Fitness of Antibiotic-Resistant Bacteria in the Environment: A Laboratory Activity
In this laboratory experiment, we propose an opportunity for students to broaden their understanding of the ecology of antibiotic-resistant and sensitive waterborne bacteria. Antibiotics can be found in rivers or soil as a consequence of agricultural practices or as a result of human use. Concentrat...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
American Society for Microbiology
2017
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/65d5aabef14543aa9198491dc14d350e |
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| Sumario: | In this laboratory experiment, we propose an opportunity for students to broaden their understanding of the ecology of antibiotic-resistant and sensitive waterborne bacteria. Antibiotics can be found in rivers or soil as a consequence of agricultural practices or as a result of human use. Concentrations of antibiotics in the environment may range from a few ng to μg L−1. Such concentrations can affect the selection and fitness of resistant bacteria. In this laboratory activity, students learn how to set up a fitness experiment by using an isogenic pair of antibiotic-resistant and sensitive bacteria in the presence or absence of selective pressure. Microcosms were generated by using filtered river water containing populations of resistant and sensitive bacteria. Competition of both populations was measured in the presence or absence of antibiotics. Students appreciated the use of microcosms for in vitro experiments and the extent to which the fitness of resistant and sensitive bacteria changed in the presence and/or absence of a selective pressure in river water. Student learning was measured by using different types of assessments: multiple-choice, true/false, fill in the blanks, laboratory skills observations, and laboratory reports. After the laboratory activity, the percentage of correct answers significantly rose from ~20% to ~85%. Laboratory skills were also evaluated during the exercises, showing no major issues during the experiment. Students showed proficiency in analyzing the complexity of fitness data by reaching a mean of 5.57 (standard error 0.57) over a maximum score of 7 points. |
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