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

ATM in focus:a damage sensor and cancer target

The ability of a cell to conserve and maintain its native DNA sequence is fundamental for the survival and normal functioning of the whole organism and protection from cancer development. Here we review recently obtained results and current topics concerning the role of the ataxia-telangiectasia mutated (ATM) protein kinase as a damage sensor and its potential as therapeutic target for treating cancer. This monograph discusses DNA repair mechanisms activated after DNA double-strand breaks (DSBs), i.e. non-homologous end joining, homologous recombination and single strand annealing and the role of ATM in the above types of repair. In addition to DNA repair, ATM participates in a diverse set of physiological processes involving metabolic regulation, oxidative stress, transcriptional modulation, protein degradation and cell proliferation. Full understanding of the complexity of ATM functions and the design of therapeutics that modulate its activity to combat diseases such as cancer necessitates parallel theoretical and experimental efforts. This could be best addressed by employing a systems biology approach, involving mathematical modelling of cell signalling pathways

Finding new edges:systems approaches to MTOR signaling

Cells have evolved highly intertwined kinase networks to finely tune cellular homeostasis to the environment. The network converging on the mechanistic target of rapamycin (MTOR) kinase constitutes a central hub that integrates metabolic signals and adapts cellular metabolism and functions to nutritional changes and stress. Feedforward and feedback loops, crosstalks and a plethora of modulators finely balance MTOR-driven anabolic and catabolic processes. This complexity renders it difficult - if not impossible - to intuitively decipher signaling dynamics and network topology. Over the last two decades, systems approaches have emerged as powerful tools to simulate signaling network dynamics and responses. In this review, we discuss the contribution of systems studies to the discovery of novel edges and modulators in the MTOR network in healthy cells and in disease

Identification of novel molecular signatures of IgA nephropathy through an integrative -omics analysis

IgA nephropathy (IgAN) is the most prevalent among primary glomerular diseases worldwide. Although our understanding of IgAN has advanced significantly, its underlying biology and potential drug targets are still unexplored. We investigated a combinatorial approach for the analysis of IgAN-relevant -omics data, aiming at identification of novel molecular signatures of the disease. Nine published urinary proteomics datasets were collected and the reported differentially expressed proteins in IgAN vs. healthy controls were integrated into known biological pathways. Proteins participating in these pathways were subjected to multi-step assessment, including investigation of IgAN transcriptomics datasets (Nephroseq database), their reported protein-protein interactions (STRING database), kidney tissue expression (Human Protein Atlas) and literature mining. Through this process, from an initial dataset of 232 proteins significantly associated with IgAN, 20 pathways were predicted, yielding 657 proteins for further analysis. Step-wise evaluation highlighted 20 proteins of possibly high relevance to IgAN and/or kidney disease. Experimental validation of 3 predicted relevant proteins, adenylyl cyclase-associated protein 1 (CAP1), SHC-transforming protein 1 (SHC1) and prolylcarboxypeptidase (PRCP) was performed by immunostaining of human kidney sections. Collectively, this study presents an integrative procedure for -omics data exploitation, giving rise to biologically relevant results

Dynamical models of the mammalian target of rapamycin network in ageing

Phd ThesisThe mammalian Target of Rapamycin (mTOR)kinase is a central regulator of cellular growth and metabolism and plays an important role in ageing and age- related diseases. The increase of invitro data collected to extend our knowledge on its regulation, and consequently improve drug intervention,has highlighted the complexity of the mTOR network. This complexity is also aggravated by the intrinsic time-dependent nature of cellular regulatory network cross-talks and feedbacks. Systems biology constitutes a powerful tool for mathematically for- malising biological networks and investigating such dynamical properties. The present work discusses the development of three dynamical models of the mTOR network. The first aimed at the analysis of the current literature-based hypotheses of mTOR Complex2(mTORC2)regulation. For each hypothesis, the model predicted specific differential dynamics which were systematically tested by invitro experiments. Surprisingly, nocurrent hypothesis could explain the data and a new hypothesis of mTORC2 activation was proposed.The second model extended the previous one with an AMPK module. In this study AMPK was reported to be activated by insulin. Using a hypothesis ranking approach based on model goodness-of-fit, AMPK activity was insilico predicted and in vitro tested to be activated by the insulin receptor substrate(IRS).Finally,the last model linked mTOR with the oxidative stress response, mitochondrial reg- ulation, DNA damage and FoxO transcription factors. This work provided the characterisation of a dynamical mechanism to explain the state transition from normal to senescent cells and their reversibility of the senescentphenotype.European Council 6FP NoE LifeSpan, School of the Faculty of Medical Sciences, Newcastle Universit

