生物样品中荧光团寿命的提取提供了关于探针环境的有用信息,该信息不容易从单独的荧光强度获得。细胞膜电位,pH值,氧浓度([O2]),钙([Ca2+]),NADH和其他离子和代谢物都通过基于寿命的技术定期测量。这些测量提供了关于细胞稳态的宝贵知识,与细胞环境的新陈代谢和交流。荧光寿命成像显微镜(FLIM)产生的空间图与时间相关的单光子计数(TCSPC)直方图在每个像素收集和分析,但是传统的TCSPC分析通常受到可以合理收集的光子数量少的阻碍,同时保持高空间分辨率。更重要的是,传统的分析未能利用图像内的空间联系。这里,我们提出了一种不同的方法,在这里我们工作的假设下,一个整体的生命集的混合(通常只有2或3)可以描述整个图像。我们通过全局拟合在感兴趣的大空间区域上聚集的精确衰减来确定这些寿命分量,然后我们执行衰减幅度的逐像素计算(通过应用于较粗的时间窗口的简单线性代数)。这会产生准确的振幅图像(衰减关联图像,DAI),其中包含有关基础混合物的化学计量信息,同时保留单像素分辨率。我们使用配备了商用单光子计数卡的双光子显微镜系统收集了染料混合物和表达荧光蛋白的细菌的FLIM数据,我们使用这些数据对gDAI程序进行了基准测试。
The extraction of fluorophore lifetimes in a biological sample provides useful information about the probe environment that is not readily available from fluorescence intensity alone. Cell membrane potential, pH, concentration of oxygen ([O2]), calcium ([Ca2+]), NADH and other ions and metabolites are all regularly measured by lifetime-based techniques. These measurements provide invaluable knowledge about cell homeostasis, metabolism and communication with the cell environment. Fluorescence lifetime imaging microscopy (FLIM) produces spatial maps with time-correlated single-photon counting (TCSPC) histograms collected and analyzed at each pixel, but traditional TCSPC analysis is often hampered by the low number of photons that can reasonably be collected while maintaining high spatial resolution. More important, traditional analysis fails to employ the spatial linkages within the image. Here, we present a different approach, where we work under the assumption that mixtures of a global set of lifetimes (often only 2 or 3) can describe the entire image. We determine these lifetime components by globally fitting precise decays aggregated over large spatial regions of interest, and then we perform a pixel-by-pixel calculation of decay amplitudes (via simple linear algebra applied to coarser time-windows). This yields accurate amplitude images (Decay Associate Images, DAI) that contain stoichiometric information about the underlying mixtures while retaining single pixel resolution. We collected FLIM data of dye mixtures and bacteria expressing fluorescent proteins with a two-photon microscope system equipped with a commercial single-photon counting card, and we used these data to benchmark the gDAI program.