2012年9月27日 讯 /生物谷BIOON/ --在一项新的研究中，美国德拉华大学电子与计算机工程助理教授Abhyudai Singh描述了一种新方法来理解基因表达中“噪音”的来源，其中这种噪音使得蛋白水平发生变化。相关研究结果于近期刊登在Molecular Systems Biology期刊上。
理解哪些生物化学过程导致这种变化是一个重要的问题，这是因为蛋白变化发挥着重要的作用，比如促进遗传上完全相同的细胞产生不同的细胞，以及让细胞群体对抗它们环境中发生的不可预测的有害变化。
这种方法利用单个细胞内的蛋白水平变化来精确地发现基因表达噪音的主要来源。
通过与来自美国加州大学旧金山分校格拉斯通病毒学与免疫学研究所的Leor Weinberger教授研究团队合作，Singh将这种方法应用到人免疫缺陷病毒(HIV)系统，在这种系统中，基因表达噪音能够促进HIV病毒进入潜伏期，即一种休眠的耐药状态。
这些结果揭示在HIV感染人细胞期间，mRNA复制的随机性突增导致关键性病毒调节蛋白水平发生变化。Singh说，“我们认为理解这种病毒基因表达噪声的来源将在设计阻止HIV病毒进入潜伏期的疗法中产生重要的影响。”(生物谷：Bioon.com)
doi: 10.1038/msb.2012.38
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Dynamics of protein noise can distinguish between alternate sources of gene-expression variability
Abhyudai Singh1,2,a, Brandon S Razooky1,3,4,a, Roy D Dar4,5 & Leor S Weinberger
Within individual cells, two molecular processes have been implicated as sources of noise in gene expression: (i) Poisson fluctuations in mRNA abundance arising from random birth and death of individual mRNA transcripts or (ii) promoter fluctuations arising from stochastic promoter transitions between different transcriptional states. Steady-state measurements of variance in protein levels are insufficient to discriminate between these two mechanisms, and mRNA single-molecule fluorescence in situ hybridization (smFISH) is challenging when cellular mRNA concentrations are high. Here, we present a perturbation method that discriminates mRNA birth/death fluctuations from promoter fluctuations by measuring transient changes in protein variance and that can operate in the regime of high molecular numbers. Conceptually, the method exploits the fact that transcriptional blockage results in more rapid increases in protein variability when mRNA birth/death fluctuations dominate over promoter fluctuations. We experimentally demonstrate the utility of this perturbation approach in the HIV-1 model system. Our results support promoter fluctuations as the primary noise source in HIV-1 expression. This study illustrates a relatively simple method that complements mRNA smFISH hybridization and can be used with existing GFP-tagged libraries to include or exclude alternate sources of noise in gene expression.
