Publications by authors named "Shimshi Atar"

Viral genomes not only code the protein content, but also include silent, overlapping codes which are important to the regulation of the viral life cycle and affect its evolution. Due to the high density of these codes, their non-modular nature and the complex intracellular processes they encode, the ability of current approaches to decipher them is very limited. We describe the first computational-experimental pipeline for studying the effects of viral silent and non-silent information on its fitness.

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Motivation: Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species.

Results: To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii.

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Motivation: The COP9 signalosome is a highly conserved multi-protein complex consisting of eight subunits, which influences key developmental pathways through its regulation of protein stability and transcription. In Arabidopsis thaliana, mutations in the COP9 signalosome exhibit a number of diverse pleiotropic phenotypes. Total or partial loss of COP9 signalosome function in Arabidopsis leads to misregulation of a number of genes involved in DNA methylation, suggesting that part of the pleiotropic phenotype is due to global effects on DNA methylation.

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Background: Synthetic virology is an important multidisciplinary scientific field, with emerging applications in biotechnology and medicine, aiming at developing methods to generate and engineer synthetic viruses. In particular, many of the RNA viruses, including among others the Dengue and Zika, are widespread pathogens of significant importance to human health. The ability to design and synthesize such viruses may contribute to exploring novel approaches for developing vaccines and virus based therapies.

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Various species of microalgae have recently emerged as promising host-organisms for use in biotechnology industries due to their unique properties. These include efficient conversion of sunlight into organic compounds, the ability to grow in extreme conditions and the occurrence of numerous post-translational modification pathways. However, the inability to obtain high levels of nuclear heterologous gene expression in microalgae hinders the development of the entire field.

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Deducing generic causal relations between RNA transcript features and protein expression profiles from endogenous gene expression data remains a major unsolved problem in biology. The analysis of gene expression from heterologous genes contributes significantly to solving this problem, but has been heavily biased toward the study of the effect of 5' transcript regions and to prokaryotes. Here, we employ a synthetic biology driven approach that systematically differentiates the effect of different regions of the transcript on gene expression up to 240 nucleotides into the ORF.

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The COP9 signalosome protein complex has a central role in the regulation of development of multicellular organisms. While the function of this complex in ubiquitin-mediated protein degradation is well established, results over the past few years have hinted that the COP9 signalosome may function more broadly in the regulation of gene expression. Here, using DamID technology, we show that COP9 signalosome subunit 7 functionally associates with a large number of genomic loci in the Drosophila genome, and show that the expression of many genes within these loci is COP9 signalosome-dependent.

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Multiple sclerosis (MS) is a central nervous system autoimmune inflammatory T-cell-mediated disease with a relapsing-remitting course in the majority of patients. In this study, we performed a high-resolution systems biology analysis of gene expression and physical interactions in MS relapse and remission. To this end, we integrated 164 large-scale measurements of gene expression in peripheral blood mononuclear cells of MS patients in relapse or remission and healthy subjects, with large-scale information about the physical interactions between these genes obtained from public databases.

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