We show that oomycete-derived Nep1 (for necrosis and ethylene-inducing peptide1)-like proteins (NLPs) trigger a comprehensive immune response in Arabidopsis thaliana, comprising posttranslational activation of mitogen-activated protein kinase activity, deposition of callose, production of nitric oxide, reactive oxygen intermediates, ethylene, and the phytoalexin camalexin, as well as cell death. Transcript profiling experiments revealed that NLPs trigger extensive reprogramming of the Arabidopsis transcriptome closely resembling that evoked by bacteria-derived flagellin. NLP-induced cell death is an active, light-dependent process requiring HSP90 but not caspase activity, salicylic acid, jasmonic acid, ethylene, or functional SGT1a/SGT1b. Studies on animal, yeast, moss, and plant cells revealed that sensitivity to NLPs is not a general characteristic of phospholipid bilayer systems but appears to be restricted to dicot plants. NLP-induced cell death does not require an intact plant cell wall, and ectopic expression of NLP in dicot plants resulted in cell death only when the protein was delivered to the apoplast. Our findings strongly suggest that NLP-induced necrosis requires interaction with a target site that is unique to the extracytoplasmic side of dicot plant plasma membranes. We propose that NLPs play dual roles in plant pathogen interactions as toxin-like virulence factors and as triggers of plant innate immune responses.

A combination of bioinformatic tools, high-throughput gene expression profiles, and the use of synthetic promoters is a powerful approach to discover and evaluate novel cis-sequences in response to specific stimuli. With Arabidopsis (Arabidopsis thaliana) microarray data annotated to the PathoPlant database, 732 different queries with a focus on fungal and oomycete pathogens were performed, leading to 510 up-regulated gene groups. Using the binding site estimation suite of tools, BEST, 407 conserved sequence motifs were identified in promoter regions of these coregulated gene sets. Motif similarities were determined with STAMP, classifying the 407 sequence motifs into 37 families. A comparative analysis of these 37 families with the AthaMap, PLACE, and AGRIS databases revealed similarities to known cis-elements but also led to the discovery of cis-sequences not yet implicated in pathogen response. Using a parsley (Petroselinum crispum) protoplast system and a modified reporter gene vector with an internal transformation control, 25 elicitor-responsive cis-sequences from 10 different motif families were identified. Many of the elicitor-responsive cis-sequences also drive reporter gene expression in an Agrobacterium tumefaciens infection assay in Nicotiana benthamiana. This work significantly increases the number of known elicitor-responsive cis-sequences and demonstrates the successful integration of a diverse set of bioinformatic resources combined with synthetic promoter analysis for data mining and functional screening in plant-pathogen interaction.

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Cutinase, a fungal extracellular esterase, has been proposed to be crucial in the early events of plant infection by many pathogenic fungi. To test the long-standing hypothesis that cutinase of Nectria haematococca (Fusarium solani f sp piso is essential to pathogenicity, we constructed cutinase-deficient mutants by transformation-mediated gene disruption of the single cutinase gene of a highly virulent N. haematococca strain. Four independent mutants were obtained lacking a functional cutinase gene, as confirmed by gel blot analyses and enzyme assays. Bioassays of the cutinasedeficient strains showed no difference in pathogenicity and virulence on pea compared to the wild type and a control transformant. We conclude that the cutinase of N. haematococca is not essential for the infection of pea.

SummaryAccess to the complete gene inventory of an organism is crucial to understanding physiological processes like development, differentiation, pathogenesis, or adaptation to the environment. Transcripts from many active genes are present at low copy numbers. Therefore, procedures that rely on random EST sequencing or on normalisation and subtraction methods have to produce massively redundant data to get access to low-abundance genes. Here, we present an improved oligonucleotide fingerprinting (ofp) approach to the genome of sugar beet (Beta vulgaris), a plant for which practically no molecular information has been available. To identify distinct genes and to provide a representative 'unigene' cDNA set for sugar beet, 159 936 cDNA clones were processed utilizing large-scale, high-throughput data generation and analysis methods. Data analysis yielded 30 444 ofp clusters reflecting the number of different genes in the original cDNA sample. A sample of 10 961 cDNA clones, each representing a different cluster, were selected for sequencing. Standard sequence analysis confirmed that 89% of these EST sequences did represent different genes. These results indicate that the full set of 30 444 ofp clusters represent up to 25 000 genes. We conclude that the ofp analysis pipeline is an accurate and effective way to construct large representative 'unigene' sets for any plant of interest with no requirement for prior molecular sequence data.