Now showing 1 - 10 of 48
  • Publication
    Evaluating Strategies to Normalise Biological Replicates of Western Blot Data
    Western blot data are widely used in quantitative applications such as statistical testing and mathematical modelling. To ensure accurate quantitation and comparability between experiments, Western blot replicates must be normalised, but it is unclear how the available methods affect statistical properties of the data. Here we evaluate three commonly used normalisation strategies: (i) by fixed normalisation point or control; (ii) by sum of all data points in a replicate; and (iii) by optimal alignment of the replicates. We consider how these different strategies affect the coefficient of variation (CV) and the results of hypothesis testing with the normalised data. Normalisation by fixed point tends to increase the mean CV of normalised data in a manner that naturally depends on the choice of the normalisation point. Thus, in the context of hypothesis testing, normalisation by fixed point reduces false positives and increases false negatives. Analysis of published experimental data shows that choosing normalisation points with low quantified intensities results in a high normalised data CV and should thus be avoided. Normalisation by sum or by optimal alignment redistributes the raw data uncertainty in a mean-dependent manner, reducing the CV of high intensity points and increasing the CV of low intensity points. This causes the effect of normalisations by sum or optimal alignment on hypothesis testing to depend on the mean of the data tested; for high intensity points, false positives are increased and false negatives are decreased, while for low intensity points, false positives are decreased and false negatives are increased. These results will aid users of Western blotting to choose a suitable normalisation strategy and also understand the implications of this normalisation for subsequent hypothesis testing.
      450Scopus© Citations 145
  • Publication
    Signalling mechanisms regulating phenotypic changes in breast cancer cells
    In MCF-7 breast cancer cells epidermal growth factor (EGF) induces cell proliferation, whereas heregulin (HRG)/neuregulin (NRG) induces irreversible phenotypic changes accompanied by lipid accumulation. Although these changes in breast cancer cells resemble processes that take place in the tissue, there is no understanding of signalling mechanisms regulating it. To identify molecular mechanisms mediating this cell-fate decision process, we applied different perturbations to pathways activated by these growth factors. The results demonstrate that phosphoinositide 3 (PI3) kinase (PI3K) and mammalian target of rapamycin (mTOR) complex (mTORC)1 activation is necessary for lipid accumulation that can also be induced by insulin, whereas stimulation of the extracellular-signal-regulated kinase (ERK) pathway is surprisingly dispensable. Interestingly, insulin exposure, as short as 4 h, was sufficient for triggering the lipid accumulation, whereas much longer treatment with HRG was required for achieving similar cellular response. Further, activation patterns of ATP citratelyase (ACLY), an enzyme playing a central role in linking glycolytic and lipogenic pathways, suggest that lipids accumulated within cells are produced de novo rather than absorbed from the environment. In the present study, we demonstrate that PI3K pathway regulates phenotypic changes in breast cancer cells, whereas signal intensity and duration is crucial for cell fate decisions and commitment. Our findings reveal that MCF-7 cell fate decisions are controlled by a network of positive and negative regulators of both signalling and metabolic pathways.
    Scopus© Citations 9  347
  • Publication
    Formation of Intracellular Concentration Landscapes by Multisite Protein Modification
    Multiple cellular proteins are covalently modified (e.g., phosphorylated/dephosphorylated) at several sites, which leads to diverse signaling activities. Here, we consider a signaling cascade that is activated at the plasma membrane and composed of two-site protein modification cycles, and we focus on the radial profile of the concentration landscapes created by different protein forms in the cytoplasm. We show that under proper conditions, the concentrations of modified proteins generate a series of peaks that propagate into the cell interior. Proteins modified at both sites form activity gradients with long plateaus that abruptly decay at successive locations along the path from the membrane to the nucleus. We demonstrate under what conditions signals generated at the membrane stall in the vicinity of that membrane or propagate into the cell. We derive analytical approximations for the main characteristics of the protein concentration profiles and demonstrate what we believe to be a novel steady-state pattern formation mechanism capable of generating precise spatial guidance for diverse cellular processes.
    Scopus© Citations 2  241
  • Publication
    Advances in dynamic modeling of colorectal cancer signaling-network regions, a path toward targeted therapies
    The interconnected network of pathways downstream of the TGFβ, WNT and EGF-families of receptor ligands play an important role in colorectal cancer pathogenesis. We studied and implemented dynamic simulations of multiple downstream pathways and described the section of the signaling network considered as a Molecular Interaction Map (MIM). Our simulations used Ordinary Differential Equations (ODEs), which involved 447 reactants and their interactions. Starting from an initial "physiologic condition", the model can be adapted to simulate individual pathologic cancer conditions implementing alterations/mutations in relevant onco-proteins. We verified some salient model predictions using the mutated colorectal cancer lines HCT116 and HT29. We measured the amount of MYC and CCND1 mRNAs and AKT and ERK phosphorylated proteins, in response to individual or combination onco-protein inhibitor treatments. Experimental and simulation results were well correlated. Recent independently published results were also predicted by our model. Even in the presence of an approximate and incomplete signaling network information, a predictive dynamic modeling seems already possible. An important long term road seems to be open and can be pursued further, by incremental steps, toward even larger and better parameterized MIMs. Personalized treatment strategies with rational associations of signaling-proteins inhibitors, could become a realistic goal.
