[show abstract][hide abstract] ABSTRACT: The observation that, through a titration mechanism, microRNAs (miRNAs) can
act as mediators of effective interactions among their common targets
(competing endogenous RNAs or ceRNAs) has brought forward the idea ('ceRNA
hypothesis') that RNAs can regulate each other in extended 'cross-talk'
networks. Such an ability might play a major role in post-transcriptional
regulation (PTR) in shaping a cell's protein repertoire. Recent work focusing
on the emergent properties of the cross-talk networks has emphasized the high
flexibility and selectivity that may be achieved at stationarity. On the other
hand, dynamical aspects, possibly crucial on the relevant time scales, are far
less clear. We have carried out a dynamical study of the ceRNA hypothesis on a
model of PTR. Sensitivity analysis shows that ceRNA cross-talk is dynamically
extended, i.e. it may take place on time scales shorter than those required to
achieve stationairity even in cases where no cross-talk occurs in the steady
state, and is possibly amplified. Besides, in case of large, transfection-like
perturbations the system may develop strongly non-linear, threshold response.
Finally, we show that the ceRNA effect provides a very efficient way for a cell
to achieve fast positive shifts in the level of a ceRNA when necessary. These
results indicate that competition for miRNAs may indeed provide an elementary
mechanism to achieve system-level regulatory effects on the transcriptome over
physiologically relevant time scales.
[show abstract][hide abstract] ABSTRACT: Thermodynamics constrains the flow of matter in a reaction network to occur
through routes along which the Gibbs energy decreases, implying that viable
steady-state flux patterns should be void of closed reaction cycles.
Identifying and removing cycles in large reaction networks can unfortunately be
a highly challenging task from a computational viewpoint. We propose here a
method that accomplishes it by combining a relaxation algorithm and a Monte
Carlo procedure to detect loops, with ad hoc rules (discussed in detail) to
eliminate them. As test cases, we tackle (a) the problem of identifying
infeasible cycles in the E. coli metabolic network and (b) the problem of
correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions
for 15 human cell-type specific metabolic networks. Results for (a) are
compared with previous analyses of the same issue, while results for (b) are
weighed against alternative methods to retrieve thermodynamically viable flux
patterns based on minimizing specific global quantities. Our method on one hand
outperforms previous techniques and, on the other, corrects loopy solutions to
Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal
possible inconsistencies in model reconstructions.
[show abstract][hide abstract] ABSTRACT: The energetics of cerebral activity critically relies on the functional and metabolic interactions between neurons and astrocytes. Important open questions include the relation between neuronal versus astrocytic energy demand, glucose uptake and intercellular lactate transfer, as well as their dependence on the level of activity.
We have developed a large-scale, constraint-based network model of the metabolic partnership between astrocytes and glutamatergic neurons that allows for a quantitative appraisal of the extent to which stoichiometry alone drives the energetics of the system. We find that the velocity of the glutamate-glutamine cycle (Vcyc) explains part of the uncoupling between glucose and oxygen utilization at increasing Vcyc levels. Thus, we are able to characterize different activation states in terms of the tissue oxygen-glucose index (OGI). Calculations show that glucose is taken up and metabolized according to cellular energy requirements, and that partitioning of the sugar between different cell types is not significantly affected by Vcyc. Furthermore, both the direction and magnitude of the lactate shuttle between neurons and astrocytes turn out to depend on the relative cell glucose uptake while being roughly independent of Vcyc.
These findings suggest that, in absence of ad hoc activity-related constraints on neuronal and astrocytic metabolism, the glutamate-glutamine cycle does not control the relative energy demand of neurons and astrocytes, and hence their glucose uptake and lactate exchange.
BMC Systems Biology 10/2013; 7(1):103. · 2.98 Impact Factor
[show abstract][hide abstract] ABSTRACT: We report a high-precision finite-size scaling study of the critical behavior
of the three-dimensional Ising Edwards-Anderson model (the Ising spin glass).
