Single-cell profiling reveals distinct immune phenotypes that contribute to ischaemia-reperfusion injury after steatotic liver transplantation
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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. Keywords: fatty graft; ischaemia-reperfusion injury; liver transplantation; single-cell RNA-sequencing.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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