825 research outputs found

    Using answer set programming to integrate RNA expression with signalling pathway information to infer how mutations affect ageing.

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    A challenge of systems biology is to integrate incomplete knowledge on pathways with existing experimental data sets and relate these to measured phenotypes. Research on ageing often generates such incomplete data, creating difficulties in integrating RNA expression with information about biological processes and the phenotypes of ageing, including longevity. Here, we develop a logic-based method that employs Answer Set Programming, and use it to infer signalling effects of genetic perturbations, based on a model of the insulin signalling pathway. We apply our method to RNA expression data from Drosophila mutants in the insulin pathway that alter lifespan, in a foxo dependent fashion. We use this information to deduce how the pathway influences lifespan in the mutant animals. We also develop a method for inferring the largest common sub-paths within each of our signalling predictions. Our comparisons reveal consistent homeostatic mechanisms across both long- and short-lived mutants. The transcriptional changes observed in each mutation usually provide negative feedback to signalling predicted for that mutation. We also identify an S6K-mediated feedback in two long-lived mutants that suggests a crosstalk between these pathways in mutants of the insulin pathway, in vivo. By formulating the problem as a logic-based theory in a qualitative fashion, we are able to use the efficient search facilities of Answer Set Programming, allowing us to explore larger pathways, combine molecular changes with pathways and phenotype and infer effects on signalling in in vivo, whole-organism, mutants, where direct signalling stimulation assays are difficult to perform. Our methods are available in the web-service NetEffects: http://www.ebi.ac.uk/thornton-srv/software/NetEffects

    Neurofly 2008 abstracts : the 12th European Drosophila neurobiology conference 6-10 September 2008 Wuerzburg, Germany

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    This volume consists of a collection of conference abstracts

    Exploiting gene expression and protein data for predicting remote homology and tissue specificity

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    In this thesis I describe my investigations of applying machine learning methods to high throughput experimental and predicted biological data. The importance of such analysis as a means of making inferences about biological functions is widely acknowledged in the bioinformatics community. Specifically, this work makes three novel contributions based on the systematic analysis of publicly archived data of protein sequences, three dimensional structures, gene expression and functional annotations: (a) remote homology detection based on amino acid sequences and secondary structures; (b) the analysis of tissue-specific gene expression for predictive signals in the sequence and secondary structure of the resulting protein product; and (c) a study of ageing in the fruit fly, a commonly used model organism, in which tissue specific and whole-organism gene expression changes are contrasted. In the problem of remote homology detection, a kernel-based method that combines pairwise alignment scores of amino acid sequences and secondary structures is shown to improve the prediction accuracies in a benchmark task defined using the Structural Classification of Proteins (SCOP) database. While the task of predicting SCOP superfamilies should be regarded as an easy one, with not much room for performance improvement, it is still widely accepted as the gold standard due to careful manual annotation by experts in the subject of protein evolution.A similar method is introduced to investigate whether tissue specificity of gene expression is correlated with the sequence and secondary structure of the resulting protein product. An information theoretic approach is adopted for sorting fruit fly and mouse genes according to their tissue specificity based on gene expression data. A classifier is then trained to predict the degree of specificity for these genes. The study concludes that the tissue specificity of gene expression is correlated with the sequence, and to a certain extent, with the secondary structure of the gene’s protein product.The sorted list of genes introduced in the previous chapter is used to investigate the tissue specificity of transcript profiles obtained from a study of ageing in the fruit fly. The same list is utilised to investigate how filtering tissue-restricted genes affects gene set enrichment analysis in the ageing study, and to examine the specificity of age-associated genes identified in the literature. The conclusion drawn in this chapter is that categorisation of genes according to their tissue specificity using Shannon’s information theory is useful for the interpretation of whole-fly gene expression data

    Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster

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    Aging affects almost all aspects of an organism -- its morphology, its physiology, its behavior. Isolating which biological mechanisms are regulating these changes, however, has proven difficult, potentially due to our inability to characterize the full repertoire of an animal's behavior across the lifespan. Using data from fruit flies (D. melanogaster) we measure the full repertoire of behaviors as a function of age. We observe a sexually dimorphic pattern of changes in the behavioral repertoire during aging. Although the stereotypy of the behaviors and the complexity of the repertoire overall remains relatively unchanged, we find evidence that the observed alterations in behavior can be explained by changing the fly's overall energy budget, suggesting potential connections between metabolism, aging, and behavior

