167 research outputs found

    Cerebellum Transcriptome of Mice Bred for High Voluntary Activity Offers Insights into Locomotor Control and Reward-Dependent Behaviors.

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    The role of the cerebellum in motivation and addictive behaviors is less understood than that in control and coordination of movements. High running can be a self-rewarding behavior exhibiting addictive properties. Changes in the cerebellum transcriptional networks of mice from a line selectively bred for High voluntary running (H) were profiled relative to an unselected Control (C) line. The environmental modulation of these changes was assessed both in activity environments corresponding to 7 days of Free (F) access to running wheel and to Blocked (B) access on day 7. Overall, 457 genes exhibited a significant (FDR-adjusted P-value < 0.05) genotype-by-environment interaction effect, indicating that activity genotype differences in gene expression depend on environmental access to running. Among these genes, network analysis highlighted 6 genes (Nrgn, Drd2, Rxrg, Gda, Adora2a, and Rab40b) connected by their products that displayed opposite expression patterns in the activity genotype contrast within the B and F environments. The comparison of network expression topologies suggests that selection for high voluntary running is linked to a predominant dysregulation of hub genes in the F environment that enables running whereas a dysregulation of ancillary genes is favored in the B environment that blocks running. Genes associated with locomotor regulation, signaling pathways, reward-processing, goal-focused, and reward-dependent behaviors exhibited significant genotype-by-environment interaction (e.g. Pak6, Adora2a, Drd2, and Arhgap8). Neuropeptide genes including Adcyap1, Cck, Sst, Vgf, Npy, Nts, Penk, and Tac2 and related receptor genes also exhibited significant genotype-by-environment interaction. The majority of the 183 differentially expressed genes between activity genotypes (e.g. Drd1) were under-expressed in C relative to H genotypes and were also under-expressed in B relative to F environments. Our findings indicate that the high voluntary running mouse line studied is a helpful model for understanding the molecular mechanisms in the cerebellum that influence locomotor control and reward-dependent behaviors

    The ancient history of the structure of ribonuclease P and the early origins of Archaea

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    Towards the first linkage map of the Didymella rabiei genome.

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    A genetic map was developed for the ascomycete Didymella rabiei (Kovachevski) v. Arx (anamorph: Ascochyta rabiei Pass. Labr.), the causal agent of Ascochyta blight in chickpea (Cicer arietinum L.). The map was generated with 77 F1 progeny derived from crossing an isolate from the U.S.A. and an isolate from Syria. A total of 232 DAF (DNA AmplificationFingerprinting) primers and 37 STMS (Sequence-Tagged Microsatellite Site) primer pairs were tested for polymorphism between the parental isolates; 50 markers were mapped, 36 DAFs and 14 STMSs. These markers cover 261.4cM in ten linkage groups. Nineteen markers remained unlinked. Significant deviation from the expected 1:1 segregation ratios was observed for only two markers (Prob. of x2 <0.05). The implications of our results on ploidy level of the asexual spores are discussed

    Visual Network Analysis of Dynamic Metabolic Pathways

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    Abstract. We extend our previous work on the exploration of static metabolic networks to evolving, and therefore dynamic, pathways. We apply our visualization software to data from a simulation of early metabolism. Thereby, we show that our technique allows us to test and argue for or against different scenarios for the evolution of metabolic pathways. This supports a profound and efficient analysis of the structure and properties of the generated metabolic networks and its underlying components, while giving the user a vivid impression of the dynamics of the system. The analysis process is inspired by Ben Shneiderman’s mantra of information visualization. For the overview, user-defined diagrams give insight into topological changes of the graph as well as changes in the attribute set associated with the participating enzymes, substances and reactions. This way, “interesting features” in time as well as in space can be recognized. A linked view implementation enables the navigation into more detailed layers of perspective for in-depth analysis of individual network configuration

    The Impact of Oxygen on Metabolic Evolution: A Chemoinformatic Investigation

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    The appearance of planetary oxygen likely transformed the chemical and biochemical makeup of life and probably triggered episodes of organismal diversification. Here we use chemoinformatic methods to explore the impact of the rise of oxygen on metabolic evolution. We undertake a comprehensive comparative analysis of structures, chemical properties and chemical reactions of anaerobic and aerobic metabolites. The results indicate that aerobic metabolism has expanded the structural and chemical space of metabolites considerably, including the appearance of 130 novel molecular scaffolds. The molecular functions of these metabolites are mainly associated with derived aspects of cellular life, such as signal transfer, defense against biotic factors, and protection of organisms from oxidation. Moreover, aerobic metabolites are more hydrophobic and rigid than anaerobic compounds, suggesting they are better fit to modulate membrane functions and to serve as transmembrane signaling factors. Since higher organisms depend largely on sophisticated membrane-enabled functions and intercellular signaling systems, the metabolic developments brought about by oxygen benefit the diversity of cellular makeup and the complexity of cellular organization as well. These findings enhance our understanding of the molecular link between oxygen and evolution. They also show the significance of chemoinformatics in addressing basic biological questions

    Emergence of light-driven protometabolism on recruitment of a photocatalytic cofactor by a self-replicator

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    Establishing how life can emerge from inanimate matter is among the grand challenges of contemporary science. Chemical systems that capture life’s essential characteristics—replication, metabolism and compartmentalization—offer a route to understanding this momentous process. The synthesis of life, whether based on canonical biomolecules or fully synthetic molecules, requires the functional integration of these three characteristics. Here we show how a system of fully synthetic self-replicating molecules, on recruiting a cofactor, acquires the ability to transform thiols in its environment into disulfide precursors from which the molecules can replicate. The binding of replicator and cofactor enhances the activity of the latter in oxidizing thiols into disulfides through photoredox catalysis and thereby accelerates replication by increasing the availability of the disulfide precursors. This positive feedback marks the emergence of light-driven protometabolism in a system that bears no resemblance to canonical biochemistry and constitutes a major step towards the highly challenging aim of creating a new and completely synthetic form of life. [Figure not available: see fulltext.]

    Small Cofactors May Assist Protein Emergence from RNA World: Clues from RNA-Protein Complexes

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    It is now widely accepted that at an early stage in the evolution of life an RNA world arose, in which RNAs both served as the genetic material and catalyzed diverse biochemical reactions. Then, proteins have gradually replaced RNAs because of their superior catalytic properties in catalysis over time. Therefore, it is important to investigate how primitive functional proteins emerged from RNA world, which can shed light on the evolutionary pathway of life from RNA world to the modern world. In this work, we proposed that the emergence of most primitive functional proteins are assisted by the early primitive nucleotide cofactors, while only a minority are induced directly by RNAs based on the analysis of RNA-protein complexes. Furthermore, the present findings have significant implication for exploring the composition of primitive RNA, i.e., adenine base as principal building blocks
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