Information theoretical quantification of cooperativity in signalling complexes

<p>Abstract</p> <p>Background</p> <p>Intra-cellular information exchange, propelled by cascades of interacting signalling proteins, is essential for the proper functioning and survival of cells. Now that the interactome of several organisms is being mapped and several structural mechanisms of cooperativity at the molecular level in proteins have been elucidated, the formalization of this fundamental quantity, i.e. information, in these very diverse biological contexts becomes feasible.</p> <p>Results</p> <p>We show here that Shannon's mutual information quantifies information in biological system and more specifically the cooperativity inherent to the assembly of macromolecular complexes. We show how protein complexes can be considered as particular instances of noisy communication channels. Further we show, using a portion of the p27 regulatory pathway, how classical equilibrium thermodynamic quantities such as binding affinities and chemical potentials can be used to quantify information exchange but also to determine engineering properties such as channel noise and channel capacity. As such, this information measure identifies and quantifies those protein concentrations that render the biochemical system most effective in switching between the active and inactive state of the intracellular process.</p> <p>Conclusion</p> <p>The proposed framework provides a new and original approach to analyse the effects of cooperativity in the assembly of macromolecular complexes. It shows the conditions, provided by the protein concentrations, for which a particular system acts most effectively, i.e. exchanges the most information. As such this framework opens the possibility of grasping biological qualities such as system sensitivity, robustness or plasticity directly in terms of their effect on information exchange. Although these parameters might also be derived using classical thermodynamic parameters, a recasting of biological signalling in terms of information exchange offers an alternative framework for visualising network cooperativity that might in some cases be more intuitive.</p

A model of estrogen-related gene expression reveals non-linear effects in transcriptional response to tamoxifen

SynthSys is a Centre for Integrative Systems Biology (CISB) funded by BBSRC and EPSRC, reference BB/D019621/1.Background: Estrogen receptors alpha (ER) are implicated in many types of female cancers, and are the common target for anti-cancer therapy using selective estrogen receptor modulators (SERMs, such as tamoxifen). However, cell-type specific and patient-to-patient variability in response to SERMs (from suppression to stimulation of cancer growth), as well as frequent emergence of drug resistance, represents a serious problem. The molecular processes behind mixed effects of SERMs remain poorly understood, and this strongly motivates application of systems approaches. In this work, we aimed to establish a mathematical model of ER-dependent gene expression to explore potential mechanisms underlying the variable actions of SERMs. Results: We developed an equilibrium model of ER binding with 17 beta-estradiol, tamoxifen and DNA, and linked it to a simple ODE model of ER-induced gene expression. The model was parameterised on the broad range of literature available experimental data, and provided a plausible mechanistic explanation for the dual agonism/antagonism action of tamoxifen in the reference cell line used for model calibration. To extend our conclusions to other cell types we ran global sensitivity analysis and explored model behaviour in the wide range of biologically plausible parameter values, including those found in cancer cells. Our findings suggest that transcriptional response to tamoxifen is controlled in a complex non-linear way by several key parameters, including ER expression level, hormone concentration, amount of ER-responsive genes and the capacity of ER-tamoxifen complexes to stimulate transcription (e. g. by recruiting co-regulators of transcription). The model revealed non-monotonic dependence of ER-induced transcriptional response on the expression level of ER, that was confirmed experimentally in four variants of the MCF-7 breast cancer cell line. Conclusions: We established a minimal mechanistic model of ER-dependent gene expression, that predicts complex non-linear effects in transcriptional response to tamoxifen in the broad range of biologically plausible parameter values. Our findings suggest that the outcome of a SERM's action is defined by several key components of cellular micro-environment, that may contribute to cell-type-specific effects of SERMs and justify the need for the development of combinatorial biomarkers for more accurate prediction of the efficacy of SERMs in specific cell types.Publisher PDFPeer reviewe

Ligand binding dynamics for pre-dimerised G protein-coupled receptor homodimers: Linear models and analytical solutions

