Structural and functional analysis of cellular networks with CellNetAnalyzer

BACKGROUND: Mathematical modelling of cellular networks is an integral part of Systems Biology and requires appropriate software tools. An important class of methods in Systems Biology deals with structural or topological (parameter-free) analysis of cellular networks. So far, software tools providing such methods for both mass-flow (metabolic) as well as signal-flow (signalling and regulatory) networks are lacking. RESULTS: Herein we introduce CellNetAnalyzer, a toolbox for MATLAB facilitating, in an interactive and visual manner, a comprehensive structural analysis of metabolic, signalling and regulatory networks. The particular strengths of CellNetAnalyzer are methods for functional network analysis, i.e. for characterising functional states, for detecting functional dependencies, for identifying intervention strategies, or for giving qualitative predictions on the effects of perturbations. CellNetAnalyzer extends its predecessor FluxAnalyzer (originally developed for metabolic network and pathway analysis) by a new modelling framework for examining signal-flow networks. Two of the novel methods implemented in CellNetAnalyzer are discussed in more detail regarding algorithmic issues and applications: the computation and analysis (i) of shortest positive and shortest negative paths and circuits in interaction graphs and (ii) of minimal intervention sets in logical networks. CONCLUSION: CellNetAnalyzer provides a single suite to perform structural and qualitative analysis of both mass-flow- and signal-flow-based cellular networks in a user-friendly environment. It provides a large toolbox with various, partially unique, functions and algorithms for functional network analysis.CellNetAnalyzer is freely available for academic use

Human cerebrovascular contractile receptors are upregulated via a B-Raf/MEK/ERK-sensitive signaling pathway

<p>Abstract</p> <p>Background</p> <p>Cerebral ischemia results in a rapid increase in contractile cerebrovascular receptors, such as the 5-hydroxytryptamine type 1B (5-HT_1B), angiotensin II type 1 (AT₁), and endothelin type B (ET_B) receptors, in the vessel walls within the ischemic region, which further impairs local blood flow and aggravates tissue damage. This receptor upregulation occurs via activation of the mitogen-activated protein kinase pathway. We therefore hypothesized an important role for B-Raf, the first signaling molecule in the pathway. To test our hypothesis, human cerebral arteries were incubated at 37°C for 48 h in the absence or presence of a B-Raf inhibitor: SB-386023 or SB-590885. Contractile properties were evaluated in a myograph and protein expression of the individual receptors and activated phosphorylated B-Raf (p-B-Raf) was evaluated immunohistochemically.</p> <p>Results</p> <p>5-HT_1B, AT₁, and ET_Breceptor-mediated contractions were significantly reduced by application of SB-590885, and to a smaller extent by SB-386023. A marked reduction in AT₁receptor immunoreactivity was observed after treatment with SB-590885. Treatment with SB-590885 and SB-386023 diminished the culture-induced increase of p-B-Raf immunoreactivity.</p> <p>Conclusions</p> <p>B-Raf signaling has a key function in the altered expression of vascular contractile receptors observed after organ culture. Therefore, specific targeting of B-Raf might be a novel approach to reduce tissue damage after cerebral ischemia by preventing the previously observed upregulation of contractile receptors in smooth muscle cells.</p

Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbed large-scale biological networks

<p>Abstract</p> <p>Background</p> <p>For large-scale biological networks represented as signed graphs, the index of frustration measures how far a network is from a monotone system, i.e., how incoherently the system responds to perturbations.</p> <p>Results</p> <p>In this paper we find that the frustration is systematically lower in transcriptional networks (modeled at functional level) than in signaling and metabolic networks (modeled at stoichiometric level). A possible interpretation of this result is in terms of energetic cost of an interaction: an erroneous or contradictory transcriptional action costs much more than a signaling/metabolic error, and therefore must be avoided as much as possible. Averaging over all possible perturbations, however, we also find that unlike for transcriptional networks, in the signaling/metabolic networks the probability of finding the system in its least frustrated configuration tends to be high also in correspondence of a moderate energetic regime, meaning that, in spite of the higher frustration, these networks can achieve a globally ordered response to perturbations even for moderate values of the strength of the interactions. Furthermore, an analysis of the energy landscape shows that signaling and metabolic networks lack energetic barriers around their global optima, a property also favouring global order.</p> <p>Conclusion</p> <p>In conclusion, transcriptional and signaling/metabolic networks appear to have systematic differences in both the index of frustration and the transition to global order. These differences are interpretable in terms of the different functions of the various classes of networks.</p

Temporal Controls of the Asymmetric Cell Division Cycle in Caulobacter crescentus

The asymmetric cell division cycle of Caulobacter crescentus is orchestrated by an elaborate gene-protein regulatory network, centered on three major control proteins, DnaA, GcrA and CtrA. The regulatory network is cast into a quantitative computational model to investigate in a systematic fashion how these three proteins control the relevant genetic, biochemical and physiological properties of proliferating bacteria. Different controls for both swarmer and stalked cell cycles are represented in the mathematical scheme. The model is validated against observed phenotypes of wild-type cells and relevant mutants, and it predicts the phenotypes of novel mutants and of known mutants under novel experimental conditions. Because the cell cycle control proteins of Caulobacter are conserved across many species of alpha-proteobacteria, the model we are proposing here may be applicable to other genera of importance to agriculture and medicine (e.g., Rhizobium, Brucella)

Activation of the NALP3 inflammasome is triggered by low intracellular potassium concentration.

Inflammasomes are Nod-like receptor(NLR)- and caspase-1-containing cytoplasmic multiprotein complexes, which upon their assembly, process and activate the proinflammatory cytokines interleukin (IL)-1beta and IL-18. The inflammasomes harboring the NLR members NALP1, NALP3 and IPAF have been best characterized. While the IPAF inflammasome is activated by bacterial flagellin, activation of the NALP3 inflammasome is triggered not only by several microbial components, but also by a plethora of danger-associated host molecules such as uric acid. How NALP3 senses these chemically unrelated activators is not known. Here, we provide evidence that activation of NALP3, but not of the IPAF inflammasome, is blocked by inhibiting K(+) efflux from cells. Low intracellular K(+) is also a requirement for NALP1 inflammasome activation by lethal toxin of Bacillus anthracis. In vitro, NALP inflammasome assembly and caspase-1 recruitment occurs spontaneously at K(+) concentrations below 90 mM, but is prevented at higher concentrations. Thus, low intracellular K(+) may be the least common trigger of NALP-inflammasome activation

Network reconstruction of platelet metabolism identifies metabolic signature for aspirin resistance

Recently there has not been a systematic, objective assessment of the metabolic capabilities of the human platelet. A manually curated, functionally tested, and validated biochemical reaction network of platelet metabolism, iAT-PLT-636, was reconstructed using 33 proteomic datasets and 354 literature references. The network contains enzymes mapping to 403 diseases and 231 FDA approved drugs, alluding to an expansive scope of biochemical transformations that may affect or be affected by disease processes in multiple organ systems. The effect of aspirin (ASA) resistance on platelet metabolism was evaluated using constraint-based modeling, which revealed a redirection of glycolytic, fatty acid, and nucleotide metabolism reaction fluxes in order to accommodate eicosanoid synthesis and reactive oxygen species stress. These results were confirmed with independent proteomic data. The construction and availability of iAT-PLT-636 should stimulate further data-driven, systems analysis of platelet metabolism towards the understanding of pathophysiological conditions including, but not strictly limited to, coagulopathies