Virus-host protein co-expression networks reveal temporal organization and strategies of viral infection

Viral replication is a complex dynamical process involving the global remodeling of the host cellular machinery across several stages. In this study, we provide a unified view of the virus-host interaction at the proteome level reconstructing protein co-expression networks from quantitative temporal data of four large DNA viruses. We take advantage of a formal framework, the theory of competing networks, to describe the viral infection as a dynamical system taking place on a network of networks where perturbations induced by viral proteins spread to hijack the host proteome for the virus benefit. Our methodology demonstrates how the viral replication cycle can be effectively examined as a complex interaction between protein networks, providing useful insights into the viral and host's temporal organization and strategies, key protein nodes targeted by the virus and dynamical bottlenecks during the course of the infectionThe authors acknowledge technical assistance from I. Pérez-Jover, S. Backlund, and M. Sierra-González, and fruitful discussions with J. M. Buldú, J. García-Ojalvo, J. Iranzo and A. Pons. J.A. and R.G. received support from grant No. PID2021-122936NB-I00 and J.A. from grant No. MDM-2017-0737 Unidad de Excelencia ‘‘María de Maeztu’’ - Centro de Astrobiología (CSIC-INTA), all of them funded by the Spanish Ministry of Science and Innovation/State Agency of Research MCIN/AEI/10.13039/501100011033 and by ‘‘ERDF A way of making Europe’

Dynamical community structure of populations evolving on genotype networks

Neutral evolutionary dynamics of replicators occurs on large and heterogeneous networks of genotypes. These networks, formed by all genotypes that yield the same phenotype, have a complex architecture that conditions the molecular composition of populations and their movements on genome spaces. Here we consider as an example the case of populations evolving on RNA secondary structure neutral networks and study the community structure of the network revealed through dynamical properties of the population at equilibrium and during adaptive transients. We unveil a rich hierarchical community structure that, eventually, can be traced back to the non-trivial relationship between RNA secondary structure and sequence composition. We demonstrate that usual measures of modularity that only take into account the static, topological structure of networks, cannot identify the community structure disclosed by population dynamics.This study has been supported by project FIS2011-27569 from the Spanish Ministry of Economy and Competitivity.Publicad

Taming out-of-equilibrium dynamics on interconnected networks

A wide variety of social, biological or technological systems can be described as processes taking place on networked structures in continuous interaction with other networks. We propose here a new methodology to describe, anticipate and manage, in real time, the out-of-equilibrium dynamics of processes that evolve on interconnected networks. This goal is achieved through the full analytical treatment of the phenomenology and its reduction to a two-dimensional flux diagram, allowing us to predict at every time step the dynamical consequences of modifying the links between the different ensembles. Our results are consistent with real data and the methodology can be translated to clustered networks and/or interconnected networks of any size, topology or origin, from the struggle for knowledge on innovation structures to international economic relations or disease spreading on social groups.Ministerio de Economía y Competitividad; Comunidad de Madri

On the networked architecture of genotype spaces and its critical effects on molecular evolution

Evolutionary dynamics is often viewed as a subtle process of change accumulation that causes a divergence among organisms and their genomes. However, this interpretation is an inheritance of a gradualistic view that has been challenged at the macroevolutionary, ecological and molecular level. Actually, when the complex architecture of genotype spaces is taken into account, the evolutionary dynamics of molecular populations becomes intrinsically non-uniform, sharing deep qualitative and quantitative similarities with slowly driven physical systems: nonlinear responses analogous to critical transitions, sudden state changes or hysteresis, among others. Furthermore, the phenotypic plasticity inherent to genotypes transforms classical fitness landscapes into multiscapes where adaptation in response to an environmental change may be very fast. The quantitative nature of adaptive molecular processes is deeply dependent on a network-of-networks multilayered structure of the map from genotype to function that we begin to unveil.This work has been supported by the Spanish Ministerio de Economía y Competitividad and FEDER funds of the EU through grants ViralESS (FIS2014-57686-P) and VARIANCE (FIS2015-64349-P). J.A. is supported through grant no. SEV-2013-0347. P.C. is supported through the European Union's YEI funds

