A simple model for Lutz and Bujard's controllable promoters and its application for analyzing a simple genetic oscillator.

Q2 Medicine
C G Zamora-Chimal, E S Zeron
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Abstract

We develop an exact and flexible mathematical model for Lutz and Bujard's controllable promoters. It can be used as a building block for modeling genetic systems based on them. Special attention is paid to deduce all the model parameters from reported (in vitro) experimental data. We validate our model by comparing the regulatory ranges measured in vivo by Lutz and Bujard against the ranges predicted by the model, and which are calculated as the reporter activity obtained under inducing conditions divided by the activity measured under maximal repression. In particular, we verify Bond et al. assertion that the cooperativity between two lac operators can be assumed to be negligible when their central base pairs are separated by 22 or 32 bp [Gene repression by minimal lac loops in vivo, Nucleic Acids Res, 38 (2010) 8072-8082]. Moreover, we also find that the probability that two repressors LacI bind to these operators at the same time can be assumed to be negligible as well. We finally use the model for the promoter P(LlacO-1) to analyze a synthetic genetic oscillator recently build by Stricker et al. [A fast, robust and tunable synthetic gene oscillator, Nature, 456 (2008) 516-519].

Abstract Image

Abstract Image

Abstract Image

Lutz和Bujard可控启动子的简单模型及其在简单遗传振荡器分析中的应用。
我们为Lutz和Bujard的可控启动子建立了一个精确而灵活的数学模型。它可以用作基于它们的遗传系统建模的构建块。特别注意从报告的(体外)实验数据中推导出所有模型参数。我们通过比较Lutz和Bujard在体内测量的调节范围与模型预测的范围来验证我们的模型,模型预测的范围是在诱导条件下获得的报告细胞活性除以在最大抑制条件下测量的活性。特别是,我们验证了Bond等人的断言,即当两个lac操作子的中心碱基对相隔22或32 bp时,它们之间的协同性可以被认为是可以忽略不计的[体内最小lac环的基因抑制,核酸研究,38(2010)8072-8082]。此外,我们还发现两个阻遏子LacI同时结合到这些操作符的概率也可以假设为可以忽略不计。我们最后使用启动子P(LlacO-1)的模型来分析最近由Stricker等人构建的合成基因振荡器[一个快速,稳健和可调的合成基因振荡器,Nature, 456(2008) 516-519]。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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