In silico comparison of transcript abundances during Arabidopsis thaliana and Glycine max resistance to Fusarium virguliforme

SnRK1 Phosphorylates and Destabilizes WRKY3 to Enhance Barley Immunity to Powdery Mildew

Plants recognize pathogens and activate immune responses, which usually involve massive transcriptional reprogramming. The evolutionarily conserved kinase, Sucrose non-fermenting-related kinase 1 (SnRK1), functions as a metabolic regulator that is essential for plant growth and stress responses. Here, we identify barley SnRK1 and a WRKY3 transcription factor by screening a cDNA library. SnRK1 interacts with WRKY3 in yeast, as confirmed by pull-down and luciferase complementation assays. Förster resonance energy transfer combined with noninvasive fluorescence lifetime imaging analysis indicates that the interaction occurs in the barley nucleus. Transient expression and virus-induced gene silencing analyses indicate that WRKY3 acts as a repressor of disease resistance to the Bgh fungus. Barley plants overexpressing WRKY3 have enhanced fungal microcolony formation and sporulation. Phosphorylation assays show that SnRK1 phosphorylates WRKY3 mainly at Ser83 and Ser112 to destabilize the repressor, and WRKY3 non-phosphorylation-null mutants at these two sites are more stable than the wild-type protein. SnRK1-overexpressing barley plants display enhanced disease resistance to Bgh. Transient expression of SnRK1 reduces fungal haustorium formation in barley cells, which probably requires SnRK1 nuclear localization and kinase activity. Together, these findings suggest that SnRK1 is directly involved in plant immunity through phosphorylation and destabilization of the WRKY3 repressor, revealing a new regulatory mechanism of immune derepression in plants.

Soybean Sudden Death Syndrome Caused by Fusarium virguliforme is Impaired by Prolonged Flooding and Anaerobic Conditions

High soil moisture usually favors soybean sudden death syndrome (SDS), caused by Fusarium virguliforme (Fv), but the effects of the duration of the flooding period and accompanying anaerobic conditions on the soybean-Fv interaction are not clear. Greenhouse studies were conducted using susceptible and resistant cultivars exposed to the following treatments: 3, 5, or 7 days of continuous flooding, repeated short-term flooding of 8 h/week for 3 weeks, and a no-flood check treatment. At 7, 14, and 21 days after flooding (DAF), seedlings in the no-flood, 3-day, and repeated short-term treatments showed the highest root rot and foliar symptom severity, whereas seedlings in the 7-day treatment showed the lowest severity. Fv inoculum density in soil was lowest in the 7-day flooding treatment. In a hydroponic system, the steady transcript levels of soybean defense genes and Fv candidate virulence genes were measured in response to different oxygen levels using qPCR. Fv-infected roots exposed to 12 h of anaerobic conditions showed down-regulation of the defense-related soybean genes Laccase, PR3, PR10, PAL, and CHS, and the Fv virulence genes pectate lyase (PL), and Fv homolog of the pisatin demethylase (PDA). Our study suggests that short-term flooding tends to increase SDS, while prolonged flooding negatively impacts SDS due to reduction of Fv density in soil. Moreover, anaerobic conditions down-regulate both soybean defense genes and Fv candidate virulence genes.

Investigation of the Fusarium virguliforme Transcriptomes Induced during Infection of Soybean Roots Suggests that Enzymes with Hydrolytic Activities Could Play a Major Role in Root Necrosis

Sudden death syndrome (SDS) is caused by the fungal pathogen, Fusarium virguliforme, and is a major threat to soybean production in North America. There are two major components of this disease: (i) root necrosis and (ii) foliar SDS. Root symptoms consist of root necrosis with vascular discoloration. Foliar SDS is characterized by interveinal chlorosis and leaf necrosis, and in severe cases by flower and pod abscission. A major toxin involved in initiating foliar SDS has been identified. Nothing is known about how root necrosis develops. In order to unravel the mechanisms used by the pathogen to cause root necrosis, the transcriptome of the pathogen in infected soybean root tissues of a susceptible cultivar, 'Essex', was investigated. The transcriptomes of the germinating conidia and mycelia were also examined. Of the 14,845 predicted F. virguliforme genes, we observed that 12,017 (81%) were expressed in germinating conidia and 12,208 (82%) in mycelia and 10,626 (72%) in infected soybean roots. Of the 10,626 genes induced in infected roots, 224 were transcribed only following infection. Expression of several infection-induced genes encoding enzymes with oxidation-reduction properties suggests that degradation of antimicrobial compounds such as the phytoalexin, glyceollin, could be important in early stages of the root tissue infection. Enzymes with hydrolytic and catalytic activities could play an important role in establishing the necrotrophic phase. The expression of a large number of genes encoding enzymes with catalytic and hydrolytic activities during the late infection stages suggests that cell wall degradation could be involved in root necrosis and the establishment of the necrotrophic phase in this pathogen.

Tanscriptomic Study of the Soybean-Fusarium virguliforme Interaction Revealed a Novel Ankyrin-Repeat Containing Defense Gene, Expression of Whose during Infection Led to Enhanced Resistance to the Fungal Pathogen in Transgenic Soybean Plants

Fusarium virguliforme causes the serious disease sudden death syndrome (SDS) in soybean. Host resistance to this pathogen is partial and is encoded by a large number of quantitative trait loci, each conditioning small effects. Breeding SDS resistance is therefore challenging and identification of single-gene encoded novel resistance mechanisms is becoming a priority to fight this devastating this fungal pathogen. In this transcriptomic study we identified a few putative soybean defense genes, expression of which is suppressed during F. virguliforme infection. The F. virguliforme infection-suppressed genes were broadly classified into four major classes. The steady state transcript levels of many of these genes were suppressed to undetectable levels immediately following F. virguliforme infection. One of these classes contains two novel genes encoding ankyrin repeat-containing proteins. Expression of one of these genes, GmARP1, during F. virguliforme infection enhances SDS resistance among the transgenic soybean plants. Our data suggest that GmARP1 is a novel defense gene and the pathogen presumably suppress its expression to establish compatible interaction.

The SnRK1 Energy Sensor in Plant Biotic Interactions

Our understanding of plant biotic interactions has grown significantly in recent years with the identification of the mechanisms involved in innate immunity, hormone signaling, and secondary metabolism. The impact of such interactions on primary metabolism and the role of metabolic signals in the response of the plants, however, remain far less explored. The SnRK1 (SNF1-related kinase 1) kinases act as metabolic sensors, integrating very diverse stress conditions, and are key in maintaining energy homeostasis for growth and survival. Consistently, an important role is emerging for these kinases as regulators of biotic stress responses triggered by viral, bacterial, fungal, and oomycete infections as well as by herbivory. While this identifies SnRK1 as a promising target for directed modification or selection for more quantitative and sustainable resistance, its central function also increases the chances of unwanted side effects on growth and fitness, stressing the need for identification and in-depth characterization of the mechanisms and target processes involved. VIDEO ABSTRACT.

Effect of Fusarium virguliforme phytotoxin on soybean gene expression suggests a role in multidimensional defence

Sudden death syndrome (SDS), caused by Fusarium virguliforme, is an important yield-limiting disease of soybean. This soil-borne fungus colonizes soybean roots causing root rot, and also releases a phytotoxin that is translocated to leaves causing interveinal chlorosis and necrosis leading to defoliation and early maturation. The objective of our study was to compare gene expression profiles during the early response of soybean leaves exposed to sterile culture filtrates of F. virguliforme in soybean genotypes with different levels of resistance to SDS. The analysis identified SDS-related defence genes that were induced in the most resistant genotype, but not in the other genotypes. Further functional annotations based on sequence homology suggested that some of the induced genes probably encode proteins involved in cell wall modification, detoxification, defence responses, primary metabolism and membrane transport. Quantitative real-time reverse-transcribed polymerase chain reaction confirmed the differential transcript accumulation of a subset of these genes. In addition, in silico mapping of differentially expressed genes to SDS-resistant quantitative trait loci allowed for the identification of new potential defence genes that could be genetically mapped to the soybean genome, and could be used further in a marker-assisted selection programme. A comparison of the response of soybean to F. virguliforme phytotoxin (Fv toxin) relative to other biotic and abiotic stresses revealed that the resistance response to Fv toxin is quite similar to the response to inoculation with an incompatible Pseudomonas syringae pv. glycinea strain, suggesting that Fv toxin might induce hypersensitive response pathways in soybean leaf tissues in the absence of pathogen in these tissues.

