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Evolution under Fluctuating Environments Explains Observed Robustness in Metabolic Networks

Soyer, Orkun S.; Pfeiffer, Thomas
Fonte: Public Library of Science Publicador: Public Library of Science
Tipo: Artigo de Revista Científica
EN_US
Relevância na Pesquisa
679.7945%
A high level of robustness against gene deletion is observed in many organisms. However, it is still not clear which biochemical features underline this robustness and how these are acquired during evolution. One hypothesis, specific to metabolic networks, is that robustness emerges as a byproduct of selection for biomass production in different environments. To test this hypothesis we performed evolutionary simulations of metabolic networks under stable and fluctuating environments. We find that networks evolved under the latter scenario can better tolerate single gene deletion in specific environments. Such robustness is underlined by an increased number of independent fluxes and multifunctional enzymes in the evolved networks. Observed robustness in networks evolved under fluctuating environments was “apparent,” in the sense that it decreased significantly as we tested effects of gene deletions under all environments experienced during evolution. Furthermore, when we continued evolution of these networks under a stable environment, we found that any robustness they had acquired was completely lost. These findings provide evidence that evolution under fluctuating environments can account for the observed robustness in metabolic networks. Further...

Attractor Metabolic Networks

Fuente, Ildefonso M. de la; Cort??s, Jes??s M.; Pelta, David Alejandro; Veguillas, Juan
Fonte: Public Library of Science (PLOS) Publicador: Public Library of Science (PLOS)
Tipo: Artigo de Revista Científica
ENG
Relevância na Pesquisa
676.0991%
Background The experimental observations and numerical studies with dissipative metabolic networks have shown that cellular enzymatic activity self-organizes spontaneously leading to the emergence of a Systemic Metabolic Structure in the cell, characterized by a set of different enzymatic reactions always locked into active states (metabolic core) while the rest of the catalytic processes are only intermittently active. This global metabolic structure was verified for Escherichia coli, Helicobacter pylori and Saccharomyces cerevisiae, and it seems to be a common key feature to all cellular organisms. In concordance with these observations, the cell can be considered a complex metabolic network which mainly integrates a large ensemble of self-organized multienzymatic complexes interconnected by substrate fluxes and regulatory signals, where multiple autonomous oscillatory and quasi-stationary catalytic patterns simultaneously emerge. The network adjusts the internal metabolic activities to the external change by means of flux plasticity and structural plasticity; Methodology/Principal Findings In order to research the systemic mechanisms involved in the regulation of the cellular enzymatic activity we have studied different catalytic activities of a dissipative metabolic network under different external stimuli. The emergent biochemical data have been analysed using statistical mechanic tools...

Computational tools for pathway optimization towards metabolic engineering applications

Liu, Filipe Alexandre Wang
Fonte: Universidade do Minho Publicador: Universidade do Minho
Tipo: Dissertação de Mestrado
Publicado em //2013 POR
Relevância na Pesquisa
577.178%
Dissertação de mestrado em Engenharia Informática; Metabolic Engineering targets the microorganism's cellular metabolism to design new strains with an industrial purpose. Applications of these metabolic manipulations in Biotechnological derive from the need of enhanced production of valuable compounds. The development of in silico metabolic models proposes a quantifiable approach for the manipulation these microorganisms. In this context, constraint based modelling is one of the major approaches to predict cellular behaviour. It allows to prune the feasible space of possibilities describing possible phenotype outcomes in terms of metabolic fluxes. Under these conditions, cellular metabolism can be represented as an algebraic system constrained by the laws of mass balance and thermodynamics. These systems are prone to be represented as networks, taking advantage of different graph-based paradigms, including bipartite graphs, hypergraphs and process graphs. This thesis explores these representations and underlying algorithms for metabolic network topological analysis. The main aim will be to identify potential pathways towards the optimized biochemical production of selected compounds. Related to this task, algorithms will also be designed aiming to complement networks of specific organisms...

Dynamic optimization of metabolic networks coupled with gene expression

Waldherr, Steffen; Oyarzún, Diego A.; Bockmayr, Alexander
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
575.16316%
The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients...

