Numeric simulation of plant signaling networks

The CBL-CIPK Calcium Signaling Network: Unified Paradigm from 20 Years of Discoveries

Calcium (Ca²⁺) serves as an essential nutrient as well as a signaling agent in all eukaryotes. In plants, calcineurin B-like proteins (CBLs) are a unique group of Ca²⁺ sensors that decode Ca²⁺ signals by activating a family of plant-specific protein kinases known as CBL-interacting protein kinases (CIPKs). Interactions between CBLs and CIPKs constitute a signaling network that enables information integration and physiological coordination in response to a variety of extracellular cues such as nutrient deprivation and abiotic stresses. Studies in the past two decades have established a unified paradigm that illustrates the functions of CBL-CIPK complexes in controlling membrane transport through targeting transporters and channels in the plasma membrane and tonoplast.

Transcriptomic analysis of the role of carboxylic acids in metabolite signaling in Arabidopsis leaves

The transcriptional response to metabolites is an important mechanism by which plants integrate information about cellular energy and nutrient status. Although some carboxylic acids have been implicated in the regulation of gene expression for select transcripts, it is unclear whether all carboxylic acids have the same effect, how many transcripts are affected, and how carboxylic acid signaling is integrated with other metabolite signals. In this study, we demonstrate that perturbations in cellular concentrations of citrate, and to a lesser extent malate, have a major impact on nucleus-encoded transcript abundance. Functional categories of transcripts that were targeted by both organic acids included photosynthesis, cell wall, biotic stress, and protein synthesis. Specific functional categories that were only regulated by citrate included tricarboxylic acid cycle, nitrogen metabolism, sulfur metabolism, and DNA synthesis. Further quantitative real-time polymerase chain reaction analysis of specific citrate-responsive transcripts demonstrated that the transcript response to citrate is time and concentration dependent and distinct from other organic acids and sugars. Feeding of isocitrate as well as the nonmetabolizable citrate analog tricarballylate revealed that the abundance of selected marker transcripts is responsive to citrate and not downstream metabolites. Interestingly, the transcriptome response to citrate feeding was most similar to those observed after biotic stress treatments and the gibberellin biosynthesis inhibitor paclobutrazol. Feeding of citrate to mutants with defects in plant hormone signaling pathways did not completely abolish the transcript response but hinted at a link with jasmonic acid and gibberellin signaling pathways. Our results suggest that changes in carboxylic acid abundances can be perceived and signaled in Arabidopsis (Arabidopsis thaliana) by as yet unknown signaling pathways.

Signalling network construction for modelling plant defence response

Plant defence signalling response against various pathogens, including viruses, is a complex phenomenon. In resistant interaction a plant cell perceives the pathogen signal, transduces it within the cell and performs a reprogramming of the cell metabolism leading to the pathogen replication arrest. This work focuses on signalling pathways crucial for the plant defence response, i.e., the salicylic acid, jasmonic acid and ethylene signal transduction pathways, in the Arabidopsis thaliana model plant. The initial signalling network topology was constructed manually by defining the representation formalism, encoding the information from public databases and literature, and composing a pathway diagram. The manually constructed network structure consists of 175 components and 387 reactions. In order to complement the network topology with possibly missing relations, a new approach to automated information extraction from biological literature was developed. This approach, named Bio3graph, allows for automated extraction of biological relations from the literature, resulting in a set of (component1, reaction, component2) triplets and composing a graph structure which can be visualised, compared to the manually constructed topology and examined by the experts. Using a plant defence response vocabulary of components and reaction types, Bio3graph was applied to a set of 9,586 relevant full text articles, resulting in 137 newly detected reactions between the components. Finally, the manually constructed topology and the new reactions were merged to form a network structure consisting of 175 components and 524 reactions. The resulting pathway diagram of plant defence signalling represents a valuable source for further computational modelling and interpretation of omics data. The developed Bio3graph approach, implemented as an executable language processing and graph visualisation workflow, is publically available at http://ropot.ijs.si/bio3graph/and can be utilised for modelling other biological systems, given that an adequate vocabulary is provided.

