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线性规划模型可以解释发酵产物的呼吸作用。

Linear programming model can explain respiration of fermentation products.

作者信息

Möller Philip, Liu Xiaochen, Schuster Stefan, Boley Daniel

机构信息

Dept. of Bioinformatics, Friedrich-Schiller-Universität, Jena, Germany.

Dept. of Computer Science and Eng., University of Minnesota, Minneapolis, MN, United States of America.

出版信息

PLoS One. 2018 Feb 7;13(2):e0191803. doi: 10.1371/journal.pone.0191803. eCollection 2018.

DOI:10.1371/journal.pone.0191803
PMID:29415045
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5802903/
Abstract

Many differentiated cells rely primarily on mitochondrial oxidative phosphorylation for generating energy in the form of ATP needed for cellular metabolism. In contrast most tumor cells instead rely on aerobic glycolysis leading to lactate to about the same extent as on respiration. Warburg found that cancer cells to support oxidative phosphorylation, tend to ferment glucose or other energy source into lactate even in the presence of sufficient oxygen, which is an inefficient way to generate ATP. This effect also occurs in striated muscle cells, activated lymphocytes and microglia, endothelial cells and several mammalian cell types, a phenomenon termed the "Warburg effect". The effect is paradoxical at first glance because the ATP production rate of aerobic glycolysis is much slower than that of respiration and the energy demands are better to be met by pure oxidative phosphorylation. We tackle this question by building a minimal model including three combined reactions. The new aspect in extension to earlier models is that we take into account the possible uptake and oxidation of the fermentation products. We examine the case where the cell can allocate protein on several enzymes in a varying distribution and model this by a linear programming problem in which the objective is to maximize the ATP production rate under different combinations of constraints on enzymes. Depending on the cost of reactions and limitation of the substrates, this leads to pure respiration, pure fermentation, and a mixture of respiration and fermentation. The model predicts that fermentation products are only oxidized when glucose is scarce or its uptake is severely limited.

摘要

许多分化细胞主要依靠线粒体氧化磷酸化来产生细胞代谢所需的ATP形式的能量。相比之下,大多数肿瘤细胞则更多地依赖有氧糖酵解产生乳酸,其程度与呼吸作用相当。瓦尔堡发现,癌细胞即使在有充足氧气的情况下,也倾向于将葡萄糖或其他能量来源发酵成乳酸以支持氧化磷酸化,这是一种低效的ATP生成方式。这种效应也发生在横纹肌细胞、活化的淋巴细胞和小胶质细胞、内皮细胞以及几种哺乳动物细胞类型中,这种现象被称为“瓦尔堡效应”。乍一看,这种效应似乎自相矛盾,因为有氧糖酵解的ATP生成速率比呼吸作用慢得多,而且能量需求最好通过纯氧化磷酸化来满足。我们通过构建一个包含三个联合反应的最小模型来解决这个问题。与早期模型相比,新的方面是我们考虑了发酵产物的可能摄取和氧化。我们研究了细胞可以以不同分布在几种酶上分配蛋白质的情况,并通过一个线性规划问题对其进行建模,其中目标是在酶的不同约束组合下最大化ATP生成速率。根据反应成本和底物限制,这会导致纯呼吸作用、纯发酵作用以及呼吸作用和发酵作用的混合。该模型预测,只有当葡萄糖稀缺或其摄取受到严重限制时,发酵产物才会被氧化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/71e82910dc8d/pone.0191803.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/4a1cd4576f40/pone.0191803.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/a4eb791aea53/pone.0191803.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/2c6ab9dc055a/pone.0191803.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/6748150c428c/pone.0191803.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/b296c7383896/pone.0191803.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/69bad218063c/pone.0191803.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/84c52bac3bbc/pone.0191803.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/42fab65afd0f/pone.0191803.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/24d1798274b8/pone.0191803.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/71e82910dc8d/pone.0191803.g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/4a1cd4576f40/pone.0191803.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/a4eb791aea53/pone.0191803.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/2c6ab9dc055a/pone.0191803.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/6748150c428c/pone.0191803.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/b296c7383896/pone.0191803.g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/69bad218063c/pone.0191803.g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/84c52bac3bbc/pone.0191803.g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/42fab65afd0f/pone.0191803.g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/24d1798274b8/pone.0191803.g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e64/5802903/71e82910dc8d/pone.0191803.g010.jpg

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