Impact of limited solvent capacity on metabolic rate, enzyme activities, and metabolite concentrations of S. cerevisiae glycolysis

The cell's cytoplasm is crowded by its various molecular components, resulting in a limited solvent capacity for the allocation of new proteins, thus constraining various cellular processes such as metabolism. Here we study the impact of the limited solvent capacity constraint on the metabolic rate, enzyme activities, and metabolite concentrations using a computational model of Saccharomyces cerevisiae glycolysis as a case study. We show that given the limited solvent capacity constraint, the optimal enzyme activities and the metabolite concentrations necessary to achieve a maximum rate of glycolysis are in agreement with their experimentally measured values. Furthermore, the predicted maximum glycolytic rate determined by the solvent capacity constraint is close to that measured in vivo. These results indicate that the limited solvent capacity is a relevant constraint acting on S. cerevisiae at physiological growth conditions, and that a full kinetic model together with the limited solvent capacity constraint can be used to predict both metabolite concentrations and enzyme activities in vivo. © 2008 Vazquez et al

Carbon catabolite repression correlates with the maintenance of near invariant molecular crowding in proliferating E. coli cells

Background: Carbon catabolite repression (CCR) is critical for optimal bacterial growth, and in bacterial (and yeast) cells it leads to their selective consumption of a single substrate from a complex environment. However, the root cause(s) for the development of this regulatory mechanism is unknown. Previously, a flux balance model (FBAwMC) of Escherichia coli metabolism that takes into account the crowded intracellular milieu of the bacterial cell correctly predicted selective glucose uptake in a medium containing five different carbon sources, suggesting that CCR may be an adaptive mechanism that ensures optimal bacterial metabolic network activity for growth.Results: Here, we show that slowly growing E. coli cells do not display CCR in a mixed substrate culture and gradual activation of CCR correlates with an increasing rate of E. coli cell growth and proliferation. In contrast, CCR mutant cells do not achieve fast growth in mixed substrate culture, and display differences in their cell volume and density compared to wild-type cells. Analyses of transcriptome data from wt E. coli cells indicate the expected regulation of substrate uptake and metabolic pathway utilization upon growth rate change. We also find that forced transient increase of intracellular crowding or transient perturbation of CCR delay cell growth, the latter leading to associated cell density-and volume alterations.Conclusions: CCR is activated at an increased bacterial cell growth rate when it is required for optimal cell growth while intracellular macromolecular density is maintained within a narrow physiological range. In addition to CCR, there are likely to be other regulatory mechanisms of cell metabolism that have evolved to ensure optimal cell growth in the context of the fundamental biophysical constraint imposed by intracellular molecular crowding. © 2013 Zhou et al.; licensee BioMed Central Ltd

Cycle-centrality in complex networks

Networks are versatile representations of the interactions between entities in complex systems. Cycles on such networks represent feedback processes which play a central role in system dynamics. In this work, we introduce a measure of the importance of any individual cycle, as the fraction of the total information flow of the network passing through the cycle. This measure is computationally cheap, numerically well-conditioned, induces a centrality measure on arbitrary subgraphs and reduces to the eigenvector centrality on vertices. We demonstrate that this measure accurately reflects the impact of events on strategic ensembles of economic sectors, notably in the US economy. As a second example, we show that in the protein-interaction network of the plant Arabidopsis thaliana, a model based on cycle-centrality better accounts for pathogen activity than the state-of-art one. This translates into pathogen-targeted-proteins being concentrated in a small number of triads with high cycle-centrality. Algorithms for computing the centrality of cycles and subgraphs are available for download

Vascular endothelial growth factor (VEGF) upregulates BCL-2 and inhibits apoptosis in human and murine mammary adenocarcinoma cells

Tumour progression is regulated by the balance of proliferation and apoptosis in the tumour cell population. To date, the role of vascular endothelial growth factor (VEGF) in tumour growth has been attributed to the induction of angiogenesis. VEGF has been shown to be a survival factor for endothelial cells, preventing apoptosis by inducing Bcl-2 expression. In both murine (4T1) and human (MDA-MB-231) metastatic mammary carcinoma cell lines, we found that VEGF upregulated Bcl-2 expression and anti-VEGF antibodies reduced Bcl-2 expression. These alterations in Bcl-2 expression were reflected by the levels of tumour cell apoptosis. VEGF resulted in reduced tumour cell apoptosis, whereas its inhibition with anti-VEGF neutralizing antibodies induced apoptosis directly in tumour cells. Therefore, in addition to its role in angiogenesis and vessel permeability, VEGF acts as a survival factor for tumour cells, inducing Bcl-2 expression and inhibiting tumour cell apoptosis. © 2001 Cancer Research Campaign http://www.bjcancer.co

HiNO: An Approach for Inferring Hierarchical Organization from Regulatory Networks