A gene regulatory network model for floral transition of the shoot apex in maize and its dynamic modeling

The transition from the vegetative to reproductive development is a critical event in the plant life cycle. The accurate prediction of flowering time in elite germplasm is important for decisions in maize breeding programs and best agronomic practices. The understanding of the genetic control of flowering time in maize has significantly advanced in the past decade. Through comparative genomics, mutant analysis, genetic analysis and QTL cloning, and transgenic approaches, more than 30 flowering time candidate genes in maize have been revealed and the relationships among these genes have been partially uncovered. Based on the knowledge of the flowering time candidate genes, a conceptual gene regulatory network model for the genetic control of flowering time in maize is proposed. To demonstrate the potential of the proposed gene regulatory network model, a first attempt was made to develop a dynamic gene network model to predict flowering time of maize genotypes varying for specific genes. The dynamic gene network model is composed of four genes and was built on the basis of gene expression dynamics of the two late flowering id1 and dlf1 mutants, the early flowering landrace Gaspe Flint and the temperate inbred B73. The model was evaluated against the phenotypic data of the id1 dlf1 double mutant and the ZMM4 overexpressed transgenic lines. The model provides a working example that leverages knowledge from model organisms for the utilization of maize genomic information to predict a whole plant trait phenotype, flowering time, of maize genotypes.

Plant systems biology: network matters

Systems biology is all about networks. A recent trend has been to associate systems biology exclusively with the study of gene regulatory or protein-interaction networks. However, systems biology approaches can be applied at many other scales, from the subatomic to the ecosystem scales. In this review, we describe studies at the sub-cellular, tissue, whole plant and crop scales and highlight how these studies can be related to systems biology. We discuss the properties of system approaches at each scale as well as their current limits, and pinpoint in each case advances unique to the considered scale but representing potential for the other scales. We conclude by examining plant models bridging different scales and considering the future prospects of plant systems biology.

Computational models in plant-pathogen interactions: the case of Phytophthora infestans

BACKGROUND

Phytophthora infestans is a devastating oomycete pathogen of potato production worldwide. This review explores the use of computational models for studying the molecular interactions between P. infestans and one of its hosts, Solanum tuberosum.

MODELING AND CONCLUSION

Deterministic logistics models have been widely used to study pathogenicity mechanisms since the early 1950s, and have focused on processes at higher biological resolution levels. In recent years, owing to the availability of high throughput biological data and computational resources, interest in stochastic modeling of plant-pathogen interactions has grown. Stochastic models better reflect the behavior of biological systems. Most modern approaches to plant pathology modeling require molecular kinetics information. Unfortunately, this information is not available for many plant pathogens, including P. infestans. Boolean formalism has compensated for the lack of kinetics; this is especially the case where comparative genomics, protein-protein interactions and differential gene expression are the most common data resources.

Back to the future: evolution of computational models in plant morphogenesis

There has been a recent surge of studies in plant biology that combine experimental data with computational modeling. Here, we categorize a diversity of theoretical models and emphasize the need to tailor modeling approaches to the questions at hand. Models can start from biophysical or purely heuristic basic principles, and can focus at several levels of biological organization. Recent examples illustrate that this entire spectrum can be useful to understand plant development, and point to a future direction where more approaches are combined in fruitful ways--either by proving the same result with different basic principles or by exploring interactions across levels, in the so-called multilevel models.

Salicylic acid production in response to biotic and abiotic stress depends on isochorismate in Nicotiana benthamiana

Salicylic acid (SA) is an important signal involved in the activation of defence responses against abiotic and biotic stress. In tobacco, benzoic acid or glucosyl benzoate were proposed to be precursors of SA. This is in sharp contrast with studies in Arabidopsis thaliana, where SA derives from isochorismate. We have determined the importance of isochorismate for SA biosynthesis in Nicotiana benthamiana using virus-induced gene silencing of the isochorismate synthase (ICS) gene. Plants with silenced ICS expression do not accumulate SA after exposure to UV or to pathogen stress. Plants with silenced ICS expression also exhibit strongly decreased levels of phylloquinone, a product of isochorismate. Our data provide evidence for an isochorismate-derived synthesis of SA in N. benthamiana.

