Global Analysis of Arabidopsis/Downy Mildew Interactions Reveals Prevalence of Incomplete Resistance and Rapid Evolution of Pathogen Recognition

Interactions between Arabidopsis thaliana and its native obligate oomycete pathogen Hyaloperonospora arabidopsidis (Hpa) represent a model system to study evolution of natural variation in a host/pathogen interaction. Both Arabidopsis and Hpa genomes are sequenced and collections of different sub-species are available. We analyzed ∼400 interactions between different Arabidopsis accessions and five strains of Hpa. We examined the pathogen's overall ability to reproduce on a given host, and performed detailed cytological staining to assay for pathogen growth and hypersensitive cell death response in the host. We demonstrate that intermediate levels of resistance are prevalent among Arabidopsis populations and correlate strongly with host developmental stage. In addition to looking at plant responses to challenge by whole pathogen inoculations, we investigated the Arabidopsis resistance attributed to recognition of the individual Hpa effectors, ATR1 and ATR13. Our results suggest that recognition of these effectors is evolutionarily dynamic and does not form a single clade in overall Arabidopsis phylogeny for either effector. Furthermore, we show that the ultimate outcome of the interactions can be modified by the pathogen, despite a defined gene-for-gene resistance in the host. These data indicate that the outcome of disease and disease resistance depends on genome-for-genome interactions between the host and its pathogen, rather than single gene pairs as thought previously

Prostate cancer risk and consumption of fish oils: a dietary biomarker-based case–control study

Experimental studies suggest that the risk of prostate cancer is reduced with the intake of long-chain n-3 polyunsaturated fatty acids derived from marine foods, such as eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). However, few human studies have been conducted due to difficulties in assessing the dietary intake of these fatty acids. The authors examined the relationship between prostate cancer risk and EPA and DHA in erythrocyte biomarkers in a population-based case–control study in Auckland, New Zealand during 1996–1997 involving 317 prostate cancer cases and 480 age-matched community controls. Reduced prostate cancer risk was associated with high erythrocyte phosphatidylcholine levels of EPA (multivariate relative risk = 0.59; 95% confidence interval 0.37–0.95, upper vs lowest quartile) and DHA (multivariate relative risk = 0.62; 95% confidence interval 0.39–0.98, upper vs lowest quartile). These analyses support evidence from in vitro experiments for a reduced risk of prostate cancer associated with dietary fish oils, possibly acting via inhibition of arachidonic acid-derived eicosanoid biosynthesis. © 1999 Cancer Research Campaig

Imbalanced Lignin Biosynthesis Promotes the Sexual Reproduction of Homothallic Oomycete Pathogens

Lignin is incorporated into plant cell walls to maintain plant architecture and to ensure long-distance water transport. Lignin composition affects the industrial value of plant material for forage, wood and paper production, and biofuel technologies. Industrial demands have resulted in an increase in the use of genetic engineering to modify lignified plant cell wall composition. However, the interaction of the resulting plants with the environment must be analyzed carefully to ensure that there are no undesirable side effects of lignin modification. We show here that Arabidopsis thaliana mutants with impaired 5-hydroxyguaiacyl O-methyltransferase (known as caffeate O-methyltransferase; COMT) function were more susceptible to various bacterial and fungal pathogens. Unexpectedly, asexual sporulation of the downy mildew pathogen, Hyaloperonospora arabidopsidis, was impaired on these mutants. Enhanced resistance to downy mildew was not correlated with increased plant defense responses in comt1 mutants but coincided with a higher frequency of oomycete sexual reproduction within mutant tissues. Comt1 mutants but not wild-type Arabidopsis accumulated soluble 2-O-5-hydroxyferuloyl-l-malate. The compound weakened mycelium vigor and promoted sexual oomycete reproduction when applied to a homothallic oomycete in vitro. These findings suggested that the accumulation of 2-O-5-hydroxyferuloyl-l-malate accounted for the observed comt1 mutant phenotypes during the interaction with H. arabidopsidis. Taken together, our study shows that an artificial downregulation of COMT can drastically alter the interaction of a plant with the biotic environment

Promotion of prostatic metastatic migration towards human bone marrow stoma by Omega 6 and its inhibition by Omega 3 PUFAs

Epidemiological studies have shown not only a relationship between the intake of dietary lipids and an increased risk of developing metastatic prostate cancer, but also the type of lipid intake that influences the risk of metastatic prostate cancer. The Omega-6 poly-unsaturated fatty acid, Arachidonic acid, has been shown to enhance the proliferation of malignant prostate epithelial cells and increase the risk of advanced prostate cancer. However, its role in potentiating the migration of cancer cells is unknown. Here we show that arachidonic acid at concentrations ⩽5 μM is a potent stimulator of malignant epithelial cellular invasion, which is able to restore invasion toward hydrocortisone-deprived adipocyte-free human bone marrow stroma completely. This observed invasion is mediated by the arachidonic acid metabolite prostaglandin E2 and is inhibited by the Omega-3 poly-unsaturated fatty acids eicosapentaenoic acid and docosahexaenoic acid at a ratio of 1 : 2 Omega-3 : Omega-6, and by the COX-2 inhibitor NS-398. These results identify a mechanism by which arachidonic acid may potentiate the risk of metastatic migration and secondary implantation in vivo, a risk which can be reduced with the uptake of Omega-3 poly-unsaturated fatty acids

