Transgenic expression of the dicotyledonous pattern recognition receptor EFR in rice leads to ligand-dependent activation of defense responses

Plant plasma membrane localized pattern recognition receptors (PRRs) detect extracellular pathogen-associated molecules. PRRs such as Arabidopsis EFR and rice XA21 are taxonomically restricted and are absent from most plant genomes. Here we show that rice plants expressing EFR or the chimeric receptor EFR::XA21, containing the EFR ectodomain and the XA21 intracellular domain, sense both Escherichia coli- and Xanthomonas oryzae pv. oryzae (Xoo)-derived elf18 peptides at sub-nanomolar concentrations. Treatment of EFR and EFR::XA21 rice leaf tissue with elf18 leads to MAP kinase activation, reactive oxygen production and defense gene expression. Although expression of EFR does not lead to robust enhanced resistance to fully virulent Xoo isolates, it does lead to quantitatively enhanced resistance to weakly virulent Xoo isolates. EFR interacts with OsSERK2 and the XA21 binding protein 24 (XB24), two key components of the rice XA21-mediated immune response. Rice-EFR plants silenced for OsSERK2, or overexpressing rice XB24 are compromised in elf18-induced reactive oxygen production and defense gene expression indicating that these proteins are also important for EFR-mediated signaling in transgenic rice. Taken together, our results demonstrate the potential feasibility of enhancing disease resistance in rice and possibly other monocotyledonous crop species by expression of dicotyledonous PRRs. Our results also suggest that Arabidopsis EFR utilizes at least a subset of the known endogenous rice XA21 signaling components

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome

Sorting Signals, N-Terminal Modifications and Abundance of the Chloroplast Proteome

Characterization of the chloroplast proteome is needed to understand the essential contribution of the chloroplast to plant growth and development. Here we present a large scale analysis by nanoLC-Q-TOF and nanoLC-LTQ-Orbitrap mass spectrometry (MS) of ten independent chloroplast preparations from Arabidopsis thaliana which unambiguously identified 1325 proteins. Novel proteins include various kinases and putative nucleotide binding proteins. Based on repeated and independent MS based protein identifications requiring multiple matched peptide sequences, as well as literature, 916 nuclear-encoded proteins were assigned with high confidence to the plastid, of which 86% had a predicted chloroplast transit peptide (cTP). The protein abundance of soluble stromal proteins was calculated from normalized spectral counts from LTQ-Obitrap analysis and was found to cover four orders of magnitude. Comparison to gel-based quantification demonstrates that ‘spectral counting’ can provide large scale protein quantification for Arabidopsis. This quantitative information was used to determine possible biases for protein targeting prediction by TargetP and also to understand the significance of protein contaminants. The abundance data for 550 stromal proteins was used to understand abundance of metabolic pathways and chloroplast processes. We highlight the abundance of 48 stromal proteins involved in post-translational proteome homeostasis (including aminopeptidases, proteases, deformylases, chaperones, protein sorting components) and discuss the biological implications. N-terminal modifications were identified for a subset of nuclear- and chloroplast-encoded proteins and a novel N-terminal acetylation motif was discovered. Analysis of cTPs and their cleavage sites of Arabidopsis chloroplast proteins, as well as their predicted rice homologues, identified new species-dependent features, which will facilitate improved subcellular localization prediction. No evidence was found for suggested targeting via the secretory system. This study provides the most comprehensive chloroplast proteome analysis to date and an expanded Plant Proteome Database (PPDB) in which all MS data are projected on identified gene models

PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity

<p>Abstract</p> <p>Background</p> <p>Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. Due to the difficulty in performing high-throughput mass spectrometry-based experiment, there is a desire to predict phosphorylation sites using computational methods. However, previous studies regarding <it>in silico </it>prediction of plant phosphorylation sites lack the consideration of kinase-specific phosphorylation data. Thus, we are motivated to propose a new method that investigates different substrate specificities in plant phosphorylation sites.</p> <p>Results</p> <p>Experimentally verified phosphorylation data were extracted from TAIR9-a protein database containing 3006 phosphorylation data from the plant species <it>Arabidopsis thaliana</it>. In an attempt to investigate the various substrate motifs in plant phosphorylation, maximal dependence decomposition (MDD) is employed to cluster a large set of phosphorylation data into subgroups containing significantly conserved motifs. Profile hidden Markov model (HMM) is then applied to learn a predictive model for each subgroup. Cross-validation evaluation on the MDD-clustered HMMs yields an average accuracy of 82.4% for serine, 78.6% for threonine, and 89.0% for tyrosine models. Moreover, independent test results using <it>Arabidopsis thaliana </it>phosphorylation data from UniProtKB/Swiss-Prot show that the proposed models are able to correctly predict 81.4% phosphoserine, 77.1% phosphothreonine, and 83.7% phosphotyrosine sites. Interestingly, several MDD-clustered subgroups are observed to have similar amino acid conservation with the substrate motifs of well-known kinases from Phospho.ELM-a database containing kinase-specific phosphorylation data from multiple organisms.</p> <p>Conclusions</p> <p>This work presents a novel method for identifying plant phosphorylation sites with various substrate motifs. Based on cross-validation and independent testing, results show that the MDD-clustered models outperform models trained without using MDD. The proposed method has been implemented as a web-based plant phosphorylation prediction tool, PlantPhos <url>http://csb.cse.yzu.edu.tw/PlantPhos/</url>. Additionally, two case studies have been demonstrated to further evaluate the effectiveness of PlantPhos.</p

