Página 1 dos resultados de 2081 itens digitais encontrados em 0.008 segundos

## Evolution under Fluctuating Environments Explains Observed Robustness in Metabolic Networks

Fonte: Public Library of Science
Publicador: Public Library of Science

Tipo: Artigo de Revista Científica

EN_US

Relevância na Pesquisa

679.7945%

#biochemistry#molecular evolution#theory and simulation#cell biology#microbial physiology and metabolism#computational biology#evolutionary modeling#metabolic networks#systems biology#evolutionary biology#microbial evolution and genomics

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...

Link permanente para citações:

## Attractor Metabolic Networks

Fonte: Public Library of Science (PLOS)
Publicador: Public Library of Science (PLOS)

Tipo: Artigo de Revista Científica

ENG

Relevância na Pesquisa

676.0991%

#Allosteric regulation#Cell metabolism#Enzyme metabolism#Enzyme regulation#Enzymes#Memory#Metabolic networks#Metabolic processes

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...

Link permanente para citações:

## Computational tools for pathway optimization towards metabolic engineering applications

Fonte: Universidade do Minho
Publicador: Universidade do Minho

Tipo: Dissertação de Mestrado

Publicado em //2013
POR

Relevância na Pesquisa

577.178%

#Metabolic networks#Flux analysis#Synthetic biology#Pathway optimization#Network topological analysis#Subgraph extraction#Redes metabólicas#Análise de fluxo#Biologia sintética#Optimização de vias metabólicas#Análise topológica de redes

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...

Link permanente para citações:

## Dynamic optimization of metabolic networks coupled with gene expression

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...

Link permanente para citações:

## Why Optimal States Recruit Fewer Reactions in Metabolic Networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 04/06/2012

Relevância na Pesquisa

575.9602%

#Quantitative Biology - Molecular Networks#Condensed Matter - Disordered Systems and Neural Networks#Nonlinear Sciences - Adaptation and Self-Organizing Systems#92C42, 90C35

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

Link permanente para citações:

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

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

Link permanente para citações:

## Topological Properties of Citation and Metabolic Networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 16/03/2001

Relevância na Pesquisa

575.67066%

#Condensed Matter - Disordered Systems and Neural Networks#Condensed Matter - Statistical Mechanics#Quantitative Biology

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

Link permanente para citações:

## Randomizing genome-scale metabolic networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

576.75914%

#Quantitative Biology - Molecular Networks#Condensed Matter - Statistical Mechanics#Physics - Biological Physics#Physics - Computational Physics

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

Link permanente para citações:

## Principles in the Evolution of Metabolic Networks

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...

Link permanente para citações:

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

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 31/03/2006

Relevância na Pesquisa

576.7042%

#Quantitative Biology - Molecular Networks#Condensed Matter - Disordered Systems and Neural Networks

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.

Link permanente para citações:

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

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...

Link permanente para citações:

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

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

Link permanente para citações:

## Size Dependent Growth in Metabolic Networks

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

Link permanente para citações:

## Phylogeny of Metabolic Networks: A Spectral Graph Theoretical Approach

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...

Link permanente para citações:

## Phenotypic constraints promote latent versatility and carbon efficiency in metabolic networks

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

Link permanente para citações:

## Hierarchical modularity of nested bow-ties in metabolic networks

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...

Link permanente para citações:

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

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

Link permanente para citações:

## The Regularizing Capacity of Metabolic Networks

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

Link permanente para citações:

## Metabolic networks are almost nonfractal: A comprehensive evaluation

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Relevância na Pesquisa

581.07504%

#Quantitative Biology - Molecular Networks#Physics - Data Analysis, Statistics and Probability#Physics - Physics and Society

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

Link permanente para citações:

## A statistical mechanics description of environmental variability in metabolic networks

Fonte: Universidade Cornell
Publicador: Universidade Cornell

Tipo: Artigo de Revista Científica

Publicado em 01/03/2013

Relevância na Pesquisa

578.05504%

#Quantitative Biology - Molecular Networks#Condensed Matter - Statistical Mechanics#Physics - Biological Physics#92B05

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.

Link permanente para citações: