This model reveals the same scenario in the giant petri dish experiment on the evolution of antibiotic resistance conducted by the researchers from Harvard Medical School and Technion-Israel Institute of Technology (http://news.harvard.edu/gazette/story/2016/09/a-cinematic-approach-to-drug-resistance/). Mutation and reproduction rates are included to expand user's exploration of the process.
Grades: 9-12, College Introductory Biology;
NGSS standards: HS-LS4-3
The antibiotic concentrations are set at low, medium, high, and peak levels from two sides to the center of the model.
The model starts from the strain with resistance between 1-2.
The bacteria reproduce asexually.
At a chance of defined mutation-rate, the offspring resistance may increase or decrease within the mutation range.
In each tick, all bacteria may move a small distance in a random direction.
Students may adjust the growth rates of the strain with different resistance. Note: we should not assume the growth rate being the same or different. Remember, this is a model. It helps us generate ideas. We need empirical evidence to test the ideas.
The nutrient in a patch may run out and lead to the death of the bacteria on the patch. But the nutrient is refilled in the next tick on the patch (which does not happen in real bacterial culture).
The model has two views. The bacteria view gives a more realistic view, while the icon view allows the model to run faster.
How does the mutation range affect the evolution of antibiotic resistance?
How does the growth rate affect the competition among strains with different resistance when antibiotics are present?
How does the growth rate affect the competition among strains with different resistance when antibiotics are absent?
What happens when all strains have the same or different growth rates?
Does the strain with higher resistance always first appear where the antibiotic concentration is higher?
What will happen to the strains if you keep increasing dose?
Dr. Lin Xiang made this model in 2017 and revised in 2021 at the University of Kentucky. If you mention this model in a publication, we ask that you include the citations below.
Xiang, L. (2021). Evolution of antibiotic resistance. Department of STEM Education, University of Kentucky , Lexington, KY.
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