Controls environmental parameters of the simulation.
Play/Pause: Begins and pauses the simulation.
Reset: Generates a population of cells based on the parameter sliders and moves them to the origin of the simulation.
Gradient type: Controls how the concentration of attractant changes along the simulation’s x-axis:
Exponential - The attractant concentation is an exponential function of x-axis position.
Linear - The attractant concentration is a linear function of x-axis position.
Periodic - The attractant concentration oscillates from high to low several times along the x-axis.
Food - Fills the world with simulated food, which acts as the attractant. Cells eat food and remove it from the environment, so they generate their own concentration gradient as they spread.
Cursor - Creates an exponential attractant gradient centered on the location of the mouse cursor when the left mouse button is held down. Releasing the left mouse button causes the attractant gradient to disappear.
Walls: Controls what kind of walls appear. Cells cannot pass through walls, so different shapes will have different impacts on how cells can move within the simulation. Walls are only active when the “On” checkbox is selected:
Draw - Allows you to draw walls inside of the simulation. Just click and drag your mouse to draw the walls.
Erase - Turns on eraser mode, which works just like “Draw”, but erases walls instead of creating them.
Square - Causes a series of walls with gaps to appear.
Round - Causes a series of evenly-spaced circles to appear.
Pebbles - Similar to “Round”, but instead of being a few large circles that are the same size, it consists of many small irregularly shaped objects.
Clear - Completely removes all walls from the simulation.
Trails: The simulation will draw a faint trail behind the cells, allowing you to more easily follow the cells’ paths.
Plots: Controls whether the simulation is drawn, the graphs are drawn, or if both are shown. Switching to graph only mode may speed up the simulation.
Evolve: When unselected, the cells will bounce off of the right edge of the simulation, just as they do for the other edges. When enabled, cells reaching the right edge of the simulation are copied several times to produce daughter cells. These daughter cells are placed at the origin. Simultaneously, several old cells are deleted from the simulation so the total number of cells remains constant. Natural selection will then being to optimize the chemotaxis parameters of the population.
Save pop: Moves the parameter sliders so that they tightly bound the current population parameters. Useful when combined with “Evolve population”, since you can let the population evolve, causing the chemotaxis parameters to become well-adapted to the current environment, then hit “Set population”. You can then change the population size, gradient, walls, etc. and restart the simulation with your evolved population in a new environment and see how they respond.
Set pop: Moves the parameter sliders to generate a population of cells that are generally good at chemotaxis in most environments.
Reset pop: Reset the parameter sliders to a wide range of phenotypes. Useful to restart an evolutionary experiment.
The sliders for receptor activity, adaptation time, motor gain, and switching rate have two buttons. The top button sets the upper bound, and the lower one sets the lower bound for the population.
Cell number: Controls the number of cells in the simulation.
Gradient slope: Controls the rate of change of attractant (“food”) concentration from left to right. Larger values cause the concentration to increase more quickly.
Receptor activity: Set the range of population receptor activities. Higher values indicate a higher resting CheY-P level.
Adaptation time: Set the range of population adaptation times, which are the rate at which the chemotaxis system returns to the resting state after being exposed to attractant. Larger adaptation times mean that CheY-P levels return to the resting state more slowly after the cell is exposed to attractant.
Motor Gain: Sets the amplitude of the motor response. High gain mean that the motor has a sharp transition from spending most of its time running to spending most of its time tumbling, as a function of CheY-P concentration. Low gain means that the transition occurs more smoothly from mostly running to mostly tumbling.
Switching Rate: The rate at which the cell switches between running and tumbling. A high switching rate indicates the cell rapidly transitions between runs and tumbles, while low values mean the cell rarely transitions between runs and tumbles. Said another way, a low switching rate indicates that the cell likes to continue doing what it is currently doing, and so resists changes between the run and tumble states. A high switching rate indicates the opposite; the cell freely alternates between running and tumbling.
In the scatterplots each point represents a single cell. In the other graphs the lines show the average population parameters.
Colors: Controls whether cells are colored based on their receptor phenotype or their motor phenotype.
dYp vs dx: Shows the change in CheY-P concentration (dYp) caused as a function of change in X position of the cell (dx). This should normally have a slight downwards slope from left to right, as chemotaxing cells tend to move towards the right side of the simulation (positive dx), which is also towards higher levels of attractant. Increasing attractant concentration causes a drop in cheY-P levels (negative dYp).
Methylation vs X position: The degree of MCP methylation as a function of position along the x-axis.
Drift velocity vs Diff. coeff.: The diffusion coefficient, which describes the rate at which a particle diffuses through space, as a function of drift velocity. The drift velocity is the net speed the cell moves up the gradient.
Adaptation time vs Adapted Yp: Shows the phenotypic space for the receptors, which is a function of adapted (resting) CheY-P levels, and the adaptation time, ie. how quickly does the cell return to adapt to the current level of attractant and return to the resting state.
Yp vs Time: Describes how CheY-P recovers after exposure to a constant level of attractant. Increases from left to right before leveling off.
Motor switching rate vs motor gain: Shows the phenotypic space for the motor, which is a function of motor gain, how sharp is the transition from mostly running to mostly tumbling as a function of CheY-P levels, and motor switching rate, which determines whether the motor freely switch between running and tumbling, or prefers to keep doing what it's doing.
Mean run/tumble time vs Yp vs Motor Bias: The green and red lines describe the average length of a run or tumble, respectively, as a function of Yp. The black line is the tumble bias, which is the proportion of time the motor spends in the tumble state as a function of Yp. The sharpness of this transition is mediated by the motor gain. High gain make the mean run/tumble times change quickly over a narrow Yp interval. Low gain means the transition occurs over a wide Yp interval.