226 research outputs found

    Formation of regulatory modules by local sequence duplication

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    Turnover of regulatory sequence and function is an important part of molecular evolution. But what are the modes of sequence evolution leading to rapid formation and loss of regulatory sites? Here, we show that a large fraction of neighboring transcription factor binding sites in the fly genome have formed from a common sequence origin by local duplications. This mode of evolution is found to produce regulatory information: duplications can seed new sites in the neighborhood of existing sites. Duplicate seeds evolve subsequently by point mutations, often towards binding a different factor than their ancestral neighbor sites. These results are based on a statistical analysis of 346 cis-regulatory modules in the Drosophila melanogaster genome, and a comparison set of intergenic regulatory sequence in Saccharomyces cerevisiae. In fly regulatory modules, pairs of binding sites show significantly enhanced sequence similarity up to distances of about 50 bp. We analyze these data in terms of an evolutionary model with two distinct modes of site formation: (i) evolution from independent sequence origin and (ii) divergent evolution following duplication of a common ancestor sequence. Our results suggest that pervasive formation of binding sites by local sequence duplications distinguishes the complex regulatory architecture of higher eukaryotes from the simpler architecture of unicellular organisms

    Disorders of compulsivity: a common bias towards learning habits.

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    Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.This study was funded by the WT fellowship grant for VV (093705/Z/ 10/Z) and Cambridge NIHR Biomedical Research Centre. VV and NAH are Wellcome Trust (WT) intermediate Clinical Fellows. YW is supported by the Fyssen Fondation and MRC Studentships. PD is supported by the Gatsby Charitable Foundation. JEG has received grants from the National Institute of Drug Abuse and the National Center for Responsible Gaming. TWR and BJS are supported on a WT Programme Grant (089589/Z/09/Z). The BCNI is supported by a WT and MRC grant.This is the final published version. It's also available from Molecular Psychiatry at http://www.nature.com/mp/journal/vaop/ncurrent/full/mp201444a.html

    Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

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    One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution

    Valence-dependent influence of serotonin depletion on model-based choice strategy.

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    Human decision-making arises from both reflective and reflexive mechanisms, which underpin goal-directed and habitual behavioural control. Computationally, these two systems of behavioural control have been described by different learning algorithms, model-based and model-free learning, respectively. Here, we investigated the effect of diminished serotonin (5-hydroxytryptamine) neurotransmission using dietary tryptophan depletion (TD) in healthy volunteers on the performance of a two-stage decision-making task, which allows discrimination between model-free and model-based behavioural strategies. A novel version of the task was used, which not only examined choice balance for monetary reward but also for punishment (monetary loss). TD impaired goal-directed (model-based) behaviour in the reward condition, but promoted it under punishment. This effect on appetitive and aversive goal-directed behaviour is likely mediated by alteration of the average reward representation produced by TD, which is consistent with previous studies. Overall, the major implication of this study is that serotonin differentially affects goal-directed learning as a function of affective valence. These findings are relevant for a further understanding of psychiatric disorders associated with breakdown of goal-directed behavioural control such as obsessive-compulsive disorders or addictions.This research was funded by Wellcome Trust Grants awarded to VV (Intermediate WT Fellowship) and Programme Grant (089589/Z/09/Z) awarded to TWR, BJE, ACR, JWD and BJS. It was conducted at the Behavioural and Clinical Neuroscience Institute, which is supported by a joint award from the Medical Research Council and Wellcome Trust (G00001354). YW was supported by the Fyssen Foundation. SP is supported by Marie Curie Intra-European Fellowship (FP7-People-2012-IEF).This is the final version of the article. It first appeared from NPG via http://dx.doi.org/10.1038/mp.2015.4

    Rapid generation of human B-cell lymphomas via combined expression of Myc and Bcl2 and their use as a preclinical model for biological therapies

