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Abrupt and Dynamic Changes in Gene Expression Revealed by Live Cell Arrays

机译:活细胞阵列揭示基因表达的突变和动态变化

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A description of the noise associated with gene expression is presented, based on a simplified form of the combined multistep processes of transcription and translation. These processes are influenced by numerous factors, including the accessibility of promoter regions to the transcriptional machinery, the kinetics of assembly of the transcription complexes, and the synthesis and degradation of both mRNA and proteins, among others. Ultimately, stochasticity in cellular processes results in variation in protein levels. Here we constructed a rationally designed RNA-based transcriptional activator to reduce these variables and provide a cleaner, more detailed portrayal of cellular noise. Functioning at a level comparable to natural transcription activation, this activator is isolated to a lacZ reporter gene in yeast cells to quantitatively describe the efficiency of the combined processes of transcription and translation. By employing single-cell array techniques to monitor individual cells simultaneously and in real time, a statistical approach to investigate noise inherent in gene expression is possible. Live cell arrays enabled cell populations to be characterized temporally at the individual cell level. The array platform allowed for a relative measure of protein production in real time and could characterize protein bursts with variable size and random timing, such that bursts occurred in a temporally indiscriminate fashion. The inherent variability and randomness of these processes is characterized, with almost half (47percent) of cells experiencing bursting behavior at least once over the course of the experiment. We demonstrate that cells identified on the upper periphery of activity exhibit behaviors that are substantially different from the majority of the population, and such variable activities within a population will provide a more accurate characterization of the population.
机译:基于转录和翻译的组合多步过程的简化形式,介绍了与基因表达相关的噪声。这些过程受许多因素的影响,其中包括启动子区域对转录机制的可及性,转录复合物组装的动力学以及mRNA和蛋白质的合成和降解等。最终,细胞过程的随机性导致蛋白质水平的变化。在这里,我们构建了一个合理设计的基于RNA的转录激活因子,以减少这些变量并提供更清晰,更详细的细胞噪声描述。该激活剂的功能与天然转录激活相当,可与酵母细胞中的lacZ报告基因分离,以定量描述转录和翻译结合过程的效率。通过采用单细胞阵列技术同时并实时监测单个细胞,可以采用统计方法研究基因表达中固有的噪声。活细胞阵列使细胞群体可以在单个细胞水平上进行时间表征。该阵列平台可以实时测量蛋白质的相对产量,并且可以通过可变大小和随机时间来表征蛋白质爆发,从而爆发在时间上不加区分。这些过程的固有可变性和随机性具有特征,在实验过程中,几乎一半(47%)的细胞至少经历一次爆发行为。我们证明,在活动的上边缘确定的细胞表现出的行为与大多数人的行为大不相同,而这种在人群中的可变活动将提供更准确的人群特征。

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