Revisiting APP secretases: an overview on the holistic effects of retinoic acid receptor stimulation in APP processing.

Alzheimer's disease (AD) is the leading cause of dementia worldwide and is characterized by the accumulation of the ß-amyloid peptide (Aß) in the brain, along with profound alterations in phosphorylation-related events and regulatory pathways. The production of the neurotoxic Aß peptide via amyloid precursor protein (APP) proteolysis is a crucial step in AD development. APP is highly expressed in the brain and is complexly metabolized by a series of sequential secretases, commonly denoted the α-, ß-, and γ-cleavages. The toxicity of resulting fragments is a direct consequence of the first cleaving event. ß-secretase (BACE1) induces amyloidogenic cleavages, while α-secretases (ADAM10 and ADAM17) result in less pathological peptides. Hence this first cleavage event is a prime therapeutic target for preventing or reverting initial biochemical events involved in AD. The subsequent cleavage by γ-secretase has a reduced impact on Aß formation but affects the peptides' aggregating capacity. An array of therapeutic strategies are being explored, among them targeting Retinoic Acid (RA) signalling, which has long been associated with neuronal health. Additionally, several studies have described altered RA levels in AD patients, reinforcing RA Receptor (RAR) signalling as a promising therapeutic strategy. In this review we provide a holistic approach focussing on the effects of isoform-specific RAR modulation with respect to APP secretases and discuss its advantages and drawbacks in subcellular AD related events.

Optimized Automated Analysis of Live Neuronal Mitochondria Homeostasis Modulation by Isoform-Specific Retinoic Acid Receptors.

The complex mitochondrial network makes it very challenging to segment, follow, and analyze live cells. MATLAB tools allow the analysis of mitochondria in timelapse files, considerably simplifying and speeding up the process of image processing. Nonetheless, existing tools produce a large output volume, requiring individual manual attention, and basic experimental setups have an output of thousands of files, each requiring extensive and time-consuming handling. To address these issues, a routine optimization was developed, in both MATLAB code and live-script forms, allowing for swift file analysis and significantly reducing document reading and data processing. With a speed of 100 files/min, the optimization allows an overall rapid analysis. The optimization achieves the results output by averaging frame-specific data for individual mitochondria throughout time frames, analyzing data in a defined manner, consistent with those output from existing tools. Live confocal imaging was performed using the dye tetramethylrhodamine methyl ester, and the routine optimization was validated by treating neuronal cells with retinoic acid receptor (RAR) agonists, whose effects on neuronal mitochondria are established in the literature. The results were consistent with the literature and allowed further characterization of mitochondrial network behavior in response to isoform-specific RAR modulation. This new methodology allowed rapid and validated characterization of whole-neuron mitochondria network, but it also allows for differentiation between axon and cell body mitochondria, an essential feature to apply in the neuroscience field. Moreover, this protocol can be applied to experiments using fast-acting treatments, allowing the imaging of the same cells before and after treatments, transcending the field of neuroscience.