We have thermalized lattices up to L=40 using the Janus dedicated computer. Our
analysis takes into account leading-order corrections to scaling. We obtain Tc
= 1.1019(29) for the critical temperature, \nu = 2.562(42) for the thermal
exponent, \eta = -0.3900(36) for the anomalous dimension and \omega = 1.12(10)
for the exponent of the leading corrections to scaling. Standard (hyper)scaling
relations yield \alpha = -5.69(13), \beta = 0.782(10) and \gamma = 6.13(11). We
also compute several universal quantities at Tc.
[show abstract][hide abstract] ABSTRACT: This paper describes the architecture, the development and the implementation
of Janus II, a new generation application-driven number cruncher optimized for
Monte Carlo simulations of spin systems (mainly spin glasses). This domain of
computational physics is a recognized grand challenge of high-performance
computing: the resources necessary to study in detail theoretical models that
can make contact with experimental data are by far beyond those available using
commodity computer systems. On the other hand, several specific features of the
associated algorithms suggest that unconventional computer architectures, which
can be implemented with available electronics technologies, may lead to order
of magnitude increases in performance, reducing to acceptable values on human
scales the time needed to carry out simulation campaigns that would take
centuries on commercially available machines. Janus II is one such machine,
recently developed and commissioned, that builds upon and improves on the
successful JANUS machine, which has been used for physics since 2008 and is
still in operation today. This paper describes in detail the motivations behind
the project, the computational requirements, the architecture and the
implementation of this new machine and compares its expected performances with
those of currently available commercial systems.
[show abstract][hide abstract] ABSTRACT: We study the off-equilibrium dynamics of the three-dimensional Ising spin
glass in the presence of an external magnetic field. We have performed
simulations both at fixed temperature and with an annealing protocol. Thanks to
the Janus special-purpose computer, based on FPGAs, we have been able to reach
times equivalent to 0.01 seconds in experiments. We have studied the system
relaxation both for high and for low temperatures, clearly identifying a
dynamical transition point. This dynamical temperature is strictly positive and
depends on the external applied magnetic field. We discuss different
possibilities for the underlying physics, which include a thermodynamical
spin-glass transition or a mode-coupling crossover.
[show abstract][hide abstract] ABSTRACT: It has recently been suggested that the competition for a finite pool of microRNAs (miRNA) gives rise to effective interactions among their common targets (competing endogenous RNAs or ceRNAs) that could prove to be crucial for posttranscriptional regulation. We have studied a minimal model of posttranscriptional regulation where the emergence and the nature of such interactions can be characterized in detail at steady state. Sensitivity analysis shows that binding free energies and repression mechanisms are the key ingredients for the cross-talk between ceRNAs to arise. Interactions emerge in specific ranges of repression values, can be symmetrical (one ceRNA influences another and vice versa) or asymmetrical (one ceRNA influences another but not the reverse), and may be highly selective, while possibly limited by noise. In addition, we show that nontrivial correlations among ceRNAs can emerge in experimental readouts due to transcriptional fluctuations even in the absence of miRNA-mediated cross-talk.
[show abstract][hide abstract] ABSTRACT: The integration of various types of genomic data into predictive models of biological networks is one of the main challenges currently faced by computational biology. Constraint-based models in particular play a key role in the attempt to obtain a quantitative understanding of cellular metabolism at genome scale. In essence, their goal is to frame the metabolic capabilities of an organism based on minimal assumptions that describe the steady states of the underlying reaction network via suitable stoichiometric constraints, specifically mass balance and energy balance (i.e. thermodynamic feasibility). The implementation of these requirements to generate viable configurations of reaction fluxes and/or to test given flux profiles for thermodynamic feasibility can however prove to be computationally intensive. We propose here a fast and scalable stoichiometry-based method to explore the Gibbs energy landscape of a biochemical network at steady state. The method is applied to the problem of reconstructing the Gibbs energy landscape underlying metabolic activity in the human red blood cell, and to that of identifying and removing thermodynamically infeasible reaction cycles in the Escherichia coli metabolic network (iAF1260). In the former case, we produce consistent predictions for chemical potentials (or log-concentrations) of intracellular metabolites; in the latter, we identify a restricted set of loops (23 in total) in the periplasmic and cytoplasmic core as the origin of thermodynamic infeasibility in a large sample (10(6)) of flux configurations generated randomly and compatibly with the prior information available on reaction reversibility.