    Evolutionary conservation of regulated longevity assurance mechanisms

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    Short abstract: A multi-level cross-species comparative analysis of gene-expression changes accompanying increased longevity in mutant nematodes, fruit flies and mice with reduced insulin/IGF-1 signaling revealed candidate conserved mechanisms

    Sexual Deprivation, Emotion, and Longevity: Neuropeptidergic Regulation of Aging in Drosophila

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    While researchers often focus on the brain as a victim of aging via neurodegenerative diseases, recent work has demonstrated that the aging process is regulated by neural mechanisms. Thus, we asked which mechanisms and inputs might be important for the brain to regulate aging. We found that in male Drosophila melanogaster, the costs of reproduction on survival are mediated entirely through perception of the opposite sex, and that mating itself is actually beneficial. These effects are mediated through distinct neural circuits, with neuropeptide F (npf, an NPY homolog) required for the negative effects of pheromones and corazonin (crz, a GnRH homolog) driving the beneficial effects of mating. dFoxo, a common mediator of aging, regulates these effects on aging through an insulin-independent mechanism. Investigation of the dynamics of the effects of pheromones on mortality revealed two hypotheses: either population mortality rates reverse as a result of heterogeneity in individual probabilities of death, or the effects of pheromones on mortality rates are reversible in individuals. By combining in vivo and in silico approaches, we revealed that both explanations are correct, with individual reversibility dominating dynamics early in life, and heterogeneity becoming important in middle-age. Using a more global approach, we examined the effects of manipulating 78 distinct subsets of neurons on lifespan, and identified specific brain structures that are of prime importance for modulating aging. One of these structures is home to neurons expressing diuretic hormone 44 (Dh44, a CRH homolog). Dh44 and one of its receptors, Dh44R1, modulate lifespan, likely through insulin-like signaling pathways. Furthermore, this effect of Dh44 on lifespan is independent of diet, a fact obtained in part using the Fly Liquid-food Interaction Counter (FLIC), a novel assay developed to continuously measure feeding behavior in individual flies. The evolutionarily conserved neural circuits identified herein link aging to neural states consistent with primitive emotions in Drosophila, and these mechanisms deserve further exploration for their potential to explain connections between stress, emotions, and health in humans.PHDMol & Integrtv Physiology PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144128/1/harvanek_1.pd

    An Extensive Empirical Comparison of Probabilistic Hierarchical Classifiers in Datasets of Ageing-Related Genes

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    This study comprehensively evaluates the performance of 5 types of probabilistic hierarchical classification methods used for predicting Gene Ontology (GO) terms related to ageing. Of those tested, a new hybrid of a Local Hierarchical Classifier (LHC) and the Predictive Clustering Tree algorithm (LHC-PCT) had the best predictive accuracy results. We also tested the impact of two types of variations in most hierarchical classification algorithms, namely: (a) changing the base algorithm (we tested Naive Bayes and Support Vector Machines), and the impact of (b) using or not the Correlation based Feature Selection (CFS) algorithm in a pre-processing step. In total, we evaluated the predictive performance of 17 variations of hierarchical classifiers across 15 datasets of ageing and longevityrelated genes. We conclude that the LHC-PCT algorithm ranks better across several tests (7 out of 12). In addition, we interpreted the models generated by the PCT algorithm to show how hierarchical classification algorithms can be used to extract biological insights out of the ageing-related datasets that we compiled

    Essential Physiological Differences Characterize Short- and Long-Lived Strains of Drosophila melanogaster

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    Aging is a multifactorial process which affects all animals. Aging as a result of damage accumulation is the most accepted explanation but the proximal causes remain to be elucidated. There is also evidence indicating that aging has an important genetic component. Animal species age at different rates and specific signaling pathways, such as insulin/insulin-like growth factor, can regulate life span of individuals within a species by reprogramming cells in response to environmental changes. Here, we use an unbiased approach to identify novel factors that regulate life span in Drosophila melanogaster. We compare the transcriptome and metabolome of two wild-type strains used widely in aging research: short-lived Dahomey and long-lived Oregon R flies. We found that Dahomey flies carry several traits associated with short-lived individuals and species such as increased lipoxidative stress, decreased mitochondrial gene expression, and increased Target of Rapamycin signaling. Dahomey flies also have upregulated octopamine signaling known to stimulate foraging behavior. Accordingly, we present evidence that increased foraging behavior, under laboratory conditions where nutrients are in excess increases damage generation and accelerates aging. In summary, we have identified several new pathways, which influence longevity highlighting the contribution and importance of the genetic component of aging.This work was supported by the European Research Council (260632 - ComplexI&Aging to A.S.); the Academy of Finland (252048 to A.S); the Biotechnology and Biological Sciences Research Council ( BB/M023311/1 to A.S.); the Centre for International Mobility (CIMO) (TM-12- 8391 and TM-13-8919 to N.G.); the Spanish Ministry of Economy and Competitiveness, Institute of Health Carlos III (PI14/00328 to R.P. and PI17/01286 to P.N.); the Autonomous Government of Catalonia (2017SGR696 and SLT002/16/00250 to R.P.); the Ministry of Education and Science of Ukraine (grant number 0117U006426 to O.L.); FEDER funds from the European Union (“A way to build Europe” to R.P.); and the Doctoral Programme in Medicine and Life Sciences of University of Tampere (to T.R). R.S is a Sir Henry Wellcome Postdoctoral Fellow funded by Wellcome (204715/Z/16/Z

    Genome-wide dFOXO targets and topology of the transcriptomic response to stress and insulin signalling

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    FoxO transcription factors, inhibited by insulin/insulin-like growth factor signalling (IIS), are crucial players in numerous organismal processes including lifespan. Using genomic tools, we uncover over 700 direct dFOXO targets in adult female Drosophila. dFOXO is directly required for transcription of several IIS components and interacting pathways, such as TOR, in the wild-type fly. The genomic locations occupied by dFOXO in adults are different from those observed in larvae or cultured cells. These locations remain unchanged upon activation by stresses or reduced IIS, but the binding is increased and additional targets activated upon genetic reduction in IIS. We identify the part of the IIS transcriptional response directly controlled by dFOXO and the indirect effects and show that parts of the transcriptional response to IIS reduction do not require dfoxo. Promoter analyses revealed GATA and other forkhead factors as candidate mediators of the indirect and dfoxoindependent effects. We demonstrate genome-wide evolutionary conservation of dFOXO targets between the fly and the worm Caenorhabditis elegans, enriched for a second tier of regulators including the dHR96/daf-12 nuclear hormone receptor. Molecular Systems Biology 7: 502; published online 21 June 2011; doi:10.1038/msb.2011.3

    A CellAgeClock for expedited discovery of anti-ageing compounds

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    We aim to improve anti-ageing drug discovery, currently achieved through laborious and lengthy longevity analysis. Recent studies demonstrated that the most accurate molecular method to measure human age is based on CpG methylation profiles, as exemplified by several epigenetics clocks that can accurately predict an individual’s age. Here, we developed CellAgeClock, a new epigenetic clock that measures subtle ageing changes in primary human cells in vitro . As such, it provides a unique tool to measure effects of relatively short pharmacological treatments on ageing. We validated the CellAgeClock against known longevity drugs such as rapamycin and trametinib. Moreover, we uncovered novel anti-ageing drugs, torin2 and Dactolisib (BEZ-235), demonstrating the value of our approach as a screening and discovery platform for anti-ageing strategies. The CellAgeClock outperforms other epigenetic clocks in measuring subtle ageing changes in primary human cells in culture. The tested drug treatments reduced senescence and other ageing markers, further consolidating our approach as a screening platform. Finally, we show that the novel anti-ageing drugs we uncovered in vitro , indeed increased longevity in vivo . Our method expands the scope of CpG methylation profiling from measuring human chronological and biological age from human samples in years, to accurately and rapidly detecting anti-ageing potential of drugs using human cells in vitro , providing a novel accelerated discovery platform to test sought after geroprotectors
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