32 research outputs found

    Genetic landscape of common epilepsies: advancing towards precision in treatment

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    Epilepsy, a neurological disease characterized by recurrent seizures, is highly heterogeneous in nature. Based on the prevalence, epilepsy is classified into two types: common and rare epilepsies. Common epilepsies affecting nearly 95% people with epilepsy, comprise generalized epilepsy which encompass idiopathic generalized epilepsy like childhood absence epilepsy, juvenile myoclonic epilepsy, juvenile absence epilepsy and epilepsy with generalized tonic-clonic seizure on awakening and focal epilepsy like temporal lobe epilepsy and cryptogenic focal epilepsy. In 70% of the epilepsy cases, genetic factors are responsible either as single genetic variant in rare epilepsies or multiple genetic variants acting along with different environmental factors as in common epilepsies. Genetic testing and precision treatment have been developed for a few rare epilepsies and is lacking for common epilepsies due to their complex nature of inheritance. Precision medicine for common epilepsies require a panoramic approach that incorporates polygenic background and other non-genetic factors like microbiome, diet, age at disease onset, optimal time for treatment and other lifestyle factors which influence seizure threshold. This review aims to comprehensively present a state-of-art review of all the genes and their genetic variants that are associated with all common epilepsy subtypes. It also encompasses the basis of these genes in the epileptogenesis. Here, we discussed the current status of the common epilepsy genetics and address the clinical application so far on evidence-based markers in prognosis, diagnosis, and treatment management. In addition, we assessed the diagnostic predictability of a few genetic markers used for disease risk prediction in individuals. A combination of deeper endo-phenotyping including pharmaco-response data, electro-clinical imaging, and other clinical measurements along with genetics may be used to diagnose common epilepsies and this marks a step ahead in precision medicine in common epilepsies management

    Francisella tularensis Elicits IL-10 via a PGE2-Inducible Factor, to Drive Macrophage MARCH1 Expression and Class II Down-Regulation

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    Francisella tularensis is a bacterial pathogen that uses host-derived PGE2 to subvert the host's adaptive immune responses in multiple ways. Francisella-induced PGE2 acts directly on CD4 T cells to blunt production of IFN-Ξ³. Francisella-induced PGE2 can also elicit production of a >10 kDa soluble host factor termed FTMØSN (F. tularensis macrophage supernatant), which acts on IFN-Ξ³ pre-activated MØ to down-regulate MHC class II expression via a ubiquitin-dependent mechanism, blocking antigen presentation to CD4 T cells. Here, we report that FTMØSN-induced down-regulation of MØ class II is the result of the induction of MARCH1, and that MØ expressing MARCH1 β€œresistant” class II molecules are resistant to FTMØSN-induced class II down-regulation. Since PGE2 can induce IL-10 production and IL-10 is the only reported cytokine able to induce MARCH1 expression in monocytes and dendritic cells, these findings suggested that IL-10 is the active factor in FTMØSN. However, use of IL-10 knockout MØ established that IL-10 is not the active factor in FTMØSN, but rather that Francisella-elicited PGE2 drives production of a >10 kDa host factor distinct from IL-10. This factor then drives MØ IL-10 production to induce MARCH1 expression and the resultant class II down-regulation. Since many human pathogens such as Salmonella typhi, Mycobacterium tuberculosis and Legionella pneumophila also induce production of host PGE2, these results suggest that a yet-to-be-identified PGE2-inducible host factor capable of inducing IL-10 is central to the immune evasion mechanisms of multiple important human pathogens

    TLR2 Signaling Contributes to Rapid Inflammasome Activation during F. novicida Infection

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    Early detection of microorganisms by the innate immune system is provided by surface-expressed and endosomal pattern recognition receptors (PRRs) such as Toll-like receptors (TLRs). Detection of microbial components by TLRs initiates a signaling cascade leading to the expression of proinflammatory cytokines including IL-6 and IL-1Ξ². Some intracellular bacteria subvert the TLR response by rapidly escaping the phagosome and entering the cytosol. However, these bacteria may be recognized by the inflammasome, a multi-protein complex comprised of a sensor protein, ASC and the cysteine protease caspase-1. Inflammasome activation leads to release of the proinflammatory cytokines IL-1Ξ² and IL-18 and death of the infected cell, an important host defense that eliminates the pathogen's replicative niche. While TLRs and inflammasomes are critical for controlling bacterial infections, it is unknown whether these distinct host pathways cooperate to activate defenses against intracellular bacteria.Using the intracellular bacterium Francisella novicida as a model, we show that TLR2(-/-) macrophages exhibited delayed inflammasome activation compared to wild-type macrophages as measured by inflammasome assembly, caspase-1 activation, cell death and IL-18 release. TLR2 also contributed to inflammasome activation in response to infection by the cytosolic bacterium Listeria monocytogenes. Components of the TLR2 signaling pathway, MyD88 and NF-ΞΊB, were required for rapid inflammasome activation. Furthermore, TLR2(-/-) mice exhibited lower levels of cell death, caspase-1 activation, and IL-18 production than wild-type mice upon F. novicida infection.These results show that TLR2 is required for rapid inflammasome activation in response to infection by cytosolic bacterial pathogens. In addition to further characterizing the role of TLR2 in host defense, these findings broaden our understanding of how the host integrates signals from spatiotemporally separated PRRs to coordinate an innate response against intracellular bacteria

