672 research outputs found

    ResponseNet: revealing signaling and regulatory networks linking genetic transcriptomic screening data

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    Cellular response to stimuli is typically complex and involves both regulatory and metabolic processes. Large-scale experimental efforts to identify components of these processes often comprise of genetic screening and transcriptomic profiling assays. We previously established that in yeast genetic screens tend to identify response regulators, while transcriptomic profiling assays tend to identify components of metabolic processes. ResponseNet is a network-optimization approach that integrates the results from these assays with data of known molecular interactions. Specifically, ResponseNet identifies a high-probability sub-network, composed of signaling and regulatory molecular interaction paths, through which putative response regulators may lead to the measured transcriptomic changes. Computationally, this is achieved by formulating a minimum-cost flow optimization problem and solving it efficiently using linear programming tools. The ResponseNet web server offers a simple interface for applying ResponseNet. Users can upload weighted lists of proteins and genes and obtain a sparse, weighted, molecular interaction sub-network connecting their data. The predicted sub-network and its gene ontology enrichment analysis are presented graphically or as text. Consequently, the ResponseNet web server enables researchers that were previously limited to separate analysis of their distinct, large-scale experiments, to meaningfully integrate their data and substantially expand their understanding of the underlying cellular response. ResponseNet is available at http://bioinfo.bgu.ac.il/respnet.Seventh Framework Programme (European Commission) (FP7-PEOPLE-MCA-IRG)United States-Israel Binational Science Foundation (Grant 2009323

    Compounds from an Unbiased Chemical Screen Reverse Both Er-to-Golgi Trafficking Defects and Mitochondrial Dysfunction in Parkinson's Disease Models

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    α-Synuclein (α-syn) is a small lipid-binding protein involved in vesicle trafficking whose function is poorly characterized. It is of great interest to human biology and medicine because α-syn dysfunction is associated with several neurodegenerative disorders, including Parkinson’s disease (PD). We previously created a yeast model of α-syn pathobiology, which established vesicle trafficking as a process that is particularly sensitive to α-syn expression. We also uncovered a core group of proteins with diverse activities related to α-syn toxicity that is conserved from yeast to mammalian neurons. Here, we report that a yeast strain expressing a somewhat higher level of α-syn also exhibits strong defects in mitochondrial function. Unlike our previous strain, genetic suppression of endoplasmic reticulum (ER)-to-Golgi trafficking alone does not suppress α-syn toxicity in this strain. In an effort to identify individual compounds that could simultaneously rescue these apparently disparate pathological effects of α-syn, we screened a library of 115,000 compounds. We identified a class of small molecules that reduced α-syn toxicity at micromolar concentrations in this higher toxicity strain. These compounds reduced the formation of α-syn foci, re-established ER-to-Golgi trafficking and ameliorated α-syn-mediated damage to mitochondria. They also corrected the toxicity of α-syn in nematode neurons and in primary rat neuronal midbrain cultures. Remarkably, the compounds also protected neurons against rotenone-induced toxicity, which has been used to model the mitochondrial defects associated with PD in humans. That single compounds are capable of rescuing the diverse toxicities of α-syn in yeast and neurons suggests that they are acting on deeply rooted biological processes that connect these toxicities and have been conserved for a billion years of eukaryotic evolution. Thus, it seems possible to develop novel therapeutic strategies to simultaneously target the multiple pathological features of PD.MGH/MIT Morris Udall Center of Excellence in Parkinson Disease Research (NS038372)Michael J. Fox Foundation for Parkinson's ResearchHoward Hughes Medical InstituteUnited States. National Institutes of Health (NS049221)American Parkinson Disease Association, Inc

    CRISPR-Cas9 screens in human cells and primary neurons identify modifiers of C9ORF72 dipeptide-repeat-protein toxicity.

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    Hexanucleotide-repeat expansions in the C9ORF72 gene are the most common cause of amyotrophic lateral sclerosis and frontotemporal dementia (c9ALS/FTD). The nucleotide-repeat expansions are translated into dipeptide-repeat (DPR) proteins, which are aggregation prone and may contribute to neurodegeneration. We used the CRISPR-Cas9 system to perform genome-wide gene-knockout screens for suppressors and enhancers of C9ORF72 DPR toxicity in human cells. We validated hits by performing secondary CRISPR-Cas9 screens in primary mouse neurons. We uncovered potent modifiers of DPR toxicity whose gene products function in nucleocytoplasmic transport, the endoplasmic reticulum (ER), proteasome, RNA-processing pathways, and chromatin modification. One modifier, TMX2, modulated the ER-stress signature elicited by C9ORF72 DPRs in neurons and improved survival of human induced motor neurons from patients with C9ORF72 ALS. Together, our results demonstrate the promise of CRISPR-Cas9 screens in defining mechanisms of neurodegenerative diseases

    Ratings of age of acquisition of 299 words across 25 languages: Is there a cross-linguistic order of words?