Altered Germination and Subcellular Localization Patterns for PUB44/SAUL1 in Response to Stress and Phytohormone Treatments

BACKGROUND: In plants, the ubiquitin-proteasome system is emerging as a significant regulatory system throughout the plant lifecycle. The ubiquitination of a target protein requires the sequential actions of the E1, E2 and E3 enzymes, with the latter E3 enzyme conferring target selection in this process. There are a large number of predicted E3 enzymes in plant genomes, and very little is known about the functions of many of these predicted genes. Here we report here an analysis of two closely-related members of the Arabidopsis Plant U-box (PUB) family of E3 ubiquitin ligases, PUB43 and PUB44. PRINCIPAL FINDINGS: Homozygous pub44/pub44 mutant seedlings were found displayed a seedling lethal phenotype and this corresponded with widespread cell death lesions throughout the cotyledons and roots. Interestingly, heterozygous PUB44/pub44 seedlings were wild-type in appearance yet displayed intermediate levels of cell death lesions in comparison to pub44/pub44 seedlings. In contrast, homozygous pub43/pub43 mutants were viable and did not show any signs of cell death despite the PUB43 gene being more highly expressed than PUB44. The PUB44 mutants are not classical lesion mimic mutants as they did not have increased resistance to plant pathogens. We also observed increased germination rates in mutant seeds for both PUB44 and PUB43 under inhibitory concentrations of abscisic acid. Finally, the subcellular localization of PUB44 was investigated with transient expression assays in BY-2 cells. Under varying conditions, PUB44 was observed to be localized to the cytoplasm, plasma membrane, or nucleus. CONCLUSIONS: Based on mutant plant analyses, the Arabidopsis PUB43 and PUB44 genes are proposed to function during seed germination and early seedling growth. Given PUB44's ability to shuttle from the nucleus to the plasma membrane, PUB44 may be active in different subcellular compartments as part of these biological functions

Global Analysis of Gene Expression Profiles in Developing Physic Nut (Jatropha curcas L.) Seeds

Background: Physic nut (Jatropha curcas L.) is an oilseed plant species with high potential utility as a biofuel. Furthermore, following recent sequencing of its genome and the availability of expressed sequence tag (EST) libraries, it is a valuable model plant for studying carbon assimilation in endosperms of oilseed plants. There have been several transcriptomic analyses of developing physic nut seeds using ESTs, but they have provided limited information on the accumulation of stored resources in the seeds. Methodology/Principal Findings: We applied next-generation Illumina sequencing technology to analyze global gen

Exploiting members of the BAHD acyltransferase family to synthesize multiple hydroxycinnamate and benzoate conjugates in yeast

