Papers by Maximino Aldana
Informatica Didactica, 2020
| An important property of many complex systems is the presence of scaling laws, which are charac... more | An important property of many complex systems is the presence of scaling laws, which are characterized by the fact that some of the variables that describe the behavior of the system are related through power-laws. Scaling laws have two important general implications: (i) the self-similarity of the system over a wide range of scales (each part of the system is similar to the entire system), and (ii) "rare events" which should occur with low probability are in fact not so "rare" and occur much more often than expected. In this work we discuss dynamical criticality as one of the main mechanisms generating scaling laws in complex systems. We will focus mainly on majority voter models and neuronal networks. It is surprising that two systems which are apparently so different (networks of voters and networks of neurons) can actually be described using the same conceptual and methodological tools. This illustrates the universality of critical phenomena and the corresponding scaling laws.
ABSTRACTOver the last decades, analyses of the connectivity of large biological and artificial ne... more ABSTRACTOver the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks’ hubs, recent experiments have revealed that they can show behaviors oscillating between ‘on’ and ‘off’ states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network c...
Physical Review E, 2005
We study static annihilation on complex networks, in which pairs of connected particles annihilat... more We study static annihilation on complex networks, in which pairs of connected particles annihilate at a constant rate during time. Through a mean-field formalism, we compute the temporal evolution of the distribution of surviving sites with an arbitrary number of connections. This general formalism, which is exact for disordered networks, is applied to Kronecker, Erdös-Rényi (i.e. Poisson) and scale-free networks. We compare our theoretical results with extensive numerical simulations obtaining excellent agreement. Although the mean-field approach applies in an exact way neither to ordered lattices nor to small-world networks, it qualitatively describes the annihilation dynamics in such structures. Our results indicate that the higher the connectivity of a given network element, the faster it annihilates. This fact has dramatic consequences in scale-free networks, for which, once the "hubs" have been annihilated, the network disintegrates and only isolated sites are left.
The dynamics of Boolean networks (the N-K model) with scale-free topology are studied here. The e... more The dynamics of Boolean networks (the N-K model) with scale-free topology are studied here. The existence of a phase transition governed by the value of the scale-free exponent of the network is shown analytically by analyzing the overlap between two distinct trajectories. The phase diagram shows that the phase transition occurs for values of the scale-free exponent in the open interval (2,2.5). Since the Boolean networks under study are directed graphs, the scale-free topology of the input connections and that of the output connections are studied separately. Ultimately these two topologies are shown to be equivalent. An important result of this work is that the fine-tuning usually required to achieve stability in Boolean networks with a totally random topology is no longer necessary when the network topology is scale-free.
RESEARCH ARTICLE Adaptive Resistance in Bacteria Requires Epigenetic Inheritance, Genetic Noise, and Cost of Efflux Pumps
Adaptive resistance emerges when populations of bacteria are subjected to gradual in-creases of a... more Adaptive resistance emerges when populations of bacteria are subjected to gradual in-creases of antibiotics. It is characterized by a rapid emergence of resistance and fast re-versibility to the non-resistant phenotype when the antibiotic is removed from the medium. Recent work shows that adaptive resistance requires epigenetic inheritance and heteroge-neity of gene expression patterns that are, in particular, associated with the production of porins and efflux pumps. However, the precise mechanisms by which inheritance and vari-ability govern adaptive resistance, and what processes cause its reversibility remain un-clear. Here, using an efflux pump regulatory network (EPRN) model, we show that the following three mechanisms are essential to obtain adaptive resistance in a bacterial popu-lation: 1) intrinsic variability in the expression of the EPRN transcription factors; 2) epigenet-ic inheritance of the transcription rate of EPRN associated genes; and 3) energetic cost of the effl...
