Team:UPO-Sevilla/Modeling

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<h2> Bacteria motion</h2>
<h2> Bacteria motion</h2>
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The main actuator of <i>E. Coli</i> is a flagellar motor that can rotate clock and counterclockwise.
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Through a set of transmembrane receptors proteins, <i>E. Coli</i> is able to detect chemoattractants. Moreover, this detection influences the motion of the flagellar motor.
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E. Coli has two main motion modes, which we will name:
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<ol>
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<li> Random Walk </li>
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<li> Gradient climbing </li>
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</ol>
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<b>Random walk mode</b>
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When no gradient of chemoattractant is present, <i>E. Coli</i> is in random walk mode. In this case, the bacteria performs smooth runs followed by tumbles.
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Mathematically, we will model this as a Brownian motion:
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<center>
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<img src="https://static.igem.org/mediawiki/2010/b/bc/UPO-Model-Eq5.png" width="300 "alt="First Fick Law"/>
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</center>
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where <b>x</b> is the position of the bacteria and <b>v</b> is the velocity. This (vector) velocity is randomly sampled from a normal distribution of zero mean and a certain covariance matrix that models the potential .
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<center>
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<img src="https://static.igem.org/mediawiki/2010/b/bd/UPO-Model-Eq6.png" width="150 "alt="First Fick Law"/>
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</center>
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The bacteria will move for a time &Delta; <i>t</i><sub>rm</sub> with constant velocity <b>v</b>(<i>t</i>). At next time instant, a new velocity is (randomly selected) selected 
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<b>Gradient climbing behaviour</b>
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When a positive difference of concentration (a gradient) on the chemoattractant is detected, the bacteria enters into a new mode that we will call gradient climbing.
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In this mode, the flagellar motor tends to move counterclockwise; as a result, the smooth runs last for more time, and the tumbling frequency decreases.
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In order to model that, we use the same model than above, but a larger tumbling interval (smaller tumbling frequency) $\Delta t_{gc}$

Revision as of 09:17, 7 October 2010



Models

The members of the dry lab are simulating the different components of the full system. Three main components can be identified:
  1. The difussion of the chemoattractant through the medium.
  2. The motion of the bacterias through the medium due to the gradient on the chemoattractant concentration.
  3. The chemoattractant generation within the bacteria.

Chemoattractant Diffusion

The basic equations for the diffusion of the chemoattractant in the medium are the Fick laws of diffusion, which govern the variation of the concentration of a substance within a medium.

The flux J (that is, the amount of substance that flows through a given surface per unit of time mol m-2s-1) is given by:

First Fick Law

where φ is the concentration (mol m-3) in a given point. D is a constant called the diffusion coefficient, and that depends on the medium .

Basically, the equation states that the is directed towards places with lower concentration (thus the minus sign). If the concentration is constant in the space (∇φ=0) there is no flux.

If the flux is known, it is possible to determine the amount of substance that goes through a small surface S and a small amount of time dt

First Fick Law

In order to simulate the diffusion, we define the environment and discretize it in very small cells. Each cell determines a given volume V, and has a surface S. At a given time instant, the cell has an amount of substance c (and then a concentration c\V).

If the cells and time step Δt are small, we can consider that the gradient of concentration can be approximated though the differences in concentration between a cell i and 4 (or 8) neighbors j. Thus:

First Fick Law

and then, the amount of substance that diffusses from i to j:

First Fick Law

Bacteria motion

The main actuator of E. Coli is a flagellar motor that can rotate clock and counterclockwise. Through a set of transmembrane receptors proteins, E. Coli is able to detect chemoattractants. Moreover, this detection influences the motion of the flagellar motor. E. Coli has two main motion modes, which we will name:
  1. Random Walk
  2. Gradient climbing
Random walk mode When no gradient of chemoattractant is present, E. Coli is in random walk mode. In this case, the bacteria performs smooth runs followed by tumbles. Mathematically, we will model this as a Brownian motion:
First Fick Law
where x is the position of the bacteria and v is the velocity. This (vector) velocity is randomly sampled from a normal distribution of zero mean and a certain covariance matrix that models the potential .
First Fick Law
The bacteria will move for a time Δ trm with constant velocity v(t). At next time instant, a new velocity is (randomly selected) selected Gradient climbing behaviour When a positive difference of concentration (a gradient) on the chemoattractant is detected, the bacteria enters into a new mode that we will call gradient climbing. In this mode, the flagellar motor tends to move counterclockwise; as a result, the smooth runs last for more time, and the tumbling frequency decreases. In order to model that, we use the same model than above, but a larger tumbling interval (smaller tumbling frequency) $\Delta t_{gc}$

Chemical reactions

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