In addition to intensity and wavelength, lifetime is a supplementary source of contrast in fluorescence microscopy, which greatly increases access to the biological information in living cells. Fluorescence Lifetime Imaging Microscopy (FLIM) has indeed been successfully applied to differentiate spectrally undistinguishable molecular species (1) and to map local modifications in labeled samples in terms of ion concentration (2), pH (3), and oxygen (4). FLIM has also been widely used to explore conformational change of proteins (5) or to separate interacting and non-interacting molecular fractions in Förster Resonance Energy Transfer (FRET) experiments (6, 7).

However, because of the low number of collected photons per pixel and the variability of the molecular environment inside a living cell, FLIM is usually limited to two lifetime components in the same pixel. This restriction makes it difficult to extract biologically relevant information from autofluorescent, heterogeneous, light-scattering samples such as biological tissue. Because of optical properties of tissue, a dedicated temporally and spectrally resolved system (called SLIM for Spectral and Lifetime Imaging Microscopy) is necessary for example to be able to explore molecular interactions on a nanometric scale (with FRET experiments).

Temporal and spectral measurements can be performed using two approaches, either frequency domain (8, 9) or time domain (10–12) measurements. In both cases, the determination of lifetimes and contributions of each molecular species are mainly achieved by fitting the collected data at each pixel using equations with multiple unknowns. Fast analysis of SLIM images constitutes then a major challenge. Indeed, because of the number of mathematical algorithms, the number of unknown parameters and the correlation between lifetimes and species contributions, obtaining reliable results with this fitting approach is time consuming and necessitates a high level of expertise (13, 14).

Recently, many efforts have been made to help simplify the results interpretation in classic FLIM experiments for nonspecialists (15–17). Among all these techniques, the polar plot or phasor (16, 18–20) is a promising approach that avoids complex fitting algorithm strategies and provides a fast, graphical representation of fluorescence lifetimes. This polar approach has successfully been applied in classic FLIM and FRET experiments (single spectral channel) by Digman et al. (16).

We propose to extend this concept on SLIM acquisitions by calculating the polar representation for each spectral channel to obtain a multispectral polar (MSP) representation (with emission wavelength as third dimension). Succinctly, this is done by calculating the Fourier sine and cosine transforms of all temporal decays and mapping the corresponding two-dimensional distributions to obtain a polar image for each spectral channel. Using this mathematical operation, each pixel of the intensity SLIM image corresponds to a point in the MSP representation and vice versa.

The main scope of this article is to demonstrate that this new and visual MSP representation is a useful method of SLIM image analysis, which should considerably facilitates the retrieval of biologically relevant information, thanks to the model free and nonfitting characteristics of this approach.

In a first part of this article, we describe the principle of this original MSP representation. We illustrate in a second part its interest for SLIM acquisition of a cross section of plant tissue; we then show its potential for measuring the FRET phenomenon occurring in living cells, which we can easily and visually differentiate from the cellular autofluorescence. Finally, we discuss the advantages and limitations of this method in the last section of this article.