Single-cell profiling reveals distinct immune phenotypes that contribute to ischaemia-reperfusion injury after steatotic liver transplantation
Xinyu Yang,Di Lu,Rui Wang,Zhengxing Lian,Zuyuan Lin,Jianyong Zhuo,Hao Chen,Modan Yang,Winyen Tan,Mengfan Yang,Xuyong Wei,Qiang Wei,Shusen Zheng,Xiao Xu +13 more
TLDR
In this paper, a single-cell RNA-sequencing (scRNA-Seq) was carried out on 23,675 cells from transplanted rat livers to assess the functional properties, transcriptional regulation, phenotypic switching and cell-cell interactions of different cell subtypes.Abstract:
OBJECTIVES The discrepancy between supply and demand of organ has led to an increased utilization of steatotic liver for liver transplantation (LT). Hepatic steatosis, however, is a major risk factor for graft failure due to increased susceptibility to ischaemia-reperfusion (I/R) injury during transplantation. MATERIALS AND METHODS To assess the plasticity and phenotype of immune cells within the microenvironment of steatotic liver graft at single-cell level, single-cell RNA-sequencing (scRNA-Seq) was carried out on 23 675 cells from transplanted rat livers. Bioinformatic analyses and multiplex immunohistochemistry were performed to assess the functional properties, transcriptional regulation, phenotypic switching and cell-cell interactions of different cell subtypes. RESULTS We have identified 11 different cell types in transplanted livers and found that the highly complex ecosystem was shaped by myeloid-derived cell subsets that transit between different states and interact mutually. Notably, a pro-inflammatory phenotype of Kupffer cells (KCs) with high expression of colony-stimulating factor 3 (CSF3) that was enriched in transplanted steatotic livers was potentially participated in fatty graft injury. We have also detected a subset of dendritic cells (DCs) with highly expressing XCR1 that was correlated with CD8+ T cells, mediating the severer steatotic liver damage by I/R injury. CONCLUSIONS The findings of our study provide new insight into the mechanisms by which steatosis exacerbates liver damage from I/R injury. Interventions based on these observations create opportunities in attenuating fatty liver graft injury and expanding the donor pool.read more
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Heterogeneity and Function of Kupffer Cells in Liver Injury
Weiyang Li,Na Chang,Liying Li +2 more
TL;DR: Insight is afforded on heterogeneity and functions of KCs in liver injury using the existing findings to provide opportunities for the therapy of liver injury.
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Liver Organoids, Novel and Promising Modalities for Exploring and Repairing Liver Injury
Chiyu He,Di Lu,Zuyuan Lin,Hao Chen,Huigang Li,Xinyu Yang,Modan Yang,Kai Wang,Xuyong Wei,Shusen Zheng,Xiao Xu +10 more
TL;DR: Wang et al. as discussed by the authors reviewed the history of the development of liver organoids and summarized the application of liver organs and recent studies using organoids to explore and further repair the liver injury.
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Characterization and Proteomic Analyses of Proinflammatory Cytokines in a Mouse Model of Liver Transplant Rejection
Shi-Peng Li,Xin-Qiang Li,Xiao-Jie Chen,Jin-Ming Zhang,Guang-Peng Zhou,Liu-Xin Zhou,Hai-Qing Zhang,Li-Ying Sun,Zhi-Jun Zhu +8 more
TL;DR: Findings provide new insights into some of the critical factors associated with liver transplant rejection and thus offer new targets for the treatment and prevention of this condition.
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Cancer Risk and Mutational Patterns Following Organ Transplantation
TL;DR: The application of high-throughput sequencing and organoids in the field of organ transplantation, the mutational patterns of cancer genomes, and a new research strategy for understanding the mechanism of cancer following organ transplants are summarized.
Journal ArticleDOI
Revisiting transplant immunology through the lens of single-cell technologies
Arianna Barbetta,Brittany Rocque,Deepika N Sarode,Johanna M. Ascher Bartlett,Juliet Emamaullee +4 more
TL;DR: A review of single-cell techniques in the context of solid organ transplantation can be found in this article , where the authors present an optimal strategy to analyze and create predictive models using these complex datasets and will likely be essential for future clinical application of patient-level results based on singlecell data.
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