Autophagy: detection methods and experimental and bioinformatic models

 Background:

 Macroautophagy or simply autophagy is an evolutionarily conserved catabolic process through which various intracellular entities (e.g. macromolecular aggregates and damaged organelles) are sequestered within double-membrane vesicles, so-called autophagosomes, and delivered to lysosome for bulk degradation and recycling. The primary goal of this quality control process, which is driven by the activation of autophagy-related genes, is to help cells maintain homeostasis and survival under stressful conditions, including nutrient starvation, infection and hypoxia. However, excessive autophagy may culminate in type II programmed (autophagic) cell death. Recent evidence shows that both insufficient and extensive activity of autophagy can be associated with the pathological conditions in a variety of diseases, including cancer and neurodegenerative disorders. Therefore, both blockade and induction of autophagy hold promising potential for the development of new therapies for human diseases. In this one-day workshop, we are going to draw the attention of researchers from Iran and neighbor countries to the importance of autophagy research and methods and protocols that need to run a standard  autophagy research.
 
Following topics will be covered in this workshop (8 h):
1. Autophagy: introduction, molecular mechanisms and its relation with human diseases (1.5 h)
 
2. Standard autophagy detection methods (2 h):
2.1. Fluorescent microscopy and western blotting
2.2. The concept of autophagy flux or block
 
3. Experimental models of autophagy (1.5 h):
3.1. In vitro models
3.2. In vivo models
 
4. Bioinformatic tools for studying autophagy (3 h)
 
 5. Free discussion
 
Lecturers (will be confirmed later): 
 
- Dr. Mohammad Amin Moosavi, NIGEB (autophagy: introduction and detection methods) in collaboration with investigators from Leeds University, UK, and INSERM, France.
 
- Dr. Marveh Rahmati, TUMS (experimental models)
 
- Dr. Ali Shariati and Zoha Nayeri, NIGEB (Bioinformatics)
 




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