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    We present a new set of subjective age-of-acquisition (AoA) ratings for 299 words (158 nouns, 141 verbs) in 25 languages from five language families (Afro-Asiatic: Semitic languages; Altaic: one Turkic language: Indo-European: Baltic, Celtic, Germanic, Hellenic, Slavic, and Romance languages; Niger-Congo: one Bantu language; Uralic: Finnic and Ugric languages). Adult native speakers reported the age at which they had learned each word. We present a comparison of the AoA ratings across all languages by contrasting them in pairs. This comparison shows a consistency in the orders of ratings across the 25 languages. The data were then analyzed (1) to ascertain how the demographic characteristics of the participants influenced AoA estimations and (2) to assess differences caused by the exact form of the target question (when did you learn vs. when do children learn this word); (3) to compare the ratings obtained in our study to those of previous studies; and (4) to assess the validity of our study by comparison with quasi-objective AoA norms derived from the MacArthur–Bates Communicative Development Inventories (MB-CDI). All 299 words were judged as being acquired early (mostly before the age of 6 years). AoA ratings were associated with the raters’ social or language status, but not with the raters’ age or education. Parents reported words as being learned earlier, and bilinguals reported learning them later. Estimations of the age at which children learn the words revealed significantly lower ratings of AoA. Finally, comparisons with previous AoA and MB-CDI norms support the validity of the present estimations. Our AoA ratings are available for research or other purposes

    The bottleneck may be the solution, not the problem

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    As a highly consequential biological trait, a memory \u201cbottleneck\u201d cannot escape selection pressures. It must therefore co-evolve with other cognitive mechanisms rather than act as an independent constraint. Recent theory and an implemented model of language acquisition suggest that a limit on working memory may evolve to help learning. Furthermore, it need not hamper the use of language for communication

    Evolution of defence portfolios in exploiter-victim systems

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    Some organisms maintain a battery of defensive strategies against their exploiters (predators, parasites or parasitoids), while others fail to employ a defence that seems obvious. In this paper, we shall investigate the circumstances under which defence strategies might be expected to evolve. Brood parasites and their hosts provide our main motivation, and we shall discuss why the reed warbler Acrocephalus scirpaceus has evolved an egg-rejection but not a chick-rejection strategy as a defence against the common (Eurasian) cuckoo Cuculus canorus, while the superb fairy-wren Malurus cyaneus has evolved a chick-rejection but not an egg-rejection strategy as a defence against Horsfield's bronze-cuckoo Chrysococcyx basalis. We suggest that the answers lie in strategy-blocking, where one strategy (the blocking strategy) prevents the appearance of another (the blocked strategy) that would be adaptive in its absence. This may be common in exploiter-victim systems. © 2006 Springer Science+Business Media, Inc

    Noun and verb knowledge in monolingual preschool children across 17 languages: Data from cross-linguistic lexical tasks (LITMUS-CLT)

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    This article investigates the cross-linguistic comparability of the newly developed lexical assessment tool Cross-linguistic Lexical Tasks (LITMUS-CLT). LITMUS-CLT is a part the Language Impairment Testing in Multilingual Settings (LITMUS) battery (Armon-Lotem, de Jong & Meir, 2015). Here we analyse results on receptive and expressive word knowledge tasks for nouns and verbs across 17 languages from eight different language families: Baltic (Lithuanian), Bantu (isiXhosa), Finnic (Finnish), Germanic (Afrikaans, British English, South African English, German, Luxembourgish, Norwegian, Swedish), Romance (Catalan, Italian), Semitic (Hebrew), Slavic (Polish, Serbian, Slovak) and Turkic (Turkish). The participants were 639 monolingual children aged 3;0-6;11 living in 15 different countries. Differences in vocabulary size were small between 16 of the languages; but isiXhosa-speaking children knew significantly fewer words than speakers of the other languages. There was a robust effect of word class: accuracy was higher for nouns than verbs. Furthermore, comprehension was more advanced than production. Results are discussed in the context of cross-linguistic comparisons of lexical development in monolingual and bilingual populations

    The Index-Based Subgraph Matching Algorithm (ISMA): Fast Subgraph Enumeration in Large Networks Using Optimized Search Trees

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    Subgraph matching algorithms are designed to find all instances of predefined subgraphs in a large graph or network and play an important role in the discovery and analysis of so-called network motifs, subgraph patterns which occur more often than expected by chance. We present the index-based subgraph matching algorithm (ISMA), a novel tree-based algorithm. ISMA realizes a speedup compared to existing algorithms by carefully selecting the order in which the nodes of a query subgraph are investigated. In order to achieve this, we developed a number of data structures and maximally exploited symmetry characteristics of the subgraph. We compared ISMA to a naive recursive tree-based algorithm and to a number of well-known subgraph matching algorithms. Our algorithm outperforms the other algorithms, especially on large networks and with large query subgraphs. An implementation of ISMA in Java is freely available at http://sourceforge.net/projects/isma
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