Mathematical modeling of Cajal body formation
European Microscopy Congress 2016: Proceedings(2016)
Abstract
In the living cells, there are many structures and organelles enveloped with a membrane that defines their border and controls the communication between the inner and outer environment. In contrast to membrane bound compartment, cells contain numerous membrane‐less structures, whose formation is based on specific interactions among their components. These types of structures include Cajal bodies (CBs), PML bodies and P‐Bodies found in most cell types, stress granules that appear upon environmental stress (heat shock, oxidative stress etc.) or various aggregates that form as result of protein/RNA mutations (e.g. protein inclusions in ALS). The biological role of the membrane‐less structures is a topic of intensive research and the function of several bodies have been revealed. However, little is known about principles that lead to their formation. As an archetypal compartment, we employed the CB (Fig.1), the self‐organizing structure involved in metabolism of various ribonucleoprotein particles. We employed time‐gated Stimulated Emission Depletion (gSTED) microscopy to acquire superresolution microscopy images of the CB and surrounding nucleoplasm. We have visualized the CB scaffolding protein coilin using indirect immunofluorescence in situ. Our preliminary data clearly showed the sub‐resolution structures of the CB (subCBs). Moreover, the substructures are also visible in the surrounding nucleoplasm and indicate that the CB is an aggregate of those basic building blocks (Fig.2‐B). Here, we would like to present our work on a mathematical model based on the fundamental thermodynamic rules of condensation and phase‐separation to describe the formation of membrane‐less bodies. We will present superresolution fluorescence microscopy, photo‐kinetic experiments and fast time‐lapse live cell imaging results and progress of the work on determining of basic biophysical behavior of individual CB components. The project is interdisciplinary and combines advanced fluorescence microscopy techniques and mathematical modeling and simulations.
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