BACKGROUND: Gene expression as governed by the interplay of the components of regulatory networks is indeed one of the most complex fundamental processes in biological systems. Although several methods have been published to unravel the hierarchical structure of regulatory networks, weaknesses such as the incorrect or inconsistent assignment of elements to their hierarchical levels, the incapability to cope with cyclic dependencies within the networks or the need for a manual curation to retrieve non-overlapping levels remain unsolved. METHODOLOGY/RESULTS: We developed HiNO as a significant improvement of the so-called breadth-first-search (BFS) method. While BFS is capable of determining the overall hierarchical structures from gene regulatory networks, it especially has problems solving feed-forward type of loops leading to conflicts within the level assignments. We resolved these problems by adding a recursive correction approach consisting of two steps. First each vertex is placed on the lowest level that this vertex and its regulating vertices are assigned to (downgrade procedure). Second, vertices are assigned to the next higher level (upgrade procedure) if they have successors with the same level assignment and have themselves no regulators. We evaluated HiNO by comparing it with the BFS method by applying them to the regulatory networks from Saccharomyces cerevisiae and Escherichia coli, respectively. The comparison shows clearly how conflicts in level assignment are resolved in HiNO in order to produce correct hierarchical structures even on the local levels in an automated fashion. CONCLUSIONS: We showed that the resolution of conflicting assignments clearly improves the BFS-method. While we restricted our analysis to gene regulatory networks, our approach is suitable to deal with any directed hierarchical networks structure such as the interaction of microRNAs or the action of non-coding RNAs in general. Furthermore we provide a user-friendly web-interface for HiNO that enables the extraction of the hierarchical structure of any directed regulatory network. AVAILABILITY: HiNO is freely accessible at http://mips.helmholtz-muenchen.de/hino/

Exploring the Free Energy Landscape: From Dynamics to Networks and Back

The knowledge of the Free Energy Landscape topology is the essential key to understand many biochemical processes. The determination of the conformers of a protein and their basins of attraction takes a central role for studying molecular isomerization reactions. In this work, we present a novel framework to unveil the features of a Free Energy Landscape answering questions such as how many meta-stable conformers are, how the hierarchical relationship among them is, or what the structure and kinetics of the transition paths are. Exploring the landscape by molecular dynamics simulations, the microscopic data of the trajectory are encoded into a Conformational Markov Network. The structure of this graph reveals the regions of the conformational space corresponding to the basins of attraction. In addition, handling the Conformational Markov Network, relevant kinetic magnitudes as dwell times or rate constants, and the hierarchical relationship among basins, complete the global picture of the landscape. We show the power of the analysis studying a toy model of a funnel-like potential and computing efficiently the conformers of a short peptide, the dialanine, paving the way to a systematic study of the Free Energy Landscape in large peptides.Comment: PLoS Computational Biology (in press

Reduced expression of BAX is associated with poor prognosis in patients with epithelial ovarian cancer: a multifactorial analysis of TP53, p21, BAX and BCL-2

Traditional clinicopathological features do not predict which patients will develop chemotherapy resistance. The TP53 gene is frequently altered in ovarian cancer but its prognostic implications are controversial. Little is known on the impact of TP53-downstream genes on prognosis. Using molecular and immunohistochemical analyses we examined TP53 and its downstream genes p21 BAX and BCL-2 in ovarian tumour tissues and have evaluated the results in relation to clinico-pathological parameters, clinical outcome and response to platinum-based chemotherapy. Associations of tested factors and patient and tumour characteristics were studied by Spearman rank correlation and Pearsons χ2 test. The Cox proportional hazard model was used for univariate and multivariate analysis. The associations of tested factors with response was tested using logistic regression analysis. TP53 mutation, p21 and BCL-2 expression were not associated with increased rates of progression and death. Expression of TP53 was associated with a shorter overall survival only (relative hazard rate [RHR] 2.01 P = 0.03). Interestingly, when combining TP53 mutation and expression data, this resulted in an increased association with overall survival (P = 0.008). BAX expression was found to be associated with both progression-free (RHR 0.44 P = 0.05) and overall survival (RHR 0.42 P = 0.03). Those patients who simultaneously expressed BAX and BCL-2 had a longer progression-free and overall survival compared to patients whose tumours did not express BCL-2 (P = 0.05 and 0.015 respectively). No relations were observed between tested factors and response to platinum-based chemotherapy. We conclude that BAX expression may represent a prognostic indicator for patients with ovarian cancer and that the combined evaluation of BAX and BCL-2 may provide additional prognostic significance.   http://www.bjcancer.com © 2001 Cancer Research Campaig

