Instituto de Biocomputación y Física de Sistemas Complejos

During interphase chromosomes decondense, but fluorescent in situ hybridization experiments reveal the existence of distinct territories occupied by individual chromosomes inside the nuclei of most eukaryotic cells. We use computer simulations to show that the existence and stability of territories is a kinetic effect that can be explained without invoking an underlying nuclear scaffold or protein-mediated interactions between DNA sequences. In particular, we show that the experimentally observed territory shapes and spatial distances between marked chromosome sites for human, Drosophila, and budding yeast chromosomes can be reproduced by a parameter-free minimal model of decondensing chromosomes. Our results suggest that the observed interphase structure and dynamics are due to generic polymer effects: confined Brownian motion conserving the local topological state of long chain molecules and segregation of mutually unentangled chains due to topological constraints.

Real-space grids are a powerful alternative for the simulation of electronic systems. One of the main advantages of the approach is the flexibility and simplicity of working directly in real space where the different fields are discretized on a grid, combined with competitive numerical performance and great potential for parallelization. These properties constitute a great advantage at the time of implementing and testing new physical models. Based on our experience with the Octopus code, in this article we discuss how the real-space approach has allowed for the recent development of new ideas for the simulation of electronic systems. Among these applications are approaches to calculate response properties, modeling of photoemission, optimal control of quantum systems, simulation of plasmonic systems, and the exact solution of the Schrödinger equation for low-dimensionality systems.

In spite of its relevance to the origin of complex networks, the interplay between form and function and its role during network formation remains largely unexplored. While recent studies introduce dynamics by considering rewiring processes of a pre-existent network, we study network growth and formation by proposing an evolutionary preferential attachment model, its main feature being that the capacity of a node to attract new links depends on a dynamical variable governed in turn by the node interactions. As a specific example, we focus on the problem of the emergence of cooperation by analyzing the formation of a social network with interactions given by the Prisoner's Dilemma. The resulting networks show many features of real systems, such as scale-free degree distributions, cooperative behavior and hierarchical clustering. Interestingly, results such as the cooperators being located mostly on nodes of intermediate degree are very different from the observations of cooperative behavior on static networks. The evolutionary preferential attachment mechanism points to an evolutionary origin of scale-free networks and may help understand similar feedback problems in the dynamics of complex networks by appropriately choosing the game describing the interaction of nodes.

The ionization probability of ${\mathrm{N}}_{2}$, ${\mathrm{O}}_{2}$, and ${\mathrm{CO}}_{2}$ in intense laser fields is studied theoretically as a function of the alignment angle by solving the time-dependent Schr\"odinger equation numerically assuming only the single-active-electron approximation. The results are compared to recent experimental data [D. Pavi\ifmmode \check{c}\else \v{c}\fi{}i\ifmmode \acute{c}\else \'{c}\fi{} et al., Phys. Rev. Lett. 98, 243001 (2007)] and good agreement is found for ${\mathrm{N}}_{2}$ and ${\mathrm{O}}_{2}$. For ${\mathrm{CO}}_{2}$ a possible explanation is provided for the failure of simplified single-active-electron models to reproduce the experimentally observed narrow ionization distribution. It is based on a field-induced coherent core-trapping effect.

Oxidative conversion of 5-hydroxymethylfurfural (HMF) is of biotechnological interest for the production of renewable (lignocellulose-based) platform chemicals, such as 2,5-furandicarboxylic acid (FDCA). To the best of our knowledge, the ability of fungal aryl-alcohol oxidase (AAO) to oxidize HMF is reported here for the first time, resulting in almost complete conversion into 2,5-formylfurancarboxylic acid (FFCA) in a few hours. The reaction starts with alcohol oxidation, yielding 2,5-diformylfuran (DFF), which is rapidly converted into FFCA by carbonyl oxidation, most probably without leaving the enzyme active site. This agrees with the similar catalytic efficiencies of the enzyme with respect to oxidization of HMF and DFF, and its very low activity on 2,5-hydroxymethylfurancarboxylic acid (which was not detected by GC-MS). However, AAO was found to be unable to directly oxidize the carbonyl group in FFCA, and only modest amounts of FDCA are formed from HMF (most probably by chemical oxidation of FFCA by the H2 O2 previously generated by AAO). As aldehyde oxidation by AAO proceeds via the corresponding geminal diols (aldehyde hydrates), the various carbonyl oxidation rates may be related to the low degree of hydration of FFCA compared with DFF. The conversion of HMF was completed by introducing a fungal unspecific heme peroxygenase that uses the H2 O2 generated by AAO to transform FFCA into FDCA, albeit more slowly than the previous AAO reactions. By adding this peroxygenase when FFCA production by AAO has been completed, transformation of HMF into FDCA may be achieved in a reaction cascade in which O2 is the only co-substrate required, and water is the only by-product formed.

We compare the structural properties of the street networks of ten different European cities using their primal representation. We investigate the properties of the geometry of the networks and a set of centrality measures highlighting differences and similarities between cases. In particular, we found that cities share structural similarities due to their quasiplanarity but that there are also several distinctive geometrical properties. A principal component analysis is performed on the distributions of centralities and their respective moments, which is used to find distinctive characteristics by which we can classify cities into families. We believe that, beyond the improvement of the empirical knowledge on streets' network properties, our findings can open new perspectives into the scientific relationship between city planning and complex networks, stimulating the debate on the effectiveness of the set of knowledge that statistical physics can contribute for city planning and urban-morphology studies.

A new "on the fly" method to perform Born-Oppenheimer ab initio molecular dynamics (AIMD) simulations is presented. Inspired by Ehrenfest dynamics in time-dependent density functional theory, the electronic orbitals are evolved by a Schrödinger-like equation, where the orbital time derivative is multiplied by a parameter. This parameter controls the time scale of the fictitious electronic motion and speeds up the calculations with respect to standard Ehrenfest dynamics. In contrast with other methods, wave function orthogonality needs not be imposed as it is automatically preserved, which is of paramount relevance for large-scale AIMD simulations.

We propose a theoretical framework for the study of epidemics in structured metapopulations, with heterogeneous agents, subjected to recurrent mobility patterns. We propose to represent the heterogeneity in the composition of the metapopulations as layers in a multiplex network, where nodes would correspond to geographical areas and layers account for the mobility patterns of agents of the same class. We analyze both the classical Susceptible-Infected-Susceptible and the Susceptible-Infected-Removed epidemic models within this framework, and compare macroscopic and microscopic indicators of the spreading process with extensive Monte Carlo simulations. Our results are in excellent agreement with the simulations. We also derive an exact expression of the epidemic threshold on this general framework revealing a non-trivial dependence on the mobility parameter. Finally, we use this new formalism to address the spread of diseases in real cities, specifically in the city of Medellin, Colombia, whose population is divided into six socio-economic classes, each one identified with a layer in this multiplex formalism.

Low-temperature properties of crystalline solids can be understood using harmonic perturbations around a perfect lattice, as in Debye's theory. Low-temperature properties of amorphous solids, however, strongly depart from such descriptions, displaying enhanced transport, activated slow dynamics across energy barriers, excess vibrational modes with respect to Debye's theory (i.e., a boson peak), and complex irreversible responses to small mechanical deformations. These experimental observations indirectly suggest that the dynamics of amorphous solids becomes anomalous at low temperatures. Here, we present direct numerical evidence that vibrations change nature at a well-defined location deep inside the glass phase of a simple glass former. We provide a real-space description of this transition and of the rapidly growing time- and lengthscales that accompany it. Our results provide the seed for a universal understanding of low-temperature glass anomalies within the theoretical framework of the recently discovered Gardner phase transition.

Abstract. Community definitions usually focus on edges, inside and between the communities. However, the high density of edges within a community determines correlations between nodes going beyond nearest-neighbours, and which are indicated by the presence of motifs. We show how motifs can be used to define general classes of nodes, including communities, by extending the mathematical expression of Newman-Girvan modularity. We construct then a general framework and apply it to some synthetic and real networks. PACS number: 89.75 ‡ Author to whom any correspondence should be addressedMotif-based communities in complex networks 2

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 ${T}_{\mathrm{c}}=1.1019(29)$ for the critical temperature, $\ensuremath{\nu}=2.562(42)$ for the thermal exponent, $\ensuremath{\eta}=\ensuremath{-}0.3900(36)$ for the anomalous dimension, and $\ensuremath{\omega}=1.12(10)$ for the exponent of the leading corrections to scaling. Standard (hyper)scaling relations yield $\ensuremath{\alpha}=\ensuremath{-}5.69(13)$, $\ensuremath{\beta}=0.782(10)$, and $\ensuremath{\gamma}=6.13(11)$. We also compute several universal quantities at ${T}_{\mathrm{c}}$.

