Center for Biological Physics, Arizona State University, Tempe, Arizona; Department of Physics, Arizona State University, Tempe, Arizona.
Department of Biomedical Engineering, University of California Irvine, Irvine, California; Laboratory of Fluorescence Dynamics, The Henry Samueli School of Engineering, University of California Irvine, Irvine, California.
Biophys J. 2023 Feb 21;122(4):672-683. doi: 10.1016/j.bpj.2023.01.014. Epub 2023 Jan 19.
Fluorescence lifetime imaging captures the spatial distribution of chemical species across cellular environments employing pulsed illumination confocal setups. However, quantitative interpretation of lifetime data continues to face critical challenges. For instance, fluorescent species with known in vitro excited-state lifetimes may split into multiple species with unique lifetimes when introduced into complex living environments. What is more, mixtures of species, which may be both endogenous and introduced into the sample, may exhibit 1) very similar lifetimes as well as 2) wide ranges of lifetimes including lifetimes shorter than the instrumental response function or whose duration may be long enough to be comparable to the interpulse window. By contrast, existing methods of analysis are optimized for well-separated and intermediate lifetimes. Here, we broaden the applicability of fluorescence lifetime analysis by simultaneously treating unknown mixtures of arbitrary lifetimes-outside the intermediate, Goldilocks, zone-for data drawn from a single confocal spot leveraging the tools of Bayesian nonparametrics (BNP). We benchmark our algorithm, termed BNP lifetime analysis, using a range of synthetic and experimental data. Moreover, we show that the BNP lifetime analysis method can distinguish and deduce lifetimes using photon counts as small as 500.
荧光寿命成像技术采用脉冲激发共焦设置，可捕获细胞环境中化学物质的空间分布。然而，寿命数据的定量解释仍然面临着严峻的挑战。例如，当已知的体外激发态寿命的荧光物质被引入复杂的活体环境中时，可能会分裂成具有独特寿命的多个物质。更有甚者，可能既有内源性的也有引入到样本中的物质的混合物，其寿命可能具有以下特征：1）非常相似；2）寿命范围很宽，包括比仪器响应函数短的寿命，或者寿命可能足够长，可以与脉冲间隔窗口相媲美。相比之下，现有的分析方法是针对分离良好且处于中间寿命范围的物质进行优化的。在这里，我们通过利用贝叶斯非参数化（BNP）的工具，同时处理来自单个共焦点的任意寿命的未知混合物（处于中间、黄金区域之外）的数据，拓宽了荧光寿命分析的适用性。我们使用一系列合成和实验数据来对我们的算法（称为 BNP 寿命分析）进行基准测试。此外，我们还表明，BNP 寿命分析方法可以使用少至 500 个光子计数来区分和推断寿命。