Predicting essential components of signal transduction networks: a dynamic model of guard cell abscisic acid signaling

Plants both lose water and take in carbon dioxide through microscopic stomatal pores, each of which is regulated by a surrounding pair of guard cells. During drought, the plant hormone abscisic acid (ABA) inhibits stomatal opening and promotes stomatal closure, thereby promoting water conservation. Dozens of cellular components have been identified to function in ABA regulation of guard cell volume and thus of stomatal aperture, but a dynamic description is still not available for this complex process. Here we synthesize experimental results into a consistent guard cell signal transduction network for ABA-induced stomatal closure, and develop a dynamic model of this process. Our model captures the regulation of more than 40 identified network components, and accords well with previous experimental results at both the pathway and whole-cell physiological level. By simulating gene disruptions and pharmacological interventions we find that the network is robust against a significant fraction of possible perturbations. Our analysis reveals the novel predictions that the disruption of membrane depolarizability, anion efflux, actin cytoskeleton reorganization, cytosolic pH increase, the phosphatidic acid pathway, or K(+) efflux through slowly activating K(+) channels at the plasma membrane lead to the strongest reduction in ABA responsiveness. Initial experimental analysis assessing ABA-induced stomatal closure in the presence of cytosolic pH clamp imposed by the weak acid butyrate is consistent with model prediction. Simulations of stomatal response as derived from our model provide an efficient tool for the identification of candidate manipulations that have the best chance of conferring increased drought stress tolerance and for the prioritization of future wet bench analyses. Our method can be readily applied to other biological signaling networks to identify key regulatory components in systems where quantitative information is limited.

A methodology for the structural and functional analysis of signaling and regulatory networks

Background

Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks.

Results

We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the dynamic behavior.

We have implemented these methods in our software tool CellNetAnalyzer (successor of FluxAnalyzer) and illustrate their applicability using a logical model of T-Cell receptor signaling providing non-intuitive results regarding feedback loops, essential elements, and (logical) signal processing upon different stimuli.

Conclusion

The methods and formalisms we propose herein are another step towards the comprehensive functional analysis of cellular interaction networks. Their potential, shown on a realistic T-cell signaling model, makes them a promising tool.

A methodology for the structural and functional analysis of signaling and regulatory networks

BACKGROUND

Structural analysis of cellular interaction networks contributes to a deeper understanding of network-wide interdependencies, causal relationships, and basic functional capabilities. While the structural analysis of metabolic networks is a well-established field, similar methodologies have been scarcely developed and applied to signaling and regulatory networks.

RESULTS

We propose formalisms and methods, relying on adapted and partially newly introduced approaches, which facilitate a structural analysis of signaling and regulatory networks with focus on functional aspects. We use two different formalisms to represent and analyze interaction networks: interaction graphs and (logical) interaction hypergraphs. We show that, in interaction graphs, the determination of feedback cycles and of all the signaling paths between any pair of species is equivalent to the computation of elementary modes known from metabolic networks. Knowledge on the set of signaling paths and feedback loops facilitates the computation of intervention strategies and the classification of compounds into activators, inhibitors, ambivalent factors, and non-affecting factors with respect to a certain species. In some cases, qualitative effects induced by perturbations can be unambiguously predicted from the network scheme. Interaction graphs however, are not able to capture AND relationships which do frequently occur in interaction networks. The consequent logical concatenation of all the arcs pointing into a species leads to Boolean networks. For a Boolean representation of cellular interaction networks we propose a formalism based on logical (or signed) interaction hypergraphs, which facilitates in particular a logical steady state analysis (LSSA). LSSA enables studies on the logical processing of signals and the identification of optimal intervention points (targets) in cellular networks. LSSA also reveals network regions whose parametrization and initial states are crucial for the dynamic behavior. We have implemented these methods in our software tool CellNetAnalyzer (successor of FluxAnalyzer) and illustrate their applicability using a logical model of T-Cell receptor signaling providing non-intuitive results regarding feedback loops, essential elements, and (logical) signal processing upon different stimuli.

CONCLUSION

The methods and formalisms we propose herein are another step towards the comprehensive functional analysis of cellular interaction networks. Their potential, shown on a realistic T-cell signaling model, makes them a promising tool.