Why Optimal States Recruit Fewer Reactions in Metabolic Networks

Lee, Joo Sang; Nishikawa, Takashi; Motter, Adilson E.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 04/06/2012
Relevância na Pesquisa
575.9602%
The metabolic network of a living cell involves several hundreds or thousands of interconnected biochemical reactions. Previous research has shown that under realistic conditions only a fraction of these reactions is concurrently active in any given cell. This is partially determined by nutrient availability, but is also strongly dependent on the metabolic function and network structure. Here, we establish rigorous bounds showing that the fraction of active reactions is smaller (rather than larger) in metabolic networks evolved or engineered to optimize a specific metabolic task, and we show that this is largely determined by the presence of thermodynamically irreversible reactions in the network. We also show that the inactivation of a certain number of reactions determined by irreversibility can generate a cascade of secondary reaction inactivations that propagates through the network. The mathematical results are complemented with numerical simulations of the metabolic networks of the bacterium Escherichia coli and of human cells, which show, counterintuitively, that even the maximization of the total reaction flux in the network leads to a reduced number of active reactions.; Comment: Contribution to the special issue in honor of John Guckenheimer on the occasion of his 65th birthday

Analysis of the impact degree distribution in metabolic networks using branching process approximation

Takemoto, Kazuhiro; Tamura, Takeyuki; Cong, Yang; Ching, Wai-Ki; Vert, Jean-Philippe; Akutsu, Tatsuya
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 12/08/2011
Relevância na Pesquisa
575.9602%
Theoretical frameworks to estimate the tolerance of metabolic networks to various failures are important to evaluate the robustness of biological complex systems in systems biology. In this paper, we focus on a measure for robustness in metabolic networks, namely, the impact degree, and propose an approximation method to predict the probability distribution of impact degrees from metabolic network structures using the theory of branching process. We demonstrate the relevance of this method by testing it on real-world metabolic networks. Although the approximation method possesses a few limitations, it may be a powerful tool for evaluating metabolic robustness.; Comment: 17 pages, 4 figures, 4 tables

Topological Properties of Citation and Metabolic Networks

Bilke, S.; Peterson, C.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 16/03/2001
Relevância na Pesquisa
575.67066%
Topological properties of "scale-free" networks are investigated by determining their spectral dimensions $d_S$, which reflect a diffusion process in the corresponding graphs. Data bases for citation networks and metabolic networks together with simulation results from the growing network model \cite{barab} are probed. For completeness and comparisons lattice, random, small-world models are also investigated. We find that $d_S$ is around 3 for citation and metabolic networks, which is significantly different from the growing network model, for which $d_S$ is approximately 7.5. This signals a substantial difference in network topology despite the observed similarities in vertex order distributions. In addition, the diffusion analysis indicates that whereas the citation networks are tree-like in structure, the metabolic networks contain many loops.; Comment: 11 pages, 3 figures

Randomizing genome-scale metabolic networks

Samal, Areejit; Martin, Olivier C.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
576.75914%
Networks coming from protein-protein interactions, transcriptional regulation, signaling, or metabolism may appear to have "unusual" properties. To quantify this, it is appropriate to randomize the network and test the hypothesis that the network is not statistically different from expected in a motivated ensemble. However, when dealing with metabolic networks, the randomization of the network using edge exchange generates fictitious reactions that are biochemically meaningless. Here we provide several natural ensembles of randomized metabolic networks. A first constraint is to use valid biochemical reactions. Further constraints correspond to imposing appropriate functional constraints. We explain how to perform these randomizations with the help of Markov Chain Monte Carlo (MCMC) and show that they allow one to approach the properties of biological metabolic networks. The implication of the present work is that the observed global structural properties of real metabolic networks are likely to be the consequence of simple biochemical and functional constraints.; Comment: 30 Pages, 6 Main Figures, 6 Supplementary Figures, 1 Supplementary Table

