Fluorescence lifetime sensing enables researchers to probe the physicochemical environment of a fluorophore providing a window through which we can observe the complex molecular make-up of the cell. Fluorescence lifetime imaging microscopy (FLIM) quantifies and maps cell biochemistry, a complex ensemble of dynamic processes. Unfortunately, typical high-resolution FLIM systems exhibit rather limited acquisition speeds, often insufficient to capture the time evolution of biochemical processes in living cells. Here, we describe the theoretical background that justifies the developments of high-speed single photon counting systems. We show that systems with low dead-times not only result in faster acquisition throughputs but also improved dynamic range and spatial resolution. We also share the implementation of hardware and software as an open platform, show applications of fast FLIM biochemical imaging on living cells and discuss strategies to balance precision and accuracy in FLIM. The recent innovations and commercialisation of fast time-domain FLIM systems are likely to popularise FLIM within the biomedical community, to impact biomedical research positively and to foster the adoption of other FLIM techniques as well. While supporting and indeed pursuing these developments, with this work we also aim to warn the community about the possible shortcomings of fast single photon counting techniques and to highlight strategies to acquire data of high quality.

Revealing mechanisms underpinning cell function requires understanding the relationship between different biochemical reactions in living cells. However, our capabilities to monitor more than two biochemical reactions in living cells are limited. Therefore, the development of methods for real-time biochemical multiplexing is of fundamental importance. Here, we show that data acquired with multicolor (mcFLIM) or spectrally resolved (sFLIM) fluorescence lifetime imaging can be conveniently described with multidimensional phasor transforms. We demonstrate a computational framework capable of demixing three Forster resonance energy transfer (FRET) probes and quantifying multiplexed biochemical activities in single living cells. We provide a comparison between mcFLIM and sFLIM suggesting that sFLIM might be advantageous for the future development of heavily multiplexed assays. However, mcFLIM—more readily available with commercial systems—can be applied for the concomitant monitoring of three enzymes in living cells without significant losses.