Dynamics and Bifurcations of Population Structures Induced by Cell Cycle Feedback

描述（由申请人提供）：已发现群体、密度或效率感测以及其他形式的细胞间通信影响生物学、医学和人类健康中重要的许多生理过程。在酵母中的工作，我们已经表明，细胞周期依赖的反馈的非本地形式可以产生振荡的人口密度。在广泛的模型中观察到的数学结果，无论有无随机性，都表明这种现象是稳健的。当细胞周期的一部分（G 0、G1、S、G2、M）中的细胞通过代谢物和/或信息素与另一部分中的细胞通信时，观察到该现象，结果是后面的群体经历其生长速率的进展和/或延迟。提前或延迟的结果是人口密度变得多模式和聚集。（想想交通信号灯是如何产生汽车集群的。）实验数据支持这样的观察，即这种形式的反馈产生一致地穿过细胞周期的伪同步细胞簇。我们先前的工作表明，细胞周期内信号和响应区域的大小和位置以及细胞年龄影响了出现的集群的整数。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有影响力。通过（1）专注于反馈的现象学模型，包括密度依赖性和细胞周期的几何形状，以及（2）将测量与建模和分析紧密耦合，我们将朝着理解集群种群现象取得进展，并在这种情况下奠定分叉理论的基础，描述集群的数量如何能够并将对外部和遗传变异做出反应。在实验室和临床中，可以利用振荡群体密度来延长细胞周期同步性或降低蛋白质纯化的成本。细胞周期依赖性几乎可以混淆涉及增殖细胞群体的任何测定，从生物分子和生物标志物的诊断测量到肿瘤进展的代谢研究。能够预测和去卷积种群结构影响的模型可能在系统生物学和生物医学中很有用。公共卫生相关性：单个微生物、病原体和肿瘤细胞的行为受到生长和分裂过程的影响。当在群体中观察时，这种变化可能会影响测试和实验的结果。群体内的变异可以受到群体成员之间的交流的影响。因此，生长和分裂过程的模型以及它们如何受到传播的影响对于正确解释测试和实验是重要的。

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. PUBLIC HEALTH RELEVANCE: The behavior of individual microorganisms, pathogens and tumor cells is influenced by the process of growth and division. When observed in populations, as is normal the case, this variation can influence the outcome of tests and experiments. The variation within a population can be influenced by communication among members of the population. Therefore, models of the process of growth and division and how they are effected bv communication is important for the correct interpretation of tests and experiments