Combining high-resolution single cell tracking experiments with numerical simulations, we show that starvation-induced fruiting body formation in Myxococcus xanthus is a phase separation driven by cells that tune their motility over time. The phase separation can be understood in terms of cell density and a dimensionless Péclet number that captures cell motility through speed and reversal frequency. Our work suggests that M. xanthus takes advantage of a self-driven nonequilibrium phase transition that can be controlled at the single cell level.

According to the mosaic scenario, relaxation in supercooled liquids is ruled by two competing mechanisms: surface tension, opposing the creation of local excitations, and entropy, providing the drive to the configurational rearrangement of a given region. We test this scenario through numerical simulations well below the Mode Coupling temperature. For an equilibrated configuration, we freeze all the particles outside a sphere and study the thermodynamics of this sphere. The frozen environment acts as a pinning field. Measuring the overlap between the unpinned and pinned equilibrium configurations of the sphere, we can see whether it has switched to a different state. We do not find any clear evidence of the mosaic scenario. Rather, our results seem compatible with the existence of a single (liquid) state. However, we find evidence of a growing static correlation length, apparently unrelated to the mosaic one.

Spectral and catalytic properties of the flavoenzyme AAO (aryl-alcohol oxidase) from Pleurotus eryngii were investigated using recombinant enzyme. Unlike most flavoprotein oxidases, AAO does not thermodynamically stabilize a flavin semiquinone radical and forms no sulphite adduct. AAO catalyses the oxidative dehydrogenation of a wide range of unsaturated primary alcohols with hydrogen peroxide production. This differentiates the enzyme from VAO (vanillyl-alcohol oxidase), which is specific for phenolic compounds. Moreover, AAO is optimally active in the pH range of 5-6, whereas VAO has an optimum at pH 10. Kinetic studies showed that AAO is most active with p-anisyl alcohol and 2,4-hexadien-1-ol. AAO converts m- and p-chlorinated benzyl alcohols at a similar rate as it does benzyl alcohol, but introduction of a p-methoxy substituent in benzyl alcohol increases the reaction rate approx. 5-fold. AAO also exhibits low activity on aromatic aldehydes. 19F NMR analysis showed that fluorinated benzaldehydes are converted into the corresponding benzoic acids. Inhibition studies revealed that the AAO active site can bind a wide range of aromatic ligands, chavicol (4-allylphenol) and p-anisic (4-methoxybenzoic) acid being the best competitive inhibitors. Uncompetitive inhibition was observed with 4-methoxybenzylamine. The properties described above render AAO a unique oxidase. The possible mechanism of AAO binding and oxidation of substrates is discussed in the light of the results of the inhibition and kinetic studies.

We study numerically the nonequilibrium dynamics of the Ising spin glass, for a time spanning 11 orders of magnitude, thus approaching the experimentally relevant scale (i.e., seconds). We introduce novel analysis techniques to compute the coherence length in a model-independent way. We present strong evidence for a replicon correlator and for overlap equivalence. The emerging picture is compatible with noncoarsening behavior.

Different members of the Mycobacterium genus have evolved to cause tuberculosis in diverse human populations and in a variety of animal species. Our cumulative knowledge of mycobacterial genomes indicates that mutations in the PhoPR two-component virulence system were acquired not only during the natural evolution of mycobacterial species but also during in vitro subculture, which has given rise to the attenuated reference strain H37Ra or to different daughter strains of Mycobacterium bovis BCG. PhoPR is a well-known regulator of pathogenic phenotypes, including secretion of the virulence factor ESAT-6, biosynthesis of acyltrehalose-based lipids, and modulation of antigen export, in members of the Mycobacterium tuberculosis complex (MTBC). Evolutionarily conserved polymorphisms in PhoPR from Mycobacterium africanum, M. bovis, or M. tuberculosis H37Ra result in loss of functional phenotypes. Interestingly, some members of the MTBC have acquired compensatory mutations to counteract these polymorphisms and, probably, to maintain their pathogenic potential. Some of these compensatory mutations include the insertion of the IS6110 element upstream from phoPR in a particular M. bovis strain that is able to transmit between humans or polymorphisms in M. africanum and M. bovis that affect the regulatory region of the espACD operon, allowing PhoPR-independent ESAT-6 secretion. This review highlights the increasing knowledge of the significance of PhoPR in the evolution of the MTBC and its potential application in the construction of new attenuated vaccines based on phoPR inactivation. In this context, the live attenuated vaccine MTBVAC, based on a phoP fadD26 deletion mutant of M. tuberculosis, is the first vaccine of this kind to successfully enter into clinical development, representing a historic milestone in the field of human vaccinology.