Evidence suggests that many G protein-coupled receptors (GPCRs) are bound together forming dimers. The implications of dimerisation for cellular signalling outcomes, and ultimately drug discovery and therapeutics, remain unclear. Consideration of ligand binding and signalling via receptor dimers is therefore required as an addition to classical receptor theory, which is largely built on assumptions of monomeric receptors. A key factor in developing theoretical models of dimer signalling is cooperativity across the dimer, whereby binding of a ligand to one protomer affects the binding of a ligand to the other protomer. Here, we present and analyse linear models for one-ligand and two-ligand binding dynamics at homodimerised receptors, as an essential building block in the development of dimerised receptor theory. For systems at equilibrium, we compute analytical solutions for total bound labeled ligand, and derive conditions on the cooperativity factors underwhich multiphasic log-dose-response curves are expected. This could help explain data extracted from pharmacological experiments that does not fit to the standard Hill curves that are often used in this type of analysis. For the time-dependent problems, we also obtain analytical solutions. For the single-ligand case, the construction of the analytical solution is straightforward; it is bi-exponential in time, sharing a similar structure to the well known monomeric competition dynamics of Motulsky-Mahan. We suggest that this model is therefore practically usable by the pharmacologist towards developing insights into the potential dynamics and consequences of dimerised receptors

Regulatory Mechanisms of Bacterial Stress Responses

Bacterial growth and survival critically hinges on the ability to rapidly adapt to ever-changing environmental conditions. Elaborated stress response systems allow bacteria to sensitively detect and adequately respond to fluctuations in environmental conditions, such as pH, temperature, osmolarity, or the concentrations of nutrients and harmful substances. Often, bacterial stress responses towards a specific stressor involve multiple interconnected mechanisms - controlled by a sophisticated network involving signal-transduction cascades, metabolic pathways and gene expression regulation. In this thesis, bacterial stress responses towards two different environmental stressors are analysed; mainly focussing on the regulatory mechanisms that give rise to the overall cellular response. The first part of this thesis addresses the heme stress response in Corynebacterium glutamucim. Heme is an essential cofactor and alternative iron source for almost all bacterial species but can cause severe toxicity when present in elevated concentrations. Consequently, heme homeostasis needs to be tightly controlled. Therefore, one important challenge is to understand how bacteria regulate heme stress responses to both benefit from heme while simultaneously eliminating the associated toxicity. It is shown that C. glutamicum induces a heme detoxification mechanism (mediated via the heme exporter HrtBA) and a heme utilization mechanism (mediated via the heme ogygenase HmuO) in a temporal hierarchy, with prioritisation of detoxification over utilization. A combined approach of experimental reporter profiling and computational modelling reveals how differential biochemical properties of the two two-component systems that sense heme in C. glutamicum - ChrSA and HrrSA - and an additional regulator (the global iron-regulator DtxR) control this hierarchical expression of the two stress response modules. This analysis sheds light on the multi-layered heme stress response that contributes to overall heme homeostasis in C. glutamicum and adds on to the understanding of bacterial strategies to deal with the Janus-faced nature of heme. The second part of this thesis focusses on bacterial response strategies towards cell wall antibiotics, which play a key role in bacterial antibiotic resistance. To combat resistance evolution, it is important to understand how cell wall antibiotics affect bacterial cell wall biosynthesis and how bacteria orchestrate stress response mechanisms to protect themselves from cell wall damage. The first question is addressed through a comprehensive mathematical model describing the bacterial cell wall synthetic pathway - the lipid II cycle - and its systems-level behaviour under antibiotic treatment. It is found that the lipid II cycle features a highly asymmetric distribution of pathway intermediates and that the efficacy of antibiotics in vivo scales directly with the abundance of targeted pathway intermediates: The lower the relative abundance of a lipid II intermediate within the lipid II cycle, the lower the in vivo efficacy of an antibiotic targeting this intermediate. This leads to the formulation of a novel principle of ‘minimal target exposure’ as an intrinsic bacterial resistance mechanism and it is demonstrated that cooperativity in drug-target binding can mitigate the associated resistance. The development of new drugs to counteract antibiotic resistance clearly benefit from these insights. The second question is then addresses by an experimental-based expansion of the model, which allows the analysis of the interplay between multiple stress response mechanisms that protect against a single antibiotic - focussing here on the well-studied response of Bacillus subtilis towards the cell wall antibiotic bacitracin. This study reveals that the properties of the lipid II cycle itself control the interaction between the primary bacitracin stress response determinant BceAB mediating bacitracin detoxification, and the secondary determinant BcrC, which contributes to cell wall homeostasis under bacitracin treatment. By elucidating regulatory mechanisms of the multi-layered response towards bacitracin, this analysis contributes to an advanced understanding of bacterial antibiotic resistance

