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	Resource allocation strategies for multi-objective optimization in bacteria
	Hailin Meng
	2018
会议日期	2018
会议地点	上海
英文摘要	Bacteria live in a complex and changeable environment with limited resources. They are usually confronted with multiple tasks or objectives such as growth, motility, biosynthesis of secondary metabolite, to achieve the best fitness under certain environmental conditions. What strategies are adopted by the cell to allocate resource so as to reconcile the trade-off among these competitive objectives? It is an intractable problem of the cellular economics. Traditionally, single objective optimization methods (e.g. flux balance analysis and its derivatives) 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, often resulting in dramatic inconsistency with experimental data. Here in this work, we built a novel computational model based on multi-objective decision-making theory from operational research and Pareto optimization from economics, and used it to investigate the resource allocation strategies for multi-objective optimization in the model bacterium Escherichia coli. With the combination of genome-scale metabolic model iJO1366, the new method can finely predict the intracellular metabolic flux distribution: the results were in good agreement with 13C-labeled metabolic flux analysis of the strain. The computational platform established in this work is expected to further reveal the mechanism of microbial metabolism, and may help rational design of novel biological systems for synthetic biology to get higher efficient cell factories or chassis cells.
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/14804]
专题	深圳先进技术研究院_南沙所
推荐引用方式 GB/T 7714	Hailin Meng. Resource allocation strategies for multi-objective optimization in bacteria[C]. 见:. 上海. 2018.

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