细菌在多目标优化下的资源分配策略

Bacteria live in a complex and volatile environment with limited resource. They are confronted with multiple tasks or objectives e.g. growth, motility, biosynthesis of secondary metabolite, to achieve the best fitness under certain environmental conditions. What strategies are adopted by the cell to allocate the resource and make a trade-off among these objectives? It is an interesting question of the cellular economics. Traditionally, single objective optimization methods such as flux balance analysis were widely used to evaluate the resource allocation at the level of metabolic flux distribution. However, such methods cannot truly reflect the multi-objective optimization in bacteria under different conditions, resulting in dramatic inconsistency with experimental values. Accordingly in this project, a novel mathematical model is built based on multi-objective decision-making theory in operational research and Pareto optimal model in economics, and used to illustrate the resource allocation strategies for multi-objective optimization in bacteria. In addition, Escherichia coli serves as a model bacterium for research, and 13C-labeled metabolic flux analysis is applied to verify the intracellular flux distribution. The mathematical model established in this work is expected to further reveal the mechanism of biological systems, especially the metabolic system. It also helps to rationally design novel biological systems in synthetic biology to get higher efficient cell factories or chassis cells.

细菌生活在资源有限且复杂多变的环境中，它是如何合理地分配资源，以权衡生长繁殖、运动、合成次级代谢产物等目标，从而获得对环境最大的适应性？这是一个有趣的细胞经济学问题。传统以流量平衡分析为代表的单目标最优化方法从代谢流量分布上解析了细菌对资源的分配，但不能真实反映细菌在不同环境条件下所追求目标的多样性，其模拟结果往往与实验值差距显著。据此，本项目拟借助运筹学中的多目标决策理论和经济学中的帕累托最优模型，以大肠杆菌为模式细菌，构建新的数学模型来阐释细菌在多目标优化下的资源分配策略，并采用碳13标记的代谢流量分析来对胞内流量分布进行验证。本研究建立的数学模型将进一步揭示生命系统尤其是代谢系统的运行机制，同时也有助于理性地设计新的生命系统，获得更高效的细胞工厂或底盘细胞。

基因组测序技术的快速发展使越来越多物种的全基因组代谢模型得以构建。人们可从系统的角度来模拟和预测基因改造对菌体细胞代谢表型带来的影响，考察细菌资源分配利用情况，进而指导菌种的设计与改造。以流量平衡分析为代表的单目标最优化算法虽然在某种程度上实现了该目标，但它不能真实反映细菌在不同环境条件下所追求目标的多样性，其模拟结果往往与实验值差距显著，改造效率低下。据此，本研究通过借助运筹学中的多目标决策理论和经济学中的帕累托最优模型，以大肠杆菌为模式细菌，构建新的数学模型来阐释细菌在多目标优化下的资源分配策略，并用于指导菌种改良设计。本研究建立的数学模型进一步揭示了生命系统尤其是代谢系统的运行机制，同时也有助于理性地设计新的生命系统，获得更高效的细胞工厂或底盘细胞。