Adaptive Queueing in Intracellular Networks

对环境波动的快速和协调的反应以及在广泛条件下保持功能的能力是在生物界生存的关键。因此，生物采用复杂的调节策略，结合敏感性和稳健性来应对环境变化。通过最近对酶网络的研究，这种反应性的一个潜在机制是蛋白质丰度的排队效应。这种现象似乎在生物学中很普遍。本研究项目采用数学建模和合成生物学来探索和更好地理解这一机制及其在生物功能中的作用。本项目研究细胞内网络中的排队效应。当加工酶从负荷不足过渡到负荷过重时，相应的蛋白质丰度（队列）以高度协调的方式急剧增加。最近的一些观察表明，酶网络通常处于负荷不足和过载状态之间的平衡点附近，这使得它们对短暂的环境波动高度敏感和敏感。这种现象在生物学中似乎很普遍；此外，它应该通过适应性调节机制对广泛的环境条件进行高度优化。在这个项目中，研究人员将严格的数学分析与定量计算建模和合成生物学相结合，以确定机制，并探索适应性排队在细菌和酵母的小基因回路以及大细胞内酶网络动力学中的作用。研究人员利用他们在排队理论、随机动力学建模、鲁棒合成基因电路设计和微流体技术方面的综合专业知识，阐明和表征自适应排队在细菌和高等生物中作为一种快速灵活的信号转导和调节机制的作用。

Rapid and coordinated response to environmental fluctuations and the ability to maintain function in a broad range of conditions is a key to survival in the biological world. Therefore, organisms employ complex regulatory strategies that combine sensitivity and robustness in response to environmental changes. One potential mechanism for such responsiveness that has emerged through recent studies of enzymatic networks is a queueing effect in protein abundances. The phenomenon appears to be widespread in biology. This research project employs mathematical modeling and synthetic biology to explore and better understand this mechanism and its role in biological functions.This project investigates a queueing effect in intracellular networks. As processing enzymes transition from underloaded to overloaded conditions, the corresponding protein abundances (queues) increase drastically, and in a highly coordinated fashion. A number of recent observations suggest that enzymatic networks are often poised near the balance point between underloaded and overloaded regimes where it makes them highly sensitive and responsive to transient environmental fluctuations. This phenomenon appears to be widespread in biology; furthermore it should be highly optimized to a broad range of environmental conditions by adaptive regulatory mechanisms. In this project, the investigators combine rigorous mathematical analysis with quantitative computational modeling and synthetic biology to pinpoint the mechanisms and probe the role of adaptive queueing in the dynamics of small gene circuits as well as large intracellular enzymatic networks in bacteria and yeast. The investigators make use of their combined expertise in queueing theory, stochastic kinetic modeling, design of robust synthetic gene circuits and microfluidic technology to elucidate and characterize the role of adaptive queueing as a fast and flexible signal transduction and regulatory mechanism in bacteria and higher organisms.