BACKGROUND: BAHD acyltransferases, named after the first four biochemically characterized enzymes of the group, are plant-specific enzymes that catalyze the transfer of coenzyme A-activated donors onto various acceptor molecules. They are responsible for the synthesis in plants of a myriad of secondary metabolites, some of which are beneficial for humans either as therapeutics or as specialty chemicals such as flavors and fragrances. The production of pharmaceutical, nutraceutical and commodity chemicals using engineered microbes is an alternative, green route to energy-intensive chemical syntheses that consume petroleum-based precursors. However, identification of appropriate enzymes and validation of their functional expression in heterologous hosts is a prerequisite for the design and implementation of metabolic pathways in microbes for the synthesis of such target chemicals. RESULTS: For the synthesis of valuable metabolites in the yeast Saccharomyces cerevisiae, we selected BAHD acyltransferases based on their preferred donor and acceptor substrates. In particular, BAHDs that use hydroxycinnamoyl-CoAs and/or benzoyl-CoA as donors were targeted because a large number of molecules beneficial to humans belong to this family of hydroxycinnamate and benzoate conjugates. The selected BAHD coding sequences were synthesized and cloned individually on a vector containing the Arabidopsis gene At4CL5, which encodes a promiscuous 4-coumarate:CoA ligase active on hydroxycinnamates and benzoates. The various S. cerevisiae strains obtained for co-expression of At4CL5 with the different BAHDs effectively produced a wide array of valuable hydroxycinnamate and benzoate conjugates upon addition of adequate combinations of donors and acceptor molecules. In particular, we report here for the first time the production in yeast of rosmarinic acid and its derivatives, quinate hydroxycinnamate esters such as chlorogenic acid, and glycerol hydroxycinnamate esters. Similarly, we achieved for the first time the microbial production of polyamine hydroxycinnamate amides; monolignol, malate and fatty alcohol hydroxycinnamate esters; tropane alkaloids; and benzoate/caffeate alcohol esters. In some instances, the additional expression of Flavobacterium johnsoniae tyrosine ammonia-lyase (FjTAL) allowed the synthesis of p-coumarate conjugates and eliminated the need to supplement the culture media with 4-hydroxycinnamate. CONCLUSION: We demonstrate in this study the effectiveness of expressing members of the plant BAHD acyltransferase family in yeast for the synthesis of numerous valuable hydroxycinnamate and benzoate conjugates

Muc2 Protects against Lethal Infectious Colitis by Disassociating Pathogenic and Commensal Bacteria from the Colonic Mucosa

Despite recent advances in our understanding of the pathogenesis of attaching and effacing (A/E) Escherichia coli infections, the mechanisms by which the host defends against these microbes are unclear. The goal of this study was to determine the role of goblet cell-derived Muc2, the major intestinal secretory mucin and primary component of the mucus layer, in host protection against A/E pathogens. To assess the role of Muc2 during A/E bacterial infections, we inoculated Muc2 deficient (Muc2−/−) mice with Citrobacter rodentium, a murine A/E pathogen related to diarrheagenic A/E E. coli. Unlike wildtype (WT) mice, infected Muc2−/− mice exhibited rapid weight loss and suffered up to 90% mortality. Stool plating demonstrated 10–100 fold greater C. rodentium burdens in Muc2−/− vs. WT mice, most of which were found to be loosely adherent to the colonic mucosa. Histology of Muc2−/− mice revealed ulceration in the colon amid focal bacterial microcolonies. Metabolic labeling of secreted mucins in the large intestine demonstrated that mucin secretion was markedly increased in WT mice during infection compared to uninfected controls, suggesting that the host uses increased mucin release to flush pathogens from the mucosal surface. Muc2 also impacted host-commensal interactions during infection, as FISH analysis revealed C. rodentium microcolonies contained numerous commensal microbes, which was not observed in WT mice. Orally administered FITC-Dextran and FISH staining showed significantly worsened intestinal barrier disruption in Muc2−/− vs. WT mice, with overt pathogen and commensal translocation into the Muc2−/− colonic mucosa. Interestingly, commensal depletion enhanced C. rodentium colonization of Muc2−/− mice, although colonic pathology was not significantly altered. In conclusion, Muc2 production is critical for host protection during A/E bacterial infections, by limiting overall pathogen and commensal numbers associated with the colonic mucosal surface. Such actions limit tissue damage and translocation of pathogenic and commensal bacteria across the epithelium

Effects of Heavy Metals and Arbuscular Mycorrhiza on the Leaf Proteome of a Selected Poplar Clone: A Time Course Analysis

Arbuscular mycorrhizal (AM) fungi establish a mutualistic symbiosis with the roots of most plant species. While receiving photosynthates, they improve the mineral nutrition of the plant and can also increase its tolerance towards some pollutants, like heavy metals. Although the fungal symbionts exclusively colonize the plant roots, some plant responses can be systemic. Therefore, in this work a clone of Populus alba L., previously selected for its tolerance to copper and zinc, was used to investigate the effects of the symbiosis with the AM fungus Glomus intraradices on the leaf protein expression. Poplar leaf samples were collected from plants maintained in a glasshouse on polluted (copper and zinc contaminated) or unpolluted soil, after four, six and sixteen months of growth. For each harvest, about 450 proteins were reproducibly separated on 2DE maps. At the first harvest the most relevant effect on protein modulation was exerted by the AM fungi, at the second one by the metals, and at the last one by both treatments. This work demonstrates how importantly the time of sampling affects the proteome responses in perennial plants. In addition, it underlines the ability of a proteomic approach, targeted on protein identification, to depict changes in a specific pattern of protein expression, while being still far from elucidating the biological function of each protein