Principles in the Evolution of Metabolic Networks

Ueda, Hiroki R.; Hogenesch, John B.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 28/03/2005
Relevância na Pesquisa
579.0349%
Understanding design principles of complex cellular organization is one of the major challenges in biology. Recent analysis of the large-scale cellular organization has revealed the scale-free nature and robustness of metabolic and protein networks. However, the underlying evolutional process that creates such a cellular organization is not fully elucidated. To approach this problem, we analyzed the metabolic networks of 126 organisms, whose draft or complete genome sequences have been published. This analysis has revealed that the evolutional process of metabolic networks follows the same and surprisingly simple principles in Archaea, Bacteria and Eukaryotes; where highly linked metabolites change their chemical links more dynamically than less linked metabolites. Here we demonstrate that this rich-travel-more mechanism rather than the previously proposed rich-get-richer mechanism can generate the observed scale-free organization of metabolic networks. These findings illustrate universal principles in evolution of metabolic networks and suggest marked flexibility of metabolic network throughout evolution.; Comment: 37 pages(15 pages for main text, 18 pages for supplementary information, 4 figures); 5 Supplementary Figures are omitted from this submission because of file size limitation (<1MB). This work was presented on March 15th 2004...

Currency and commodity metabolites: Their identification and relation to the modularity of metabolic networks

Huss, Mikael; Holme, Petter
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 31/03/2006
Relevância na Pesquisa
576.7042%
The large-scale shape and function of metabolic networks are intriguing topics of systems biology. Such networks are on one hand commonly regarded as modular (i.e. built by a number of relatively independent subsystems), but on the other hand they are robust in a way not expected of a purely modular system. To address this question we carefully discuss the partition of metabolic networks into subnetworks. The practice of preprocessing such networks by removing the most abundant substrates, "currency metabolites," is formalized into a network-based algorithm. We study partitions for metabolic networks of many organisms and find cores of currency metabolites and modular peripheries of what we call "commodity metabolites." The networks are found to be more modular than random networks but far from perfectly divisible into modules. We argue that cross-modular edges are the key for the robustness of metabolism.

Conservation of high-flux backbone in alternate optimal and near-optimal flux distributions of metabolic networks

Samal, Areejit
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 16/05/2009
Relevância na Pesquisa
574.6643%
Constraint-based flux balance analysis (FBA) has proven successful in predicting the flux distribution of metabolic networks in diverse environmental conditions. FBA finds one of the alternate optimal solutions that maximizes the biomass production rate. Almaas et al have shown that the flux distribution follows a power law, and it is possible to associate with most metabolites two reactions which maximally produce and consume a give metabolite, respectively. This observation led to the concept of high-flux backbone (HFB) in metabolic networks. In previous work, the HFB has been computed using a particular optima obtained using FBA. In this paper, we investigate the conservation of HFB of a particular solution for a given medium across different alternate optima and near-optima in metabolic networks of E. coli and S. cerevisiae. Using flux variability analysis (FVA), we propose a method to determine reactions that are guaranteed to be in HFB regardless of alternate solutions. We find that the HFB of a particular optima is largely conserved across alternate optima in E. coli, while it is only moderately conserved in S. cerevisiae. However, the HFB of a particular near-optima shows a large variation across alternate near-optima in both organisms. We show that the conserved set of reactions in HFB across alternate near-optima has a large overlap with essential reactions and reactions which are both uniquely consuming (UC) and uniquely producing (UP). Our findings suggest that the structure of the metabolic network admits a high degree of redundancy and plasticity in near-optimal flow patterns enhancing system robustness for a given environmental condition.; Comment: 11 pages...