[show abstract][hide abstract] ABSTRACT: We study the 3D Edwards-Anderson spin glasses, by analyzing spin-spin
correlation functions in thermalized spin configurations at low T on large
lattices. We consider individual disorder samples and analyze connected
clusters of very correlated sites: we analyze how the volume and the surface of
these clusters increases with the lattice size. We qualify the important
excitations of the system by checking how large they are, and we define a
correlation length by measuring their gyration radius. We find that the
clusters have a very dense interface, compatible with being space filling.
Journal of Statistical Mechanics Theory and Experiment 05/2012; 2012(12). · 1.87 Impact Factor
[show abstract][hide abstract] ABSTRACT: We review recent work on the statistical mechanics of Von Neumann's growth
model and discuss its application to cellular metabolic networks. In this
context, we present a detailed analysis of the physiological scenario
underlying optimality a la Von Neumann in the metabolism of the bacterium
Escherichia coli, showing that optimal solutions are characterized by a
considerable microscopic flexibility accompanied by a robust emergent picture
for the key physiological functions. This suggests that the ideas behind
optimal economic growth in Von Neumann's model can be helpful in uncovering
functional organization principles of cell energetics.
The European Physical Journal Special Topics 05/2012; 212(1). · 1.80 Impact Factor
[show abstract][hide abstract] ABSTRACT: We describe Janus, a massively parallel FPGA-based computer optimized for the
simulation of spin glasses, theoretical models for the behavior of glassy
materials. FPGAs (as compared to GPUs or many-core processors) provide a
complementary approach to massively parallel computing. In particular, our
model problem is formulated in terms of binary variables, and floating-point
operations can be (almost) completely avoided. The FPGA architecture allows us
to run many independent threads with almost no latencies in memory access, thus
updating up to 1024 spins per cycle. We describe Janus in detail and we
summarize the physics results obtained in four years of operation of this
machine; we discuss two types of physics applications: long simulations on very
large systems (which try to mimic and provide understanding about the
experimental non-equilibrium dynamics), and low-temperature equilibrium
simulations using an artificial parallel tempering dynamics. The time scale of
our non-equilibrium simulations spans eleven orders of magnitude (from
picoseconds to a tenth of a second). On the other hand, our equilibrium
simulations are unprecedented both because of the low temperatures reached and
for the large systems that we have brought to equilibrium. A finite-time
scaling ansatz emerges from the detailed comparison of the two sets of
simulations. Janus has made it possible to perform spin-glass simulations that
would take several decades on more conventional architectures. The paper ends
with an assessment of the potential of possible future versions of the Janus
architecture, based on state-of-the-art technology.
The European Physical Journal Special Topics 04/2012; 210(1). · 1.80 Impact Factor
[show abstract][hide abstract] ABSTRACT: Spin glasses are a longstanding model for the sluggish dynamics that appears
at the glass transition. However, spin glasses differ from structural glasses
for a crucial feature: they enjoy a time reversal symmetry. This symmetry can
be broken by applying an external magnetic field, but embarrassingly little is
known about the critical behaviour of a spin glass in a field. In this context,
the space dimension is crucial. Simulations are easier to interpret in a large
number of dimensions, but one must work below the upper critical dimension
(i.e., in d<6) in order for results to have relevance for experiments. Here we
show conclusive evidence for the presence of a phase transition in a
four-dimensional spin glass in a field. Two ingredients were crucial for this
achievement: massive numerical simulations were carried out on the Janus
special-purpose computer, and a new and powerful finite-size scaling method.
Proceedings of the National Academy of Sciences 02/2012; 109(17). · 9.74 Impact Factor
[show abstract][hide abstract] ABSTRACT: Using the results of large scale numerical simulations we study the
probability distribution of the pseudo critical temperature for the
three-dimensional Edwards-Anderson Ising spin glass and for the fully connected
Sherrington-Kirkpatrick model. We find that the behavior of our data is nicely
described by straightforward finite-size scaling relations.
