BackgroundThe yellow potato cyst nematode, Globodera rostochiensis, is a devastating plant pathogen of global economic importance. This biotrophic parasite secretes effectors from pharyngeal glands, some of which were acquired by horizontal gene transfer, to manipulate host processes and promote parasitism. G. rostochiensis is classified into pathotypes with different plant resistance-breaking phenotypes.ResultsWe generate a high quality genome assembly for G. rostochiensis pathotype Ro1, identify putative effectors and horizontal gene transfer events, map gene expression through the life cycle focusing on key parasitic transitions and sequence the genomes of eight populations including four additional pathotypes to identify variation. Horizontal gene transfer contributes 3.5 % of the predicted genes, of which approximately 8.5 % are deployed as effectors. Over one-third of all effector genes are clustered in 21 putative ‘effector islands’ in the genome. We identify a dorsal gland promoter element motif (termed DOG Box) present upstream in representatives from 26 out of 28 dorsal gland effector families, and predict a putative effector superset associated with this motif. We validate gland cell expression in two novel genes by in situ hybridisation and catalogue dorsal gland promoter element-containing effectors from available cyst nematode genomes. Comparison of effector diversity between pathotypes highlights correlation with plant resistance-breaking.ConclusionsThese G. rostochiensis genome resources will facilitate major advances in understanding nematode plant-parasitism. Dorsal gland promoter element-containing effectors are at the front line of the evolutionary arms race between plant and parasite and the ability to predict gland cell expression a priori promises rapid advances in understanding their roles and mechanisms of action.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-016-0985-1) contains supplementary material, which is available to authorized users.

Ultraviolet-C (UV-C) radiation has been reported to induce defence responses to pathogens in growing crops and described as a new environmentally friendly method for disease control. However, whether the effect of the induced defence mechanisms will persist after the stress imposed by UV-C is alleviated and how these mechanisms interact with pathogen elicitors upon infection have not yet been investigated. Thus, we inoculated strawberry plants with Mycosphaerella fragariae, the causal agent of leaf spot disease, after 5 weeks of repeated UV-C irradiation treatment (cumulative dose of 10.2 kJ m −2 ) and investigated the alteration of gene expression and biochemical phenotypes. The results revealed that UV-C treatment had a significant impact on gene expression in strawberry leaves and led to the overexpression of a set of genes involved in plant-pathogen interaction. UV-C-treated leaves displayed a stronger response to infection after inoculation, with reduced symptoms and increases in accumulation of total phenolics and volatile terpenes, higher expression of pathogenesis-related proteins and the activity of several defence enzymes. This study presumptively describe, for the first time, the involvement of terpenes, reactive oxygen species, and abscisic acid, salicylic acid, jasmonic acid, and their transduction factors, in the network underpinning UV-C priming of growing crops for improved protection against pathogens.

BackgroundHeterodera glycines, commonly referred to as the soybean cyst nematode (SCN), is an obligatory and sedentary plant parasite that causes over a billion-dollar yield loss to soybean production annually. Although there are genetic determinants that render soybean plants resistant to certain nematode genotypes, resistant soybean cultivars are increasingly ineffective because their multi-year usage has selected for virulent H. glycines populations. The parasitic success of H. glycines relies on the comprehensive re-engineering of an infection site into a syncytium, as well as the long-term suppression of host defense to ensure syncytial viability. At the forefront of these complex molecular interactions are effectors, the proteins secreted by H. glycines into host root tissues. The mechanisms of effector acquisition, diversification, and selection need to be understood before effective control strategies can be developed, but the lack of an annotated genome has been a major roadblock.ResultsHere, we use PacBio long-read technology to assemble a H. glycines genome of 738 contigs into 123 Mb with annotations for 29,769 genes. The genome contains significant numbers of repeats (34%), tandem duplicates (18.7 Mb), and horizontal gene transfer events (151 genes). A large number of putative effectors (431 genes) were identified in the genome, many of which were found in transposons.ConclusionsThis advance provides a glimpse into the host and parasite interplay by revealing a diversity of mechanisms that give rise to virulence genes in the soybean cyst nematode, including: tandem duplications containing over a fifth of the total gene count, virulence genes hitchhiking in transposons, and 107 horizontal gene transfers not reported in other plant parasitic nematodes thus far. Through extensive characterization of the H. glycines genome, we provide new insights into H. glycines biology and shed light onto the mystery underlying complex host-parasite interactions. This genome sequence is an important prerequisite to enable work towards generating new resistance or control measures against H. glycines.Electronic supplementary materialThe online version of this article (10.1186/s12864-019-5485-8) contains supplementary material, which is available to authorized users.

