Mathematical modeling of bacteria communication in continuous cultures
Quorum sensing is a bacterial cell-to-cell communication mechanism and is based on gene regulatory networks, which control and regulate the production of signaling molecules in the environment. In the past years, mathematical modeling of quorum sensing has provided an understanding of key components...
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| Main Authors: | , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
16 May 2016
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| In: |
Applied Sciences
Year: 2016, Volume: 6, Issue: 5 |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app6050149 |
| Online Access: | Verlag, kostenfrei, Volltext: http://dx.doi.org/10.3390/app6050149 Verlag, kostenfrei, Volltext: http://www.mdpi.com/2076-3417/6/5/149 
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| Author Notes: | Maria Vittoria Barbarossa, Christina Kuttler |
MARC
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| 520 | |a Quorum sensing is a bacterial cell-to-cell communication mechanism and is based on gene regulatory networks, which control and regulate the production of signaling molecules in the environment. In the past years, mathematical modeling of quorum sensing has provided an understanding of key components of such networks, including several feedback loops involved. This paper presents a simple system of delay differential equations (DDEs) for quorum sensing of Pseudomonas putida with one positive feedback plus one (delayed) negative feedback mechanism. Results are shown concerning fundamental properties of solutions, such as existence, uniqueness, and non-negativity; the last feature is crucial for mathematical models in biology and is often violated when working with DDEs. The qualitative behavior of solutions is investigated, especially the stationary states and their stability. It is shown that for a certain choice of parameter values, the system presents stability switches with respect to the delay. On the other hand, when the delay is set to zero, a Hopf bifurcation might occur with respect to one of the negative feedback parameters. Model parameters are fitted to experimental data, indicating that the delay system is sufficient to explain and predict the biological observations. | ||
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