Monteoliva Diana, McCarthy Christina B, Diambra Luis
Instituto de Física, Universidad Nacional de La Plata, La Plata, Argentina.
Laboratorio de Metagenómica de Microorganismos, Centro Regional de Estudios Genómicos, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, Florencio Varela, Argentina ; Departamento de Informática y Tecnología, Universidad Nacional del Noroeste de la Provincia de Buenos Aires, Pergamino, Buenos Aires, Argentina.
PLoS One. 2013 Dec 23;8(12):e84020. doi: 10.1371/journal.pone.0084020. eCollection 2013.
Gene expression is subject to stochastic variation which leads to fluctuations in the rate of protein production. Recently, a study in yeast at a genomic scale showed that, in some cases, gene expression variability alters phenotypes while, in other cases, these remain unchanged despite fluctuations in the expression of other genes. These studies suggested that noise in gene expression is a physiologically relevant trait and, to prevent harmful stochastic variation in the expression levels of some genes, it can be subject to minimisation. However, the mechanisms for noise minimisation are still unclear. In the present work, we analysed how noise expression depends on the architecture of the cis-regulatory system, in particular on the number of regulatory binding sites. Using analytical calculations and stochastic simulations, we found that the fluctuation level in noise expression decreased with the number of regulatory sites when regulatory transcription factors interacted with only one other bound transcription factor. In contrast, we observed that there was an optimal number of binding sites when transcription factors interacted with many bound transcription factors. This finding suggested a new mechanism for preventing large fluctuations in the expression of genes which are sensitive to the concentration of regulators.
基因表达会受到随机变异的影响，这会导致蛋白质产生速率的波动。最近，一项在酵母中进行的全基因组规模研究表明，在某些情况下，基因表达变异性会改变表型，而在其他情况下，尽管其他基因的表达存在波动，但表型仍保持不变。这些研究表明，基因表达中的噪声是一种与生理相关的特性，为了防止某些基因表达水平出现有害的随机变异，这种噪声可以被最小化。然而，噪声最小化的机制仍不清楚。在本研究中，我们分析了噪声表达如何依赖于顺式调控系统的结构，特别是调控结合位点的数量。通过分析计算和随机模拟，我们发现当调控转录因子仅与另一个结合的转录因子相互作用时，噪声表达的波动水平会随着调控位点数量的增加而降低。相反，我们观察到当转录因子与多个结合的转录因子相互作用时，存在一个最佳的结合位点数量。这一发现提示了一种防止对调节因子浓度敏感的基因表达出现大幅波动的新机制。
