Single-cell gene expression profiles of mouse macrophages stimulated with immune ligands. Single-cell gene expression profiles of mouse macrophages stimulated with immune ligands
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https://www.ncbi.nlm.nih.gov/bioproject/PRJNA912189
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Immune sentinel macrophages initiate responses to pathogens via hundreds of immune response genes. Each immune threat demands a tailored response, suggesting that the capacity for stimulus-specific gene expression is a key functional hallmark of healthy macrophages. To quantify this property, termed Response Specificity, we developed a single-cell experimental workflow and analytical approaches based on information theory and machine learning. We found that Response Specificity of macrophages is driven by combinations of specific immune genes that show low cell-to-cell heterogeneity and are targets of separate signaling pathways. The Response Specificity Profile, a systematic comparison of multiple stimulus response distributions, was distinctly altered by polarizing cytokines and enabled an assessment of the functional state of macrophages. Indeed, the Response Specificity Profile of peritoneal macrophages from old and obese mice showed characteristic differences, suggesting that Response Specificity may be a basis for measuring the functional state of innate immune cells. Overall design: Macrophages were collected from the mouse peritoneum or differentiated from myeloid progenitors, and stimulated with a panel of immune ligands for 3hrs. Cells were collected into suspension and scRNAseq was performed using the BD Rhapsody platform.
免疫哨兵型巨噬细胞通过数百个免疫应答基因启动对病原体的免疫应答。每一种免疫威胁都需要定制化的应答反应,这表明刺激特异性基因表达能力是健康巨噬细胞的关键功能特征。为了量化这一被命名为应答特异性(Response Specificity)的特性,我们开发了一套单细胞实验流程以及基于信息论与机器学习的分析方法。我们发现,巨噬细胞的应答特异性由一系列特定免疫基因的组合所驱动:这些基因的细胞间异质性较低,且属于不同信号通路的靶基因。应答特异性特征谱(Response Specificity Profile)是对多种刺激应答分布的系统性比较,可因极化细胞因子而发生显著改变,且可用于评估巨噬细胞的功能状态。事实上,老年小鼠与肥胖小鼠腹腔巨噬细胞的应答特异性特征谱呈现出特征性差异,这表明应答特异性或可作为衡量先天免疫细胞功能状态的核心指标。实验整体设计:研究人员从小鼠腹腔中分离巨噬细胞,或从髓系祖细胞诱导分化获得巨噬细胞,随后用一组免疫配体刺激3小时。将细胞制备为单细胞悬液后,采用BD Rhapsody平台完成单细胞RNA测序(single-cell RNA sequencing,简称scRNAseq)。
创建时间:
2022-12-14



