RESUMO
Plants have evolved an intricate signaling apparatus that integrates relevant information and allows an optimal response to environmental conditions. For instance, the coordination of defense responses against pathogens involves sophisticated molecular detection and communication systems. Multiple protection strategies may be deployed differentially by the plant according to the nature of the invading organism. These responses are also influenced by the environment, metabolism, and developmental stage of the plant. Though the cellular signaling processes traditionally have been described as linear sequences of events, it is now evident that they may be represented more accurately as network-like structures. The emerging paradigm can be represented readily with the use of Boolean language. This digital (numeric) formalism allows an accurate qualitative description of the signal transduction processes, and a dynamic representation through computer simulation. Moreover, it provides the required power to process the increasing amount of information emerging from the fields of genomics and proteomics, and from the use of new technologies such as microarray analysis. In this review, we have used the Boolean language to represent and analyze part of the signaling network of disease resistance in Arabidopsis.
Assuntos
Arabidopsis/genética , Simulação por Computador , Transdução de Sinais , Algoritmos , Modelos Biológicos , Doenças das Plantas , Linguagens de ProgramaçãoRESUMO
Cell signaling integrates independent stimuli using connections between biochemical pathways. The sensory apparatus can be represented as a network, and the connections between pathways are termed crosstalk. Here, we describe several examples of crosstalk in plant biology. To formalize the network of signal transduction we evaluated the relevance of mechanistic models used in artificial intelligence. Although the perceptron model of neural networking provides a good description of the process, we suggest that Boolean networks should be used as a starting framework. The Boolean network model allows genetic data to be integrated into the logical network of connections deduced from DNA microarray data.
RESUMO
A new mutant called psi2 (for phytochrome signaling) was isolated by screening for elevated activity of a chlorophyll a/b binding protein-luciferase (CAB2-LUC) transgene in Arabidopsis. This mutant exhibited hypersensitive induction of CAB1, CAB2, and the small subunit of ribulose-1,5-bisphosphate carboxylase (RBCS) promoters in the very low fluence range of red light and a hypersensitive response in hypocotyl growth in continuous red light of higher fluences. In addition, at high- but not low-light fluence rates, the mutant showed light-dependent superinduction of the pathogen-related protein gene PR-1a and developed spontaneous necrotic lesions in the absence of any pathogen. Expression of genes responding to various hormone and environmental stress pathways in the mutant was not significantly different from that of the wild type. Analysis of double mutants demonstrated that the effects of the psi2 mutation are dependent on both phytochromes phyA and phyB. The mutation is recessive and maps to the bottom of chromosome 5. Together, our results suggest that PSI2 specifically and negatively regulates both phyA and phyB phototransduction pathways. The induction of cell death by deregulated signaling pathways observed in psi2 is reminiscent of retinal degenerative diseases in animals and humans.