66 research outputs found
Computational modelling of the regulation of Insulin signalling by oxidative stress
BACKGROUND: Existing models of insulin signalling focus on short term dynamics, rather than the longer term dynamics necessary to understand many physiologically relevant behaviours. We have developed a model of insulin signalling in rodent adipocytes that includes both transcriptional feedback through the Forkhead box type O (FOXO) transcription factor, and interaction with oxidative stress, in addition to the core pathway. In the model Reactive Oxygen Species are both generated endogenously and can be applied externally. They regulate signalling though inhibition of phosphatases and induction of the activity of Stress Activated Protein Kinases, which themselves modulate feedbacks to insulin signalling and FOXO. RESULTS: Insulin and oxidative stress combined produce a lower degree of activation of insulin signalling than insulin alone. Fasting (nutrient withdrawal) and weak oxidative stress upregulate antioxidant defences while stronger oxidative stress leads to a short term activation of insulin signalling but if prolonged can have other effects including degradation of the insulin receptor substrate (IRS1) and FOXO. At high insulin the protective effect of moderate oxidative stress may disappear. CONCLUSION: Our model is consistent with a wide range of experimental data, some of which is difficult to explain. Oxidative stress can have effects that are both up- and down-regulatory on insulin signalling. Our model therefore shows the complexity of the interaction between the two pathways and highlights the need for such integrated computational models to give insight into the dysregulation of insulin signalling along with more data at the individual level. A complete SBML model file can be downloaded from BIOMODELS (https://www.ebi.ac.uk/biomodels-main) with unique identifier MODEL1212210000. Other files and scripts are available as additional files with this journal article and can be downloaded from https://github.com/graham1034/Smith2012_insulin_signalling
TimiRGeN: R/Bioconductor package for time series microRNA-mRNA integration and analysis
Motivation: The analysis of longitudinal datasets and construction of gene regulatory networks (GRNs) provide a valuable means to disentangle the complexity of microRNA (miRNA)-mRNA interactions. However, there are no computational tools that can integrate, conduct functional analysis and generate detailed networks from longitudinal miRNA-mRNA datasets. Results: We present TimiRGeN, an R package that uses time point-based differential expression results to identify miRNA-mRNA interactions influencing signaling pathways of interest. miRNA-mRNA interactions can be visualized in R or exported to PathVisio or Cytoscape. The output can be used for hypothesis generation and directing in vitro or further in silico work such as GRN construction
Predominant Asymmetrical Stem Cell Fate Outcome Limits the Rate of Niche Succession in Human Colonic Crypts.
Stem cell (SC) dynamics within the human colorectal crypt SC niche remain poorly understood, with previous studies proposing divergent hypotheses on the predominant mode of SC self-renewal and the rate of SC replacement. Here we use age-related mitochondrial oxidative phosphorylation (OXPHOS) defects to trace clonal lineages within human colorectal crypts across the adult life-course. By resolving the frequency and size distribution of OXPHOS-deficient clones, quantitative analysis shows that, in common with mouse, long-term maintenance of the colonic epithelial crypt relies on stochastic SC loss and replacement mediated by competition for limited niche access. We find that the colonic crypt is maintained by ~5 effective SCs. However, with a SC loss/replacement rate estimated to be slower than once per year, our results indicate that the vast majority of individual SC divisions result in asymmetric fate outcome. These findings provide a quantitative platform to detect and study deviations from human colorectal crypt SC niche homeostasis during the process of colorectal carcinogenesis.Wellcome Trus
Explaining sex differences in lifespan in terms of optimal energy allocation in the baboon
Data from: Explaining sex differences in lifespan in terms of optimal energy allocation in the baboon
We provide a quantitative test of the hypothesis that sex role specialisation may account for sex differences in lifespan in baboons if such specialisation causes the dependency of fitness upon longevity, and consequently the optimal resolution to an energetic trade-off between somatic maintenance and other physiological functions, to differ between males and females. We present a model in which females provide all offspring care and males compete for access to reproductive females and in which the partitioning of available energy between the competing fitness-enhancing functions of growth, maintenance and reproduction is modelled as a dynamic behavioural game, with the optimal decision for each individual depending upon his/her state and the behaviour of other members of the population. Our model replicates the sexual dimorphism in body size and sex differences in longevity and reproductive scheduling seen in natural populations of baboons. We show that this outcome is generally robust to perturbations in model parameters, an important finding given the same behaviour is seen across multiple populations and species in the wild. This supports the idea that sex differences in longevity result from differences in the value of somatic maintenance relative to other fitness-enhancing functions in keeping with the disposable soma theory
Method for modelling, optimizing, parameterizing, testing and/or validating a dynamic network or network perturbations
Method for modelling, optimizing, parameterizing, testing and/or validating a dynamic network or network perturbations
The present invention relates to a method (2) for predicting the response of a structure (4), of a group of structures (16) and/or of a network profile (18), as a result to a perturbation, in particular by an agent (6) or a combination of agents (8) through modelling, optimizing, paramaterizing, testing and/or validating a dynamic network or network perturbations
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