The Gammaherpesvirus m2 Protein Manipulates the Fyn/Vav Pathway through a Multidocking Mechanism of Assembly

To establish latent infections in B-cells, gammaherpesviruses express proteins in the infected B-cells of the host that spuriously activate signalling pathways located downstream of the B-cell receptor. One such protein is M2, a murine gammaherpesvirus 68-encoded molecule that activates the Vav1/Rac1 pathway via the formation of trimolecular complexes with Scr family members. Previous reports have shown that the formation of this heteromolecular complex involves interactions between a proline rich region of M2 and the Vav1 and Fyn SH3 domains. Here, we show that the optimal association of these proteins requires a second structural motif encompassing two tyrosine residues (Tyr120 and 129). These residues are inducibly phosphorylated by Fyn in non-hematopoietic cells and constitutively phosphorylated in B-cells. We also demonstrate that the phosphorylation of Tyr120 creates specific docking sites for the SH2 domains of both Vav1 and Fyn, a condition sine qua non for the optimal association of these two signalling proteins in vivo. Interestingly, signaling experiments indicate that the expression of M2 in B-cells promotes the tyrosine phosphorylation of Vav1 and additional signaling proteins, a biological process that requires the integrity of both the M2 phosphotyrosine and proline rich region motifs. By infecting mice with viruses mutated in the m2 locus, we show that the integrity of each of these two M2 docking motifs is essential for the early steps of murine gammaherpesvirus-68 latency. Taken together, these results indicate that the M2 phosphotyrosine motif and the previously described M2 proline rich region work in a concerted manner to manipulate the signaling machinery of the host B-cell

Sequence Variations of Latent Membrane Protein 2A in Epstein-Barr Virus-Associated Gastric Carcinomas from Guangzhou, Southern China

Latent membrane protein 2A (LMP2A), expressed in most Epstein-Barr virus (EBV)-associated malignancies, has been demonstrated to be responsible for the maintenance of latent infection and epithelial cell transformation. Besides, it could also act as the target for a CTL-based therapy for EBV-associated malignancies. In the present study, sequence variations of LMP2A in EBV-associated gastric carcinoma (EBVaGC) and healthy EBV carriers from Guangzhou, southern China, where nasopharyngeal carcinoma (NPC) is endemic, were investigated. Widespread sequence variations in the LMP2A gene were found, with no sequence identical to the B95.8 prototype. No consistent mutation was detected in all isolates. The immunoreceptor tyrosine-based activation motif (ITAM) and PY motifs in the amino terminus of LMP2A were strictly conserved, suggesting their important roles in virus infection; while 8 of the 17 identified CTL epitopes in the transmembrane region of LMP2A were affected by at least one point mutation, which may implicate that the effect of LMP2A polymorphisms should be considered when LMP2A-targeted immunotherapy is conducted. The polymorphisms of LMP2A in EBVaGC in gastric remnant carcinoma (GRC) were for the first time investigated in the world. The LMP2A sequence variations in EBVaGC in GRC were somewhat different from those in EBVaGC in conventional gastric carcinoma. The sequence variations of LMP2A in EBVaGC were similar to those in throat washing of healthy EBV carriers, indicating that these variations are due to geographic-associated polymorphisms rather than EBVaGC-associated mutations. This, to our best knowledge, is the first detailed investigation of LMP2A polymorphisms in EBVaGC in Guangzhou, southern China, where NPC is endemic

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Genetic and Environmental Etiology of Nicotine Use in Sri Lankan Male Twins

Little is known about the prevalence and etiology of tobacco use in Asian populations. This study aims to test whether the finding of substantial heritability for tobacco-related phenotypes in Western populations is generalizable to developing countries. The twin method was used to estimate the relative contribution of genetic and environmental influences on nicotine-related phenotypes. Participants were selected from the population based Sri Lankan Twin Registry. The Composite International Diagnostic Interview was administered to 1804 male individuals to assess five phenotypes: nicotine use; desire and unsuccessful attempts to quit smoking; subjective feeling of being tobacco dependent; and two DSM-IV diagnoses; nicotine dependence and nicotine withdrawal. Almost one third of the male twins were life-time smokers. The genetic results were consistent with the previously reported findings from Western and Chinese populations, in that the nicotine use traits were significantly heritable, with environmental influences being of the non-shared nature. The results derived from the Causal Contingent Common pathway model (CCC) supported previous findings that show that liabilities to regular smoking and subsequent problem smoking have both shared and specific genetic influences