Sensitivity dependent model of protein-protein interaction networks

The scale free structure p(k)~k^{-gamma} of protein-protein interaction networks can be reproduced by a static physical model in simulation. We inspect the model theoretically, and find the key reason for the model to generate apparent scale free degree distributions. This explanation provides a generic mechanism of "scale free" networks. Moreover, we predict the dependence of gamma on experimental protein concentrations or other sensitivity factors in detecting interactions, and find experimental evidence to support the prediction.Comment: organization improved, and experimental evidence of predicted dependence on sensitivity is addresse

Consequences of local gauge symmetry in empirical tight-binding theory

A method for incorporating electromagnetic fields into empirical tight-binding theory is derived from the principle of local gauge symmetry. Gauge invariance is shown to be incompatible with empirical tight-binding theory unless a representation exists in which the coordinate operator is diagonal. The present approach takes this basis as fundamental and uses group theory to construct symmetrized linear combinations of discrete coordinate eigenkets. This produces orthogonal atomic-like "orbitals" that may be used as a tight-binding basis. The coordinate matrix in the latter basis includes intra-atomic matrix elements between different orbitals on the same atom. Lattice gauge theory is then used to define discrete electromagnetic fields and their interaction with electrons. Local gauge symmetry is shown to impose strong restrictions limiting the range of the Hamiltonian in the coordinate basis. The theory is applied to the semiconductors Ge and Si, for which it is shown that a basis of 15 orbitals per atom provides a satisfactory description of the valence bands and the lowest conduction bands. Calculations of the dielectric function demonstrate that this model yields an accurate joint density of states, but underestimates the oscillator strength by about 20% in comparison to a nonlocal empirical pseudopotential calculation.Comment: 23 pages, 7 figures, RevTeX4; submitted to Phys. Rev.

An integrated mathematical model of cellular cholesterol biosynthesis and lipoprotein metabolism

Cholesterol regulation is an important aspect of human health. In this work we bring together and extend two recent mathematical models describing cholesterol biosynthesis and lipoprotein endocytosis to create an integrated model of lipoprotein metabolism in the context of a single hepatocyte. The integrated model includes a description of low density lipoprotein (LDL) receptor and cholesterol synthesis, delipidation of very low density lipoproteins (VLDLs) to LDLs and subsequent lipoprotein endocytosis. Model analysis shows that cholesterol biosynthesis produces the majority of intracellular cholesterol. The availability of free receptors does not greatly effect the concentration of intracellular cholesterol, but has a detrimental effect on extracellular VLDL and LDL levels. We test our model by considering its ability to reproduce the known biology of Familial Hypercholesterolaemia and statin therapy. In each case the model reproduces the known biological behaviour. Quantitative differences in response to statin therapy are discussed in the context of the need to extend the work to a more {\it in vivo} setting via the incorporation of more dietary lipoprotein related processes and the need for further testing and parameterisation of {\it in silico} models of lipoprotein metabolism

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

Quantitative functional interrelations within the cis-regulatory system of the S. purpuratus Endo16 gene

Embryonic expression of the Endo16 gene of Strongylocentrotus purpuratus is controlled by interactions with at least 13 different DNA-binding factors. These interactions occur within a cis-regulatory domain that extends about 2300 bp upstream from the transcription start site. A recent functional characterization of this domain reveals six different subregions, or cis-regulatory modules, each of which displays a specific regulatory subfunction when linked with the basal promoter and in some cases various other modules (C.-H. Yuh and E. Davidson (1996) Development 122, 1069-1082). In the present work, we analyzed quantitative time-course measurements of the CAT enzyme output of embryos bearing expression constructs controlled by various Endo16 regulatory modules, either singly or in combination. Three of these modules function positively in that, in isolation, each is capable of promoting expression in vegetal plate and adjacent cell lineages, though with different temporal profiles of activity. Models for the mode of interaction of the three positive modules with one another were tested by assuming mathematical relations that would generate, from the measured single module time courses, the experimentally observed profiles of activity obtained when the relevant modules are physically linked in the same construct. The generated and observed time functions were compared, and the differences were minimized by least squares adjustment of a scale parameter. When the modules were tested in context of the endogenous promoter region, one of the positive modules (A) was found to increase the output of the others (B and G), by a constant factor. In contrast, a solution in which the time-course data of modules A and B are multiplied by one another was required for the interrelations of the positive modules when a minimal SV40 promoter was used. One interpretation is that, in this construct, each module independently stimulates the basal transcription complex. We used a similar approach to analyze the repressive activity of the three Endo16 cis-regulatory modules that act negatively in controlling spatial expression. The evidence obtained confirms that the repressive modules act only by affecting the output of module A (C.-H. Yuh and E. Davidson (1996) Development 122, 1069-1082). A new hierarchical model of the cis-regulatory system was formulated in which module A plays a central integrating role, and which also implies specific functions for certain DNA-binding sites within the basal promoter fragment of the gene. Additional kinetic experiments were then carried out, and key aspects of the model were confirmed

Vibrational temperature of the adlayer in "hot atom" reaction mechanism

Hot-atoms reactions mechanisms bring about reaction rates which are several orders of magnitude higher than those expected in the case of ad-atoms which have thermalized with the surface. This paper addresses the issue of a possible thermodynamic characterization of the adlayer under reactive conditions and at the steady state. In turn, this implies to tackle the question of determining the temperature of the ad-atoms. This is done by means of a nonequilibrium statistical thermodynamic approach, by exploiting a suitable definition of the entropy. The interplay between reaction rate, vibrational temperature of the ad-atoms and adsorbed quantities is highlighted. It is shown that the vibrational temperature depends on reaction rate logarithmically and exhibits a non-linear scaling on physical quantities linked to the energetics of the reaction, namely the adsorption energy and the binding energy of the molecule. The present modeling is also discussed in connection with response equations of nonequilibrium thermodynamics.Comment: 29 pages, 8 figure

Dynamic GATA4 enhancers shape the chromatin landscape central to heart development and disease.

How stage-specific enhancer dynamics modulate gene expression patterns essential for organ development, homeostasis and disease is not well understood. Here, we addressed this question by mapping chromatin occupancy of GATA4--a master cardiac transcription factor--in heart development and disease. We find that GATA4 binds and participates in establishing active chromatin regions by stimulating H3K27ac deposition, which facilitates GATA4-driven gene expression. GATA4 chromatin occupancy changes markedly between fetal and adult heart, with a limited binding sites overlap. Cardiac stress restored GATA4 occupancy to a subset of fetal sites, but many stress-associated GATA4 binding sites localized to loci not occupied by GATA4 during normal heart development. Collectively, our data show that dynamic, context-specific transcription factors occupancy underlies stage-specific events in development, homeostasis and disease

Consensus clustering and functional interpretation of gene-expression data

Microarray analysis using clustering algorithms can suffer from lack of inter-method consistency in assigning related gene-expression profiles to clusters. Obtaining a consensus set of clusters from a number of clustering methods should improve confidence in gene-expression analysis. Here we introduce consensus clustering, which provides such an advantage. When coupled with a statistically based gene functional analysis, our method allowed the identification of novel genes regulated by NFκB and the unfolded protein response in certain B-cell lymphomas