Department of Cell and Developmental Biology, University College London, London WC1E 6BT, U.K.
UCL Genetics Institute, University College London, London WC1E 6BT, U.K.
ACS Synth Biol. 2020 Sep 18;9(9):2258-2266. doi: 10.1021/acssynbio.0c00296. Epub 2020 Sep 1.
The measurement of gene expression using fluorescence markers has been a cornerstone of synthetic biology for the past two decades. However, the use of arbitrary units has limited the usefulness of these data for many quantitative purposes. Calibration of fluorescence measurements from flow cytometry and plate reader spectrophotometry has been implemented previously, but the tools are disjointed. Here we pull together, and in some cases improve, extant methods into a single software tool, written as a package in the R statistical framework. The workflow is validated using engineered to express green fluorescent protein (GFP) from a set of commonly used constitutive promoters. We then demonstrate the package's power by identifying the time evolution of distinct subpopulations of bacteria from bulk plate reader data, a task previously reliant on laborious flow cytometry or colony counting experiments. Along with standardized parts and experimental methods, the development and dissemination of usable tools for quantitative measurement and data analysis will benefit the synthetic biology community by improving interoperability.
在过去的二十年中，使用荧光标记物测量基因表达一直是合成生物学的基石。然而，这些数据的任意单位的使用限制了它们在许多定量目的的用途。先前已经实施了来自流式细胞仪和板读分光光度计的荧光测量的校准，但这些工具是不连贯的。在这里，我们将（这些工具）整合在一起，并且在某些情况下进行了改进，将现有的方法集成到一个单一的软件工具中，该工具是用 R 统计框架编写的一个软件包。使用一组常用的组成型启动子来表达绿色荧光蛋白（GFP）的工程菌来验证工作流程。然后，我们通过从批量板读数据中识别细菌的不同亚群的时间演变，展示了该软件包的强大功能，这是以前依赖于繁琐的流式细胞术或菌落计数实验的任务。随着标准化部件和实验方法的发展和传播，用于定量测量和数据分析的可用工具的开发和传播将通过提高互操作性使合成生物学社区受益。
