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Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the mouse liver.

ABSTRACT: Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.

SUBMITTER: Hildebrandt F

PROVIDER: S-EPMC8640072 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the liver

Project description:Reconstruction of heterogeneity through single-cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we implement Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology. Additional data to reproduce the data presented in this study with instrctions can be found at https://github.com/almaan/ST-mLiver and https://zenodo.org/record/4399655

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Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the liver

Project description:Spatial Transcriptomics to define transcriptional patterns of zonation and structural components in the liver

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Glucagon contributes to liver zonation.

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Project description:Human hepatocytes differ in gene expression and function across the hexagonal lobules of the tissue microarchitecture, a phenomenon referred to as liver zonation. Hepatocytes also display intra-lobular differences in cell size, but to what extent zonal expression and function correlate with cell size in isolated human hepatocytes is not entirely clear. Here, we first used our accumulated experience of nearly 100 hepatocyte isolations to assess the impact of donor background and process parameters on hepatocyte quality. We observed substantial inter-batch variability in cell size distributions and a tendency for overall cell size to affect the outcome of hepatocyte isolation and cryopreservation. We further separated cells into different size fractions and analyzed them with label-free quantitative proteomics. This showed that protein abundances in different hepatocyte size fractions recapitulated the in vivo expression patterns of well-known zonal markers. We also found that proteins with sequential enrichment across fractions largely represented biological processes with known zonal specificity. This was confirmed by differences in the metabolic activity of zonated CYP enzymes. Altogether, our results show that hepatocyte size corresponds to zonal origin, and that our size fractionation approach can be used to study zone-specific liver functions in vitro.

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