Using systems biology approaches to study a multidrug resistance network
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- TL;DR
- Multidrug resistance, a major challenge in human health, agro-food, and environmental biotechnology, is often driven by the transcriptional activation of drug efflux pumps.
- Problem
- Not specified in the abstract.
- Method
- Using data from the YEASTRACT database and experimental findings, researchers defined the transcriptional regulatory network controlling the FLR1 gene in yeast under fungicide stress. They then built a mathematical model using the Genetic Network Analyzer (GNA) software to simulate the system's behavior across different genetic backgrounds.
- Results
- The approach identified essential features of the transition from unstressed to fungicide-stressed cells and generated new predictions about the system's dynamics, which were successfully validated experimentally.
- Contributions
- Not specified in the abstract.
- Limitations
- Not specified in the abstract.
- Takeaways
- This work demonstrates a successful combination of experimental and computational approaches within a systems biology framework to study gene regulation.
- Applications
- Not specified in the abstract.
- Topics
- Not specified in the abstract.
- For industry
- Agro-Food, Environmental Biotechnology, and Human Health.
- Why it matters
- Provides a robust systems biology framework for understanding multidrug resistance mechanisms across health and environmental sectors.
Abstract
Multidrug resistance (MDR), a phenomenon with impact in Human Health and in Agro-Food and Environmental Biotechnology, often results from the activation of drug efflux pumps, many times controlled at the transcriptional level. The complex transcriptional control of these genes has been on the focus of our research, guided by the information gathered in the YEASTRACT database. In this paper, the approach used to elucidate the transcriptional control of FLR1, encoding a Saccharomyces cerevisiae Drug:H Antiporter, in response to stress induced by the fungicide mancozeb is explained. The transcription regulatory network underlying FLR1 activation was defined based on experimental data. Subsequently, a mathematical model describing this network was built and its response to mancozeb stress in different genetic backgrounds was simulated, using the Genetic Network Analyzer (GNA) software. This approach allowed the identification of essential features of the transition from unstressed to fungicide stressed cells and to make new predictions on the dynamical behavior of the system, which were validated experimentally. This work provides a good example of the successful combination of experimental and computational approaches in a systems biology perspective.