Journal of Statistical Mechanics Theory and Experiment 08/2011; 2011(10). · 1.87 Impact Factor
[show abstract][hide abstract] ABSTRACT: We study the sample-to-sample fluctuations of the overlap probability
densities from large-scale equilibrium simulations of the three-dimensional
Edwards-Anderson spin glass below the critical temperature. Ultrametricity,
Stochastic Stability and Overlap Equivalence impose constraints on the moments
of the overlap probability densities that can be tested against numerical data.
We found small deviations from the Ghirlanda-Guerra predictions, which get
smaller as system size increases. We also focus on the shape of the overlap
distribution, comparing the numerical data to a mean-field-like prediction in
which finite-size effects are taken into account by substituting delta
functions with broad peaks
[show abstract][hide abstract] ABSTRACT: The analysis of non-equilibrium steady states of biochemical reaction
networks relies on finding the configurations of fluxes and chemical potentials
satisfying stoichiometric (mass balance) and thermodynamic (energy balance)
constraints. Efficient methods to explore such states are crucial to predict
reaction directionality, calculate physiologic ranges of variability, estimate
correlations, and reconstruct the overall energy balance of the network from
the underlying molecular processes. While different techniques for sampling the
space generated by mass balance constraints are currently available,
thermodynamics is generically harder to incorporate. Here we introduce a method
to sample the free energy landscape of a reaction network at steady state. In
its most general form, it allows to calculate distributions of fluxes and
concentrations starting from trial functions that may contain prior biochemical
information. We apply our method to the human red blood cell's metabolic
network, whose space of mass-balanced flux states has been sampled extensively
in recent years. Specifically, we profile its thermodynamically feasible flux
configurations, characterizing in detail how fluctuations of fluxes and
potentials are correlated. Based on this, we derive the cell's energy balance
in terms of entropy production, chemical work done and thermodynamic
[show abstract][hide abstract] ABSTRACT: We argue that complex systems must possess long range correlations and
illustrate this idea on the example of the mean field spin glass model. Defined
on the complete graph, this model has no genuine concept of distance, but the
long range character of correlations is translated into a broad distribution of
the spin-spin correlation coefficients for almost all realizations of the
random couplings. When we sample the whole phase space we find that this
distribution is so broad indeed that at low temperatures it essentially becomes
uniform, with all possible correlation values appearing with the same
probability. The distribution of correlations inside a single phase space
valley is also studied and found to be much narrower.
Journal of Statistical Mechanics Theory and Experiment 10/2010; 2(02). · 1.87 Impact Factor
[show abstract][hide abstract] ABSTRACT: We numerically study the aging properties of the dynamical heterogeneities in the Ising spin glass. We find that a phase transition takes place during the aging process. Statics-dynamics correspondence implies that systems of finite size in equilibrium have static heterogeneities that obey finite-size scaling, thus signaling an analogous phase transition in the thermodynamical limit. We compute the critical exponents and the transition point in the equilibrium setting, and use them to show that aging in dynamic heterogeneities can be described by a finite-time scaling ansatz, with potential implications for experimental work.
[show abstract][hide abstract] ABSTRACT: We present a massive equilibrium simulation of the three-dimensional Ising spin glass at low temperatures. The Janus special-purpose computer has allowed us to equilibrate, using parallel tempering, L=32 lattices down to T=0.64 Tc. We demonstrate the relevance of equilibrium finite-size simulations to understand experimental non-equilibrium spin glasses in the thermodynamical limit by establishing a time-length dictionary. We conclude that non-equilibrium experiments performed on a time scale of one hour can be matched with equilibrium results on L=110 lattices. A detailed investigation of the probability distribution functions of the spin and link overlap, as well as of their correlation functions, shows that Replica Symmetry Breaking is the appropriate theoretical framework for the physically relevant length scales. Besides, we improve over existing methodologies to ensure equilibration in parallel tempering simulations. Comment: 48 pages, 19 postscript figures, 9 tables. Version accepted for publication in the Journal of Statistical Mechanics
Journal of Statistical Mechanics Theory and Experiment 03/2010; · 1.87 Impact Factor