An eQTL Analysis of Partial Resistance to Puccinia hordei in Barley

Background - Genetic resistance to barley leaf rust caused by Puccinia hordei involves both R genes and quantitative trait loci. The R genes provide higher but less durable resistance than the quantitative trait loci. Consequently, exploring quantitative or partial resistance has become a favorable alternative for controlling disease. Four quantitative trait loci for partial resistance to leaf rust have been identified in the doubled haploid Steptoe (St)/Morex (Mx) mapping population. Further investigations are required to study the molecular mechanisms underpinning partial resistance and ultimately identify the causal genes.Methodology/Principal Findings - We explored partial resistance to barley leaf rust using a genetical genomics approach. We recorded RNA transcript abundance corresponding to each probe on a 15K Agilent custom barley microarray in seedlings from St and Mx and 144 doubled haploid lines of the St/Mx population. A total of 1154 and 1037 genes were, respectively, identified as being P. hordei-responsive among the St and Mx and differentially expressed between P. hordei-infected St and Mx. Normalized ratios from 72 distant-pair hybridisations were used to map the genetic determinants of variation in transcript abundance by expression quantitative trait locus (eQTL) mapping generating 15685 eQTL from 9557 genes. Correlation analysis identified 128 genes that were correlated with resistance, of which 89 had eQTL co-locating with the phenotypic quantitative trait loci (pQTL). Transcript abundance in the parents and conservation of synteny with rice allowed us to prioritise six genes as candidates for Rphq11, the pQTL of largest effect, and highlight one, a phospholipid hydroperoxide glutathione peroxidase (HvPHGPx) for detailed analysis.Conclusions/Significance - The eQTL approach yielded information that led to the identification of strong candidate genes underlying pQTL for resistance to leaf rust in barley and on the general pathogen response pathway. The dataset will facilitate a systems appraisal of this host-pathogen interaction and, potentially, for other traits measured in this populatio

Gene family expansions and contractions are associated with host range in plant pathogens of the genus Colletotrichum

Background: Many species belonging to the genus Colletotrichum cause anthracnose disease on a wide range of plant species. In addition to their economic impact, the genus Colletotrichum is a useful model for the study of the evolution of host specificity, speciation and reproductive behaviors. Genome projects of Colletotrichum species have already opened a new era for studying the evolution of pathogenesis in fungi. Results: We sequenced and annotated the genomes of four strains in the Colletotrichum acutatum species complex (CAsc), a clade of broad host range pathogens within the genus. The four CAsc proteomes and secretomes along with those representing an additional 13 species (six Colletotrichum spp. and seven other Sordariomycetes) were classified into protein families using a variety of tools. Hierarchical clustering of gene family and functional domain assignments, and phylogenetic analyses revealed lineage specific losses of carbohydrate-active enzymes (CAZymes) and proteases encoding genes in Colletotrichum species that have narrow host range as well as duplications of these families in the CAsc. We also found a lineage specific expansion of necrosis and ethylene-inducing peptide 1 (Nep1)-like protein (NLPs) families within the CAsc. Conclusions: This study illustrates the plasticity of Colletotrichum genomes, and shows that major changes in host range are associated with relatively recent changes in gene content

Generative Embedding for Model-Based Classification of fMRI Data

Decoding models, such as those underlying multivariate classification algorithms, have been increasingly used to infer cognitive or clinical brain states from measures of brain activity obtained by functional magnetic resonance imaging (fMRI). The practicality of current classifiers, however, is restricted by two major challenges. First, due to the high data dimensionality and low sample size, algorithms struggle to separate informative from uninformative features, resulting in poor generalization performance. Second, popular discriminative methods such as support vector machines (SVMs) rarely afford mechanistic interpretability. In this paper, we address these issues by proposing a novel generative-embedding approach that incorporates neurobiologically interpretable generative models into discriminative classifiers. Our approach extends previous work on trial-by-trial classification for electrophysiological recordings to subject-by-subject classification for fMRI and offers two key advantages over conventional methods: it may provide more accurate predictions by exploiting discriminative information encoded in ‘hidden’ physiological quantities such as synaptic connection strengths; and it affords mechanistic interpretability of clinical classifications. Here, we introduce generative embedding for fMRI using a combination of dynamic causal models (DCMs) and SVMs. We propose a general procedure of DCM-based generative embedding for subject-wise classification, provide a concrete implementation, and suggest good-practice guidelines for unbiased application of generative embedding in the context of fMRI. We illustrate the utility of our approach by a clinical example in which we classify moderately aphasic patients and healthy controls using a DCM of thalamo-temporal regions during speech processing. Generative embedding achieves a near-perfect balanced classification accuracy of 98% and significantly outperforms conventional activation-based and correlation-based methods. This example demonstrates how disease states can be detected with very high accuracy and, at the same time, be interpreted mechanistically in terms of abnormalities in connectivity. We envisage that future applications of generative embedding may provide crucial advances in dissecting spectrum disorders into physiologically more well-defined subgroups