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Temporal Decoding of MAP Kinase and CREB Phosphorylation by Selective Immediate Early Gene Expression

机译:map激酶和磷酸化CREB的即时解读通过选择性即早基因表达

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摘要

A wide range of growth factors encode information into specific temporal patterns of MAP kinase (MAPK) and CREB phosphorylation, which are further decoded by expression of immediate early gene products (IEGs) to exert biological functions. However, the IEG decoding system remain unknown. We built a data-driven based on time courses of MAPK and CREB phosphorylation and IEG expression in response to various growth factors to identify how signal is processed. We found that IEG expression uses common decoding systems regardless of growth factors and expression of each IEG differs in upstream dependency, switch-like response, and linear temporal filters. Pulsatile ERK phosphorylation was selectively decoded by expression of EGR1 rather than c-FOS. Conjunctive NGF and PACAP stimulation was selectively decoded by synergistic JUNB expression through switch-like response to c-FOS. Thus, specific temporal patterns and combinations of MAPKs and CREB phosphorylation can be decoded by selective IEG expression via distinct temporal filters and switch-like responses. The data-driven modeling is versatile for analysis of signal processing and does not require detailed prior knowledge of pathways.
机译:广泛的生长因子将信息编码为MAP激酶(MAPK)和CREB磷酸化的特定时间模式,这些信息通过立即早期基因产物(IEG)的表达进一步解码以发挥生物学功能。但是,IEG解码系统仍然未知。我们基于MAPK和CREB磷酸化以及IEG表达的时程建立了数据驱动的响应各种生长因子,以识别信号的处理方式。我们发现,无论增长因素如何,IEG表达式都使用通用的解码系统,并且每个IEG的表达式在上游依存关系,类开关响应和线性时间滤波器方面都不同。通过EGR1而不是c-FOS的表达选择性地解码了ERK的磷酸化。通过对c-FOS的开关样反应,通过协同JUNB表达选择性地解码联合NGF和PACAP刺激。因此,特定的时间模式以及MAPK和CREB磷酸化的组合可以通过选择性的IEG表达,通过不同的时间过滤器和类似开关的响应来解码。数据驱动的建模对于信号处理的分析是通用的,不需要详细的路径知识。

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