Fluorescence Lifetime Imaging Microscopy Maps Fluorophore Concentrations, a Gaussian Process Approach

Abstract

Fluorescence microscopy techniques have made many contributions to unravel rules of biological processes in the past few decades. These procedures make use of different properties, such as life-time, emission spectrum and intensity of fluorophores to learn about sub-cellular environments. In particular, fluorescence lifetime imaging microscopy (FLIM) makes use of lifetimes of fluorescent dyes to map sub-cellular environment variations, such as temperature, pH, molecule concentrations, and protein-protein interactions. In FLIM, the number of photons collected by the detector depends on the lifetimes and concentrations of the fluorescent dyes present in the sample. Therefore, FLIM equips us with a powerful tool to learn the fluorophore concentrations with high spatial resolution. FLIM analysis can be performed in either time or frequency domain. In time domain, photon arrival times are fitted to a mixture of decay profiles, which are convolutions of exponential components and the instrument response function. The current time domain approaches group the input data into multiple bins which leads to loss of information. Moreover, these techniques report sub-cellular heterogeneity with a resolution limited to the pixel size. We developed a time domain FLIM data analysis technique in a Bayesian paradigm that uses Gaussian processes to map the fluorophore concentrations with sub-pixel resolution. This method efficiently uses all the available photon arrival time information and, as such, requires a minimum number of photons to infer accurate fluorophore concentrations. The approach was validated using both empirical and simulated data.