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Noise-Induced Phenomena and Complex Rhythms: A Test Scenario for Plant Systems Biology

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Rhythms in Plants

Abstract

Combining the unravelling of the molecular bases of functions in time and of organization in space in biology, on the one hand, with nonlinear dynamics as part of theoretical physics, on the other, is promising great progress in basic understanding of nonlinear spatial pattern formation from huge amounts of data becoming available in systems biology . In this chapter, this will be assessed in terms of the “tripod” (1) experimentation, (2) modelling and (3) theory.

  1. 1.

    Empirical case studies of rhythmicity are derived from three areas of study, (i) Crassulacean acid metabolism, (ii) stomatal pore regulation by guard cells and (iii) plant memory. Biorhythmicity is underlying the former two, whose spatiotemporal dynamics can be documented by, among other techniques, chlorophyll fluorescence imaging. The third one, plant memory, is intimately related to rhythmicity and the biological clock with its set points and phase regulation. All three case studies reveal nonlinear performance with synchronization /desynchronization leading to modelling and theoretical concepts.

  2. 2.

    In modelling, maximal models, providing perfectionist “photographic” imaging of nature, are distinguished from minimal models singling out essential domains in the parameter space of systems, with heuristic aims. The latter are explored in approaches based on experiment/theory feedback .

  3. 3.

    Theoretical assessment dwells on the method of cellular automata , which are frameworks for simulating spatiotemporal patterns arising from local interactions. The theoretical concepts developed are based on the examination of stochasticity with the order-generating effects of noise in stochastic resonance and coherence resonance, where intermediate noise intensity generates quasi-rhythmic behaviour of systems from arrhythmicity.

This merges into a new path towards systems biology , where extensive data currently provided by analytical progress are integrated into the concept of universal dynamic principles. We illustrate this new path by using simple models of synchronization , this being one concept which systems biology can then exploit for the construction of more advanced models.

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Notes

  1. 1.

    Although ordinary differential equations are a frequent approach to modelling, a wide variety of other descriptions exists. One passes to partial differential equations when, in addition to changes in time, the spatial behaviour is taken into account. When a focus is on the influence of fluctuations on the dynamics, stochastic differential equations are analysed. Often, formulations which are discrete in space or time are selected due to their smaller computational demands and the capacity to incorporate local rules, which are not easily accommodated in the form of differential equations. Finite difference equations for the purely temporal case and cellular automata in the case of spatiotemporal patterns are examples of such formulations. We will briefly discuss cellular automata within the context of stomatal dynamics (Sect. 11.4).

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Authors and Affiliations

  1. Computational Systems Biology, School of Engineering and Science, International University Bremen, Campus Ring 1, 28759, Bremen, Germany

    Marc-Thorsten Hütt

  2. Fachbereich Biologie, Technische Universität Darmstadt, Schnittspahnstraße 3-5, 64287, Darmstadt, Germany

    Ulrich Lüttge

  3. 29 Bis Rue de la Chézine, 44100, Nantes, France

    Michel Thellier

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  1. Marc-Thorsten Hütt
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  2. Ulrich Lüttge
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  3. Michel Thellier
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Correspondence to Ulrich Lüttge .

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  1. Dipartimento di Scienze delle Produzioni Agroalimentari e dell'Ambiente, LINV–International Lab for Plant Neurobiology, University of Florence, Sesto Fiorentino, Italy

    Stefano Mancuso

  2. School of Land and Food, University of Tasmania, Hobart, Tasmania, Australia

    Sergey Shabala

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Hütt, MT., Lüttge, U., Thellier, M. (2015). Noise-Induced Phenomena and Complex Rhythms: A Test Scenario for Plant Systems Biology. In: Mancuso, S., Shabala, S. (eds) Rhythms in Plants. Springer, Cham. https://doi.org/10.1007/978-3-319-20517-5_11

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