Flux-based classification of reactions reveals a functional bow-tie organization of complex metabolic networks

Singh, Shalini; Samal, Areejit; Giri, Varun; Krishna, Sandeep; Raghuram, Nandula; Jain, Sanjay
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 09/12/2012
Relevância na Pesquisa
576.75914%
Unraveling the structure of complex biological networks and relating it to their functional role is an important task in systems biology. Here we attempt to characterize the functional organization of the large-scale metabolic networks of three microorganisms. We apply flux balance analysis to study the optimal growth states of these organisms in different environments. By investigating the differential usage of reactions across flux patterns for different environments, we observe a striking bimodal distribution in the activity of reactions. Motivated by this, we propose a simple algorithm to decompose the metabolic network into three sub-networks. It turns out that our reaction classifier which is blind to the biochemical role of pathways leads to three functionally relevant sub-networks that correspond to input, output and intermediate parts of the metabolic network with distinct structural characteristics. Our decomposition method unveils a functional bow-tie organization of metabolic networks that is different from the bow-tie structure determined by graph-theoretic methods that do not incorporate functionality.; Comment: 11 pages, 6 figures, 1 table

Size Dependent Growth in Metabolic Networks

Dorrian, Henry; Smallbone, Kieran; borresen, Jon
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 09/10/2012
Relevância na Pesquisa
576.75914%
Accurately determining and classifying the structure of complex networks is the focus of much current research. One class of network of particular interest are metabolic pathways, which have previously been studied from a graph theoretical viewpoint in a number of ways. Metabolic networks describe the chemical reactions within cells and are thus of prime importance from a biological perspective. Here we analyse metabolic networks from a section of microorganisms, using a range of metrics and attempt to address anomalies between the observed metrics and current descriptions of the graphical structure. We propose that the growth of the network may in some way be regulated by network size and attempt to reproduce networks with similar metrics to the metabolic pathways using a generative approach. We provide some hypotheses as to why biological networks may evolve according to these model criteria.; Comment: 5 pages, 11 figures

Phylogeny of Metabolic Networks: A Spectral Graph Theoretical Approach

Deyasi, Krishanu; Banerjee, Anirban; Deb, Bony
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
575.8572%
Many methods have been developed for finding the commonalities between different organisms to study their phylogeny. The structure of metabolic networks also reveal valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyze the phylogeny from these distances. In our analysis, we focus on the species, which belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.; Comment: 16 pages...

Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks

Bardoscia, Marco; Marsili, Matteo; Samal, Areejit
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
579.7945%
System-level properties of metabolic networks may be the direct product of natural selection or arise as a by-product of selection on other properties. Here we study the effect of direct selective pressure for growth or viability in particular environments on two properties of metabolic networks: latent versatility to function in additional environments and carbon usage efficiency. Using a Markov Chain Monte Carlo (MCMC) sampling based on Flux Balance Analysis (FBA), we sample from a known biochemical universe random viable metabolic networks that differ in the number of directly constrained environments. We find that the latent versatility of sampled metabolic networks increases with the number of directly constrained environments and with the size of the networks. We then show that the average carbon wastage of sampled metabolic networks across the constrained environments decreases with the number of directly constrained environments and with the size of the networks. Our work expands the growing body of evidence about nonadaptive origins of key functional properties of biological networks.; Comment: 9 pages, 7 figures

Hierarchical modularity of nested bow-ties in metabolic networks

Zhao, Jing; Yu, Hong; Luo, Jian-Hua; Cao, Zhi-Wei; Li, Yi-Xue
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
582.15766%
The exploration of the structural topology and the organizing principles of genome-based large-scale metabolic networks is essential for studying possible relations between structure and functionality of metabolic networks. Topological analysis of graph models has often been applied to study the structural characteristics of complex metabolic networks.In this work, metabolic networks of 75 organisms were investigated from a topological point of view. Network decomposition of three microbes (Escherichia coli, Aeropyrum pernix and Saccharomyces cerevisiae) shows that almost all of the sub-networks exhibit a highly modularized bow-tie topological pattern similar to that of the global metabolic networks. Moreover, these small bow-ties are hierarchically nested into larger ones and collectively integrated into a large metabolic network, and important features of this modularity are not observed in the random shuffled network. In addition, such a bow-tie pattern appears to be present in certain chemically isolated functional modules and spatially separated modules including carbohydrate metabolism, cytosol and mitochondrion respectively. The highly modularized bow-tie pattern is present at different levels and scales, and in different chemical and spatial modules of metabolic networks...