Computational biology for ageing

High-throughput genomic and proteomic technologies have generated a wealth of publicly available data on ageing. Easy access to these data, and their computational analysis, is of great importance in order to pinpoint the causes and effects of ageing. Here, we provide a description of the existing databases and computational tools on ageing that are available for researchers. We also describe the computational approaches to data interpretation in the field of ageing including gene expression, comparative and pathway analyses, and highlight the challenges for future developments. We review recent biological insights gained from applying bioinformatics methods to analyse and interpret ageing data in different organisms, tissues and conditions

The effects of graded levels of calorie restriction : II. Impact of short term calorie and protein restriction on circulating hormone levels, glucose homeostasis and oxidative stress in male C57BL/6 mice

This work was supported by BBSRC BB009953/1 awarded to JRS and SEM. PK and CD were funded by the Erasmus exchange programme. JRS, SEM, DD, CG, LC, JJDH, YW, DELP, DL and AD are members of the BBSRC China Partnership Award, BB/J020028/1.Peer reviewedPublisher PD

Mathematical Modelling of Metabolic Regulation in Aging

The underlying cellular mechanisms that characterize aging are complex and multifaceted. However, it is emerging that aging could be regulated by two distinct metabolic hubs. These hubs are the pathway defined by the mammalian target of rapamycin (mTOR) and that defined by the NAD+-dependent deacetylase enzyme, SIRT1. Recent experimental evidence suggests that there is crosstalk between these two important pathways; however, the mechanisms underpinning their interaction(s) remains poorly understood. In this review, we propose using computational modelling in tandem with experimentation to delineate the mechanism(s). We briefly discuss the main modelling frameworks that could be used to disentangle this relationship and present a reduced reaction pathway that could be modelled. We conclude by outlining the limitations of computational modelling and by discussing opportunities for future progress in this area

Modelling the molecular mechanisms of ageing

This document is the Accepted Manuscript version of a published work that appeared in final form in Bioscience reports. To access the final edited and published work see http://www.bioscirep.org/content/37/1/BSR20160177.The ageing process is driven at the cellular level by random molecular damage which slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the ageing process. The complexity of the ageing process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards, and discusses many specific examples of models which have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field

Metabolómica de linhas celulares: uma ferramenta para o estudo do envelhecimento

The world is aging and therefore it is essential to understand how the development of this process in organisms is, especially in human beings. Its knowing that this phenomenon does not occur in the same way in all individuals, and that there are some with a chronological age of 80 years and yet, they present a condition of a younger subject. Thus, it is essential to join efforts to understand this event. Currently, there are several models for the study of those process, from animal models, to computational or cellular models, with the latter having more advantages. Cell models, namely cell models of fibroblasts, are thus increasingly used for metabolomics research in the aging research since through these techniques we are able to indirectly study the pathways of this process, since this gives valuable insights into the composition of metabolites present in a sample. An approach that combines several of these tools, such as FTIR, MS or NMR, will be an asset and will allow for the study of aging at a molecular level and possible reveal new discoveries.O mundo está a envelhecer e, torna-se fundamental perceber como é o desenvolvimento desse processo nos organismos, principalmente nos seres humanos. É sabido que este fenómeno não ocorre da mesma forma em todos os indivíduos e que existem alguns com idade cronológica de 80 anos e, ainda assim, apresentam uma condição de um indivíduo mais jovem. Assim, é essencial unir esforços para entender este processo. Atualmente, existem vários modelos para o estudo do envelhecimento, desde modelos animais a modelos computacionais ou celulares, sendo que este último apresenta mais vantagens. Modelos celulares, nomeadamente, modelos celulares de fibroblastos são cada vez mais utilizados em metabolómica para a investigação do envelhecimento, pois através destas técnicas é possível estudar indiretamente as vias desse processo, uma vez que fornece informações valiosas sobre a composição dos metabolitos presentes numa amostra. Uma abordagem combinatória dessas ferramentas, como FTIR, MS ou NMR, constitui uma mais valia, permitirá o estudo do envelhecimento a um nível molecular e, possivelmente, revelará novas descobertas.Mestrado em Biomedicina Molecula