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Single-cell genomics and spatial transcriptomics: Discovery of novel cell states and cellular interactions in liver physiology and disease biology.单细胞基因组学和空间转录组学:在肝生理学和疾病生物学中发现新的细胞状态和细胞相互作用。
J Hepatol. 2020 Nov;73(5):1219-1230. doi: 10.1016/j.jhep.2020.06.004. Epub 2020 Jun 10.
2
Multi-omics characterization of a diet-induced obese model of non-alcoholic steatohepatitis.多组学分析饮食诱导的非酒精性脂肪性肝炎肥胖模型。
Sci Rep. 2020 Jan 24;10(1):1148. doi: 10.1038/s41598-020-58059-7.
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ShinyGO: a graphical gene-set enrichment tool for animals and plants.ShinyGO:一个用于动植物的图形基因集富集工具。
Bioinformatics. 2020 Apr 15;36(8):2628-2629. doi: 10.1093/bioinformatics/btz931.
4
Single-Cell Transcriptomics Uncovers Zonation of Function in the Mesenchyme during Liver Fibrosis.单细胞转录组学揭示肝纤维化过程中间质功能的分区。
Cell Rep. 2019 Nov 12;29(7):1832-1847.e8. doi: 10.1016/j.celrep.2019.10.024.
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Resolving the fibrotic niche of human liver cirrhosis at single-cell level.解析人肝硬化的纤维性龛位于单细胞水平。
Nature. 2019 Nov;575(7783):512-518. doi: 10.1038/s41586-019-1631-3. Epub 2019 Oct 9.
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Landscape of Intercellular Crosstalk in Healthy and NASH Liver Revealed by Single-Cell Secretome Gene Analysis.单细胞分泌组基因分析揭示健康和 NASH 肝脏中的细胞间串扰景观。
Mol Cell. 2019 Aug 8;75(3):644-660.e5. doi: 10.1016/j.molcel.2019.07.028.
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Comprehensive Integration of Single-Cell Data.单细胞数据的综合整合。
Cell. 2019 Jun 13;177(7):1888-1902.e21. doi: 10.1016/j.cell.2019.05.031. Epub 2019 Jun 6.
8
Single Cell RNA Sequencing Identifies Subsets of Hepatic Stellate Cells and Myofibroblasts in Liver Fibrosis.单细胞 RNA 测序鉴定肝纤维化中肝星状细胞和肌成纤维细胞亚群。
Cells. 2019 May 24;8(5):503. doi: 10.3390/cells8050503.
9
Dimensionality reduction for visualizing single-cell data using UMAP.使用UMAP进行单细胞数据可视化的降维方法。
Nat Biotechnol. 2018 Dec 3. doi: 10.1038/nbt.4314.
10
Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations.单细胞 RNA 测序技术揭示了人类肝脏中独特的肝内巨噬细胞群体。
Nat Commun. 2018 Oct 22;9(1):4383. doi: 10.1038/s41467-018-06318-7.

整体刻画高脂肪饮食诱导的单细胞转录组反应。

Holistic characterization of single-hepatocyte transcriptome responses to high-fat diet.

机构信息

Department of Molecular and Integrative Physiology and Institute for Gerontology, University of Michigan Medical School, Ann Arbor, Michigan.

Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan.

出版信息

Am J Physiol Endocrinol Metab. 2021 Feb 1;320(2):E244-E258. doi: 10.1152/ajpendo.00391.2020. Epub 2020 Oct 26.

DOI:10.1152/ajpendo.00391.2020
PMID:33103450
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8260362/
Abstract

During nutritional overload and obesity, hepatocyte function is grossly altered, and a subset of hepatocytes begins to accumulate fat droplets, leading to nonalcoholic fatty liver disease (NAFLD). Recent single-cell studies revealed how nonparenchymal cells, such as macrophages, hepatic stellate cells, and endothelial cells, heterogeneously respond to NAFLD. However, it remains to be characterized how hepatocytes, the major constituents of the liver, respond to nutritional overload in NAFLD. Here, using droplet-based, single-cell RNA sequencing (Drop-seq), we characterized how the transcriptomic landscape of individual hepatocytes is altered in response to high-fat diet (HFD) and NAFLD. We showed that the entire hepatocyte population undergoes substantial transcriptome changes upon HFD, although the patterns of alteration were highly heterogeneous, with zonation-dependent and -independent effects. Periportal (zone 1) hepatocytes downregulated many zone 1-specific marker genes, whereas a small number of genes mediating gluconeogenesis were upregulated. Pericentral (zone 3) hepatocytes also downregulated many zone 3-specific genes; however, they upregulated several genes that promote HFD-induced fat droplet formation, consistent with findings that zone 3 hepatocytes accumulate more lipid droplets. Zone 3 hepatocytes also upregulated ketogenic pathways as an adaptive mechanism to HFD. Interestingly, many of the top HFD-induced genes, which encode proteins regulating lipid metabolism, were strongly co-expressed with each other in a subset of hepatocytes, producing a variegated pattern of spatial co-localization that is independent of metabolic zonation. In conclusion, our data set provides a useful resource for understanding hepatocellular alteration during NAFLD at single cell level.

摘要

在营养过剩和肥胖的情况下,肝细胞的功能会发生严重改变,一部分肝细胞开始积累脂肪滴,导致非酒精性脂肪性肝病(NAFLD)。最近的单细胞研究揭示了非实质细胞(如巨噬细胞、肝星状细胞和内皮细胞)如何异质地对 NAFLD 作出反应。然而,肝细胞(肝脏的主要组成部分)如何对 NAFLD 中的营养过载作出反应仍有待阐明。在这里,我们使用基于液滴的单细胞 RNA 测序(Drop-seq)技术,描述了个体肝细胞的转录组图谱如何在高脂肪饮食(HFD)和 NAFLD 中发生改变。我们发现,整个肝细胞群体在 HFD 作用下会发生显著的转录组变化,尽管改变的模式高度异质,存在与区域有关和无关的效应。门脉周围(区域 1)肝细胞下调了许多区域 1 特异性标记基因,而少数参与糖异生的基因则上调。近中轴(区域 3)肝细胞也下调了许多区域 3 特异性基因;然而,它们上调了几个促进 HFD 诱导脂肪滴形成的基因,这与区域 3 肝细胞积累更多脂肪滴的发现一致。区域 3 肝细胞还上调了生酮途径,作为对 HFD 的适应性机制。有趣的是,许多 HFD 诱导的基因,编码调节脂质代谢的蛋白质,在一部分肝细胞中强烈共表达,产生一种与代谢区域化无关的斑驳的空间共定位模式。总之,我们的数据集为在单细胞水平上理解 NAFLD 期间肝细胞的改变提供了有用的资源。