Metabolic module mining based on Independent Component Analysis in Arabidopsis thaliana

Independent Component Analysis (ICA) has been introduced as one of the useful tools for gene-functional discovery in animals. However, this approach has been poorly utilized in the plant sciences. In the present study, we have exploited ICA combined with pathway enrichment analysis to address the statistical challenges associated with genome-wide analysis in plant system. To generate an Arabidopsis metabolic platform, we collected 4,373 Affy-metrix ATH1 microarray datasets. Out of the 3,232 metabolic genes and transcription factors, 99.47% of these genes were identified in at least one component, indicating the coverage of most of the metabolic pathways by the components. During the metabolic pathway enrichment analysis, we found components that indicate an independent regulation between the isoprenoid biosynthesis pathways. We also utilized this analysis tool to investigate some transcription factors involved in secondary cell wall biogenesis. This approach has identified remarkably more transcription factors compared to previously reported analysis tools. A website providing user-friendly searching and downloading of the entire dataset analyzed by ICA is available at http://kimjy.gnu.ac.kr/ICA.files/slide0002.htm . ICA combined with pathway enrichment analysis might provide a powerful approach for the extraction of the components responsible for a biological process of interest in plant systems.

Transcriptional analysis of soybean root response to Fusarium virguliforme, the causal agent of sudden death syndrome

Sudden death syndrome (SDS) of soybean can be caused by any of four distinct Fusarium species, with F. virguliforme and F. tucumaniae being the main casual agents in North and South America, respectively. Although the fungal tissue is largely confined to the roots, the fungus releases a toxin that is translocated to leaf tissues, in which it causes interveinal chlorosis and necrosis leading to scorching symptoms and possible defoliation. In this study, we report on an Affymetrix analysis measuring transcript abundances in resistant (PI 567.374) and susceptible (Essex) roots upon infection by F. virguliforme, 5 and 7 days postinoculation. Many of the genes with increased expression were common between resistant and susceptible plants (including genes related to programmed cell death, the phenylpropanoid pathway, defense, signal transduction, and transcription factors), but some genotype-specific expression was noted. Changes in small (sm)RNA levels between inoculated and mock-treated samples were also studied and implicate a role for these molecules in this interaction. In total, 2,467 genes were significantly changing in the experiment, with 1,694 changing in response to the pathogen; 93 smRNA and 42 microRNA that have putative soybean gene targets were identified from infected tissue. Comparing genotypes, 247 genes were uniquely modulating in the resistant host, whereas 378 genes were uniquely modulating in the susceptible host. Comparing locations of differentially expressed genes to known resistant quantitative trait loci as well as identifying smRNA that increased while their putative targets decreased (or vice versa) allowed for the narrowing of candidate SDS defense-associated genes.

Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research

Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peer-review process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine learning to recognize function in 4D), Dr. Mary Qu Yang (IEEE BIBM workshop keynote lecturer on new initiatives of detecting microscopic disease using machine learning and molecular biology, http://ieeexplore.ieee.org/servlet/opac?punumber=4425386) and Dr. Jack Y. Yang (IEEE BIBM workshop keynote lecturer on data mining and knowledge discovery in translational medicine) from the first IEEE Computer Society BioInformatics and BioMedicine (IEEE BIBM) international conference and workshops, November 2-4, 2007, Silicon Valley, California, USA.