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有读书笔记有附件Gene network dynamics controlling keratinocyte migration

2 gexiaoying 添加于 2010-4-12 15:16 | 2155 次阅读 | 0 个评论
  •  作 者

    Busch H, Camacho-Trullio D, Rogon Z, Breuhahn K, Angel P, Eils R, Szabowski A
  •  摘 要

    Translation of large-scale data into a coherent model that allows one to simulate, predict and control cellular behavior is far from being resolved. Assuming that long-term cellular behavior is reflected in the gene expression kinetics, we infer a dynamic gene regulatory network from time-series measurements of DNA microarray data of hepatocyte growth factor-induced migration of primary human keratinocytes. Transferring the obtained interactions to the level of signaling pathways, we predict in silico and verify in vitro the necessary and sufficient time-ordered events that control migration. We show that pulse-like activation of the proto-oncogene receptor Met triggers a responsive state, whereas time sequential activation of EGF-R is required to initiate and maintain migration. Context information for enhancing, delaying or stopping migration is provided by the activity of the protein kinase A signaling pathway. Our study reveals the complex orchestration of multiple pathways controlling cell migration.
  •  详细资料

    • 文献种类:期刊
    • 期刊名称: Molecular Systems Biology
    • 期刊缩写: Mol Syst Biol
    • 期卷页: 2008  4
    • ISBN: 1744-4292
  •  标 签

  • 相关链接 DOI URL 

  •  附 件

  •  gexiaoying 的文献笔记  订阅

    【原创】DNA转录成RNA,RNA翻译成蛋白质,蛋白质磷酸化,激活,泛素化,蛋白质定位。。。

    在生物受到刺激后,这些生物过程是在什么时间范围内完成的?

    这篇文章给出了生物分子发生作用的时间尺度,对于构建基因调控网络有指导意义。

    Cellular responses can be the result of either a single stimulus or a time-sequential activation of different signaling pathways upon an initial trigger signal (Janes et al, 2006). In the latter case, the response is most likely distributed over hours and requires the involvement of both protein signaling and gene regulation in a feedback-entangled process. Elucidating such a complex decision making is inherently difficult. It is hard to define and experimentally observe all required functional cellular components at a sufficiently high sampling rate. Furthermore, only a few detailed in silico models integrating both signaling and gene regulation have been developed so far (Yeang et al, 2005; Ernst et al, 2007).

     

    Assuming that long-term cellular behavior is reflected in the gene expression kinetics.Here, we propose a different complexity reduction approach based on the timescale separation of cellular events. Such events are encoded in the temporal modulation of molecule concentrations, that is, in changes of mRNA concentrations, protein complex formation, translocation in space, conformational changes or their molecular modifications. They occur on different timescales ranging from milliseconds to seconds (e.g. induced conformational changes) via seconds and minutes (e.g. post-translational protein modification) up to hours and days for gene expression kinetics and/or even years by epigenetic regulation.

     

    In this study, we consider a cellular decision that is reached on a timescale of hours. Thus, it is the protein turnover rate in the range of hours that is the slowest evolving variable. Furthermore, we assume the proportionality between protein and mRNA concentrations such that both evolve on the same timescale. Enhancement of the basal biochemical protein activities by post translational events occurs on a much shorter timescale in the order of minutes, for example, shifting the balances between a phosphorylated and nonphosphorylated form, formation and temporal presence of a multimeric protein complex or temporal translocation to its location of activity. Hence, adiabatically approximating these fast protein modulations and describing proteins in terms of their mRNA concentrations leads to the formulation of a gene regulatory network model, whose dynamics should provide information similar to a comprehensive protein interaction network (cf. Supplementary information for a detailed mathematical treatment). As a practical consequence, information on the former network can be easily accessed experimentally by time-resolved DNA microarray measurements.

    感谢invitrogen公司的技术支持告知这篇文章

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