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Feedback Control Architecture and the Bacterial Chemotaxis Network

Author

Listed:
  • Abdullah Hamadeh
  • Mark A J Roberts
  • Elias August
  • Patrick E McSharry
  • Philip K Maini
  • Judith P Armitage
  • Antonis Papachristodoulou

Abstract

Bacteria move towards favourable and away from toxic environments by changing their swimming pattern. This response is regulated by the chemotaxis signalling pathway, which has an important feature: it uses feedback to ‘reset’ (adapt) the bacterial sensing ability, which allows the bacteria to sense a range of background environmental changes. The role of this feedback has been studied extensively in the simple chemotaxis pathway of Escherichia coli. However it has been recently found that the majority of bacteria have multiple chemotaxis homologues of the E. coli proteins, resulting in more complex pathways. In this paper we investigate the configuration and role of feedback in Rhodobacter sphaeroides, a bacterium containing multiple homologues of the chemotaxis proteins found in E. coli. Multiple proteins could produce different possible feedback configurations, each having different chemotactic performance qualities and levels of robustness to variations and uncertainties in biological parameters and to intracellular noise. We develop four models corresponding to different feedback configurations. Using a series of carefully designed experiments we discriminate between these models and invalidate three of them. When these models are examined in terms of robustness to noise and parametric uncertainties, we find that the non-invalidated model is superior to the others. Moreover, it has a ‘cascade control’ feedback architecture which is used extensively in engineering to improve system performance, including robustness. Given that the majority of bacteria are known to have multiple chemotaxis pathways, in this paper we show that some feedback architectures allow them to have better performance than others. In particular, cascade control may be an important feature in achieving robust functionality in more complex signalling pathways and in improving their performance.Author Summary: Bacteria move towards favourable environments by changing their swimming pattern. An important feature of this response, which is called bacterial chemotaxis, is that their sensing ability remains independent of the background environment in which they find themselves. This feature has been studied extensively in the bacterium E. coli, which has a simple chemotaxis decision mechanism. However, it has been recently found that most bacteria could potentially have a much more complicated decision mechanism for this response. In this paper, we look at the chemotaxis behaviour of one such bacterium, R. sphaeroides. We develop mathematical models of possible decision mechanisms and undertake an experimental procedure to investigate their validity. We find that only one of four such models can explain the chemotaxis response in R. sphaeroides. Compared to the other models, this model corresponds to a decision mechanism that provides the bacterium with improved swimming performance over the others. Moreover, this decision mechanism has been used extensively to improve performance in several engineering systems. We suggest that this mechanism may play an important role in improving chemotactic performance in other bacteria and in other signalling pathways.

Suggested Citation

  • Abdullah Hamadeh & Mark A J Roberts & Elias August & Patrick E McSharry & Philip K Maini & Judith P Armitage & Antonis Papachristodoulou, 2011. "Feedback Control Architecture and the Bacterial Chemotaxis Network," PLOS Computational Biology, Public Library of Science, vol. 7(5), pages 1-15, May.
  • Handle: RePEc:plo:pcbi00:1001130
    DOI: 10.1371/journal.pcbi.1001130
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    References listed on IDEAS

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    1. Diana Clausznitzer & Olga Oleksiuk & Linda Løvdok & Victor Sourjik & Robert G Endres, 2010. "Chemotactic Response and Adaptation Dynamics in Escherichia coli," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-11, May.
    2. Leland H. Hartwell & John J. Hopfield & Stanislas Leibler & Andrew W. Murray, 1999. "From molecular to modular cell biology," Nature, Nature, vol. 402(6761), pages 47-52, December.
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