A predictive model for transcriptional control of physiology in a free living cell
A predictive model for transcriptional control of physiology in a free living cell
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DOI：
10.1016/j.cell.2007.10.053
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发表时间：
2007-12-28
期刊：
影响因子：
64.5
通讯作者：
Baliga, Nitin S.
中科院分区：
文献类型：
--
作者：
Bonneau, Richard;Facciotti, Marc T.;Baliga, Nitin S.
环境显着影响了在生物体基因组中编码的所有组件的动态表达和组装中。我们通过数据驱动的发现与80％的基因和关键的非生物因子在其催眠盐环境中相似的调节和功能相互关系的发现，在盐酸盐NRC-1中构建了该过程的模型。使用72个转录因子和9个环境因子（EFS）中的相对变化，该模型准确地预测了所有这些基因的动态转录响应，这是147个新收集的实验，代表了完全新颖的遗传背景和环境，具有显着的网络完整性。使用此模型，我们构建了和测试的假设对这种生物体与其催眠盐环境的相互作用至关重要。这项研究支持这样的说法，即生物和EF网络内的高连通性将从相对适度的实验中为任何有机体构建相似的模型。
The environment significantly influences the dynamic expression and assembly of all components encoded in the genome of an organism into functional biological networks. We have constructed a model for this process in Halobacterium salinarum NRC-1 through the data-driven discovery of regulatory and functional interrelationships among similar to 80% of its genes and key abiotic factors in its hypersaline environment. Using relative changes in 72 transcription factors and 9 environmental factors (EFs) this model accurately predicts dynamic transcriptional responses of all these genes in 147 newly collected experiments representing completely novel genetic backgrounds and environments-suggesting a remarkable degree of network completeness. Using this model we have constructed and tested hypotheses critical to this organism's interaction with its changing hypersaline environment. This study supports the claim that the high degree of connectivity within biological and EF networks will enable the construction of similar models for any organism from relatively modest numbers of experiments.