Flocculosin, a glycolipid isolated from the yeast-like fungus Pseudozyma flocculosa, was investigated for in vitro antifungal activity. The compound displayed antifungal properties against several pathogenic yeasts. Synergistic activity was observed between flocculosin and amphotericin B, and no significant cytotoxicity was demonstrated when tested against human cell lines.Although progress has been made in antifungal therapy, amphotericin B (AMB) and triazoles are still the most commonly used drugs for this purpose (9). However, their use is limited because of toxicity and resistance (4,5). Recently, the Food and Drug Administration approved caspofungin, a new promising agent with excellent antifungal activity and low toxicity. However, it has a low oral bioavailability and is only available in an intravenous formulation (1). Thus, there is a need for the isolation (or synthesis) of new drugs with different modes of action and low toxicity (3, 7).Flocculosin ( Fig. 1) is a novel low-molecular-weight glycolipid isolated from the yeast-like fungus Pseudozyma flocculosa (Traquair, Shaw and Jarvis) Boekhout and Traquair. This molecule is known to be one of the active components of Sporodex, a biological control agent of powdery mildew fungi (2, 6). Screening against plant fungal pathogens has already confirmed the broad spectrum of flocculosin (2). In an attempt to determine if flocculosin has potential against fungi commonly associated with human mycoses, the objective of this study was to evaluate its antifungal activity under different conditions and against yeast strains with various characteristics.Flocculosin was extracted from liquid culture of P. flocculosa as described previously (2), and a stock solution was prepared in methanol. Antifungal activity was determined against a panel of pathogenic yeasts, including Candida albicans, Candida glabatra, Candida lusitaniae, Saccharomyces cerevisiae, and Trichosporon asahii, or reference strains, including C. albicans (ATCC 90028, ATCC 18804, and ATCC 66027), C. krusei (ATCC 6258), C. parapsilosis (ATCC 22019), and Cryptococcus neoformans (ATCC 90112). All strains were obtained from the Laboratoire de Microbiologie de l'Hôtel-Dieu de Québec du Centre Hospitalier Universitaire de Québec, Québec, Canada.MICs were determined by the NCCLS broth microdilution M27-A2 reference method (8). Modifications were made to test the influence of pH (from 3 to 9) and temperature (25 and 37°C). Drug interactions were assessed by the same method, adapted in a checkerboard fashion. Interactions of flocculosin with AMB (Bristol-Myers Squibb Co., St-Laurent, Québec, Canada) and fluconazole (FLC) (Pfizer, Montréal, Québec, Canada) were evaluated. The MIC was defined as the lowest concentration at which growth inhibition was 100% for flocculosin and AMB and 80% for FLC. The interactions were determined by the fractional inhibitory concentration (FIC) index which is defined as follows:MIC of antifungal compound A tested in combination MIC of antifungal compound A tested alone ϩ MIC of an...

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Potato cyst nematodes (PCNs), Globodera rostochiensis and G. pallida, cause important economic losses. They are hard to manage because of their ability to remain dormant in soil for many years. Although general knowledge about these plant parasitic nematodes has considerably increased over the past decades, very little is known about molecular events involved in cyst dormancy and hatching, two key steps of their development. Here, we have studied the progression of PCN transcriptomes from dry cysts to hatched juveniles using RNA-Seq. We found that several cell detoxification-related genes were highly active in the dry cysts. Many genes linked to an increase of calcium and water uptake were up-regulated during transition from dormancy to hydration. Exposure of hydrated cysts to host plant root exudates resulted in different transcriptional response between species. After 48 h of exposure, G. pallida cysts showed no significant modulation of gene expression while G. rostochiensis had 278 differentially expressed genes. The first G. rostochiensis significantly up-regulated gene was observed after 8 h and was coding for a transmembrane metalloprotease. This enzyme is able to activate/inactivate peptide hormones and could be involved in a cascade of events leading to hatching. Several known effector genes were also up-regulated during hatching.

Supplementary data are available at Bioinformatics online.

The need for larger-scale and increasingly complex protein-protein interaction (PPI) prediction tasks demands that state-of-the-art predictors be highly efficient and adapted to inter-and cross-species predictions. Furthermore, the ability to generate comprehensive interactomes has enabled the appraisal of each PPI in the context of all predictions leading to further improvements in classification performance in the face of extreme class imbalance using the Reciprocal Perspective (RP) framework. We here describe the PIPE4 algorithm. Adaptation of the PIPE3/MP-PIPE sequence preprocessing step led to upwards of 50x speedup and the new Similarity Weighted Score appropriately normalizes for window frequency when applied to any inter-and cross-species prediction schemas. Comprehensive interactomes for three prediction schemas are generated: (1) cross-species predictions, where Arabidopsis thaliana is used as a proxy to predict the comprehensive Glycine max interactome, (2) interspecies predictions between Homo sapiens-HIV1, and (3) a combined schema involving both cross-and inter-species predictions, where both Arabidopsis thaliana and Caenorhabditis elegans are used as proxy species to predict the interactome between Glycine max (the soybean legume) and Heterodera glycines (the soybean cyst nematode). Comparing PIPE4 with the state-of-the-art resulted in improved performance, indicative that it should be the method of choice for complex PPI prediction schemas. The elucidation of protein-protein interaction (PPI) networks is central to molecular biology research. Necessary to producing mechanistic models of cellular processes, PPI networks additionally contribute to challenges such as the prediction of gene function 1-3 , identification of disease genes 4 , and pharmaceutical discovery 5,6. Computational PPI prediction techniques have been developed to supplement and guide wet-laboratory experimental work. The last decade has seen increased computational demand in both scale and complexity of PPI predictors. Predicting comprehensive interactomes (the set of all possible pairwise PPIs in or between proteomes) has only recently become possible with the advent of high-performance computing infrastructure and algorithmic optimizations. While methodologically diverse in their implementation, PPI prediction tools generally exploit information from the set of known PPIs (previously confirmed using classical wet-laboratory techniques) to determine whether any two query proteins will physically interact. The utility and scalability of any one method is subject to the information it leverages. Structure-based methods, at one extreme, require the three-dimensional (3D) characterization of each protein and therefore suffer from low coverage of the proteome. While useful to determining highly specific PPI networks, many methods require template-based modelling which tend to be computationally taxing 7-9. Furthermore, even with complete 3D structural information of each protein in an organism's proteome, the computational time comp...