Department of Electrical Engineering, Indian Institute of Technology Bombay, Mumbai 400 076, India.
BMC Bioinformatics. 2010 Jan 18;11 Suppl 1(Suppl 1):S43. doi: 10.1186/1471-2105-11-S1-S43.
In the yeast Saccharomyces cerevisiae, interactions between galactose, Gal3p, Gal80p, and Gal4p determine the transcriptional status of the genes required for the galactose utilization. Increase in the cellular galactose concentration causes the galactose molecules to bind onto Gal3p which, via Gal80p, activates Gal4p, which induces the GAL3 and GAL80 gene transcription. Recently, a linear time-invariant multi-input multi-output (MIMO) model of this GAL regulatory network has been proposed; the inputs being galactose and Gal4p, and the outputs being the active Gal4p and galactose utilization. Unfortunately, this model assumes the cell culture to be homogeneous, although it is not so in practice. We overcome this drawback by including more biochemical reactions, and derive a quadratic ordinary differential equation (ODE) based model.
We show that the model, referred to above, does not exhibit bistability. We establish sufficiency conditions for the domain of attraction of an equilibrium point of our ODE model for the special case of full-state feedback controller. We observe that the GAL regulatory system of Kluyveromyces lactis exhibits an aberration of monotone nonlinearity and apply the Rantzer multipliers to establish a class of stabilizing controllers for this system.
Feedback in a GAL regulatory system can be used to enhance the cellular memory. We show that the system can be modeled as a quadratic nonlinear system for which the effect of feedback on the domain of attraction of the equilibrium point can be characterized using linear matrix inequality (LMI) conditions that are easily implementable in software. The benefit of this result is that a mathematically sound approach to the synthesis of full-state and partial-state feedback controllers to regulate the cellular memory is now possible, irrespective of the number of state-variables or parameters of interest.
在酵母酿酒酵母中,半乳糖、Gal3p、Gal80p 和 Gal4p 之间的相互作用决定了半乳糖利用所需基因的转录状态。细胞内半乳糖浓度的增加会导致半乳糖分子与 Gal3p 结合,Gal3p 通过 Gal80p 激活 Gal4p,从而诱导 GAL3 和 GAL80 基因的转录。最近,提出了这个 GAL 调控网络的线性时不变多输入多输出(MIMO)模型;输入为半乳糖和 Gal4p,输出为活性 Gal4p 和半乳糖利用。不幸的是,该模型假设细胞培养是均匀的,而实际上并非如此。我们通过包含更多的生化反应来克服这一缺点,并推导出基于二次常微分方程(ODE)的模型。
我们表明,上述模型不表现出双稳性。对于全状态反馈控制器的特殊情况,我们建立了 ODE 模型平衡点吸引域的充分条件。我们观察到,克鲁维酵母的 GAL 调控系统表现出单调非线性的异常,并应用 Rantzer 乘数为该系统建立了一类稳定控制器。
GAL 调控系统中的反馈可用于增强细胞记忆。我们表明,该系统可以被建模为一个二次非线性系统,其反馈对平衡点吸引域的影响可以使用易于在软件中实现的线性矩阵不等式(LMI)条件来描述。该结果的优点是,现在可以使用一种合理的数学方法来综合全状态和部分状态反馈控制器,以调节细胞记忆,而与感兴趣的状态变量或参数的数量无关。