Department of Electrical and Computer Engineering, University of Delaware, Newark, DE 19716, USA.
IEEE Trans Nanobioscience. 2011 Sep;10(3):194-200. doi: 10.1109/TNB.2011.2168826.
Genetically identical cell populations exposed to the same environment can exhibit considerable cell-to-cell variation in the levels of specific proteins. This variation or expression noise arises from the inherent stochastic nature of biochemical reactions that constitute gene expression. Negative feedback loops are common motifs in gene networks that reduce expression noise and intercellular variability in protein levels. Using stochastic models of gene expression we here compare different feedback architectures in their ability to reduce stochasticity in protein levels. A mathematically controlled comparison shows that in physiologically relevant parameter regimes, feedback regulation through the mRNA provides the best suppression of expression noise. Consistent with our theoretical results we find negative feedback loops though the mRNA in essential eukaryotic genes, where feedback is mediated via intron-derived microRNAs. Finally, we find that contrary to previous results, protein-mediated translational regulation may not always provide significantly better noise suppression than protein-mediated transcriptional regulation.
暴露在相同环境中的遗传相同的细胞群体在特定蛋白质的水平上可能表现出相当大的细胞间差异。这种变化或表达噪声源于构成基因表达的生化反应固有的随机性质。负反馈回路是基因网络中的常见模式，可降低基因表达噪声和蛋白质水平的细胞间变异性。使用基因表达的随机模型，我们在这里比较了不同反馈结构在降低蛋白质水平随机性方面的能力。数学控制比较表明，在生理相关的参数范围内，通过 mRNA 的反馈调节可提供对表达噪声的最佳抑制。与我们的理论结果一致，我们发现了在必需的真核基因中通过 mRNA 的负反馈回路，其中反馈是通过内含子衍生的 microRNAs 介导的。最后，我们发现与以前的结果相反，蛋白质介导的翻译调控并不总是比蛋白质介导的转录调控提供更好的噪声抑制。
