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活跃代谢途径的数量受最大代谢速率下细胞约束数量的限制。

The number of active metabolic pathways is bounded by the number of cellular constraints at maximal metabolic rates.

机构信息

Systems Bioinformatics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

Department of Mathematics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.

出版信息

PLoS Comput Biol. 2019 Mar 11;15(3):e1006858. doi: 10.1371/journal.pcbi.1006858. eCollection 2019 Mar.

Abstract

Growth rate is a near-universal selective pressure across microbial species. High growth rates require hundreds of metabolic enzymes, each with different nonlinear kinetics, to be precisely tuned within the bounds set by physicochemical constraints. Yet, the metabolic behaviour of many species is characterized by simple relations between growth rate, enzyme expression levels and metabolic rates. We asked if this simplicity could be the outcome of optimisation by evolution. Indeed, when the growth rate is maximized-in a static environment under mass-conservation and enzyme expression constraints-we prove mathematically that the resulting optimal metabolic flux distribution is described by a limited number of subnetworks, known as Elementary Flux Modes (EFMs). We show that, because EFMs are the minimal subnetworks leading to growth, a small active number automatically leads to the simple relations that are measured. We find that the maximal number of flux-carrying EFMs is determined only by the number of imposed constraints on enzyme expression, not by the size, kinetics or topology of the network. This minimal-EFM extremum principle is illustrated in a graphical framework, which explains qualitative changes in microbial behaviours, such as overflow metabolism and co-consumption, and provides a method for identification of the enzyme expression constraints that limit growth under the prevalent conditions. The extremum principle applies to all microorganisms that are selected for maximal growth rates under protein concentration constraints, for example the solvent capacities of cytosol, membrane or periplasmic space.

摘要

生长速率是微生物物种中普遍存在的选择压力。高生长速率需要数百种代谢酶,每种酶的非线性动力学都不同,需要在物理化学限制所设定的范围内精确调整。然而,许多物种的代谢行为具有简单的生长速率、酶表达水平和代谢速率之间的关系。我们想知道这种简单性是否是进化优化的结果。事实上,当生长速率在质量守恒和酶表达约束下最大化时,我们从数学上证明了,由此产生的最佳代谢通量分布由有限数量的子网,即基本通量模式(Elementary Flux Modes,EFMs)描述。我们表明,由于 EFMs 是导致生长的最小子网,少量的活跃子网自动导致了所测量的简单关系。我们发现,通量携带 EFMs 的最大数量仅由酶表达的约束数量决定,而不是由网络的大小、动力学或拓扑结构决定。这个最小 EFMs 极值原理在图形框架中得到了说明,该框架解释了微生物行为的定性变化,例如溢出代谢和共消耗,并提供了一种方法来确定在普遍条件下限制生长的酶表达约束。极值原理适用于所有在蛋白质浓度约束下选择最大生长速率的微生物,例如细胞质、膜或周质空间的溶剂容量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5159/6428345/3feb6d7b9f1d/pcbi.1006858.g001.jpg

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