"

From 2010.igem.org

Simulations

Background

We constructed a molecular ODE model of the chemotaxis pathway which we extended for the PIF3/PhyB localization system which has red and far-red light pulses as input. This molecular model was coupled to a phenomenological model probabilistically simulating cell motility. This phenomenological model is a two-state model, with the state either corresponding to tumbling or directed movement. While in the straight swimming state the E. lemming model mainly moves in its current direction and the angular speed is low, during the tumblings the angle changes rapidly while the E. lemming rests at its current position. The probability of switching between the two states depends on the current concentration of the intracellular CheYp level, which is used to calculate the so called "bias" (time spend in directed movement divided by total time). Thus, it is possible to influence the probabilistic movement of the E. lemming model by giving short red or far-red light pulses.

The video is showing the whole model, consisting of the molecular model of the chemotaxis pathway and the cell motility model, under the supervision of an automated controller which tries to force the E. lemming to swim counter-clockwise around a huge rectangle (blue rectangle in the mini-map at the top right). The movement of the E. lemming is visualized with the help of an image generator which is coupled to the same visualization functions as used for the real experiments. As can be seen, although the movement of the E. lemming still reminds of a random walk, this random walk is biased in the direction the controller tries to force the E. lemming (indicated by the red line).

The model is thus able to simulate the whole information pathway, from the light signals, to the change in the concentrations of the intracellular species of the chemotaxis pathway, and further to their influence on cell movement. By using a microscope look-alike image generator, it is also possible to connect the model to the cell detection and tracking algorithms, as well as to the visualization functions and the controller, all of which were mainly created for the real experiments but could be tested and optimized using the model. Thus, the simulations of the model do not only have the purpose to look nice, but also decreased significantly experimental time in the laboratory.