IMAGING THE LYSOSOME IN CELLULAR SYSTEMS FOR DRUG DISCOVERY AND SCREENING (European Journal of Histochemistry)
Lysosomal storage disorders (LSDs) are a group of rare diseases characterized by a genetic-derived lysosomal metabolism error. Within the complex spectrum of symptoms, the LSDs strongly affect the central nervous system (CNS). However, currently available treatments include enzymatic replacement therapies directed to peripherical symptoms, for the inability of the proteins to pass the blood-brain barrier. In the last years innovative solutions to deliver the drug to the CNS have been designed, highlighting the need of comprehensive reliable testing systems. We set up in vitro platforms using peripheral cells, i.e. primary human fibroblasts from patients affected by two model pathologies (alpha-mannosidosis, aMAN; Niemann-Pick A, NP-A) and healthy subjects, and neuronal cells using primary neuronal/astrocytes cultures from cerebral cortex of transgenic mice models of the two diseases. Lysosomal defects were analyzed by morphological and functional tools, and validation of the readouts was performed assessing the restoration of the lysosomal features by treatment with approved enzyme replacement therapies. LAMP1 staining was set up for the analysis by confocal microscopy. Using the voxel-based IMARIS image analysis software, we reconstructed the volume of each single lysosome in the cell, quantifying the average lysosome volume per cell, also tracking the 3D intracellular distribution. We described how the mutations lead to an increase in number and volume of lysosomes, and the change in distribution, with the lysosomal net accumulating around the nucleus. We than implemented the morphological analysis with functional data using LysoTracker Red and DQ-BSA staining. The number of LysoTracker Red stained lysosomes significantly increased in mutated cells, describing an acidification of the lysosomal content. Moreover, the accumulation of DQ-BSA resulted increased as well, demonstrating that mutant lysosomes are not able to properly degrade the BSA. For each readout, scaling to High-Content Screening methodology was considered, to increase the statistical and translational power of the platform.