Abstract. Boolean threshold networks have recently been proposed as useful tools to model the dyn... more Abstract. Boolean threshold networks have recently been proposed as useful tools to model the dynamics of genetic regulatory networks, and have been successfully applied to describe the cell cycles of S. cerevisiae and S. pombe. Threshold networks assume that gene regulation processes are additive. This, however, contrasts with the mechanism proposed by S. Kauffman in which each of the logic functions must be carefully con-structed to accurately take into account the combinatorial nature of gene regulation. While Kauffman Boolean networks have been extensively studied and proved to have the necessary properties required for model-ing the fundamental characteristics of genetic regulatory networks, not much is known about the essential properties of threshold networks. Here we study the dynamical properties of these networks with different con-nectivities, activator-repressor proportions, activator-repressor strengths and different thresholds. Special attention is paid to the way in w...
arXiv: Disordered Systems and Neural Networks, 2008
We analyze order-disorder phase transitions driven by noise that occur in two kinds of network mo... more We analyze order-disorder phase transitions driven by noise that occur in two kinds of network models closely related to the self-propelled model proposed by Vicsek et. al. to describe the collective motion of groups of organisms [\emph{Phys. Rev. Lett.} {\bf 75}:1226 (1995)]. Two different types of noise, which we call intrinsic and extrinsic, are considered. The intrinsic noise, the one used by Vicsek et. al. in their original work, is related to the decision mechanism through which the particles update their positions. In contrast, the extrinsic noise, later introduced by Gr\'egoire and Chat\'e [\emph{Phys. Rev. Lett.} {\bf 92}:025702 (2004)], affects the signal that the particles receive from the environment. The network models presented here can be considered as the mean-field representation of the self-propelled model. We show analytically and numerically that, for these two network models, the phase transitions driven by the intrinsic noise are continuous, whereas the...
Many complex diseases are expressed with high incidence only in certain populations. Genealogy st... more Many complex diseases are expressed with high incidence only in certain populations. Genealogy studies determine that these diseases are inherited with a high probability. However, genetic studies have been unable to identify the genomic signatures responsible for such heritability, as identifying the genetic variants that make a population prone to a given disease is not enough to explain its high occurrence within the population. This gap is known as the missing heritability problem. We know that the microbiota plays a very important role in determining many important phenotypic characteristics of its host, in particular, the complex diseases for which the missing heritability occurs. Therefore, when computing the heritability of a phenotype it is important to consider not only the genetic variation in the host but also in its microbiota. Here we test this hypothesis by studying an evolutionary model based on gene regulatory networks. Our results show that the holobiont (the host ...
Entropy
Self-assembly is a spontaneous process through which macroscopic structures are formed from basic... more Self-assembly is a spontaneous process through which macroscopic structures are formed from basic microscopic constituents (e.g., molecules or colloids). By contrast, the formation of large biological molecules inside the cell (such as proteins or nucleic acids) is a process more akin to self-organization than to self-assembly, as it requires a constant supply of external energy. Recent studies have tried to merge self-assembly with self-organization by analyzing the assembly of self-propelled (or active) colloid-like particles whose motion is driven by a permanent source of energy. Here we present evidence that points to the fact that self-propulsion considerably enhances the assembly of polymers: self-propelled molecules are found to assemble faster into polymer-like structures than non self-propelled ones. The average polymer length increases towards a maximum as the self-propulsion force increases. Beyond this maximum, the average polymer length decreases due to the competition ...
Self-assembly is a spontaneous process through which macroscopic structures are formed from basic... more Self-assembly is a spontaneous process through which macroscopic structures are formed from basic microscopic constituents (e.g. molecules or colloids). By contrast, the formation of large biological molecules inside the cell (such as proteins or nucleic acids) is a process more akin to self-organization than to self-assembly, as it requires a constant supply of external energy. Recent studies have tried to merge self-assembly with self-organization by analyzing the assembly of self-propelled (or active) colloid-like particles whose motion is driven by a permanent source of energy. Here we present evidence that points to the fact that self-propulsion considerably enhances the assembly of polymers: self-propelled molecules are found to assemble into polymer-like structures, the average length of which increases towards a maximum as the self-propulsion force increases. Beyond this maximum, the average polymer length decreases due to the competition between bonding energy and disruptiv...