Bioinformatics and mathematical modelling in the study of receptor-receptor interactions and receptor oligomerization: focus on adenosine receptors.

none8sìThe concept of intra-membrane receptor-receptor interactions (RRIs) between different types of G protein-coupled receptors (GPCRs) and evidence for their existence was introduced by Agnati and Fuxe in 1980/81 through the biochemical analysis of the effects of neuropeptides on the binding characteristics of monoamine receptors in membrane preparations from discrete brain regions and functional studies of the interactions between neuropeptides and monoamines in the control of specific functions such as motor control and arterial blood pressure control in animal models. Whether GPCRs can form high-order structures is still a topic of an intense debate. Increasing evidence, however, suggests that the hypothesis of the existence of high-order receptor oligomers is correct. A fundamental consequence of the view describing GPCRs as interacting structures, with the likely formation at the plasma membrane of receptor aggregates of multiple receptors (Receptor Mosaics) is that it is no longer possible to describe signal transduction simply as the result of the binding of the chemical signal to its receptor, but rather as the result of a filtering/integration of chemical signals by the Receptor Mosaics (RMs) and membrane-associated proteins. Thus, in parallel with experimental research, significant efforts were spent in bioinformatics and mathematical modelling. We review here the main approaches that have been used to assess the interaction interfaces allowing the assembly of GPCRs and to shed some light on the integrative functions emerging from the complex behaviour of these RMs. Particular attention was paid to the RMs generated by adenosine A(2A), dopamine D-2, cannabinoid CB1, and metabotropic glutamate mGlu(5) receptors (A(2A). D-2, CB1, and mGlu(5), respectively), and a possible approach to model the interplay between the D-2-A(2A)-CB1 and D-2-A(2A)-mGlu(5) trimers is proposed. This article is part of a Special Issue entitled: "Adenosine Receptors". (C) 2010 Elsevier B.V. All rights reserved.openD. GUIDOLIN; F. CIRUELA; S. GENEDANI; M. GUESCINI; C. TORTORELLA; G. ALBERTIN; K. FUXE; L.F. AGNATID., Guidolin; F., Ciruela; S., Genedani; Guescini, Michele; C., Tortorella; G., Albertin; K., Fuxe; L. F., Agnat

Critical roles for EGFR and EGFR–HER2 clusters in EGF binding of SW620 human carcinoma cells

Epidermal growth factor (EGF) signalling regulates normal epithelial and other cell growth, with EGF receptor (EGFR) overexpression reported in many cancers. However, the role of EGFR clusters in cancer and their dependence on EGF binding is unclear. We present novel single-molecule total internal reflection fluorescence microscopy of (i) EGF and EGFR in living cancer cells, (ii) the action of anti-cancer drugs that separately target EGFR and human EGFR2 (HER2) on these cells and (iii) EGFR–HER2 interactions. We selected human epithelial SW620 carcinoma cells for their low level of native EGFR expression, for stable transfection with fluorescent protein labelled EGFR, and imaged these using single-molecule localization microscopy to quantify receptor architectures and dynamics upon EGF binding. Prior to EGF binding, we observe pre-formed EGFR clusters. Unexpectedly, clusters likely contain both EGFR and HER2, consistent with co-diffusion of EGFR and HER2 observed in a different model CHO-K1 cell line, whose stoichiometry increases following EGF binding. We observe a mean EGFR : EGF stoichiometry of approximately 4 : 1 for plasma membrane-colocalized EGFR–EGF that we can explain using novel time-dependent kinetics modelling, indicating preferential ligand binding to monomers. Our results may inform future cancer drug developments.journal articl

