The gate-size slider decides how wide each gate is and is measured in number of patches. The Sec gates have various alteration which can be made to them. PP1 must bind to these proteins before they are allowed to enter the Sec gate and become transported at the membrane.The SecB proteins cannot enter the periplasm. The initial number of SecB proteins (shown as green keys) can be controlled by the initial-SecB slider. The number of PP1 setup initially in the cytoplasm is controlled by the initial-PP1 slider, these are then placed at a set of random co-ordinates inside the cytoplasm. Thus, if a molecule of any kind encounters the top/bottom wall it will re-appear at the opposite wall (bottom/top respectively). Continuing this simulation, PP1 which encounters the right wall of the world is lost to the rest of the cell and so is removed in the simulation.Īlthough a similar system could be implemented for PP1 which encounters the upper and lower walls, we can simply assume that an equal number of molecules are lost to an equivalent segment above/below as enter the current segment. ![]() This is in simulation of PP1 from the rest of the cell entering our specific segment. PP1 can be produced at a user-chosen rate from the right-side of the world (PP1-production slider). We have several mechanisms in place in order to accurately simulate the operation of our bacterial mop. Fig 1 shows how the world is set up and what the different agents represent. The investigated section included the cytoplasm, inner & outer membranes, and the periplasm. ![]() coli bacterial mop which utilised the Sec protein-translocation pathway was analysed. A full explanation of how these pathways work can be found here.Ĭlick to view the simulations of these export systems: Sec Simulation Applet Tat Simulation Applet Model 1 – Sec System in E. subtilis while the Tat system was implemented in E. The wet team were utilising two pathways within the cell to transport Protein Phosphatase 1 to the desired location. ![]() The aim was to create a simulation in which variables and characteristics can be altered, depending on the cells state, allowing us to observe the effect of such changes on the operation of the mop. Dundee iGEM Team used NetLogo as a tool to allow the visualisation of intracellular interactions within our bacterial mops and so to bring the dynamics to life. NetLogo is a multi-agent programmable modelling environment. Software by the Dundee iGEM team is distributed under the terms of the GNU General Public License.
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