Systems approaches to modelling pathways and networks.

Peer reviewedPreprin

Recurrent climate winter regimes in reconstructed and modelled 500hPa geopotential height fields over the North Atlantic/European sector 1659-1990

Recurrent climate winter regimes are examined from statistically reconstructed and modelled 500hPa geopotential height fields over the North Atlantic/European sector for the period 1659-1990. We investigate the probability density function of the state space spanned by the first two empirical orthogonal functions of combined winter data. Regimes are detected as patterns that correspond to areas of the state space with an unexpected high recurrence probability using a Monte Carlo approach. The reconstruction and the model reveal four recurrent climate regimes. They correspond to the two phases of the North Atlantic Oscillation and two opposite blocking patterns. Complemented by the investigation of the temporal evolution of the climate regimes this leads to the conclusion that the reconstructed and the modelled data for this geographic sector reproduce low-frequency atmospheric variability in the form of regime-like behaviour. The overall evidence for recurrent climate regimes is higher for the model than for the reconstruction. However, comparisons with independent data sources for the period 1659-1990 revealed a more realistic temporal evolution of the regimes for the reconstructed dat

Rapamycin-coated expanded polytetrafluoroethylene bypass grafts exhibit decreased anastomotic neointimal hyperplasia in a porcine model

ObjectiveWe tested the hypothesis that rapamycin coated onto, and eluted from, expanded polytetrafluoroethylene (ePTFE) grafts would diminish neointimal hyperplasia in a porcine model.MethodsRapamycin (also called sirolimus) was coated onto the luminal surface of 6-mm-internal-diameter thin-walled ePTFE grafts by using an adhesive polymer that allows timed release of the drug. An adhesive polymer that allows timed release of rapamycin from ePTFE was developed with commercially available chemicals and applied on 6-mm ePTFE grafts. Graft integrity was characterized by scanning electron microscopy, and rapamycin levels were quantified by using high-performance liquid chromatography. Twenty-two mongrel pigs were randomized into three groups: untreated ePTFE (n = 6), adhesive-only coated ePTFE (n = 6), or adhesive- and rapamycin-coated ePTFE (n = 10). End-to-side unilateral aortoiliac bypasses were performed by using 6-mm-internal-diameter ePTFE grafts and standardized anastomotic lengths. Unilateral end-to-side aortoiliac ePTFE grafts (6-mm internal diameter) were inserted by using polypropylene sutures, 6-0 proximally and 7-0 distally; all anastomoses were 12 mm long. All animals received aspirin (325 mg orally) daily. All animals were given oral aspirin (325 mg) daily beginning on the day before surgery. At 28 days, the animals were killed, and the grafts were explanted in continuity with the adjacent aortic cuff and the outflow iliac artery. Variables compared between groups included graft patency, distal anastomotic length and cross-sectional narrowing, and intimal thickness at the arterial-graft junction indexed to the adjacent graft thickness. Microscopic analysis was performed with hematoxylin and eosin and Masson trichrome stains on paraffin sections. A pathologist blinded to experimental groups graded sections for collagen deposition, neointima formation, inflammatory cellular infiltrates, medial necrosis, and aneurysmal degeneration.ResultsAll animals survived until they were killed without clinical evidence of limb ischemia or graft infection. Preplanned t tests in the context of one-way analysis of variance showed no difference in outcome measures between the untreated ePTFE and adhesive-only coated ePTFE groups; therefore, they were combined in further comparisons with the adhesive- and rapamycin-coated ePTFE group. The Rapamycine eluting expanded polytetrafluoroethylene group had longer anastomoses (85.6% vs 60.6% of the initial anastomotic length maintained; P < .0001) and less cross-sectional narrowing in the outflow graft (16.2% vs 28.5%; P = .0007) when compared with the other two groups by using two-tailed Student t tests. There was no evidence of medial necrosis or aneurysmal degeneration. All patent grafts had complete endothelialization on hematoxylin and eosin sections. Rapamycin was detectable and quantifiable in the arterial wall at 28 days after implantation.ConclusionsRapamycin can be coated onto and eluted from ePTFE by using a nonionic polymer and a simple coating technique. At 4 weeks after implantation, the rapamycin-eluting ePTFE grafts demonstrate gross, pathologic, and morphometric features of diminished neointimal hyperplasia when compared with non–drug-eluting ePTFE. Four weeks after implantation in a porcine model, rapamycin-eluting ePTFE grafts demonstrated gross, pathologic, and morphometric features of diminished neointimal hyperplasia when compared with untreated and adhesive-only coated ePTFE grafts.Clinical RelevanceRapamycin-eluting ePTFE grafts decrease neointimal hyperplasia in a porcine model. Further studies are needed to evaluate whether patency will be improved. Rapamycin-eluting ePTFE grafts may allow the use of prosthetic grafts in situations in which autologous vein is unavailable and in which neointimal hyperplasia is pronounced, such as in small-diameter (<6-mm) vessels typical of infrapopliteal interventions

Toolbox model of evolution of metabolic pathways on networks of arbitrary topology

In prokaryotic genomes the number of transcriptional regulators is known to quadratically scale with the total number of protein-coding genes. Toolbox model was recently proposed to explain this scaling for metabolic enzymes and their regulators. According to its rules the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes. In this study we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We mathematically prove that the critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for the quadratic scaling. Conversely, the toolbox model on trees with exponentially expanding, supercritical topology is characterized by the linear scaling with logarithmic corrections. We further generalize our model to include reactions with multiple substrates/products as well as branched or cyclic metabolic pathways. Unlike the original model the new version employs evolutionary optimized pathways with the smallest number of reactions necessary to achieve their metabolic tasks. Numerical simulations of this most realistic model on the universal network from the KEGG database again produced approximately quadratic scaling. Our results demonstrate why, in spite of their "small-world" topology, real-life metabolic networks are characterized by a broad distribution of pathway lengths and sizes of metabolic regulons in regulatory networks.Comment: 34 pages, 9 figures, 2 table

