Dynamics and Bifurcations of Population Structures Induced by Cell Cycle Feedback

描述(申请人提供)：法定人数、密度或效率感知以及其他形式的细胞间通信已被发现影响许多在生物学、医学和人类健康中重要的生理过程。在酵母中的研究表明，依赖于细胞周期的非局部形式的反馈可以产生振荡的种群密度。在具有和不具有随机性的各种模型上观察到的数学结果表明，这种现象是稳健的。当细胞周期的一个部分(G0，G1，S，G2，M)的细胞通过代谢物和/或信息素与另一部分的细胞沟通时，就会观察到这种现象，结果是后者的种群经历了生长速度的加快和/或延迟。提前或延迟的结果是人口密度变得多模式和集群化。(想一想红绿灯是如何产生成群的汽车的。)实验数据支持这样的观察，即这种形式的反馈产生了一簇簇伪同步的细胞，它们一致地穿过细胞周期。我们以前的工作表明，细胞周期内信号和响应区的大小和位置，以及细胞年龄，都会影响出现簇的整数个。这些因素表明，细胞周期的几何形状比反馈的明确形式和强度更具影响力。通过(1)狭隘地关注涉及密度依赖和细胞周期几何的现象学反馈模型，以及(2)将测量与建模和分析紧密结合，我们将在理解集群种群现象方面取得进展，并在这种背景下为描述集群数量如何对外部和遗传变异做出反应的分歧理论奠定基础。振荡的种群密度可以在实验室和临床上被用来延长细胞周期同步性或降低蛋白质纯化的成本。从生物分子和生物标记物的诊断性测量到肿瘤进展的代谢研究，几乎任何涉及增殖细胞群体的分析都可以发现细胞周期依赖性。能够预测和分解种群结构影响的模型很可能在系统生物学和生物医学中有用。

DESCRIPTION (provided by applicant): Quorum, density or efficiency sensing, as well as other forms of inter-cellular communication, have been found to impact many of the physiological processes that are important in biology, medicine and human health. Working in yeast we have shown that cell cycle dependent feedback of a non-local form can produce an oscillating population density. The mathematical results, observed across a wide range of models, with and without randomness, suggest that the phenomena is robust. The phenomenon is observed when cells in one part of the cell cycle (G0,G1,S,G2,M) communicate with cells in another via metabolites and/or pheromones, with the consequence that the later population experiences advances and/or delays in their growth rate. The outcome of the advances or delays is that the population density becomes multi-modal and clustered. (Consider how traffic lights produce clusters of cars.) Experimental data support the observation that feedback of this form produces clusters of pseudo-synchronized cells that traverse the cell cycle in unison. Our prior work shows that the size and location of signaling and responsive regions within the cell cycle, and cell age, influences the integer number of emergent clusters. These factors suggests a picture in which the geometry of the cell cycle is more influential than the explicit form and strength of the feedback. By (1) focusing narrowly on phenomenological models of feedback that involve density dependence and the geometry of the cell cycle, and (2) tightly coupling measurement with modeling and analysis, we will make progress toward understanding the phenomenon of clustered populations and lay the foundations of a bifurcation theory in this setting that describes how the number of clusters can and will respond to external and genetic variation. Oscillating population density can be exploited in the laboratory and the clinic to prolong cell cycle synchrony or to reduce the cost of protein purification. Cell cycle dependence can con found virtually any assay involving populations of proliferating cells, from diagnostic measurements of bio molecules and biomarkers to metabolic studies of tumor progression. Models that can predict and de convolve the effects of population structure are likely to be useful across systems biology and biomedicine.