Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL 60637, USA; Medical Scientist Training Program, University of Chicago, Chicago, IL 60637, USA.
Pritzker School of Molecular Engineering, University of Chicago, Chicago, IL 60637, USA.
Cell Rep. 2022 Aug 16;40(7):111159. doi: 10.1016/j.celrep.2022.111159.
Many scenarios in cellular communication require cells to interpret multiple dynamic signals. It is unclear how exposure to inflammatory stimuli alters transcriptional responses to subsequent stimulus. Using high-throughput microfluidic live-cell analysis, we systematically profile the NF-κB response to different signal sequences in single cells. We find that NF-κB dynamics store the short-term history of received signals: depending on the prior pathogenic or cytokine signal, the NF-κB response to subsequent stimuli varies from no response to full activation. Using information theory, we reveal that these stimulus-dependent changes in the NF-κB response encode and reflect information about the identity and dose of the prior stimulus. Small-molecule inhibition, computational modeling, and gene expression profiling show that this encoding is driven by stimulus-dependent engagement of negative feedback modules. These results provide a model for how signal transduction networks process sequences of inflammatory stimuli to coordinate cellular responses in complex dynamic environments.
在细胞通讯的许多场景中，细胞需要解释多种动态信号。目前尚不清楚细胞暴露于炎症刺激后如何改变对后续刺激的转录反应。我们使用高通量微流控活细胞分析，系统地在单细胞中分析 NF-κB 对不同信号序列的反应。我们发现 NF-κB 动力学存储了接收到的信号的短期历史：根据先前的致病或细胞因子信号，NF-κB 对后续刺激的反应从无反应到完全激活不等。我们利用信息论揭示了 NF-κB 反应中这些依赖于刺激的变化，对先前刺激的身份和剂量进行了编码和反映。小分子抑制、计算建模和基因表达谱分析表明，这种编码是由刺激依赖性负反馈模块的参与驱动的。这些结果为信号转导网络如何处理炎症刺激序列以协调复杂动态环境中的细胞反应提供了模型。