Graph-based analysis of the metabolic exchanges between two co-resident intracellular symbionts, baumannia cicadellinicola and sulcia muelleri with their insect host, homalodisca coagulata

International audienceEndosymbiotic bacteria from different species can live inside cells of the same eukaryotic organism. Metabolic exchanges occur between host and bacteria but also between different endocytobionts. Since a complete genome annotation is available for both, we built the metabolic network of two endosymbiotic bacteria, Sulcia muelleri and Baumannia cicadellinicola, that live inside specific cells of the sharpshooter Homalodisca coagulata and studied the metabolic exchanges involving transfers of carbon atoms between the three. We automatically determined the set of metabolites potentially exogenously acquired (seeds) for both metabolic networks. We show that the number of seeds needed by both bacteria in the carbon metabolism is extremely reduced. Moreover, only three seeds are common to both metabolic networks, indicating that the complementarity of the two metabolisms is not only manifested in the metabolic capabilities of each bacterium, but also by their different use of the same environment. Furthermore, our results show that the carbon metabolism of S. muelleri may be completely independent of the metabolic network of B. cicadellinicola. On the contrary, the carbon metabolism of the latter appears dependent on the metabolism of S. muelleri, at least for two essential amino acids, threonine and lysine. Next, in order to define which subsets of seeds (precursor sets) are sufficient to produce the metabolites involved in a symbiotic function, we used a graph-based method, PITUFO, that we recently developed. Our results highly refine our knowledge about the complementarity between the metabolisms of the two bacteria and their host. We thus indicate seeds that appear obligatory in the synthesis of metabolites are involved in the symbiotic function. Our results suggest both B. cicadellinicola and S. muelleri may be completely independent of the metabolites provided by the co-resident endocytobiont to produce the carbon backbone of the metabolites provided to the symbiotic system (., thr and lys are only exploited by B. cicadellinicola to produce its proteins)

MetExplore: a web server to link metabolomic experiments and genome-scale metabolic networks

High-throughput metabolomic experiments aim at identifying and ultimately quantifying all metabolites present in biological systems. The metabolites are interconnected through metabolic reactions, generally grouped into metabolic pathways. Classical metabolic maps provide a relational context to help interpret metabolomics experiments and a wide range of tools have been developed to help place metabolites within metabolic pathways. However, the representation of metabolites within separate disconnected pathways overlooks most of the connectivity of the metabolome. By definition, reference pathways cannot integrate novel pathways nor show relationships between metabolites that may be linked by common neighbours without being considered as joint members of a classical biochemical pathway. MetExplore is a web server that offers the possibility to link metabolites identified in untargeted metabolomics experiments within the context of genome-scale reconstructed metabolic networks. The analysis pipeline comprises mapping metabolomics data onto the specific metabolic network of an organism, then applying graph-based methods and advanced visualization tools to enhance data analysis. The MetExplore web server is freely accessible at http://metexplore.toulouse.inra.fr

Use of reconstituted metabolic networks to assist in metabolomic data visualization and mining

Metabolomics experiments seldom achieve their aim of comprehensively covering the entire metabolome. However, important information can be gleaned even from sparse datasets, which can be facilitated by placing the results within the context of known metabolic networks. Here we present a method that allows the automatic assignment of identified metabolites to positions within known metabolic networks, and, furthermore, allows automated extraction of sub-networks of biological significance. This latter feature is possible by use of a gap-filling algorithm. The utility of the algorithm in reconstructing and mining of metabolomics data is shown on two independent datasets generated with LC–MS LTQ-Orbitrap mass spectrometry. Biologically relevant metabolic sub-networks were extracted from both datasets. Moreover, a number of metabolites, whose presence eluded automatic selection within mass spectra, could be identified retrospectively by virtue of their inferred presence through gap filling

Structural Sensitivity of Neural and Genetic Networks

International audienceThis paper aims at giving new results on the structural sensitivity of biological networks represented by threshold Boolean networks and ruled by Hopfield-like evolution laws classically used in the context of neural and genetic networks. Indeed, the objective is to present how certain changes and/or perturbations in such networks can modify signicantly their asymptotic behaviour. More precisely, this work has been focused on three diferent kinds of what we think to be relevant in the biological area of robustness (in both theoretical and applied frameworks): the boundary sensitivity (external fields, hormone flows, ...), the state sensitivity (axonal or somatic modulations, microRNAs actions, ...) and the updating sensitivity

Changes in the annual cycle of heavy precipitation across the British Isles within the 21st century

We investigate future changes in the annual cycle of heavy daily precipitation events across the British Isles in the periods 2021–2060 and 2061–2100, relative to present day climate. Twelve combinations of regional and global climate models forced with the A1B scenario are used. The annual cycle is modelled as an inhomogeneous Poisson process with sinusoidal models for location and scale parameters of the generalized extreme value distribution. Although the peak times of the annual cycle vary considerably between projections for the 2061–2100 period, a robust shift towards later peak times is found for the south-east, while in the north-west there is evidence for a shift towards earlier peak times. In the remaining parts of the British Isles no changes in the peak times are projected. For 2021–2060 this signal is weak. The annual cycle’s relative amplitude shows no robust signal, where differences in projected changes are dominated by global climate model differences. The relative contribution of anthropogenic forcing and internal climate variability to changes in the relative amplitude cannot be identified with the available ensemble. The results might be relevant for the development of adequate risk-reduction strategies, for insurance companies and for the management and planning of water resource

Signatures of arithmetic simplicity in metabolic network architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that several of the properties predicted by the artificial chemistry model hold for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity