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基于底物解混平台的多重生物发光成像技术

Multiplexed bioluminescence imaging with a substrate unmixing platform.

机构信息

Department of Chemistry, University of California, Irvine, Irvine, CA 92697, USA.

Department of Molecular Biology and Biochemistry, University of California, Irvine, Irvine, CA 92697, USA.

出版信息

Cell Chem Biol. 2022 Nov 17;29(11):1649-1660.e4. doi: 10.1016/j.chembiol.2022.10.004. Epub 2022 Oct 24.

Abstract

Bioluminescent tools can illuminate cellular features in whole organisms. Multi-component tracking remains challenging, though, owing to a lack of well-resolved probes and long imaging times. To address the need for more rapid, quantitative, and multiplexed bioluminescent readouts, we developed an analysis pipeline featuring sequential substrate administration and serial image acquisition. Light output from each luciferin is layered on top of the previous image, with minimal delay between substrate delivery. A MATLAB algorithm was written to analyze bioluminescent images generated from the rapid imaging protocol and deconvolute (i.e., unmix) signals from luciferase-luciferin pairs. Mixtures comprising three to five luciferase reporters were readily distinguished in under 50 min; this same experiment would require days using conventional workflows. We further showed that the algorithm can be used to accurately quantify luciferase levels in heterogeneous mixtures. Based on its speed and versatility, the multiplexed imaging platform will expand the scope of bioluminescence technology.

摘要

生物发光工具可以照亮整个生物体中的细胞特征。然而,由于缺乏分辨率高的探针和长时间的成像时间,多组分跟踪仍然具有挑战性。为了满足对更快速、定量和多重生物发光读出的需求,我们开发了一种分析管道,其特点是顺序底物给药和连续图像采集。每个荧光素的光输出叠加在前一张图像的顶部,在底物传递之间几乎没有延迟。编写了一个 MATLAB 算法来分析从快速成像协议生成的生物发光图像,并对荧光素酶-荧光素对的信号进行去卷积(即解混)。在不到 50 分钟的时间内,很容易区分包含三到五个荧光素酶报告基因的混合物;而使用传统工作流程进行相同的实验则需要数天时间。我们进一步表明,该算法可用于准确量化异质混合物中的荧光素酶水平。基于其速度和多功能性,多路复用成像平台将扩大生物发光技术的范围。

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Chem Soc Rev. 2021 May 7;50(9):5668-5705. doi: 10.1039/d0cs01492c. Epub 2021 Mar 18.
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De novo design of modular and tunable protein biosensors.从头设计模块化和可调谐的蛋白质生物传感器。
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