Department of Mathematical Sciences, Chalmers University of Technology, Gothenburg, Sweden.
Department of Mathematical Sciences, University of Gothenburg, Gothenburg, Sweden.
PLoS Comput Biol. 2022 Jul 7;18(7):e1010261. doi: 10.1371/journal.pcbi.1010261. eCollection 2022 Jul.
The accumulation of protein damage is one of the major drivers of replicative ageing, describing a cell's reduced ability to reproduce over time even under optimal conditions. Reactive oxygen and nitrogen species are precursors of protein damage and therefore tightly linked to ageing. At the same time, they are an inevitable by-product of the cell's metabolism. Cells are able to sense high levels of reactive oxygen and nitrogen species and can subsequently adapt their metabolism through gene regulation to slow down damage accumulation. However, the older or damaged a cell is the less flexibility it has to allocate enzymes across the metabolic network, forcing further adaptions in the metabolism. To investigate changes in the metabolism during replicative ageing, we developed an multi-scale mathematical model using budding yeast as a model organism. The model consists of three interconnected modules: a Boolean model of the signalling network, an enzyme-constrained flux balance model of the central carbon metabolism and a dynamic model of growth and protein damage accumulation with discrete cell divisions. The model can explain known features of replicative ageing, like average lifespan and increase in generation time during successive division, in yeast wildtype cells by a decreasing pool of functional enzymes and an increasing energy demand for maintenance. We further used the model to identify three consecutive metabolic phases, that a cell can undergo during its life, and their influence on the replicative potential, and proposed an intervention span for lifespan control.
蛋白质损伤的积累是复制性衰老的主要驱动因素之一,它描述了细胞在最佳条件下随着时间的推移繁殖能力下降的现象。活性氧和氮物种是蛋白质损伤的前体,因此与衰老密切相关。同时,它们也是细胞代谢不可避免的副产物。细胞能够感知高水平的活性氧和氮物种,随后可以通过基因调控来调整其代谢,以减缓损伤的积累。然而,细胞越老或损伤越严重,其在代谢网络中分配酶的灵活性就越低,迫使代谢进一步适应。为了研究复制性衰老过程中的代谢变化,我们使用芽殖酵母作为模型生物,开发了一个多尺度的数学模型。该模型由三个相互连接的模块组成:信号网络的布尔模型、中央碳代谢的酶约束通量平衡模型以及具有离散细胞分裂的生长和蛋白质损伤积累的动态模型。该模型可以通过功能酶的减少和维持所需能量的增加来解释复制性衰老的已知特征,例如酵母野生型细胞的平均寿命和连续分裂过程中代时的增加。我们还利用该模型确定了细胞在其生命周期中可能经历的三个连续代谢阶段,及其对复制潜力的影响,并提出了一个干预寿命控制的跨度。