    Scopus© Citations 16  307
  • Publication
    Ubiquitin chain specific auto-ubiquitination triggers sustained oscillation, bistable switches and excitable firing
    (Institution of Engineering and Technology, 2014-12) ; ; ;
    Ubiquitin modification of cellular proteins commonly targets them for proteosomal degradation, but can also convey non-proteolytic functions. Over the past years, advances in experimental approaches have helped uncover the extensive involvement of ubiquitination in protein regulation. However, our understanding of the dynamics of the ubiquitination-related networks have lagged behind. A common regulatory theme for many E3 ligases is the ability to self-catalyse their own ubiquitination without involving external E3 ligating enzymes. Here, the authors have explored computational models of both proteolytic and non-proteolytic auto-ubiquitination of E3 ligases and characterised the dynamic properties of these regulatory motifs. Remarkably, in both cases auto-ubiquitination coupled with multi-step de-ubiquitination process can bring about sustained oscillatory behaviour. In addition, the same basic wiring structures can trigger bistable switches of activity and excitable firing of the dynamic responses of the ubiquitinated E3 ligase. Bifurcation analysis allows one to derive parametric conditions that govern these dynamics. They also show that these complex non-linear behaviours persist for a more detailed mechanistic description that involves the E1 and E2 enzymes. Their work therefore provides new insights into the dynamic features of auto-ubiquitination in different cellular contexts.
      267Scopus© Citations 8
  • Publication
    Systems medicine: helping us understand the complexity of disease
    Advances in genomics and other -omic fields in the last decade have resulted in unprecedented volumes of complex data now being available. These data can enable physicians to provide their patients with care that is more personalized, predictive, preventive and participatory. The expertise required to manage and understand this data is to be found in fields outside of medical science, thus multidisciplinary collaboration coupled to a systems approach is key to unlocking its potential, with concomitant new ways of working. Systems medicine can build on the successes in the field of systems biology, recognizing the human body as the multidimensional network of networks that it is. While systems medicine can provide a conceptual and theoretical framework, its practical goal is to provide physicians the tools necessary for harnessing the rapid advances in basic biomedical science into their routine clinical arsenal.
    Scopus© Citations 28  315
  • Publication
    Competing to coordinate cell fate decisions: the MST2-Raf-1 signaling device
    How do biochemical signaling pathways generate biological specificity? This question is fundamental to modern biology, and its enigma has been accentuated by the discovery that most proteins in signaling networks serve multifunctional roles. An answer to this question may lie in analyzing network properties rather than individual traits of proteins in order to elucidate design principles of biochemical networks that enable biological decision-making. We discuss how this is achieved in the MST2/Hippo-Raf-1 signaling network with the help of mathematical modeling and model-based analysis, which showed that competing protein interactions with affinities controlled by dynamic protein modifications can function as Boolean computing devices that determine cell fate decisions. In addition, we discuss areas of interest for future research and highlight how systems approaches would be of benefit
    Scopus© Citations 23  308
  • Publication
    Signalling over a distance: gradient patterns and phosphorylation waves within single cells
    (Portland Press, 2010-10-01) ;
    Recent discoveries of phosphorylation gradients and microdomains with different protein activities have revolutionized our perception of information transfer within single cells. The different spatial localization of opposing reactions in protein-modification cycles has been shown to bring about heterogeneous stationary patterns and travelling waves of protein activities. We review spatial patterns and modes of signal transfer through phosphorylation/dephosphorylation and GDP/GTP exchange cycles and cascades. We show how switches between low-activity and high-activity states in a bistable activation–deactivation cycle can initiate the propagation of travelling protein-modification waves in the cytoplasm. Typically, an activation wave is initiated at the plasma membrane and propagates through the cytoplasm until it reaches the nucleus. An increase in deactivator activity is followed by the initiation of an inactivation wave that moves in the reverse direction from the nucleus. We show that the ratio of opposing enzyme rates is a key parameter that controls both the spread of activation through cascades and travelling waves.
    Scopus© Citations 21  384
  • Publication
    DYVIPAC: an integrated analysis and visualisation framework to probe multi-dimensional biological networks
    Biochemical networks are dynamic and multi-dimensional systems, consisting of tens or hundreds of molecular components. Diseases such as cancer commonly arise due to changes in the dynamics of signalling and gene regulatory networks caused by genetic alternations. Elucidating the network dynamics in health and disease is crucial to better understand the disease mechanisms and derive effective therapeutic strategies. However, current approaches to analyse and visualise systems dynamics can often provide only low-dimensional projections of the network dynamics, which often does not present the multi-dimensional picture of the system behaviour. More efficient and reliable methods for multi-dimensional systems analysis and visualisation are thus required. To address this issue, we here present an integrated analysis and visualisation framework for high-dimensional network behaviour which exploits the advantages provided by parallel coordinates graphs. We demonstrate the applicability of the framework, named “Dynamics Visualisation based on Parallel Coordinates” (DYVIPAC), to a variety of signalling networks ranging in topological wirings and dynamic properties. The framework was proved useful in acquiring an integrated understanding of systems behaviour.
    Scopus© Citations 19  244