Ectopic expression of EFFECTOR OF TRANSCRIPTION perturbs gibberellin-mediated plant developmental processes

The plant hormone gibberellin (GA) is known to modulate various aspects of plant cell differentiation and development. The current model of GA-mediated regulation is based on a de-repressible system and includes specific protein modification and degradation. HRT, a zinc finger protein from barley has been shown to have GA-dependent transcriptional repressing activity on the seed-specific alpha-amylase promoter [Raventos, D., Skriver, K., Schlein, M., Karnahl, K., Rogers, S.W., Rogers, J.C. and Mundy, J. 1998. J. Biol. Chem. 273: 23313-23320]. Here we report the characterization of a dicot homologue from Brassica napus (BnET) and provide evidence for its role in GA response modulation suggesting that this could be a conserved feature of this gene family. When BnET is ectopically expressed in either Arabidopsis or tobacco the phenotypes include dwarfism due to shorter internodes and late flowering, reduced germination rate, increased anthocyanin content and reduced xylem lignification as a marker for terminal cell differentiation. Transient expression in protoplasts supports the notion that this most likely is due to a transcriptional repression of GA controlled genes. Finally, histological analysis showed that in contrast to other GA deficient mutants the shorter internodes were due to fewer but not smaller cells, suggesting a function of BnET in GA-mediated cell division control.

Electronic data sources for kinetic models of cell signaling

Functional understanding of signaling pathways requires detailed information about the constituent molecules and their interactions. Simulations of signaling pathways therefore build upon a great deal of data from various sources. We first survey electronic data resources for cell signaling modeling and then based on the type of data representation the data sources are broadly classified into five groups. None of the data sources surveyed provide all required data in a ready-to-be-modeled fashion. We then put forward a "wish list" for the desired attributes for an ideal modeling centric database. Finally, we close with perspectives on how electronic data sources for cell signaling modeling have developed. We suggest that future directions in such data sources are largely model-driven and are hinged on interoperability of data sources.

Expression profiling reveals COI1 to be a key regulator of genes involved in wound- and methyl jasmonate-induced secondary metabolism, defence, and hormone interactions

The Arabidopsis gene COI1 is required for jasmonic acid (JA)-induced growth inhibition, resistance to insect herbivory, and resistance to pathogens. In addition, COI1 is also required for transcription of several genes induced by wounding or by JA. Here, we use microarray gene transcription profiling of wild type and coi1 mutant plants to examine the extent of the requirement of COI1 for JA-induced and wound-induced gene transcription. We show that COI1 is required for expression of approximately 84% of 212 genes induced by JA, and for expression of approximately 44% of 153 genes induced by wounding. Surprisingly, COI1 was also required for repression of 53% of 104 genes whose expression was suppressed by JA, and for repression of approximately 46% of 83 genes whose expression was suppressed by wounding. These results indicate that COI1 plays a pivotal role in wound- and JA signalling.

A Boolean algorithm for reconstructing the structure of regulatory networks

Advances in transcriptional analysis offer great opportunities to delineate the structure and hierarchy of regulatory networks in biochemical systems. We present an approach based on Boolean analysis to reconstruct a set of parsimonious networks from gene disruption and over expression data. Our algorithms, Causal Predictor (CP) and Relaxed Causal Predictor (RCP) distinguish the direct and indirect causality relations from the non-causal interactions, thus significantly reducing the number of miss-predicted edges. The algorithms also yield substantially fewer plausible networks. This greatly reduces the number of experiments required to deduce a unique network from the plausible network structures. Computational simulations are presented to substantiate these results. The algorithms are also applied to reconstruct the entire network of galactose utilization pathway in Saccharomyces cerevisiae. These algorithms will greatly facilitate the elucidation of regulatory networks using large scale gene expression profile data.

Solanum nigrum: a model ecological expression system and its tools

Plants respond to environmental stresses through a series of complicated phenotypic responses, which can be understood only with field studies because other organisms must be recruited for their function. If ecologists are to fully participate in the genomics revolution and if molecular biologists are to understand adaptive phenotypic responses, native plant ecological expression systems that offer both molecular tools and interesting natural histories are needed. Here, we present Solanum nigrum L., a Solanaceous relative of potato and tomato for which many genomic tools are being developed, as a model plant ecological expression system. To facilitate manipulative ecological studies with S. nigrum, we describe: (i) an Agrobacterium-based transformation system and illustrate its utility with an example of the antisense expression of RuBPCase, as verified by Southern gel blot analysis and real-time quantitative PCR; (ii) a 789-oligonucleotide microarray and illustrate its utility with hybridizations of herbivore-elicited plants, and verify responses with RNA gel blot analysis and real-time quantitative PCR; (iii) analyses of secondary metabolites that function as direct (proteinase inhibitor activity) and indirect (herbivore-induced volatile organic compounds) defences; and (iv) growth and fitness-estimates for plants grown under field conditions. Using these tools, we demonstrate that attack from flea beetles elicits: (i) a large transcriptional change consistent with elicitation of both jasmonate and salicylate signalling; and (ii) increases in proteinase inhibitor transcripts and activity, and volatile organic compound release. Both flea beetle attack and jasmonate elicitation increased proteinase inhibitors and jasmonate elicitation decreased fitness in field-grown plants. Hence, proteinase inhibitors and jasmonate-signalling are targets for manipulative studies.

