Network Dynamics in Plant Biology: Current Progress in Historical Perspective

Hütt, Marc‐Thorsten; Lüttge, Ulrich

doi:10.1007/3-540-27043-4_12

Cited by 12 publications

(7 citation statements)

References 104 publications

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“…This is also an outcome of genomics and metabolomics, the patterns of which require a network view (Hütt 2012). In a hierarchy of networks, at scalar levels networks of finer scales can become knots in networks of coarser scales, where each knot or module is again composed of modules (Watts 1999; Hütt & Lüttge 2004; Lüttge & Hütt 2009; Lüttge 2012b). This somewhat resembles Russian dolls – one placed within the other.…”

Section: Modularitymentioning

confidence: 99%

Modularity and emergence: biology’s challenge in understanding life

Lüttge

2012

Plant Biology

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This essay juxtaposes modularity and emergence in the consideration of biological systems at various scalar levels of spatio-temporal organisation. It is noted that reductionism, specialisation and modularity are basic prerequisites for understanding life. It is realised that increased progress of scientific biology in elucidating mechanisms at the level of modular components supports the accusation that the more it advances in materialistic description of details, the more it diverts from understanding the innate properties of life. It is clear that modularity, by taking the whole as the sum of its parts, is insufficient for understanding living systems. At the same time, however, there is emergence, as advocated by Robert Laughlin. Emergence after the integration of modules leads to completely new properties of individual organisms as unique unitary entities, and also of systems of organisms with synergistic and antagonistic interactions of the integrated species. The discussion is predominantly based on examples from plant biology. At hierarchically higher scalar levels emergent biological systems are networks integrating species, biotopes, ecosystems and the entire biosphere of Earth, also named Gaia by James Lovelock, in a natural scientific respect. While investigating modules remains essential, biology as a nature science needs to merge and integrate such information to be able to unfold emergence. Through efforts towards visualising and understanding emergent diversity and complexity, the research discipline of biology will provide invaluable contributions to understanding life, and thus refute the accusation that it diverts from embracing the innate properties of life.

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Section: Modularitymentioning

confidence: 99%

Modularity and emergence: biology’s challenge in understanding life

Lüttge

2012

Plant Biology

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“…Indeed, the operation of endogenous biological clocks is much discussed as a means of anticipation of and preparedness to regularly changing external conditions improving fitness (Ouyang et al 1998;Johnson and Golden 1999;Dodd et al 2005). The non-linear spatiotemporal patterns of overt phenomena of rhythmicity either due to exclusive environmental entrainment or due to the functioning of endogenous oscillators independent of the environment are both a revelation of the operation of regulatory networks (Hütt and Lüttge 2005). It is worth considering both of them.…”

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confidence: 99%

Diurnal and annual rhythms in trees

Lüttge

Hertel

2009

Trees

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Trees, perennial phanerophytes, display a rich variety of rhythmic phenomena. These are either due to exclusive environmental entrainment or due to the functioning of endogenous oscillators independent of the environment. Both types of rhythms are covered in this review. Purely environment controlled rhythms may be considered as a prelude to endogenous rhythms. Environment controlled rhythms discussed are (i) the diurnal rhythms of nyctinastic and heliotropic leaf movements and oscillatory phenomena of photosynthesis, such as the midday depression and Crassulacean acid metabolism (CAM), and (ii) the annual rhythms of annual growth ring formation, autumnal leaf senescence, over wintering mechanisms and flowering. Among the diurnal rhythms, nyctinastic movements and CAM are also free-running endogenous rhythms showing the operation of circadian clocks in trees. In leaf senescence, over wintering, and flowering control, photoperiod sensing is involved which suggests the participation of endogenous clocks. A question asked is if diurnal and annual rhythms are mechanistically correlated. Evidently, phenological phenomena based on photoperiodism (as dependent on measurement of night length) are co-ordinately regulated by the phytochrome system and the circadian clocks and many aspects of annual developments and over wintering are linked to photoperiodism. The existence in trees of circadian clock genes as known to be anchored in the genome of A. thaliana can be assessed by attempts of alignment with the sequenced genome of Populus or by isolating cDNA clones from trees to check them against the genome of A. thaliana. At extreme latitudes near the equator and north of the polar circle trees also display photoperiod-independent phenological phenomena. In the polar region, total irradiance of red and far red light could possibly be involved and the signalling pathway then involves phytochrome, and thus, may still be similar to that of photoperiodism. At the equator, total daily light irradiance received or sensing the dynamics of daily changes in solar irradiance are essential and it remains enigmatic whether signalling cascades are either attached to the circadian clocks in a still unknown way or totally independent of circadian clocks.

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“…La renaissance of network theory, and its widespread application to metabolic, social, economic, communication, and eco‐systems, constitute main foundations of Systems Biology . Network dynamics as a tool for handling large datasets in a way that gives us an interpretation of the whole system is highly promising . The topology, architecture, and connectivity properties of nonlinear dynamic systems as the constitutive core of cellular networks of biochemical and transport reactions are becoming more tractable.…”

Section: Biological Complexity and Networkmentioning

confidence: 99%

Network dynamics: quantitative analysis of complex behavior in metabolism, organelles, and cells, from experiments to models and back

Kurz

Kembro

Flesia

et al. 2016

WIREs Mechanisms of Disease

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Advancing from two core traits of biological systems: multilevel network organization and nonlinearity, we review a host of novel and readily available techniques to explore and analyze their complex dynamic behavior within the framework of experimental-computational synergy. In the context of concrete biological examples, analytical methods such as wavelet, power spectra, and metabolomics-fluxomics analyses, are presented, discussed, and their strengths and limitations highlighted. Further shown is how time series from stationary and nonstationary biological variables and signals, such as membrane potential, high-throughput metabolomics, O and CO levels, bird locomotion, at the molecular, (sub)cellular, tissue, and whole organ and animal levels, can reveal important information on the properties of the underlying biological networks. Systems biology-inspired computational methods start to pave the way for addressing the integrated functional dynamics of metabolic, organelle and organ networks. As our capacity to unravel the control and regulatory properties of these networks and their dynamics under normal or pathological conditions broadens, so is our ability to address endogenous rhythms and clocks to improve health-span in human aging, and to manage complex metabolic disorders, neurodegeneration, and cancer. WIREs Syst Biol Med 2017, 9:e1352. doi: 10.1002/wsbm.1352 For further resources related to this article, please visit the WIREs website.

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Network Dynamics in Plant Biology: Current Progress in Historical Perspective

Cited by 12 publications

References 104 publications

Modularity and emergence: biology’s challenge in understanding life

Modularity and emergence: biology’s challenge in understanding life

Diurnal and annual rhythms in trees

Network dynamics: quantitative analysis of complex behavior in metabolism, organelles, and cells, from experiments to models and back

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