Quantifying stimulus-response specificity to probe the functional state of macrophages.

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2023-03-15 Epub Date: 2023-01-18 DOI:10.1016/j.cels.2022.12.012
Katherine M Sheu, Aditya A Guru, Alexander Hoffmann
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Abstract

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 "stimulus-response specificity" (SRS), we developed a single-cell experimental workflow and analytical approaches based on information theory and machine learning. We found that the 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 it 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 SRS may be a basis for measuring the functional state of innate immune cells. A record of this paper's transparent peer review process is included in the supplemental information.

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量化刺激-反应特异性,探究巨噬细胞的功能状态。
免疫哨兵巨噬细胞通过数百个免疫反应基因启动对病原体的反应。每种免疫威胁都需要量身定制的反应,这表明刺激特异性基因表达能力是健康巨噬细胞的一个关键功能标志。为了量化这种被称为 "刺激-反应特异性"(SRS)的特性,我们开发了一种单细胞实验工作流程以及基于信息论和机器学习的分析方法。我们发现,巨噬细胞的反应特异性是由特异性免疫基因组合驱动的,这些基因显示出较低的细胞间异质性,并且是不同信号通路的靶标。反应特异性图谱 "是对多种刺激-反应分布的系统比较,极化细胞因子会明显改变反应特异性图谱,从而评估巨噬细胞的功能状态。事实上,老年小鼠和肥胖小鼠腹腔巨噬细胞的反应特异性曲线显示出特征性差异,这表明SRS可能是测量先天性免疫细胞功能状态的基础。本文的同行评审过程透明,其记录见补充信息。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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