Sporadic Creutzfeldt-Jakob disease VM1: phenotypic and molecular characterization of a novel subtype of human prion disease

The methionine (M)-valine (V) polymorphic codon 129 of the prion protein gene (PRNP) plays a central role in both susceptibility and phenotypic expression of sporadic Creutzfeldt-Jakob diseases (sCJD). Experimental transmissions of sCJD in humanized transgenic mice led to the isolation of five prion strains, named M1, M2C, M2T, V2, and V1, based on two major conformations of the pathological prion protein (PrPSc, type 1 and type 2), and the codon 129 genotype determining susceptibility and propagation efficiency. While the most frequent sCJD strains have been described in codon 129 homozygosis (MM1, MM2C, VV2) and heterozygosis (MV1, MV2K, and MV2C), the V1 strain has only been found in patients carrying VV. We identified six sCJD cases, 4 in Catalonia and 2 in Italy, carrying MV at PRNP codon 129 in combination with PrPSc type 1 and a new clinical and neuropathological profile reminiscent of the VV1 sCJD subtype rather than typical MM1/MV1. All patients had a relatively long duration (mean of 20.5 vs. 3.5 months of MM1/MV1 patients) and lacked electroencephalographic periodic sharp-wave complexes at diagnosis. Distinctive histopathological features included the spongiform change with vacuoles of larger size than those seen in sCJD MM1/MV1, the lesion profile with prominent cortical and striatal involvement, and the pattern of PrPSc deposition characterized by a dissociation between florid spongiform change and mild synaptic deposits associated with coarse, patch-like deposits in the cerebellar molecular layer. Western blot analysis of brain homogenates revealed a PrPSc type 1 profile with physicochemical properties reminiscent of the type 1 protein linked to the VV1 sCJD subtype. In summary, we have identified a new subtype of sCJD with distinctive clinicopathological features significantly overlapping with those of the VV1 subtype, possibly representing the missing evidence of V1 sCJD strain propagation in the 129MV host genotype

A meta-analysis reveals the commonalities and differences in Arabidopsis thaliana response to different viral pathogens

Understanding the mechanisms by which plants trigger host defenses in response to viruses has been a challenging problem owing to the multiplicity of factors and complexity of interactions involved. The advent of genomic techniques, however, has opened the possibility to grasp a global picture of the interaction. Here, we used Arabidopsis thaliana to identify and compare genes that are differentially regulated upon infection with seven distinct (+)ssRNA and one ssDNA plant viruses. In the first approach, we established lists of genes differentially affected by each virus and compared their involvement in biological functions and metabolic processes. We found that phylogenetically related viruses significantly alter the expression of similar genes and that viruses naturally infecting Brassicaceae display a greater overlap in the plant response. In the second approach, virus-regulated genes were contextualized using models of transcriptional and protein-protein interaction networks of A. thaliana. Our results confirm that host cells undergo significant reprogramming of their transcriptome during infection, which is possibly a central requirement for the mounting of host defenses. We uncovered a general mode of action in which perturbations preferentially affect genes that are highly connected, central and organized in modules. © 2012 Rodrigo et al.This work was supported by the Spanish Ministerio de Ciencia e Innovacion (MICINN) grants BFU2009-06993 (S. F. E.) and BIO2006-13107 (C. L.) and by Generalitat Valenciana grant PROMETEO2010/016 (S. F. E.). G. R. is supported by a graduate fellowship from the Generalitat Valenciana (BFPI2007-160) and J.C. by a contract from MICINN grant TIN2006-12860. 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Crohn’s Disease, Host–Microbiota Interactions, and Immunonutrition: Dietary Strategies Targeting Gut Microbiome as Novel Therapeutic Approaches

Crohn’s disease (CD) is a complex, disabling, idiopathic, progressive, and destructive disorder with an unknown etiology. The pathogenesis of CD is multifactorial and involves the interplay between host genetics, and environmental factors, resulting in an aberrant immune response leading to intestinal inflammation. Due to the high morbidity and long-term management of CD, the development of non-pharmacological approaches to mitigate the severity of CD has recently attracted great attention. The gut microbiota has been recognized as an important player in the development of CD, and general alterations in the gut microbiome have been established in these patients. Thus, the gut microbiome has emerged as a pre-eminent target for potential new treatments in CD. Epidemiological and interventional studies have demonstrated that diet could impact the gut microbiome in terms of composition and functionality. However, how specific dietary strategies could modulate the gut microbiota composition and how this would impact host–microbe interactions in CD are still unclear. In this review, we discuss the most recent knowledge on host–microbe interactions and their involvement in CD pathogenesis and severity, and we highlight the most up-to-date information on gut microbiota modulation through nutritional strategies, focusing on the role of the microbiota in gut inflammation and immunity

Summary of topological properties of the differentially expressed VRGs from several viral infections contextualized in the <i>A. thaliana</i> TRN and PPIN.

<p>We show the number of VRGs and VRFs (over- and under-expressed), the number of interactions (edges) manipulated by the virus, the power-law distribution exponent (for connectivity γ), the average connectivity (<i>(k)</i>), and the average betweenness (<i>(b)</i>). We also show the P-value for the tests comparing the shape and location of the VRGs distributions with respect to the corresponding whole interactome (aStudent <i>t</i>-test, bMann-Whitney <i>U</i>-test).</p

Measures of subnetwork organization.

<p>(A, B) Clustering (<i>C</i>) and (C, D) modularity (<i>M</i>) coefficients for the subnetworks generated by the VRGs, contextualized in the TRN and PPIN. <i>Rand</i> indicates the average value for random subnetworks (100 replicates). NS denotes non-significant value following a one-tailed <i>z</i>-test. Horizontal dashed lines represent the cutoff value for statistical significance.</p

Phylogenetic relationships among viruses explain the similarities in gene expression.

<p>(A) Neighbor-joining dendrogram constructed using the similarity matrix computed from the lists of differentially expressed genes. Bootstrap support values are reported next to each node. (B) Maximum-likelihood phylogenetic tree constructed from the replicase genes of the seven RNA viruses included in the study. For CaLCuV, the Rep (replicase-associated protein) was used instead. The statistical quality of the different clusters was evaluated by bootstrap. Significance levels are shown next to each node.</p

Overview of the Systems Biology approach we followed to study the viral infection in plants.

<p>We considered <i>A. thaliana</i> as model host. Microarray data from several infection experiments with viruses were collected to analyze the differentially expressed genes, and to perform functional analyses by harnessing GO annotations. In addition, by taking advantage of large databases of expression profiles derived from transcriptional perturbations, the global regulatory network of the host could be as a first approach unveiled by applying learning algorithms. The differential expression was then contextualized within the inferred network.</p

List of viruses included in this study and some of their properties.

<p>List of viruses included in this study and some of their properties.</p

Functional analysis.

<p>(A) Over- and (B) under-expressed VRFs representing biological processes. In pallid red, VRFs present in at least five of the total eight viral infections (unspecific viral response); in pallid blue, VRFs in at least three of the four potyviral infections; in pallid green, VRFs in at least three of the four <i>Brassica</i>-infecting viral infections; in pallid yellow, common VRFs for <i>Potyvirus</i> and <i>Brassica</i>-infecting viruses.</p