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Gaining a better understanding of autoprotection against drug-induced liver injury (DILI) may provide new strategies for its prevention and therapy. However, little is known about the underlying mechanisms of this phenomenon. We used single-cell RNA sequencing to characterize the dynamics and functions of hepatic non-parenchymal cells (NPCs) in autoprotection against DILI, using acetaminophen (APAP) as a model drug. Autoprotection was modeled through pretreatment with a mildly hepatotoxic dose of APAP in mice, followed by a higher dose in a secondary challenge. NPC subsets and dynamic changes were identified in the APAP (hepatotoxicity-sensitive) and APAP-resistant (hepatotoxicity-resistant) groups. A chemokine (C-C motif) ligand 2+ endothelial cell subset almost disappeared in the APAP-resistant group, and an R-spondin 3+ endothelial cell subset promoted hepatocyte proliferation and played an important role in APAP autoprotection. Moreover, the dendritic cell subset DC-3 may protect the liver from APAP hepatotoxicity by inducing low reactivity and suppressing the autoimmune response and occurrence of inflammation. DC-3 cells also promoted angiogenesis through crosstalk with endothelial cells via vascular endothelial growth factor-associated ligand-receptor pairs and facilitated liver tissue repair in the APAP-resistant group. In addition, the natural killer cell subsets NK-3 and NK-4 and the Sca-1–CD62L+ natural killer T cell subset may promote autoprotection through interferon-γ-dependent pathways. Furthermore, macrophage and neutrophil subpopulations with anti-inflammatory phenotypes promoted tolerance to APAP hepatotoxicity. Overall, this study reveals the dynamics of NPCs in the resistance to APAP hepatotoxicity and provides novel insights into the mechanism of autoprotection against DILI at a high resolution.

COVID-19 has caused severe threats to lives and damage to property worldwide. The immunopathology of the disease is of particular concern. Currently, researchers have used gene co-expression networks (GCNs) to deepen the study of molecular mechanisms of immune responses to COVID-19. However, most efforts have not fully explored dynamic changes of cell-type-specific molecular networks in the disease process. This study proposes a GCN construction pipeline named single-cell Disease Progression cellular module analysis (scDisProcema), which can trace dynamic changes of immune system response during disease progression using single-cell data. Here, scDisProcema considers changes in cell fate and expression patterns during disease development, identifying gene modules responsible for different immune cells. The hub genes are screened for each module by the specific expression level and the intercellular connectivity of modules. Based on functional items enriched by each gene module, we elucidate the biological processes of different cells involved in disease development and explain the molecular mechanisms underlying the process of cell depletion or proliferation caused by disease. Compared with traditional WGCNA methods, scDisProcema can make more convenient use of the heterogeneity information provided by scRNA-seq data and has great potential in exploring molecular changes during disease progression and organ development.