定量分析调控人类免疫缺陷病毒潜伏与激活的动力学机制

目的 治疗艾滋病最大的障碍在于无法根除人类免疫缺陷病毒（HIV）潜伏于人体细胞所形成的病毒存储库。构建描述病毒存储库建立分子机制的动力学模型需考虑生物体内的噪声环境和多重影响因素,本文通过一种全新的动力学结构分解方法将随机微分方程的确定性部分与随机性噪声分开,从而在仅需分析常微分方程不动点的情况下即可判断不同药物靶点的作用效果。方法 使用连续的随机微分方程构建了HIV转录过程的动力学模型,简化了描述系统所需方程的维度,增大了模型的可探索空间,在此基础上,通过计算得到的势能函数和概率分布函数直观表示病毒潜伏与激活的不同表达状态以及它们之间的关系。结果 定量分析了不同动力学参数对系统稳态和势函数的影响程度,分别得到了系统处于双稳态和单稳态时的参数范围,并将不同因素对动力系统分岔的影响程度与生物学实验结果对比,验证了本工作的理论基础。结论 本文突破了以往离散、随机的方法,可以通过常微分方程定量分析HIV转录调控的动力学机制,有利于推广到处理高维情况,进一步研究艾滋病在生物体内的发生发展,从而指导设计实验寻找临床上的治疗方案。     

Regulation of Torpor in the Gray Mouse Lemur:Transcriptional and Translational Controls and Role of AMPK Signaling

The gray mouse lemur (Microcebus murinus) is one of few primate species that is able to enter daily torpor or prolonged hibernation in response to environmental stresses. With an emerg-ing significance...     

Biologically meaningful update rules increase the critical connectivity of generalized Kauffman networks

We generalize random Boolean networks by softening the hard binary discretization into multiple discrete states. These multistate networks are generic models of gene regulatory networks, where each gene is known to assume a finite number of functionally different expression levels. We analytically determine the critical connectivity that separates the biologically unfavorable frozen and chaotic regimes. This connectivity is inversely proportional to a parameter which measures the heterogeneity of the update rules. Interestingly, the latter does not necessarily increase with the mean number of discrete states per node. Still, allowing for multiple states decreases the critical connectivity as compared to random Boolean networks, and thus leads to biologically unrealistic situations.Therefore, we study two approaches to increase the critical connectivity. First, we demonstrate that each network can be kept in its frozen regime by sufficiently biasing the update rules. Second, we restrict the randomly chosen update rules to a subclass of biologically more meaningful functions. These functions are characterized based on a thermodynamic model of gene regulation. We analytically show that their usage indeed increases the critical connectivity. From a general point of view, our thermodynamic considerations link discrete and continuous models of gene regulatory networks.