Herbivore-induced plant vaccination. Part II. Array-studies reveal the transience of herbivore-specific transcriptional imprints and a distinct imprint from stress combinations

Summary Microarray technology has given plant biologists the ability to simultaneously monitor changes in the expression of hundreds of genes, and yet, to date, this technology has not been applied to ecological phenomena. In native tobacco (Nicotiana attenuata), prior attack of sap-feeding mirids (Tupiocoris notatus) results in vaccination of the plant against subsequent attacks by chewing hornworms (Manduca sexta). This vaccination is mediated by a combination of direct and indirect defenses and tolerance responses, which act in concert with the attack preferences of a generalist predator. Here, we use microarrays enriched in herbivore-elicited genes with a principal components analysis (PCA) to characterize transcriptional 'imprints' of single, sequential, or simultaneous attacks by these two main herbivores of N. attenuata. The PCA identified distinctly different imprints left by individual attack from the two species after 24 h, but not after 5 days. Moreover, imprints of sequential or simultaneous attacks differed significantly from those of single attack, suggesting the existence of a distinct gene expression program responsive to the combination of biological stressors. A dissection of the transcriptional imprints revealed responses in direct and indirect defense genes that were well correlated with observed increases in defense metabolites. Attack from both herbivores elicits a switch from growth- to defense-related transcriptional processes, and herbivore-specific changes occur largely in primary metabolism and signaling cascades. PCA of these polygenic transcriptional imprints characterizes the ephemeral changes in the transcriptome that occur during the maturation of ecologically relevant phenotypic responses.

Arabidopsis kinome: after the casting

Arabidopsis thaliana is used as a favourite experimental organism for many aspects of plant biology. We capitalized on the recently available Arabidopsis genome sequence and predicted proteome, to draw up a genome-scale protein serine/threonine kinase (PSTK) inventory. The PSTKs represent about 4% of the A. thaliana proteome. In this study, we provide a description of the content and diversity of the non-receptor PSTKs. These kinases have crucial functions in sensing, mediating and coordinating cellular responses to an extensive range of stimuli. A total of 369 predicted non receptor PSTKs were detailed: the Raf superfamily, the CMGC, CaMK, AGC and STE families, as well as a few small clades and orphan sequences. An extensive relationship analysis of these kinases allows us to classify the proteins in superfamilies, families, sub-families and groups. The classification provides a better knowledge of the characteristics shared by the different clades. We focused on the MAP kinase module elements, with particular attention to their docking sites for protein-protein interaction and their biological function. The large number of A. thaliana genes encoding kinases might have been achieved through successive rounds of gene and genome duplications. The evolution towards an increasing gene number suggests that functional redundancy plays an important role in plant genetic robustness.

Genetic evidence that expression of NahG modifies defence pathways independent of salicylic acid biosynthesis in the Arabidopsis-Pseudomonas syringae pv. tomato interaction

