To investigate the dynamics of the potato – Potato virus Y (PVY) compatible interaction in relation to salicylic acid - controlled pathways we performed experiments using non-transgenic potato cv. Désirée, transgenic NahG-Désirée, cv. Igor and PVYNTN, the most aggressive strain of PVY. The importance of salicylic acid in viral multiplication and symptom development was confirmed by pronounced symptom development in NahG-Désirée, depleted in salicylic acid, and reversion of the effect after spraying with 2,6-dichloroisonicotinic acid (a salicylic acid - analogue). We have employed quantitative PCR for monitoring virus multiplication, as well as plant responses through expression of selected marker genes of photosynthetic activity, carbohydrate metabolism and the defence response. Viral multiplication was the slowest in inoculated potato of cv. Désirée, the only asymptomatic genotype in the study. The intensity of defence-related gene expression was much stronger in both sensitive genotypes (NahG-Désirée and cv. Igor) at the site of inoculation than in asymptomatic plants (cv. Désirée). Photosynthesis and carbohydrate metabolism gene expression differed between the symptomatic and asymptomatic phenotypes. The differential gene expression pattern of the two sensitive genotypes indicates that the outcome of the interaction does not rely simply on one regulatory component, but similar phenotypical features can result from distinct responses at the molecular level.

BackgroundPotato virus Y (PVY) is a major pathogen that causes substantial economic losses in worldwide potato production. Different potato cultivars differ in resistance to PVY, from severe susceptibility, through tolerance, to complete resistance. The aim of this study was to better define the mechanisms underlying tolerant responses of potato to infection by the particularly aggressive PVYNTN strain. We focused on the dynamics of the primary metabolism-related processes during PVYNTN infection.ResultsA comprehensive analysis of the dynamic changes in primary metabolism was performed, which included whole transcriptome analysis, nontargeted proteomics, and photosynthetic activity measurements in potato cv. Désirée and its transgenic counterpart depleted for accumulation of salicylic acid (NahG-Désirée). Faster multiplication of virus occurred in the NahG-Désirée, with these plants developing strong disease symptoms. We show that while the dynamics of responses at the transcriptional level are extensive and bimodal, this is only partially translated to the protein level, and to the final functional outcome. Photosynthesis-related genes are transiently induced before viral multiplication is detected and it is down-regulated later on. This is reflected as a deficiency of the photosynthetic apparatus at the onset of viral multiplication only. Interestingly, specific and constant up-regulation of some RuBisCO transcripts was detected in Désirée plants, which might be important, as these proteins have been shown to interact with viral proteins.In SA-deficient and more sensitive NahG-Désirée plants, consistent down-regulation of photosynthesis-related genes was detected. A constant reduction in the photochemical efficiency from the onset of viral multiplication was identified; in nontransgenic plants this decrease was only transient. The transient reduction in net photosynthetic rate occurred in both genotypes with the same timing, and coincided with changes in stomatal conductivity.ConclusionsDown-regulation of photosynthesis-related gene expression and decreased photosynthetic activity is in line with other studies that have reported the effects of biotic stress on photosynthesis. Here, we additionally detected induction of light-reaction components in the early stages of PVYNTN infection of tolerant interaction. As some of these components have already been shown to interact with viral proteins, their overproduction might contribute to the absence of symptoms in cv. Désirée.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1925-2) contains supplementary material, which is available to authorized users.

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.

Plant diseases caused by viral infection are affecting all major crops. Being an obligate intracellular organisms, chemical control of these pathogens is so far not applied in the field except to control the insect vectors of the viruses. Understanding of molecular responses of plant immunity is therefore economically important, guiding the enforcement of crop resistance. To disentangle complex regulatory mechanisms of the plant immune responses, understanding system as a whole is a must. However, integrating data from different molecular analysis (transcriptomics, proteomics, metabolomics, smallRNA regulation etc.) is not straightforward. We evaluated the response of potato (Solanum tuberosum L.) following the infection with potato virus Y (PVY). The response has been analyzed on two molecular levels, with microarray transcriptome analysis and mass spectroscopy-based proteomics. Within this report, we performed detailed analysis of the results on both levels and compared two different approaches for analysis of proteomic data (spectral count versus MaxQuant). To link the data on different molecular levels, each protein was mapped to the corresponding potato transcript according to StNIB paralogue grouping. Only 33% of the proteins mapped to microarray probes in a one-to-one relation and additionally many showed discordance in detected levels of proteins with corresponding transcripts. We discussed functional importance of true biological differences between both levels and showed that the reason for the discordance between transcript and protein abundance lies partly in complexity and structure of biological regulation of proteome and transcriptome and partly in technical issues contributing to it.

To develop novel crop breeding strategies, it is crucial to understand the mechanisms underlying the interaction between plants and their pathogens. Network modeling represents a powerful tool that can unravel properties of complex biological systems. In this study, we aimed to use network modeling to better understand immune signaling in potato (). For this, we first built on a reliable Arabidopsis () immune signaling model, extending it with the information from diverse publicly available resources. Next, we translated the resulting prior knowledge network (20,012 nodes and 70,091 connections) to potato and superimposed it with an ensemble network inferred from time-resolved transcriptomics data for potato. We used different network modeling approaches to generate specific hypotheses of potato immune signaling mechanisms. An interesting finding was the identification of a string of molecular events illuminating the ethylene pathway modulation of the salicylic acid pathway through Nonexpressor of PR Genes1 gene expression. Functional validations confirmed this modulation, thus supporting the potential of our integrative network modeling approach for unraveling molecular mechanisms in complex systems. In addition, this approach can ultimately result in improved breeding strategies for potato and other sensitive crops.