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    Although numerous mouse models of B-cell malignancy have been developed via the enforced expression of defined oncogenic lesions, the feasibility of generating lineage-defined human B-cell malignancies using mice reconstituted with modified human hematopoietic stem cells (HSCs) remains unclear. In fact, whether human cells can be transformed as readily as murine cells by simple oncogene combinations is a subject of considerable debate. Here, we describe the development of humanized mouse model of MYC/BCL2-driven ‘double-hit’ lymphoma. By engrafting human HSCs transduced with the oncogene combination into immunodeficient mice, we generate a fatal B malignancy with complete penetrance. This humanized-MYC/BCL2-model (hMB) accurately recapitulates the histopathological and clinical aspects of steroid-, chemotherapy- and rituximab-resistant human ‘double-hit’ lymphomas that involve the MYC and BCL2 loci. Notably, this model can serve as a platform for the evaluation of antibody-based therapeutics. As a proof of principle, we used this model to show that the anti-CD52 antibody alemtuzumab effectively eliminates lymphoma cells from the spleen, liver and peripheral blood, but not from the brain. The hMB humanized mouse model underscores the synergy of MYC and BCL2 in ‘double-hit’ lymphomas in human patients. Additionally, our findings highlight the utility of humanized mouse models in interrogating therapeutic approaches, particularly human-specific monoclonal antibodies.Kathy and Curt Marble Cancer Research FundSingapore-MIT Alliance for Research and TechnologyNational Institutes of Health (U.S.) (Grant R01-CA128803)Virginia and Daniel K. Ludwig Graduate FellowshipNational Institute of General Medical Sciences (U.S.) (Medical Scientist Training Program Grant T32GM007753)MIT School of Science (Cancer Research Fellowship

    Influence of the Stability of a Fused Protein and Its Distance to the Amyloidogenic Segment on Fibril Formation

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    Conversion of native proteins into amyloid fibrils is irreversible and therefore it is difficult to study the interdependence of conformational stability and fibrillation by thermodynamic analyses. Here we approached this problem by fusing amyloidogenic poly-alanine segments derived from the N-terminal domain of the nuclear poly (A) binding protein PABPN1 with a well studied, reversibly unfolding protein, CspB from Bacillus subtilis. Earlier studies had indicated that CspB could maintain its folded structure in fibrils, when it was separated from the amyloidogenic segment by a long linker. When CspB is directly fused with the amyloidogenic segment, it unfolds because its N-terminal chain region becomes integrated into the fibrillar core, as shown by protease mapping experiments. Spacers of either 3 or 16 residues between CspB and the amyloidogenic segment were not sufficient to prevent this loss of CspB structure. Since the low thermodynamic stability of CspB (ΔGD = 12.4 kJ/mol) might be responsible for unfolding and integration of CspB into fibrils, fusions with a CspB mutant with enhanced thermodynamic stability (ΔGD = 26.9 kJ/mol) were studied. This strongly stabilized CspB remained folded and prevented fibril formation in all fusions. Our data show that the conformational stability of a linked, independently structured protein domain can control fibril formation

    A Conserved Developmental Patterning Network Produces Quantitatively Different Output in Multiple Species of Drosophila

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    Differences in the level, timing, or location of gene expression can contribute to alternative phenotypes at the molecular and organismal level. Understanding the origins of expression differences is complicated by the fact that organismal morphology and gene regulatory networks could potentially vary even between closely related species. To assess the scope of such changes, we used high-resolution imaging methods to measure mRNA expression in blastoderm embryos of Drosophila yakuba and Drosophila pseudoobscura and assembled these data into cellular resolution atlases, where expression levels for 13 genes in the segmentation network are averaged into species-specific, cellular resolution morphological frameworks. We demonstrate that the blastoderm embryos of these species differ in their morphology in terms of size, shape, and number of nuclei. We present an approach to compare cellular gene expression patterns between species, while accounting for varying embryo morphology, and apply it to our data and an equivalent dataset for Drosophila melanogaster. Our analysis reveals that all individual genes differ quantitatively in their spatio-temporal expression patterns between these species, primarily in terms of their relative position and dynamics. Despite many small quantitative differences, cellular gene expression profiles for the whole set of genes examined are largely similar. This suggests that cell types at this stage of development are conserved, though they can differ in their relative position by up to 3–4 cell widths and in their relative proportion between species by as much as 5-fold. Quantitative differences in the dynamics and relative level of a subset of genes between corresponding cell types may reflect altered regulatory functions between species. Our results emphasize that transcriptional networks can diverge over short evolutionary timescales and that even small changes can lead to distinct output in terms of the placement and number of equivalent cells
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