cells can be tagged using oligo-labeled antibodies to link protein to RNA expression. ScATAC-seq: (single-cell assay for transposase-accessible chromatin with sequencing) is an unbiased, epigenetic regulation discovery tool that determines regions of open chromatin genomic DNA that are accessible to transcriptional machinery. Tn5 is used to sequentially cleave accessible DNA regions and to attach PCR amplification primers to generated barcoded accessible DNA fragments. RNA from single cells, DNA-oligomer labeled antibody-tagged cells, and single-nuclei or DNA from transposed nuclei are used to generate gene expression and accessible DNA libraries at a single-cell resolution through droplet-based experimental workflows such as the 10× genomics platform. Amplification of T and B cell receptor regions is used to link adaptive lymphocyte transcriptomes to their receptor sequences and determines clonal expansion. (C) Downstream analysis of these data relies on clustering to group cells together based on similarity of transcriptomic, proteomic, or epigenetic features. Trajectory inference analysis orders cells along a smooth continuous path of transcriptomic changes and can help deepen our understanding of cellular differentiation pathways and how cell states change with conditions. Differential gene expression analysis helps determine the genes directing these differences in cell type and or state and intracellular interaction analysis can be used to infer the pathways that cells use to communicate with each other in health and disease. GEX, gene expression; PCR, polymerase chain reaction; RT, reverse transcription; scRNA-seq, single-cell RNA-sequencing; snRNA-seq, single-nucleus RNA-sequencing; Tn5, Transposon Tn5.

Fig. 2

Single-cell technologies allow for a characterization of the molecular signals involved in spatial zonation across the hepatic lobule. As blood, oxygen and nutrients flow from the portal triad (made up of the portal vein, bile duct, and hepatic artery) to the central vein, functional specialization of major liver cells are mediated by key signaling pathways as indicated and intracellular crosstalk. Gene set enrichment analyses have revealed the biological pathways present in each zone of the liver, lending an insight into the changing functional specialization of hepatocytes with the gradient of oxygen and nutrients. In the healthy liver, fenestrations in the LSECs allow for the communication between Kupffer cells ( yellow ), hepatic stellate cells ( blue ), and hepatocytes. Panel: With fibrosis, there is a loss of fenestrations in the LSEC layer that prevents communication of hepatocytes and macrophages. Hepatic stellate cells secrete extracellular matrix proteins leading to a buildup of collagens in the tissue microenvironment. As a response to liver injury, chemokine release by LSECs and stellate cells results in increased monocyte ( green ) and T-cell infiltration ( purple ) to respond to and clear pathogens. HSCs: hepatic stellate cells; LSEC: liver sinusoidal endothelial cells; RBS: red blood cells.

Fig. 3

Future perspective in liver diseases: themes with potential applications of single-cell genomics. Hepatic lobules indicate different liver states in (A) steady state, (B) viral hepatitis, (C) fatty liver disease, (D) fibrosis, (E) cirrhosis, (Fi) hepatocellular carcinoma, and (Fii) intrahepatic cholangiocarcinoma and (G) autoimmune cholestatic liver diseases like primary sclerosing cholangitis (PSC) and primary biliary cholangitis (PBC). HBV, hepatitis B Virus; HSC: hepatic stellate cells; IBD, Inflammatory bowel disease; LSEC, liver sinusoidal endothelial cells.