Evolving Ecosystems: Inheritance and Selection in the Light of the Microbiome
Archives of medical research, Jan 20, 2018
The importance of microorganisms in human biology is undeniable. The amount of research that supp... more The importance of microorganisms in human biology is undeniable. The amount of research that supports that microbes have a fundamental role in animal and plant physiology is substantial and increasing every year. Even though we are only beginning to comprehend the broadness and complexity of microbial communities, evolutionary theories need to be recast in the light of such discoveries to fully understand and incorporate the role of microbes in our evolution. Fundamental evolutionary concepts such as diversity, heredity, selection, speciation, etc., which constitute the modern synthesis, are now being challenged, or at least expanded, by the emerging notion of the holobiont, which defines the genetic and metabolic networks of the host and its microbes as a single evolutionary unit. Several concepts originally developed to study ecosystems, can be used to understand the physiology and evolution of such complex systems that constitute "individuals." In this review, we discus...
Adaptive resistance to antibiotics in bacteria: a systems biology perspective
Wiley interdisciplinary reviews. Systems biology and medicine, 2016
Despite all the major breakthroughs in antibiotic development and treatment procedures, there is ... more Despite all the major breakthroughs in antibiotic development and treatment procedures, there is still no long-term solution to the bacterial antibiotic resistance problem. Among all the known types of resistance, adaptive resistance (AdR) is particularly inconvenient. This phenotype is known to emerge as a consequence of concentration gradients, as well as contact with subinhibitory concentrations of antibiotics, both known to occur in human patients and livestock. Moreover, AdR has been repeatedly correlated with the appearance of multidrug resistance, although the biological processes behind its emergence and evolution are not well understood. Epigenetic inheritance, population structure and heterogeneity, high mutation rates, gene amplification, efflux pumps, and biofilm formation have all been reported as possible explanations for its development. Nonetheless, these concepts taken independently have not been sufficient to prevent AdR's fast emergence or to predict its low s...
Inferred table of regulation
International Journal of Modern Physics B, 2009
In this work, we consider the phase transition from ordered to disordered states that occur in th... more In this work, we consider the phase transition from ordered to disordered states that occur in the Vicsek model of self-propelled particles. This model was proposed to describe the emergence of collective order in swarming systems. When noise is added to the motion of the particles, the onset of collective order occurs through a dynamical phase transition. Based on their numerical results, Vicsek and his colleagues originally concluded that this phase transition was of second order (continuous). However, recent numerical evidence seems to indicate that the phase transition might be of first order (discontinuous), thus challenging Vicsek's original results. In this work, we review the evidence supporting both aspects of this debate. We also show new numerical results indicating that the apparent discontinuity of the phase transition may in fact be a numerical artifact produced by the artificial periodicity of the boundary conditions.
PLOS ONE, 2015
Adaptive resistance emerges when populations of bacteria are subjected to gradual increases of an... more Adaptive resistance emerges when populations of bacteria are subjected to gradual increases of antibiotics. It is characterized by a rapid emergence of resistance and fast reversibility to the non-resistant phenotype when the antibiotic is removed from the medium. Recent work shows that adaptive resistance requires epigenetic inheritance and heterogeneity of gene expression patterns that are, in particular, associated with the production of porins and efflux pumps. However, the precise mechanisms by which inheritance and variability govern adaptive resistance, and what processes cause its reversibility remain unclear. Here, using an efflux pump regulatory network (EPRN) model, we show that the following three mechanisms are essential to obtain adaptive resistance in a bacterial population: 1) intrinsic variability in the expression of the EPRN transcription factors; 2) epigenetic inheritance of the transcription rate of EPRN associated genes; and 3) energetic cost of the efflux pumps activity that slows down cell growth. While the first two mechanisms acting together are responsible for the emergence and gradual increase of the resistance, the third one accounts for its reversibility. In contrast with the standard assumption, our model predicts that adaptive resistance cannot be explained by increased mutation rates. Our results identify the molecular mechanism of epigenetic inheritance as the main target for therapeutic treatments against the emergence of adaptive resistance. Finally, our theoretical framework unifies known and newly identified determinants such as the burden of efflux pumps that underlie bacterial adaptive resistance to antibiotics.
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Papers by Maximino Aldana