Beyond Fibroblast Heterogeneity: What Single-Cell RNA Sequencing Tells Us.
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ABSTRACT:
SUBMITTER: Zhou Y
PROVIDER: S-EPMC6604221 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background & aimsThe multiple vital functions of the human liver are performed by highly specialised parenchymal and non-parenchymal cells organised in complex collaborative sinusoidal units. Although crucial for homeostasis, the cellular make-up of the human liver remains to be fully elucidated. Here, single-cell RNA-sequencing was used to unravel the heterogeneity of human liver cells, in particular of hepatocytes (HEPs) and hepatic stellate cells (HSCs).MethodThe transcriptome of ~25,000 freshly isolated human liver cells was profiled using droplet-based RNA-sequencing. Recently published data sets and RNA in situ hybridisation were integrated to validate and locate newly identified cell populations.ResultsIn total, 22 cell populations were annotated that reflected the heterogeneity of human parenchymal and non-parenchymal liver cells. More than 20,000 HEPs were ordered along the portocentral axis to confirm known, and reveal previously undescribed, zonated liver functions. The existence of 2 subpopulations of human HSCs with unique gene expression signatures and distinct intralobular localisation was revealed (i.e. portal and central vein-concentrated GPC3 + HSCs and perisinusoidally located DBH + HSCs). In particular, these data suggest that, although both subpopulations collaborate in the production and organisation of extracellular matrix, GPC3 + HSCs specifically express genes involved in the metabolism of glycosaminoglycans, whereas DBH + HSCs display a gene signature that is reminiscent of antigen-presenting cells.ConclusionsThis study highlights metabolic zonation as a key determinant of HEP transcriptomic heterogeneity and, for the first time, outlines the existence of heterogeneous HSC subpopulations in the human liver. These findings call for further research on the functional implications of liver cell heterogeneity in health and disease.Lay summaryThis study resolves the cellular landscape of the human liver in an unbiased manner and at high resolution to provide new insights into human liver cell biology. The results highlight the physiological heterogeneity of human hepatic stellate cells.
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Project description:Single-cell RNA sequencing is a powerful technology for assessing heterogeneity within defined cell populations. Here, we describe the heterogeneity of a B220+CD117intCD19-NK1.1- uncommitted hematopoietic progenitor having combined lymphoid and myeloid potential. Phenotypic and functional assays revealed four subpopulations within the progenitor with distinct lineage developmental potentials. Among them, the Ly6D+SiglecH-CD11c- fraction was lymphoid-restricted exhibiting strong B-cell potential, whereas the Ly6D-SiglecH-CD11c- fraction showed mixed lympho-myeloid potential. Single-cell RNA sequencing of these subsets revealed that the latter population comprised a mixture of cells with distinct lymphoid and myeloid transcriptional signatures and identified a subgroup as the potential precursor of Ly6D+SiglecH-CD11c- Subsequent functional assays confirmed that B220+CD117intCD19-NK1.1- single cells are, with rare exceptions, not bipotent for lymphoid and myeloid lineages. A B-cell priming gradient was observed within the Ly6D+SiglecH-CD11c- subset and we propose a herein newly identified subgroup as the direct precursor of the first B-cell committed stage. Therefore, the apparent multipotency of B220+CD117intCD19-NK1.1- progenitors results from underlying heterogeneity at the single-cell level and highlights the validity of single-cell transcriptomics for resolving cellular heterogeneity and developmental relationships among hematopoietic progenitors.
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Project description:The trillions of cells in the human body can be viewed as elementary but essential biological units that achieve different body states, but the low resolution of previous cell isolation and measurement approaches limits our understanding of the cell-specific molecular profiles. The recent establishment and rapid growth of single-cell sequencing technology has facilitated the identification of molecular profiles of heterogeneous cells, especially on the transcription level of single cells [single-cell RNA sequencing (scRNA-seq)]. As a novel method, the robustness of scRNA-seq under changing conditions will determine its practical potential in major research programs and clinical applications. In this review, we first briefly presented the scRNA-seq-related methods from the point of view of experiments and computation. Then, we compared several state-of-the-art scRNA-seq analysis frameworks mainly by analyzing their performance robustness on independent scRNA-seq datasets for the same complex disease. Finally, we elaborated on our hypothesis on consensus scRNA-seq analysis and summarized the potential indicative and predictive roles of individual cells in understanding disease heterogeneity by single-cell technologies.
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