    RNA metabolism is the primary target of formamide in vivo

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    The synthesis, processing and function of coding and non-coding RNA molecules and their interacting proteins has been the focus of a great deal of research that has boosted our understanding of key molecular pathways that underlie higher order events such as cell cycle control, development, innate immune response and the occurrence of genetic diseases. In this study, we have found that formamide preferentially weakens RNA related processes in vivo. Using a non-essential Schizosaccharomyces pombe gene deletion collection, we identify deleted loci that make cells sensitive to formamide. Sensitive deletions are significantly enriched in genes involved in RNA metabolism. Accordingly, we find that previously known temperature-sensitive splicing mutants become lethal in the presence of the drug under permissive temperature. Furthermore, in a wild type background, splicing efficiency is decreased and R-loop formation is increased in the presence of formamide. In addition, we have also isolated 35 formamide-sensitive mutants, many of which display remarkable morphology and cell cycle defects potentially unveiling new players in the regulation of these processes. We conclude that formamide preferentially targets RNA related processes in vivo, probably by relaxing RNA secondary structures and/or RNA-protein interactions, and can be used as an effective tool to characterize these processes

    Host-Adaptation of Francisella tularensis Alters the Bacterium's Surface-Carbohydrates to Hinder Effectors of Innate and Adaptive Immunity

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    The gram-negative bacterium Francisella tularensis survives in arthropods, fresh water amoeba, and mammals with both intracellular and extracellular phases and could reasonably be expected to express distinct phenotypes in these environments. The presence of a capsule on this bacterium has been controversial with some groups finding such a structure while other groups report that no capsule could be identified. Previously we reported in vitro culture conditions for this bacterium which, in contrast to typical methods, yielded a bacterial phenotype that mimics that of the bacterium's mammalian, extracellular phase.SDS-PAGE and carbohydrate analysis of differentially-cultivated F. tularensis LVS revealed that bacteria displaying the host-adapted phenotype produce both longer polymers of LPS O-antigen (OAg) and additional HMW carbohydrates/glycoproteins that are reduced/absent in non-host-adapted bacteria. Analysis of wildtype and OAg-mutant bacteria indicated that the induced changes in surface carbohydrates involved both OAg and non-OAg species. To assess the impact of these HMW carbohydrates on the access of outer membrane constituents to antibody we used differentially-cultivated bacteria in vitro to immunoprecipitate antibodies directed against outer membrane moieties. We observed that the surface-carbohydrates induced during host-adaptation shield many outer membrane antigens from binding by antibody. Similar assays with normal mouse serum indicate that the induced HMW carbohydrates also impede complement deposition. Using an in vitro macrophage infection assay, we find that the bacterial HMW carbohydrate impedes TLR2-dependent, pro-inflammatory cytokine production by macrophages. Lastly we show that upon host-adaptation, the human-virulent strain, F. tularensis SchuS4 also induces capsule production with the effect of reducing macrophage-activation and accelerating tularemia pathogenesis in mice.F. tularensis undergoes host-adaptation which includes production of multiple capsular materials. These capsules impede recognition of bacterial outer membrane constituents by antibody, complement, and Toll-Like Receptor 2. These changes in the host-pathogen interface have profound implications for pathogenesis and vaccine development

    PLAS-20k: Extended Dataset of Protein-Ligand Affinities from MD Simulations for Machine Learning Applications

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    Abstract Computing binding affinities is of great importance in drug discovery pipeline and its prediction using advanced machine learning methods still remains a major challenge as the existing datasets and models do not consider the dynamic features of protein-ligand interactions. To this end, we have developed PLAS-20k dataset, an extension of previously developed PLAS-5k, with 97,500 independent simulations on a total of 19,500 different protein-ligand complexes. Our results show good correlation with the available experimental values, performing better than docking scores. This holds true even for a subset of ligands that follows Lipinski’s rule, and for diverse clusters of complex structures, thereby highlighting the importance of PLAS-20k dataset in developing new ML models. Along with this, our dataset is also beneficial in classifying strong and weak binders compared to docking. Further, OnionNet model has been retrained on PLAS-20k dataset and is provided as a baseline for the prediction of binding affinities. We believe that large-scale MD-based datasets along with trajectories will form new synergy, paving the way for accelerating drug discovery
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