Vidal Gonzalo, Vidal-Céspedes Carlos, Muñoz Silva Macarena, Castillo-Passi Carlos, Yáñez Feliú Guillermo, Federici Fernán, Rudge Timothy J
Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile.
Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK.
Synth Biol (Oxf). 2022 Oct 15;7(1):ysac020. doi: 10.1093/synbio/ysac020. eCollection 2022.
Genetic circuits are subject to variability due to cellular and compositional contexts. Cells face changing internal states and environments, the cellular context, to which they sense and respond by changing their gene expression and growth rates. Furthermore, each gene in a genetic circuit operates in a compositional context of genes which may interact with each other and the host cell in complex ways. The context of genetic circuits can, therefore, change gene expression and growth rates, and measuring their dynamics is essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of microbial gene expression and growth rate profiles from typical noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for the estimation of dynamic microbial gene expression rates and growth rates from noisy measurement data. Compared to the current state-of-the-art, our method significantly reduced the mean squared error of reconstructions from simulated data of growth and gene expression rates, improving the estimation of timing and magnitude of relevant shapes of profiles. We applied our method to characterize a triple-reporter plasmid library combining multiple transcription units in different compositional and cellular contexts in . Our analysis reveals cellular and compositional context effects on microbial growth and gene expression rate dynamics and suggests a method for the dynamic ratiometric characterization of constitutive promoters relative to an reference.
由于细胞和组成环境的原因，遗传回路存在变异性。细胞面临不断变化的内部状态和环境，即细胞环境，它们通过改变基因表达和生长速率来感知并做出反应。此外，遗传回路中的每个基因都在一个基因组成环境中运行，这些基因可能以复杂的方式相互作用以及与宿主细胞相互作用。因此，遗传回路的环境可以改变基因表达和生长速率，测量它们的动态对于理解产生功能表型的天然和合成调控网络至关重要。然而，由于低细胞密度下噪声的影响以及其他因素，从细胞群体的典型噪声测量中重建微生物基因表达和生长速率谱是困难的。我们在此提出一种从噪声测量数据中估计动态微生物基因表达率和生长速率的方法。与当前的先进技术相比，我们的方法显著降低了从生长和基因表达率模拟数据重建的均方误差，改善了对相关谱形状的时间和幅度的估计。我们应用我们的方法来表征一个在不同组成和细胞环境中结合多个转录单元的三报告质粒文库。我们的分析揭示了细胞和组成环境对微生物生长和基因表达率动态的影响，并提出了一种相对于参考物对组成型启动子进行动态比率表征的方法。
