Study of the Photobleaching Phenomenon to optimize Acquisition of 3D and 4D fluorescence images. A special scenario for trilinear and quadrilinear models.

Abstract

Emission (3D) and excitation-emission (4D) fluorescence images allow covering wide excitation and emission spectral ranges and, hence, provide very complete information for a good characterization and location of fluorophores in samples. However, when the acquisition time of the image is too long, degradation of the fluorescence signal of compounds and sample photodamage can occur due to photobleaching. This phenomenon is due to the long exposure time of the sample to the light source and can hinder the detection and the proper characterization of the fluorophores in samples. The main purpose of this research is providing a methodology to obtain and interpret the information of fluorescence images for the characterization of samples without suffering the consequences of photobleaching. Such a goal implies a first thorough knowledge of the photobleaching phenomenon to adapt the fluorescence imaging measurement for an optimal characterization of the fluorophores present in samples. The proposed approach relies first on a study of time-series of 3D or 4D fluorescence images to characterize spatially and spectroscopically the fluorophores present in the samples and their photobleaching behaviour. Since photobleaching is fluorophore-dependent, the unmixing algorithm Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) is applied to the set of fluorescence images acquired as a function of time to understand the specific behaviour of every fluorophore. The characteristics of the photobleaching phenomenon and the nature of the fluorescence measurement offer a challenging scenario to look for adapted implementations of trilinear and quadrilinear models within the MCR framework. From the results obtained, appropriate instrumental settings are adopted for an image acquisition that allows the correct spatial and spectroscopic characterization of fluorophores in samples. To test the potential of this methodology, the characterization of thin cross-sections of the Oryza sativa (commonly called rice) root have been studied due to the co-occurrence of several natural fluorophores in vegetal tissues.