Bow-tie topological features of metabolic networks and the functional significance

Jing, Zhao; Lin, Tao; Hong, Yu; Jian-Hua, Luo; Cao, Z. W.; Yixue, Li
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 03/11/2006
Relevância na Pesquisa
578.05504%
Exploring the structural topology of genome-based large-scale metabolic network is essential for investigating possible relations between structure and functionality. Visualization would be helpful for obtaining immediate information about structural organization. In this work, metabolic networks of 75 organisms were investigated from a topological point of view. A spread bow-tie model was proposed to give a clear visualization of the bow-tie structure for metabolic networks. The revealed topological pattern helps to design more efficient algorithm specifically for metabolic networks. This coarse-grained graph also visualizes the vulnerable connections in the network, and thus could have important implication for disease studies and drug target identifications. In addition, analysis on the reciprocal links and main cores in the GSC part of bow-tie also reveals that the bow-tie structure of metabolic networks has its own intrinsic and significant features which are significantly different from those of random networks.; Comment: 15 pages, 5 figures

The Regularizing Capacity of Metabolic Networks

Marr, Carsten; Mueller-Linow, Mark; Huett, Marc-Thorsten
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 11/12/2006
Relevância na Pesquisa
575.8572%
Despite their topological complexity almost all functional properties of metabolic networks can be derived from steady-state dynamics. Indeed, many theoretical investigations (like flux-balance analysis) rely on extracting function from steady states. This leads to the interesting question, how metabolic networks avoid complex dynamics and maintain a steady-state behavior. Here, we expose metabolic network topologies to binary dynamics generated by simple local rules. We find that the networks' response is highly specific: Complex dynamics are systematically reduced on metabolic networks compared to randomized networks with identical degree sequences. Already small topological modifications substantially enhance the capacity of a network to host complex dynamic behavior and thus reduce its regularizing potential. This exceptionally pronounced regularization of dynamics encoded in the topology may explain, why steady-state behavior is ubiquitous in metabolism.; Comment: 6 pages, 4 figures

Metabolic networks are almost nonfractal: A comprehensive evaluation

Takemoto, Kazuhiro
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Relevância na Pesquisa
581.07504%
Network self-similarity or fractality are widely accepted as an important topological property of metabolic networks; however, recent studies cast doubt on the reality of self-similarity in the networks. Therefore, we perform a comprehensive evaluation of metabolic network fractality using a box-covering method with an earlier version and the latest version of metabolic networks, and demonstrate that the latest metabolic networks are almost self-dissimilar, while the earlier ones are fractal, as reported in a number of previous studies. This result may be because the networks were randomized because of an increase in network density due to database updates, suggesting that the previously observed network fractality was due to a lack of available data on metabolic reactions. This finding may not entirely discount the importance of self-similarity of metabolic networks. Rather, it highlights the need for a more suitable definition of network fractality and a more careful examination of self-similarity of metabolic networks.; Comment: 7 pages, 5 figures

A statistical mechanics description of environmental variability in metabolic networks

Crofts, Jonathan J; Estrada, Ernesto
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 01/03/2013
Relevância na Pesquisa
578.05504%
Many of the chemical reactions that take place within a living cell are irreversible. Due to evolutionary pressures, the number of allowable reactions within these systems are highly constrained and thus the resulting metabolic networks display considerable asymmetry. In this paper, we explore possible evolutionary factors pertaining to the reduced symmetry observed in these networks, and demonstrate the important role environmental variability plays in shaping their structural organization. Interpreting the returnability index as an equilibrium constant for a reaction network in equilibrium with a hypothetical reference system, enables us to quantify the extent to which a metabolic network is in disequilibrium. Further, by introducing a new directed centrality measure via an extension of the subgraph centrality metric to directed networks, we are able to characterise individual metabolites by their participation within metabolic pathways. To demonstrate these ideas, we study 116 metabolic networks of bacteria. In particular, we find that the equilibrium constant for the metabolic networks decreases significantly in-line with variability in bacterial habitats, supporting the view that environmental variability promotes disequilibrium within these biochemical reaction systems.