The salicylic acid (SA)-induction deficient (sid) mutants of Arabidopsis, eds5 and sid2 accumulate normal amounts of camalexin after inoculation with Pseudomonas syringae pv. tomato (Pst), while transgenic NahG plants expressing an SA hydroxylase that degrades SA have reduced levels of camalexin and exhibit a higher susceptibility to different pathogens compared to the sid mutants. SID2 encodes an isochorismate synthase necessary for the synthesis of SA. NahG was shown to act epistatically to the sid mutant phenotype regarding accumulation of camalexin after inoculation with Pst in eds5NahG and sid2NahG plants. The effect of the pad4 mutation on the sid mutant phenotype was furthermore tested in eds5pad4 and sid2pad4 double mutants, and it was demonstrated that PAD4 acts epistatically to EDS5 and SID2 regarding the production of camalexin after inoculation with Pst. NahG plants and pad4 mutants were also found to produce less ethylene (ET) after infection with Pst in comparison to the wild type (WT) and sid mutants. Both PAD4 and NahG acted epistatically to SID regarding the Pst-dependent production of ET that was found to be necessary for the accumulation of camalexin. Early production of jasmonic acid (JA) 12 h after inoculation with Pst/avrRpt2 was absent in all plants expressing NahG compared to the other mutants tested here. These genetic studies unravel pleiotropic changes in defence signalling of NahG plants that are unlikely to result from their low SA content. This adds unexpected difficulties in the interpretation of earlier findings based solely on NahG plants.

Global analysis of gene expression using GeneChip microarrays

DNA microarray technology, especially the use of GeneChip microarrays, has become a standard tool for parallel gene expression analysis. Recent improvements in GeneChip microarrays enable whole-genome expression analysis, and thus open a new avenue for studies of the composition, dynamics, and regulation of the transcriptome in plants.

Light- and carbon-signaling pathways. Modeling circuits of interactions

Here, we report the systematic exploration and modeling of interactions between light and sugar signaling. The data set analyzed explores the interactions of sugar (sucrose) with distinct light qualities (white, blue, red, and far-red) used at different fluence rates (low or high) in etiolated seedlings and mature green plants. Boolean logic was used to model the effect of these carbon/light interactions on three target genes involved in nitrogen assimilation: asparagine synthetase (ASN1 and ASN2) and glutamine synthetase (GLN2). This analysis enabled us to assess the effects of carbon on light-induced genes (GLN2/ASN2) versus light-repressed genes (ASN1) in this pathway. New interactions between carbon and blue-light signaling were discovered, and further connections between red/far-red light and carbon were modeled. Overall, light was able to override carbon as a major regulator of ASN1 and GLN2 in etiolated seedlings. By contrast, carbon overrides light as the major regulator of GLN2 and ASN2 in light-grown plants. Specific examples include the following: Carbon attenuated the blue-light induction of GLN2 in etiolated seedlings and also attenuated the white-, blue-, and red-light induction of GLN2 and ASN2 in light-grown plants. By contrast, carbon potentiated far-red-light induction of GLN2 and ASN2 in light-grown plants. Depending on the fluence rate of far-red light, carbon either attenuated or potentiated light repression of ASN1 in light-grown plants. These studies indicate the interaction of carbon with blue, red, and far-red-light signaling and set the stage for further investigation into modeling this complex web of interacting pathways using systems biology approaches.

Plant movement. Submergence-induced petiole elongation in Rumex palustris depends on hyponastic growth

The submergence-tolerant species Rumex palustris (Sm.) responds to complete submergence by an increase in petiole angle with the horizontal. This hyponastic growth, in combination with stimulated elongation of the petiole, can bring the leaf tips above the water surface, thus restoring gas exchange and enabling survival. Using a computerized digital camera set-up the kinetics of this hyponastic petiole movement and stimulated petiole elongation were studied. The hyponastic growth is a relatively rapid process that starts after a lag phase of 1.5 to 3 h and is completed after 6 to 7 h. The kinetics of hyponastic growth depend on the initial angle of the petiole at the time of submergence, a factor showing considerable seasonal variation. For example, lower petiole angles at the time of submergence result in a shorter lag phase for hyponastic growth. This dependency of the hyponastic growth kinetics can be mimicked by experimentally manipulating the petiole angle at the time of submergence. Stimulated petiole elongation in response to complete submergence also shows kinetics that are dependent on the petiole angle at the time of submergence, with lower initial petiole angles resulting in a longer lag phase for petiole elongation. Angle manipulation experiments show that stimulated petiole elongation can only start when the petiole has reached an angle of 40 degrees to 50 degrees. The petiole can reach this "critical angle" for stimulated petiole elongation by the process of hyponastic growth. This research shows a functional dependency of one response to submergence in R. palustris (stimulated petiole elongation) on another response (hyponastic petiole growth), because petiole elongation can only contribute to the leaf reaching the water surface when the petiole has a more or less upright position.

Deciphering plant-pathogen communication: fresh perspectives for molecular resistance breeding

Activation of local and systemic plant defences in response to pathogen attack involves dramatic cellular reprogramming. Over the past 10 years many novel genes, proteins and molecules have been discovered as a result of investigating plant-pathogen interactions. Most attempts to harness this knowledge to engineer improved disease resistance in crops have failed. Although gene efficacy in transgenic plants has often been good, commercial exploitation has not been possible because of the detrimental effects on plant growth, development and crop yield. Biotechnology approaches have now shifted emphasis towards marker-assisted breeding and the construction of vectors containing highly regulated transgenes that confer resistance in several distinct ways.

Two pathways act in an additive rather than obligatorily synergistic fashion to induce systemic acquired resistance and PR gene expression

BACKGROUND

Local infection with necrotizing pathogens induces whole plant immunity to secondary challenge. Pathogenesis-related genes are induced in parallel with this systemic acquired resistance response and thought to be co-regulated. The hypothesis of co-regulation has been challenged by induction of Arabidopsis PR-1 but not systemic acquired resistance in npr1 mutant plants responding to Pseudomonas syringae carrying the avirulence gene avrRpt2. However, experiments with ndr1 mutant plants have revealed major differences between avirulence genes. The ndr1-1 mutation prevents hypersensitive cell death, systemic acquired resistance and PR-1 induction elicited by bacteria carrying avrRpt2. This mutation does not prevent these responses to bacteria carrying avrB.

RESULTS

Systemic acquired resistance, PR-1 induction and PR-5 induction were assessed in comparisons of npr1-2 and ndr1-1 mutant plants, double mutant plants, and wild-type plants. Systemic acquired resistance was displayed by all four plant lines in response to Pseudomonas syringae bacteria carrying avrB. PR-1 induction was partially impaired by either single mutation in response to either bacterial strain, but only fully impaired in the double mutant in response to avrRpt2. PR-5 induction was not fully impaired in any of the mutants in response to either avirulence gene.

CONCLUSION

Two pathways act additively, rather than in an obligatorily synergistic fashion, to induce systemic acquired resistance, PR-1 and PR-5. One of these pathways is NPR1-independent and depends on signals associated with hypersensitive cell death. The other pathway is dependent on salicylic acid accumulation and acts through NPR1. At least two other pathways also contribute additively to PR-5 induction.

Jasmonates and octadecanoids: signals in plant stress responses and development

Plants are sessile organisms. Consequently they have to adapt constantly to fluctuations in the environment. Some of these changes involve essential factors such as nutrients, light, and water. Plants have evolved independent systems to sense nutrients such as phosphate and nitrogen. However, many of the environmental factors may reach levels which represent stress for the plant. The fluctuations can range between moderate and unfavorable, and the factors can be of biotic or abiotic origin. Among the biotic factors influencing plant life are pathogens and herbivores. In case of bacteria and fungi, symbiotic interactions such as nitrogen-fixating nodules and mycorrhiza, respectively, may be established. In case of insects, a tritrophic interaction of herbivores, carnivores, and plants may occur mutualistically or parasitically. Among the numerous abiotic factors are low temperature, frost, heat, high light conditions, ultraviolet light, darkness, oxidation stress, hypoxia, wind, touch, nutrient imbalance, salt stress, osmotic adjustment, water deficit, and desiccation. In the last decade jasmonates were recognized as being signals in plant responses to most of these biotic and abiotic factors. Signaling via jasmonates was found to occur intracellularly, intercellularly, and systemically as well as interorganismically. Jasmonates are a group of ubiquitously occurring plant growth regulators originally found as the major constituents in the etheric oil of jasmine, and were first suggested to play a role in senescence due to a strong senescence-promoting effect. Subsequently, numerous developmental processes were described in which jasmonates exhibited hormone-like properties. Recent knowledge is reviewed here on jasmonates and their precursors, the octadecanoids. After discussing occurrence and biosynthesis, emphasis is placed upon the signal transduction pathways in plant stress responses in which jasmonates act as a signal. Finally, examples are described on the role of jasmonates in developmental processes.

Genome-wide identification of nodule-specific transcripts in the model legume Medicago truncatula

The Medicago truncatula expressed sequence tag (EST) database (Gene Index) contains over 140,000 sequences from 30 cDNA libraries. This resource offers the possibility of identifying previously uncharacterized genes and assessing the frequency and tissue specificity of their expression in silico. Because M. truncatula forms symbiotic root nodules, unlike Arabidopsis, this is a particularly important approach in investigating genes specific to nodule development and function in legumes. Our analyses have revealed 340 putative gene products, or tentative consensus sequences (TCs), expressed solely in root nodules. These TCs were represented by two to 379 ESTs. Of these TCs, 3% appear to encode novel proteins, 57% encode proteins with a weak similarity to the GenBank accessions, and 40% encode proteins with strong similarity to the known proteins. Nodule-specific TCs were grouped into nine categories based on the predicted function of their protein products. Besides previously characterized nodulins, other examples of highly abundant nodule-specific transcripts include plantacyanin, agglutinin, embryo-specific protein, and purine permease. Six nodule-specific TCs encode calmodulin-like proteins that possess a unique cleavable transit sequence potentially targeting the protein into the peribacteroid space. Surprisingly, 114 nodule-specific TCs encode small Cys cluster proteins with a cleavable transit peptide. To determine the validity of the in silico analysis, expression of 91 putative nodule-specific TCs was analyzed by macroarray and RNA-blot hybridizations. Nodule-enhanced expression was confirmed experimentally for the TCs composed of five or more ESTs, whereas the results for those TCs containing fewer ESTs were variable.

Phytochrome signalling modulates the SA-perceptive pathway in Arabidopsis

The interaction of phytochrome signalling with the SA signal transduction pathway has been investigated in Arabidopsis using single and multiple mutants affected in light perception (phyA and phyB deficient) and light-signal processing (psi2, phytochrome signalling). The induction of PR1 by SA and functional analogues has been found to strictly correlate with the activity of the signalling pathway controlled by both phyA and phyB photoreceptors. In darkness as well as dim light, and independently of a carbohydrate source, SA-induced PR gene expression as well as the hypersensitive response to pathogens (HR) are strongly reduced. Moreover, the initiation of HR also exhibits a strict dependence upon both the presence and the amplitude of a phytochrome-elicited signal. The growth of an incompatible strain of bacterial a pathogen (Pseudomonas syringae pv. tomato) was enhanced in phyA-phyB and decreased in psi2 mutants. While functional chloroplasts were found necessary for the development of an HR, the induction of PRs was strictly dependent on light, but independent of functional chloroplasts. Taken together, these data demonstrate that the light-induced signalling pathway interacts with the pathogen/SA-mediated signal transduction route. These results are summarized in a formalism that allows qualitative computer simulation.

Effect of yeast CTA1 gene expression on response of tobacco plants to tobacco mosaic virus infection

The response of tobacco (Nicotiana tabacum L. cv Xanthi-nc) plants with elevated catalase activity was studied after infection by tobacco mosaic virus (TMV). These plants contain the yeast (Saccharomyces cerevisiae) peroxisomal catalase gene CTA1 under the control of the cauliflower mosaic virus 35S promoter. The transgenic lines exhibited 2- to 4-fold higher total in vitro catalase activity than untransformed control plants under normal growth conditions. Cellular localization of the CTA1 protein was established using immunocytochemical analysis. Gold particles were detected mainly inside peroxisomes, whereas no significant labeling was detected in other cellular compartments or in the intercellular space. The physiological state of the transgenic plants was evaluated in respect to growth rate, general appearance, carbohydrate content, and dry weight. No significant differences were recorded in comparison with non-transgenic tobacco plants. The 3,3'-diaminobenzidine-stain method was applied to visualize hydrogen peroxide (H(2)O(2)) in the TMV infected tissue. Presence of H(2)O(2) could be detected around necrotic lesions caused by TMV infection in non-transgenic plants but to a much lesser extent in the CTA1 transgenic plants. In addition, the size of necrotic lesions was significantly bigger in the infected leaves of the transgenic plants. Changes in the distribution of H(2)O(2) and in lesion formation were not reflected by changes in salicylic acid production. In contrast to the local response, the systemic response in upper noninoculated leaves of both CTA1 transgenic and control plants was similar. This suggests that increased cellular catalase activity influences local but not systemic response to TMV infection.