Extracting the abstraction pyramid from complex networks

<p>Abstract</p> <p>Background</p> <p>At present, the organization of system modules is typically limited to either a multilevel hierarchy that describes the "vertical" relationships between modules at different levels (e.g., module A at level two is included in module B at level one), or a single-level graph that represents the "horizontal" relationships among modules (e.g., genetic interactions between module A and module B). Both types of organizations fail to provide a broader and deeper view of the complex systems that arise from an integration of vertical and horizontal relationships.</p> <p>Results</p> <p>We propose a complex network analysis tool, Pyramabs, which was developed to integrate vertical and horizontal relationships and extract information at various granularities to create a pyramid from a complex system of interacting objects. The pyramid depicts the nested structure implied in a complex system, and shows the vertical relationships between abstract networks at different levels. In addition, at each level the abstract network of modules, which are connected by weighted links, represents the modules' horizontal relationships. We first tested Pyramabs on hierarchical random networks to verify its ability to find the module organization pre-embedded in the networks. We later tested it on a protein-protein interaction (PPI) network and a metabolic network. According to Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG), the vertical relationships identified from the PPI and metabolic pathways correctly characterized the <it>inclusion </it>(i.e., <it>part-of</it>) relationship, and the horizontal relationships provided a good indication of the functional closeness between modules. Our experiments with Pyramabs demonstrated its ability to perform knowledge mining in complex systems.</p> <p>Conclusions</p> <p>Networks are a flexible and convenient method of representing interactions in a complex system, and an increasing amount of information in real-world situations is described by complex networks. We considered the analysis of a complex network as an iterative process for extracting meaningful information at multiple granularities from a system of interacting objects. The quality of the interpretation of the networks depends on the completeness and expressiveness of the extracted knowledge representations. Pyramabs was designed to interpret a complex network through a disclosure of a pyramid of abstractions. The abstraction pyramid is a new knowledge representation that combines vertical and horizontal viewpoints at different degrees of abstraction. Interpretations in this form are more accurate and more meaningful than multilevel dendrograms or single-level graphs. Pyramabs can be accessed at <url>http://140.113.166.165/pyramabs.php/</url>.</p

Src tyrosine kinase augments taxotere-induced apoptosis through enhanced expression and phosphorylation of Bcl-2

Activation of Src, which has an intrinsic protein tyrosine kinase activity, has been demonstrated in many human tumours, such as colorectal and breast cancers, and is closely associated with the pathogenesis and metastatic potential of these cancers. In this study, we have examined the effect of activated Src on the sensitivity to taxotere, an anticancer drug targeting microtubules, using v-src-transfected HAG-1 human gall bladder epithelial cells. As compared with parental HAG-1 cell line, v-src-transfected HAG/src3-1 cells became 5.9 and 7.0-fold sensitive to taxotere for 2 and 24-h exposure, respectively. By contrast, HAG-1 cells transfected with activated Ras, which acts downstream of Src, acquired approximately 2.5∼4.8-fold taxotere resistance. The taxotere sensitivity in HAG/src3-1 cells was reversed, if not completely, by herbimycin A, a specific inhibitor of Src family protein tyrosine kinase, indicating that Src protein tyrosine kinase augments sensitivity to taxotere. Treatment of HAG/src3-1 cells with taxotere resulted in phosphorylation of Bcl-2 and subsequent induction of apoptotic cell death, whereas neither Bcl-2 phosphorylation nor apoptosis occurred in parental or c-H-ras-transfected HAG-1 cells. Interestingly, the Bcl-2 protein is overexpressed in v-src-transfected cell line, compared to those in parental or Ras-transfected cell line. Treatment of HAG/src3-1 cells with herbimycin A significantly reduced the expression and phosphorylation of Bcl-2, and abrogated taxotere-induced apoptosis, suggesting a potential role for Src protein tyrosine kinase in the taxotere-induced apoptotic events. H-7, a protein kinase C inhibitor and wortmannin, a phosphatidylinositol-3 kinase (PI-3 kinase) inhibitor, neither altered taxotere sensitivity nor inhibited taxotere-induced apoptosis in these cells. These data indicate that the ability of activated Src to increase taxotere sensitivity would be mediated by apoptotic events occurring through Src to downstream signal transduction pathways toward Bcl-2 phosphorylation, but not by activated Ras, PI-3 kinase or protein kinase C

Pilocarpine-Induced Status Epilepticus in Rats Involves Ischemic and Excitotoxic Mechanisms

The neuron loss characteristic of hippocampal sclerosis in temporal lobe epilepsy patients is thought to be the result of excitotoxic, rather than ischemic, injury. In this study, we assessed changes in vascular structure, gene expression, and the time course of neuronal degeneration in the cerebral cortex during the acute period after onset of pilocarpine-induced status epilepticus (SE). Immediately after 2 hr SE, the subgranular layers of somatosensory cortex exhibited a reduced vascular perfusion indicative of ischemia, whereas the immediately adjacent supragranular layers exhibited increased perfusion. Subgranular layers exhibited necrotic pathology, whereas the supergranular layers were characterized by a delayed (24 h after SE) degeneration apparently via programmed cell death. These results indicate that both excitotoxic and ischemic injuries occur during pilocarpine-induced SE. Both of these degenerative pathways, as well as the widespread and severe brain damage observed, should be considered when animal model-based data are compared to human pathology