System identification of signaling dependent gene expression with different time-scale data.
System identification of signaling dependent gene expression with different time-scale data.
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DOI：
10.1371/journal.pcbi.1005913
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发表时间：
2017-12
影响因子：
4.3
通讯作者：
Kuroda S
中科院分区：
文献类型：
--
作者：
Tsuchiya T;Fujii M;Matsuda N;Kunida K;Uda S;Kubota H;Konishi K;Kuroda S
细胞通过下游基因表达解码信号激活的信息，在几十分钟的尺度上，在数小时到数天的尺度上，导致细胞分化等细胞命运决定。然而，目前还没有适用于如此不同时间尺度的系统识别方法。本文采用压缩感知技术，通过恢复缺失时间点的信号，建立了一种基于不同时间尺度数据的系统识别方法。我们测量了PC12细胞分化过程中ERK和CREB的磷酸化、即时早期基因表达产物以及神经突伸长解码基因的mrna，并进行了系统鉴定，揭示了信号和基因表达之间的输入-输出关系，具有分级或开关样反应的敏感性，以及时滞和增益，代表了信号传递效率。我们使用药理学扰动预测并验证了鉴定的系统。因此，我们提供了一种使用不同时间尺度的数据进行系统识别的通用方法。本研究的重点有两点：第一点是细胞分化的解码机制。我们之前在PC12细胞中通过短暂和持续的ERK激活证明了细胞命运决定信息的编码机制，并发现了PC12细胞分化所必需的解码基因，包括Metrnl、Dclk1和Serpinb1a，这些基因被称为LP （latent process）基因，它们是神经突长度信息的解码者。重要的是，LP基因的表达水平，而不是ERK的磷酸化水平，与神经突长度相关。因此，LP基因表达对信号活性的解码机制是理解细胞分化机制的关键问题。本研究通过建立系统鉴定方法，鉴定了LP基因表达的选择性NGF-和pacap -信号解码系统对神经突延伸的影响。第二点是建模。细胞通过下游基因表达解码信号激活的信息，在几十分钟的尺度上，在数小时到数天的尺度上，导致细胞分化等细胞命运决定。然而，目前还没有适用于如此不同时间尺度的系统识别方法。在这里，我们开发了一种压缩感知领域的信号恢复技术，该技术最初是为图像分析而开发的，用于不同时间尺度的信号和基因表达的生物稀疏数据。
Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input–output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales. The key points of this study are two-fold: The first point is the decoding mechanism for cell differentiation. We previously demonstrated the encoding mechanism of cell fate decision information by transient and sustained ERK activation in PC12 cells, and also identified the decoding genes essential for cell differentiation in PC12 cells, including Metrnl, Dclk1, and Serpinb1a, denoted as LP (latent process) genes, which are the decoders of neurite length information. Importantly, the expression levels of the LP genes, but not the phosphorylation level of ERK, correlate with neurite length. Thus, the decoding mechanism of signaling activities by LP gene expression is a key issue for understanding the mechanism of cell differentiation. Here we identified a selective NGF- and PACAP-signaling decoding system by LP gene expression for neurite extension by developing a system identification method. The second point is the modeling. Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we developed a signal recovery technique in the field of compressed sensing originally developed for image analysis to biological sparse data of different time scales of signaling and gene expression.
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影响因子：
8.8
作者：
Filippi S;Barnes CP;Kirk PD;Kudo T;Kunida K;McMahon SS;Tsuchiya T;Wada T;Kuroda S;Stumpf MP
通讯作者：
Stumpf MP
影响因子：
3
作者：
Candes, Emmanuel J.;Fernandez-Granda, Carlos
通讯作者：
Fernandez-Granda, Carlos
影响因子：
4
作者：
Behar, Marcelo;Hoffmann, Alexander
通讯作者：
Hoffmann, Alexander
影响因子：
4
作者：
Janes, Kevin A.;Lauffenburger, Douglas A.
通讯作者：
Lauffenburger, Douglas A.
影响因子：
3
作者：
Candes, Emmanuel J.;Recht, Benjamin
通讯作者：
Recht, Benjamin