论文标题
部分可观测时空混沌系统的无模型预测
Physical modeling of ribosomes along messenger RNA: estimating kinetic parameters from ribosome profiling experiments using a ballistic model
论文作者
论文摘要
基因表达包括从DNA上编码的信息合成蛋白质。基因表达的两个主要步骤之一是将信使RNA(mRNA)转化为氨基酸多肽序列。在这里,通过考虑mRNA降解,我们使用弹道模型对核糖体沿mRNA的运动进行建模,其中颗粒沿细丝前进而没有排除体积相互作用。以前已经使用了运输的单向模型来适应通过实验性核糖测序(Ribo-Seq)技术获得的核糖体的平均密度。在这种情况下,逆拟合可以访问动力学速率:依赖位置的速度和核糖体进入mRNA的速度。但是,降解速率并未考虑,需要来自不同实验的实验数据才能具有足够的参数以进行拟合。在这里,我们提出了一个完全新颖的实验设置和理论框架,包括将mRNA分为类别,具体取决于核糖体的数量到四到四。我们通过分析每个mRNA固定数量的核糖体,研究不同的降解状态,并提出了反拟合质量的标准。提出的方法对mRNA降解率具有很高的灵敏度。来自使用单子体(单核糖体)和多核糖体(任意数)核糖元素轮廓的其他方程式,使我们能够根据实验可访问的mRNA降解速率确定所有动力学速率。
Gene expression consists in the synthesis of proteins from the information encoded on DNA. One of the two main steps of gene expression is the translation of messenger RNA (mRNA) into polypeptide sequences of amino acids. Here, by taking into account mRNA degradation, we model the motion of ribosomes along mRNA with a ballistic model where particles advance along a filament without excluded volume interactions. Unidirectional models of transport have previously been used to fit the average density of ribosomes obtained by the experimental ribo-sequencing (Ribo-seq) technique. In this case an inverse fit gives access to the kinetic rates: the position-dependent speeds and the entry rate of ribosomes onto mRNA. The degradation rate is not, however, accounted for and experimental data from different experiments are needed to have enough parameters for the fit. Here, we propose an entirely novel experimental setup and theoretical framework consisting in splitting the mRNAs into categories depending on the number of ribosomes from one to four. We solve analytically the ballistic model for a fixed number of ribosomes per mRNA, study the different regimes of degradation, and propose a criteria for the quality of the inverse fit. The proposed method provides a high sensitivity to the mRNA degradation rate. The additional equations coming from using the monosome (single ribosome) and polysome (arbitrary number) ribo-seq profiles enable us to determine all the kinetic rates in terms of the experimentally accessible mRNA degradation rate.