Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.

中文翻译：

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使用基因组改造的人类细胞系，沿着中央教条解耦基因表达噪音。

真核蛋白质合成是固有的随机过程。这种随机性不仅源于细胞之间细胞含量的变化，还源于单个细胞中的热力学波动。最终，这些固有的随机过程表现为基因表达中的噪音，即使在同一环境中，即使遗传上相同的细胞，其蛋白质丰度也会发生变化。为了阐明造成基因表达噪音的潜在原因，我们量化了沿着中央教条在蛋白质合成过程中每个步骤的贡献。我们使用CRISPR在人类细胞中稳定整合的定制工程电路，在转录，翻译和翻译后水平上解偶联基因表达。我们提供一个通用的框架，以近似表示表达不平衡的两个报告系统的细胞群体中的内在和外在噪声。我们的分解表明，大多数内在波动源于转录，并且沿着中央教条耦合这两个基因会迫使波动沿同一路径传播和积累，从而导致观察到的产物之间的全局相关性增加。