Trends in Plant Science
PerspectivesCrosstalk in plant cell signaling: structure and function of the genetic network
Section snippets
Crosstalk in controlled defense responses
Leaves wounded by insects or by mechanical damage induce the proteinase inhibitor production both locally and systemically1 (Fig. 1, Fig. 2). Transduction of the wound-related signal involves the octadecanoid pathway, and can be mimicked by treatment with jasmonic acid2. Salicylic acid is implicated in the perception of pathogen attack in many plant species3, and inhibits the activation of wound-induced genes elicited by systemin (a systemic wound-peptide signal) and by jasmonic acid (Ref. 4).
Ethylene and jasmonic acid pathways crosstalk
In tobacco, a synergy has been observed between ethylene and methyl jasmonate (Fig. 1, Fig. 2) for the induction of two PR genes that code for PR1b and osmotin7. In tomato, upon wounding, both ethylene and jasmonic acid are required for the induction of proteinase inhibitor genes8. In the case of Arabidopsis, ethylene and methyl jasmonate concomitantly induces the expression of a gene coding for an antifungal plant defensin PDF1.2 (Ref. 9), whereas neither substance induces PR1. In Arabidopsis,
Ethylene and glucose pathways crosstalk
The phytohormone, ethylene, affects many developmental stages of plants, for instance cell elongation, seed germination, fruit ripening and senescence, and is also implicated in biotic10, 11 and abiotic stress perception8. Genetic analysis of Arabidopsis has unraveled the components involved in ethylene signal transduction11, 12. The pathway defined by this approach is a system of MAP kinase cascades.
The ethylene precursor 1-aminocyclopropane-1-carboxylic acid can phenocopy many effects of the
Crosstalk between light signal transduction and pathogenesis-related gene signaling pathway
Crosstalk has been observed between red light and PR-expression-signaling pathways14. The Arabidopsis light-hypersensitive psi2 mutant exhibits a light fluence-dependent amplification of salicylic acid-induced PR1a gene expression (T. Genoud et al., unpublished; Fig. 1, Fig. 2, Fig. 3). To confirm observations that the light signal regulates the sensitivity to salicylic acid, the expression of PR genes was scored in mutants containing no detectable phytochrome A and B proteins. In these plants,
Phytochrome signaling crosstalk with cryptochrome signaling
The proportion of blue, red and far-red light in incoming white light is interpreted by the signaling network in different ways. For example, blue light acts synergistically with red light in the activation of the phytochrome pathway, which controls processes such as cotyledon unfolding and cell elongation15.
Further experiments performed with Arabidopsis mutants deficient in one or several photoreceptors have confirmed these physiological observations. The results suggest that the level of
Crosstalk between sucrose and light signal transduction pathways
In contrast with nitrate reductase or chalcone synthase21, the phyA-activated genes involved in photosynthesis, such as CAB, RBCS and PLASTOCYANIN (PC), are repressed by glucose or sucrose21, 22 (Fig. 4). PC expression is upregulated by the phyA pathway (activated by far-red light) and repressed by sucrose, whereas hypocotyl elongation is reduced by both factors. The antagonistic and the positive activity of sucrose on the phyA pathway can be blocked in Arabidopsis sun mutants23. This
Crosstalk between amino acids and purine metabolism
The various amino acid metabolisms are interconnected, and can be linked up to the purine metabolism24. Indeed, Arabidopsis plants treated with a histidine biosynthesis inhibitor overexpress genes related to not only histidine biosynthesis but also to aromatic amino acids, to lysine synthesis and, curiously, to purine synthesis24. In addition, a reduction in glutamine synthetase activity is observed. As in the case of other eukaryotes25, a general control system might coordinate metabolite
Crosstalk in the control of flowering
In Arabidopsis, flowering induction is controlled by a complex system of signaling pathways acting in partial redundancy, the signals of which are downstream-integrated by a group of proteins, such as LFY and AP1, which further cooperate additively to confer floral meristem identity (reviewed in 26, 27, 28). Multiple opportunities for crosstalk must occur in this system because >80 genes have been found to influence the transition from vegetative to reproductive stage28. For example, the time
Signaling network: a neural network?
From a set of linear and separated signal transduction pathways, the model describing perception and information processing is now shifting towards a network-structured paradigm29. As a much higher level of complexity is observed, new models are emerging to account for the properties of living cells. In line with the mechanistic representations adapted from research into artificial intelligence, the cell apparatus involved in internal or external signal interpretation can be considered a
Structure of signaling networks: the Boolean network
Overall, signaling networks are structured like neural networks. However, the use of such a model to identify the molecular components of a signal transduction network would restrict advances in research because information-processing in neural networks is diffusely localized. Thus, for use with a genetic and, consequently, reductionistic approach, a simpler model is needed. A Boolean representation of signaling networks allows for a reductive and rational representation from which experiments
Conclusion
An isomorphism between signaling and Boolean networks appears to be emerging. This provides a logical framework that allows a materialistic description of the flow of information in cells. It implies that Boolean switches have a molecular identity, presumably as proteins that are susceptible to various modifications from convergent signals. More detailed information on pathways and crosstalk are needed to fill the gaps in our knowledge concerning signal processing. Molecular characterization of
Acknowledgements
We thank Ted Farmer and Cris Kuhlemeier for suggestions concerning the manuscript, and Dominique Genoud for helping us with the concepts of artificial intelligence. Support from the Swiss National Science Foundation (grant FN 3100-055662.98) is gratefully acknowledged.
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