Difference between revisions of "Team:Technion Israel/Model"
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| − | The experiment ran as shown in the "Introduction" section: The channel was filled with bacteria in motility buffer and then the sample was inserted. We replaced the motility buffer with water and the chemo-repellent with potassium permanganate in the following amounts: | + | The experiment ran as shown in the "Introduction" section: The channel was filled with bacteria in motility buffer and then the sample was inserted. We replaced the motility buffer with water and the chemo-repellent with potassium permanganate in the following amounts: |
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| − | Motility buffer is mostly water (98%) and can be modelled by it. Potassium | + | |
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| − | + | Motility buffer is mostly water (~98%) and can be modelled by it. Potassium permanganate is a salt with a known diffusion limit and acts as most of the materials we want detect using our system (small molecules). Also, it has a very distinct pink color in low concentration which makes diffusion limit visible. <br> | |
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| − | + | We ran the experiment 4 times, with a standard ruler to measure the distance of the diffusion limit.???? | |
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Revision as of 10:54, 18 October 2016
Introduction
The goal of this model is to describe the processes inside the Flash Lab system:
- Change in the concentration of chemo-repellent.
- Change in the concentration of bacteria.
This model is based on the Keller – Segal equation of chemotaxis (1) in a one dimensional problem (Thin channel).
It's important to notice that this model can show the overall behavior and not exact values. The final system is supposed to detect a variety of materials in many different unknown solvents, each of them has its own diffusion properties. Also, some aspects such as working conditions (temperature, humidity etc.) might change in widespread commercial use and affect the results. Taking those into account, further fitting will be necessary.
Chemo-Repellent Concentration
Model
The basic assumptions of the model for the chemo-repellent are:
There are no forces except diffusion:
-Chemo-repellent concentration in the sample is relatively low and does not cause osmotic pressure.
-The changes in pressure due to loading the sample is negligible.
-No other significant external forces (for example, moving the chip while in use).
The bacteria do not consume the chemo-repellent and its concentration does not change with time. This is not case with chemo-attractants.
We expect to detect small proteins and molecules (the materials bacterial receptors bind to). The diffusion coefficient for such materials is about 10-9[m2/s].
Because of the geometric properties of the channel and the expected diffusion coefficient, this is approximately a half-infinite one dimensional problem.
Initial condition: no chemo-repellent is present in the chip at time zero.
Boundary condition: at infinite distance the concentration is zero and the there is conservation of dissolved material mass (c).
We modelled the change in concentration of the chemo-repellent based on a "Top Hat Function" solution for the diffusion problem:
Equation 1: Chemo-repellent diffusion problem.
v[M] is the chemo-repellent concentration,
D[m2/s] is the chemo-repellent diffusion coefficient,
N[mol] is the number of repellent atoms,
A[m2] is the cut section of the channel,
x[m] is the distance on the channel,
t[s] is time.
The solution for this problem is:
Equation 2: General solution for chemo-repellent diffusion problem.
Graph 1: Chemo-repellent concentration: top hat diffusion.
In our problem, we want the diffusion to start from. Also, we are interested only in the positive part of the solution:
Equation 3: Chemo-repellent concentration.
Model Results
We ran the chemo-repellent concentration equation in Matlab - Our code can be found here. The parameters used are:
Table 1: Parameters for diffusion model.
*This is the diffusion coefficient for potassium permanganate (see "Comparison to Experiment")
** h = (Sample_volume)/(Reservoir_cut_section).
The output for different times:
Graph 2: Model for repellent concentration.
The change in distance of the diffusion limit between 0 to 15 minutes, is relatively big. As the time passes the diffusion limit's speed lowers significantly and the concentration, becomes more linear.
Comparison to Experiment
Most diffusion experiments need a dedicated system that is based on the diffusion of an isotope or a fluorescent material that can be detected easily and very precisely. In this case, we chose a more basic system given that this is only a preliminary testing as our goal is showing that the overall system behaves as we expect.
The experiment ran as shown in the "Introduction" section: The channel was filled with bacteria in motility buffer and then the sample was inserted. We replaced the motility buffer with water and the chemo-repellent with potassium permanganate in the following amounts:
Table 2: Substance for diffusion experiment.
Motility buffer is mostly water (~98%) and can be modelled by it. Potassium permanganate is a salt with a known diffusion limit and acts as most of the materials we want detect using our system (small molecules). Also, it has a very distinct pink color in low concentration which makes diffusion limit visible.
We ran the experiment 4 times, with a standard ruler to measure the distance of the diffusion limit.????
Fig. 1: Diffusion of potassium permanganate in water in different times (enhanced picture).
As expected by the mathematical model, the diffusion limit starts moving relatively fast and its speed decreases rapidly.
The difference in distance between the model to the experiment (average of 2.5[mm] fro, T=0) can be explained by:
- The actual diffusion limit is in too low concentration of potassium permanganate to be seen in the naked eye.
If the visible con-centration is about 0.000015 [M] the experiments results lines up with the model (Graph 2.2).
- The roller is a crude measuring tool. Its mistake is +/- 0.5 [mm].
- Difficulties loading the sample in a uniform way, especially in low volumes. Mistakes in loading the sample inside the bacterial fluid and not on, or sticking the
drop of sample to one of the entry slot walls will cause uneven diffusion.
Graph 2.3: Comparison of diffusion model to experiment.
Results
Outlook
References:
1. KELLER, Evelyn F.; SEGEL, Lee A. Model for chemotaxis. Journal of theoretical biology, 1971, 30.2: 225-234.
