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Prediction of kinetic parameters from DNA-binding site sequences for modeling global transcription dynamics in Escherichia coli.

机译:从DNA结合位点序列的预测在大肠杆菌中的全局转录动力学序列中的动力学参数。

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摘要

The majority of dynamic gene regulatory network (GRN) models are comprised of only a few genes and do not take multiple transcription regulation into account. The models are conceived in this way in order to minimize the number of kinetic parameters. In this paper, we propose a new approach for predicting kinetic parameters from DNA-binding site sequences by correlating the protein-DNA-binding affinities with nucleotide sequence conservation. We present the dynamic modeling of the cra modulon transcription in Escherichia coli during glucose-limited fed-batch cultivation. The concentration of the Cra regulator protein inhibitor, fructose 1,6-bis(phosphate), decreases sharply, eventually leading to the repression of transcription. Total RNA concentration data indicate a strong regulation of transcription through the availability of RNA polymerase. A critical assessment of the results of the model simulations supports this finding. This new approach for the prediction of transcription dynamics may improve the metabolic engineering of gene regulation processes.
机译:大多数动态基因调节网络(GRN)模型仅由少数基因组成,并且不考虑多种转录规则。以这种方式构思模型,以最小化动力学参数的数量。在本文中,我们提出了一种通过将蛋白质-DNA结合亲和力与核苷酸序列守恒相关来预测来自DNA结合位点序列的动力学参数的新方法。我们在葡萄糖限制送入批量栽培中介绍了大肠杆菌CRA调节转录的动态建模。 CRA调节剂蛋白抑制剂的浓度,果糖1,6-双(磷酸盐),急剧降低,最终导致抑制转录。总RNA浓度数据通过RNA聚合酶的可用性表明转录的强烈调节。对模型模拟结果的关键评估支持此发现。这种预测转录动力学的新方法可以改善基因调控过程的代谢工程。

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