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Abstract A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube ( https://github.com/ZJUFanLab/scCube ), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications.

Abstract Understanding the endogenous mechanism of adaptive response to drug‐induced liver injury (arDILI) may discover innovative strategies to manage DILI. To gain mechanistic insight into arDILI, we investigated exosomal miRNAs in the adaptive response to toosendanin‐induced liver injury (TILI) of mice. Exosomal miR‐106b‐5p was identified as a specific regulator of arDILI by comprehensive miRNA profiling. Outstandingly, miR‐106b‐5p agomir treatment alleviated TILI and other DILI by inhibiting apoptosis and promoting hepatocyte proliferation. Conversely, antagomir treatments had opposite effects, indicating that miR‐106b‐5p protects mice from liver injury. Injured hepatocytes released miR‐106b‐5p‐enriched exosomes taken up by surrounding hepatocytes. Vim (encodes vimentin) was identified as an important target of miR‐106b‐5p by dual luciferase reporter and siRNA assays. Furthermore, single‐cell RNA‐sequencing analysis of toosendanin‐injured mouse liver revealed a cluster of Vim+ hepatocytes; nonetheless declined following miR‐106b‐5p cotreatment. More importantly, Vim knockout protected mice from acetaminophen poisoning and TILI. In the clinic, serum miR‐106b‐5p expression levels correlated with the severity of DILI. Indeed, liver biopsies of clinical cases exposed to different DILI causing drugs revealed marked vimentin expression among harmed hepatocytes, confirming clinical relevance. Together, we report mechanisms of arDILI whereby miR‐106b‐5p safeguards restorative tissue repair by targeting vimentin.

Backgroud: Thymic atrophy marks the onset of immune aging, precipitating developmental anomalies in T cells. Numerous clinical and preclinical investigations have underscored the regulatory role of Ganoderma lucidum spores (GLS) in T cell development. However, the precise mechanisms underlying this regulation remain elusive.Methods: In this study, a mice model of estradiol benzoate (EB)-induced thymic atrophy was constructed, and the improvement effect of GLS on thymic atrophy was evaluated. Then, we employs multi-omics techniques to elucidate how GLS modulates T cell development amidst EB-induced thymic atrophy in mice.Results: GLS effectively mitigates EB-induced thymic damage by attenuating apoptotic thymic epithelial cells (TECs) and enhancing the output of CD4+ T cells into peripheral blood. During thymic T cell development, sporoderm-removed GLS (RGLS) promotes T cell receptor (TCR) α rearrangement by augmenting V-J fragment rearrangement frequency and efficiency. Notably, biased Vα14-Jα18 rearrangement fosters double-positive (DP) to invariant natural killer T (iNKT) cell differentiation, partially contingent on RGLS-mediated restriction of peptide-major histocompatibility complex I (pMHCⅠ)-CD8 interaction and augmented CD1d expression in DP thymocytes, thereby promoting DP to CD4+ iNKT cell development. Furthermore, RGLS amplifies interaction between a DP subpopulation, termed DPsel-7, and plasmacytoid dendritic cells (pDCs), likely facilitating the subsequent development of double-negative iNKT1 cells. Lastly, RGLS suppresses EB-induced upregulation of Abpob and Apoa4, curbing the clearance of CD4+Abpob+ and CD4+Apoa4+ T cells by mTECs, resulting in enhanced CD4+ T cell output.Discussion: These findings indicate that the RGLS effectively mitigates EB-induced TEC apoptosis and compromised double-positive thymocyte development. These insights into RGLS’s immunoregulatory role pave the way for its potential as a T-cell regeneration inducer.

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.

Panax ginseng (PG) and Panax notoginseng (PN) are highly valuable Chinese medicines (CM). Although both CMs have similar active constituents, their clinical applications are clearly different. Over the past decade, RNA sequencing (RNA-seq) analysis has been employed to investigate the molecular mechanisms of extracts or monomers. However, owing to the limited number of samples in standard RNA-seq, few studies have systematically compared the effects of PG and PN spanning multiple conditions at the transcriptomic level. Here, we developed an approach that simultaneously profiles transcriptome changes for multiplexed samples using RNA-seq (TCM-seq), a high-throughput, low-cost workflow to molecularly evaluate CM perturbations. A species-mixing experiment was conducted to illustrate the accuracy of sample multiplexing in TCM-seq. Transcriptomes from repeated samples were used to verify the robustness of TCM-seq. We then focused on the primary active components, Panax notoginseng saponins (PNS) and Panax ginseng saponins (PGS) extracted from PN and PG, respectively. We also characterized the transcriptome changes of 10 cell lines, treated with four different doses of PNS and PGS, using TCM-seq to compare the differences in their perturbing effects on genes, functional pathways, gene modules, and molecular networks. The results of transcriptional data analysis showed that the transcriptional patterns of various cell lines were significantly distinct. PGS exhibited a stronger regulatory effect on genes involved in cardiovascular disease, whereas PNS resulted in a greater coagulation effect on vascular endothelial cells. This study proposes a paradigm to comprehensively explore the differences in mechanisms of action between CMs based on transcriptome readouts.

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.