The complex signaling dynamics of transcription factors can encode both qualitative and quantitative information about the extracellular environment, which increases the information transfer capacity and potentially supports accurate cellular decision-making. An important question is how these signaling dynamics patterns are translated into functionally appropriate gene regulation programs. To address this question for transcription factors of the nuclear factor κB (NF-κB) family, we profiled the single-cell dynamics of two major NF-κB subunits, RelA and c-Rel, induced by a panel of pathogen-derived stimuli in immune and nonimmune cellular contexts. Diverse NF-κB-activating ligands produced different patterns of RelA and c-Rel signaling dynamic features, such as variations in duration or time-integrated activity. Analysis of nascent transcripts delineated putative direct targets of NF-κB as compared to genes controlled by other transcriptional and posttranscriptional mechanisms and showed that the transcription of more than half of the induced genes was tightly linked to specific dynamic features of NF-κB signaling. Fibroblast and macrophage cell lines shared a cluster of such "NF-κB dynamics-decoding" genes, as well as cell type-specific decoding genes. Dissecting the subunit specificity of dynamics-decoding genes suggested that target genes were most often linked to both RelA and c-Rel or to RelA alone. Thus, our analysis reveals the cell type-specific interpretation of pathogenic information through the signaling dynamics of NF-κB.

中文翻译：

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综合分析表明 NF-κB 动力学的细胞类型特异性解码。

转录因子的复杂信号动力学可以编码关于细胞外环境的定性和定量信息，这增加了信息传递能力并可能支持准确的细胞决策。一个重要的问题是这些信号动力学模式如何转化为功能上合适的基因调控程序。为了解决核因子 κB (NF-κB) 家族转录因子的这个问题，我们分析了由一组病原体衍生刺激诱导的两个主要 NF-κB 亚基 RelA 和 c-Rel 的单细胞动力学。免疫和非免疫细胞环境。不同的 NF-κB 激活配体产生不同模式的 RelA 和 c-Rel 信号动态特征，例如持续时间或时间积分活动的变化。与受其他转录和转录后机制控制的基因相比，对新生转录物的分析描绘了 NF-κB 的假定直接靶标，并表明超过一半的诱导基因的转录与 NF-κB 信号传导的特定动态特征密切相关。成纤维细胞和巨噬细胞系共享一组此类“NF-κB 动力学解码”基因，以及细胞类型特异性解码基因。剖析动力学解码基因的亚基特异性表明，靶基因最常与 RelA 和 c-Rel 或单独与 RelA 相关联。因此，我们的分析通过 NF-κB 的信号动力学揭示了致病信息的细胞类型特异性解释。