Department of Physics, University of Idaho, Moscow, Idaho, USA.
Department of Electrical and Computer Engineering, University of Delaware, Newark, Delaware, USA.
WIREs Mech Dis. 2021 May;13(3):e1512. doi: 10.1002/wsbm.1512. Epub 2020 Nov 23.
From the time a cell was first placed under the microscope, it became apparent that identifying two clonal cells that "look" identical is extremely challenging. Since then, cell-to-cell differences in shape, size, and protein content have been carefully examined, informing us of the ultimate limits that hinder two cells from occupying an identical phenotypic state. Here, we present recent experimental and computational evidence that similar limits emerge also in cellular metabolism. These limits pertain to stochastic metabolic dynamics and, thus, cell-to-cell metabolic variability, including the resulting adapting benefits. We review these phenomena with a focus on microbial metabolism and conclude with a brief outlook on the potential relationship between metabolic noise and adaptive evolution. This article is categorized under: Metabolic Diseases > Computational Models Metabolic Diseases > Biomedical Engineering.
从首次将细胞置于显微镜下观察开始，人们就已经意识到，要识别两个“看起来”完全相同的克隆细胞是极其困难的。从那时起，人们就一直在仔细研究细胞间在形状、大小和蛋白质含量方面的差异，这些研究让我们了解到阻碍两个细胞处于相同表型状态的最终限制因素。在这里，我们提出了最近的实验和计算证据，表明细胞代谢中也存在类似的限制。这些限制与随机代谢动力学有关，因此也与细胞间代谢变异性有关，包括由此产生的适应优势。我们将重点关注微生物代谢来综述这些现象，并简要展望代谢噪声与适应性进化之间的潜在关系。本文属于以下分类：代谢疾病 > 计算模型代谢疾病 > 生物医学工程。