Contributions to mathematical pharmacology: new receptor theory with dimeric receptor models

Classical receptor theory is largely built on assumptions of monomeric receptors. In this thesis, we contribute to receptor theory by considering the now widely accepted cases of dimeric receptors. The implications of dimerisation for drug discovery and therapeutics remain unclear. Therefore, a theoretical consideration of ligand binding and signalling via receptor dimers is warranted. Here, we develop mathematical models for ligand bind-ing at dimerised and dimerising receptors. A key factor in developing these theoretical models is cooperativity across the dimer, whereby binding of a ligand to one protomer affects the binding of a ligand to the other protomer. The effects of cooperativity on binding dynamics are a primary point of interest.The first models we present focus on G protein-coupled receptors, where we assume that all receptors are pre-dimerised. Ligand binding models give linear systems of differ-ential equations which we use to analyse time course behaviours. At equilibrium, these models may exhibit multi-phasic log dose response curves, critically depending on co-operativity factors. When considering receptor activation, we see dose response curves that are indicative of non-standard ligand-receptor interactions, giving a quantitative and qualitative platform for analysing and interpreting data when dimers are suspected. A ligand induced model for vascular endothelial growth factor receptors is developed, whereby receptors exist constitutively as monomers and dimerise in response to ligand binding. The resulting nonlinear system of differential equations is investigated using numerical computations and perturbation methods. We see an excellent fit to published data, validating the model.The utility of our models in parameter estimation is explored theoretically using structural identifiability analysis. This determines which parameters can be theoretically estimated from fitting. This analysis is valuable but often overlooked when fitting to ligand-receptor interaction models. We explore the identifiability of some canonical lig-and binding models, and our dimer binding models, providing a tutorial and results to contribute to the receptor theory toolbox

Modeling Wnt/β-catenin target gene expression in APC and Wnt gradients under wild type and mutant conditions

The Wnt/β-catenin pathway is involved in the regulation of a multitude of physiological processes by controlling the differential expression of target genes. In certain tissues such as the adult liver, the Wnt/β-catenin pathway can attain different levels of activity due to gradients of Wnt ligands and/or intracellular pathway components like APC. How graded pathway activity is converted into regionally distinct patterns of Wnt/β-catenin target gene expression is largely unknown. Here, we apply a mathematical modeling approach to investigate the impact of different regulatory mechanisms on target gene expression within Wnt or APC concentration gradients. We develop a minimal model of Wnt/beta-catenin signal transduction and combine it with various mechanisms of target gene regulation. In particular, the effects of activation, inhibition, and an incoherent feedforward loop (iFFL) are compared. To specify activation kinetics, we analyze experimental data that quantify the response of β-catenin/TCF reporter constructs to different Wnt concentrations, and demonstrate that the induction of these constructs occurs in a cooperative manner with Hill coefficients between 2 and 5. In summary, our study shows that the combination of specific gene regulatory mechanisms with a time-independent gradient of Wnt or APC is sufficient to generate distinct target gene expression patterns as have been experimentally observed in liver. We find that cooperative gene activation in combination with a TCF feedback can establish sharp borders of target gene expression in Wnt or APC gradients. In contrast, the iFFL renders gene expression independent of gradients of the upstream signaling components. Our subsequent analysis of carcinogenic pathway mutations reveals that their impact on gene expression is determined by the gene regulatory mechanism and the APC concentration of the cell in which the mutation occurs