Janus is a modular, massively parallel, and reconfigurable FPGA-based computing system. Each Janus module has one computational core and one host. Janus is tailored to, but not limited to, the needs of a class of hard scientific applications characterized by regular code structure, unconventional data-manipulation requirements, and a few Megabits database. The authors discuss this configurable system's architecture and focus on its use for Monte Carlo simulations of statistical mechanics, as Janus performs impressively on this class of application.

The occurrence of free-living amoebae (FLA) was investigated in 83 water samples from reservoirs and water treatment plants, with culture positive in 64 of them (77.1%). Polymerase chain reaction (PCR) of partial 18S rRNA gene and ITS region was performed in order to identify amoeba isolates, and the presence of Legionella pneumophila , Mycobacterium spp., Pseudomonas spp., and Microcystis aeruginosa was investigated in 43 isolates of amoebae by multiplex PCR. Of the isolated amoebae, 31 were Acanthamoeba spp., 21 were Hartmannella vermiformis, 13 were Naegleria spp., and one was Vanella spp. T2, T4, and T5 genotypes of Acanthamoeba have been identified, and T4 isolates were grouped into five subgenotypes and graphically represented with a Weblog application. Inside amoebae, L. pneumophila was detected in 13.9% (6/43) of the isolates, and Pseudomonas spp. and Mycobacterium spp. were detected in 32.6% (14/43) and 41.9% (18/43), respectively. No statistical correlation was demonstrated between FLA isolation and seasonality, but the presence of intracellular bacteria was associated with warm water temperatures, and also the intracellular presence of Mycobacterium spp. and Pseudomonas spp. were associated. These results highlight the importance of amoebae in natural waters as reservoirs of potential pathogens and its possible role in the spread of bacterial genera with interest in public and environmental health.

We present a tethered Monte Carlo simulation of the crystallization of hard spheres. Our method boosts the traditional umbrella sampling to the point of making practical the study of constrained Gibbs' free energies depending on several crystalline order parameters. We obtain high-accuracy estimates of the fluid-crystal coexistence pressure for up to 2916 particles (enough to accommodate fluid-solid interfaces). We are able to extrapolate to infinite volume the coexistence pressure [p(co)=11.5727(10)k(B)T/σ(3)] and the interfacial free energy [γ({100})=0.636(11)k(B)T/σ(2)].

The modeling of large-scale communicable epidemics has greatly benefited in the last years from the increasing availability of highly detailed data. Particullarly, in order to achieve quantitative descriptions of the evolution of epidemics, contact networks and mixing patterns are key. These heterogeneous patterns depend on several factors such as location, socioeconomic conditions, time, and age. This last factor has been shown to encapsulate a large fraction of the observed inter-individual variation in contact patterns, an observation validated by different measurements of age-dependent contact matrices. Recently, several works have studied how to project those matrices to areas where empirical data are not available. However, the dependence of contact matrices on demographic structures and their time evolution has been largely neglected. In this work, we tackle the problem of how to transform an empirical contact matrix that has been obtained for a given demographic structure into a different contact matrix that is compatible with a different demography. The methodology discussed here allows to extrapolate a contact structure measured in a particular area to any other whose demographic structure is known, as well as to obtain the time evolution of contact matrices as a function of the demographic dynamics of the populations they refer to. To quantify the effect of considering time-dynamics of contact patterns on disease modeling, we implemented a Susceptible-Exposed-Infected-Recovered (SEIR) model on 16 different countries and regions and evaluated the impact of neglecting the temporal evolution of mixing patterns. Our results show that simulated disease incidence rates, both at the aggregated and age-specific levels, are significantly dependent on contact structures variation driven by demographic evolution. The present work opens the path to eliminate technical biases from model-based impact evaluations of future epidemic threats and warns against the use of contact matrices to model diseases without correcting for demographic evolution or geographic variations.