Ma Pingchuan, Chen Peter, Sternson Scott, Chen Yao
Department of Neuroscience, Washington University in St. Louis, St. Louis, United States.
Ph.D. Program in Neuroscience, Washington University in St. Louis, St. Louis, United States.
Elife. 2025 Aug 20;13:RP101559. doi: 10.7554/eLife.101559.
Signaling dynamics are crucial in biological systems, and biosensor-based real-time imaging has revolutionized their analysis. Fluorescence lifetime imaging microscopy (FLIM) excels over the widely used fluorescence intensity imaging by allowing the measurement of absolute signal levels independent of sensor concentration. This capability enables the comparison of signaling dynamics across different animals, body regions, and timeframes. However, FLIM's advantage can be compromised by factors like autofluorescence in biological experiments. To address this, we introduce FLiSimBA, a flexible computational framework for realistic luorescence fetime ulation for iological pplications. Through simulations, we analyze the signal-to-noise ratios of fluorescence lifetime data, determining measurement uncertainty and providing necessary error bars for lifetime measurements. Furthermore, we challenge the belief that fluorescence lifetime is unaffected by sensor expression and establish quantitative limits to this insensitivity in biological applications. Additionally, we propose innovations, notably multiplexed dynamic imaging that combines fluorescence intensity and lifetime measurements. This innovation can transform the number of signals that can be simultaneously monitored, thereby enabling a systems approach in studying signaling dynamics. Thus, by incorporating different factors into our simulation framework, we uncover surprises, identify limitations, and propose advancements for fluorescence lifetime imaging in biology. This quantitative framework supports rigorous experimental design, facilitates accurate data interpretation, and paves the way for technological advancements in fluorescence lifetime imaging.
信号动力学在生物系统中至关重要，基于生物传感器的实时成像彻底改变了对其的分析。荧光寿命成像显微镜（FLIM）通过能够测量与传感器浓度无关的绝对信号水平，优于广泛使用的荧光强度成像。这种能力使得能够比较不同动物、身体区域和时间范围内的信号动力学。然而，在生物实验中，诸如自发荧光等因素可能会削弱FLIM的优势。为了解决这个问题，我们引入了FLiSimBA，这是一个用于生物学应用的真实荧光寿命模拟的灵活计算框架。通过模拟，我们分析了荧光寿命数据的信噪比，确定测量不确定性并为寿命测量提供必要的误差线。此外，我们挑战了荧光寿命不受传感器表达影响的观点，并在生物学应用中确定了这种不敏感性的定量限度。此外，我们提出了创新方法，特别是结合荧光强度和寿命测量的多重动态成像。这一创新可以改变能够同时监测的信号数量，从而在研究信号动力学时采用系统方法。因此，通过将不同因素纳入我们的模拟框架，我们发现了意外情况，识别了局限性，并为生物学中的荧光寿命成像提出了改进建议。这个定量框架支持严谨的实验设计，有助于准确的数据解释，并为荧光寿命成像的技术进步铺平了道路。
