School of Physics and Astronomy, Cardiff University, The Parade, Cardiff CF24 3AA, UK; School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK.
School of Biosciences, Cardiff University, Museum Avenue, Cardiff CF10 3AX, UK.
Med Image Anal. 2022 Nov;82:102579. doi: 10.1016/j.media.2022.102579. Epub 2022 Aug 13.
Despite their widespread use in cell biology, fluorescence lifetime imaging microscopy (FLIM) data-sets are challenging to analyse, because each spatial position can contain a superposition of multiple fluorescent components. Here, we present a data analysis method employing all information in the available photon budget, as well as being fast. The method, called uFLIM, determines spatial distributions and temporal dynamics of multiple fluorescent components with no prior knowledge. It goes significantly beyond current approaches which either assume the functional dependence of the dynamics, e.g. an exponential decay, or require dynamics to be known, or calibrated. Its efficient non-negative matrix factorization algorithm allows for real-time data processing. We validate in silico that uFLIM is capable to disentangle the spatial distribution and spectral properties of five fluorescing probes, from only two excitation and detection channels and a photon budget of 100 detected photons per pixel. By adapting the method to data exhibiting Förster resonant energy transfer (FRET), we retrieve the spatial and transfer rate distribution of the bound species, without constrains on donor and acceptor dynamics.
尽管荧光寿命成像显微镜(FLIM)在细胞生物学中得到了广泛的应用,但由于每个空间位置都可能包含多个荧光成分的叠加,因此 FLIM 数据集的分析具有挑战性。在这里,我们提出了一种数据分析方法,该方法利用可用光子预算中的所有信息,并且速度很快。该方法称为 uFLIM,它可以确定没有先验知识的多个荧光成分的空间分布和时间动态。它大大超越了当前的方法,这些方法要么假设动力学的函数依赖性,例如指数衰减,要么需要已知的动力学或进行校准。其高效的非负矩阵分解算法允许实时数据处理。我们通过在计算机上进行验证,证明 uFLIM 能够从只有两个激发和检测通道以及每个像素 100 个检测光子的光子预算中,分离出五个荧光探针的空间分布和光谱特性。通过将该方法适用于表现出Förster 共振能量转移(FRET)的数据集,我们可以检索结合物种的空间和转移速率分布,而无需对供体和受体动力学进行限制。