The struggle for space: Viral extinction through competition for cells

The design of protocols to suppress the propagation of viral infections is an enduring enterprise, especially hindered by limited knowledge of the mechanisms through which extinction of infection propagation comes about. We here report on a mechanism causing extinction of a propagating infection due to intraspecific competition to infect susceptible hosts. Beneficial mutations allow the pathogen to increase the production of progeny, while the host cell is allowed to develop defenses against infection. When the number of susceptible cells is unlimited, a feedback runaway co-evolution between host resistance and progeny production occurs. However, physical space limits the advantage that the virus can obtain from increasing offspring numbers, thus infection clearance may result from an increase in host defenses beyond a finite threshold. Our results might be relevant to better understand propagation of viral infections in tissues with mobility constraints, and the implications that environments with different geometrical properties might have in devising control strategies.Comment: 4 pages, 3 figures Accepted for publication in Physical Review Letter

Epistasis between cultural traits causes paradigm shifts in cultural evolution

Every now and then the cultural paradigm of a society changes. While current models of cultural shifts usually require a major exogenous or endogenous change, we propose that the mechanism underlying many paradigm shifts may just be an emergent feature of the inherent congruence among different cultural traits. We implement this idea through a population dynamics model in which individuals are defined by a vector of cultural traits that changes mainly through cultural contagion, biased by a 'cultural fitness' landscape, between contemporary individuals. Cultural traits reinforce or hinder each other (through a form of cultural epistasis) to prevent cognitive dissonance. Our main result is that abrupt paradigm shifts occur, in response to weak changes in the landscape, only in the presence of epistasis between cultural traits, and regardless of whether horizontal transmission is biased by homophily. A relevant consequence of this dynamics is the irreversible nature of paradigm shifts: the old paradigm cannot be restored even if the external changes are undone. Our model puts the phenomenon of paradigm shifts in cultural evolution in the same category as catastrophic shifts in ecology or phase transitions in physics, where minute causes lead to major collective changes.This work was supported by the Spanish projects VARIANCE (FIS2015-64349-P, MINECO/FEDER, UE), BASIC (FIS2018-098186-B-100, MICINN/FEDER, UE), MiMevo (FIS2017-89773-P, MINECO/FEDER, UE) and SEV-2013-0347 (MINECO).Publicad

The emergence of interstellar molecular complexity explained by interacting networks

Recent years have witnessed the detection of an increasing number of complex organicmolecules in interstellar space, some of them being of prebiotic interest. Disentanglingthe origin of interstellar prebiotic chemistry and its connection to biochemistry andultimately, to biology is an enormously challenging scientific goal where the applicationof complexity theory and network science has not been fully exploited. Encouragedby this idea, we present a theoretical and computational framework to model theevolution of simple networked structures toward complexity. In our environment,complex networks represent simplified chemical compounds and interact optimizing thedynamical importance of their nodes. We describe the emergence of a transition fromsimple networks toward complexity when the parameter representing the environmentreaches a critical value. Notably, although our system does not attempt to model the rulesof real chemistry nor is dependent on external input data, the results describe the emer-gence of complexity in the evolution of chemical diversity in the interstellar medium.Furthermore, they reveal an as yet unknown relationship between the abundances ofmolecules in dark clouds and the potential number of chemical reactions that yieldthem as products, supporting the ability of the conceptual framework presented here toshed light on real scenarios. Our work reinforces the notion that some of the propertiesthat condition the extremely complex journey from the chemistry in space to prebioticchemistry and finally, to life could show relatively simple and universal patterns

Entropic contribution to phenotype fitness

All possible phenotypes are not equally accessible to evolving populations. In fact, only phenotypes of large size, i.e. those resulting from many different genotypes, are found in populations of sequences, presumably because they are easier to discover and maintain. Genotypes that map to these phenotypes usually form mostly connected genotype networks that percolate the space of sequences, thus guaranteeing access to a large set of alternative phenotypes. Within a given environment, where specific phenotypic traits become relevant for adaptation, the replicative ability of a phenotype and its overall fitness (in competition experiments with alternative phenotypes) can be estimated. Two primary questions arise: how do phenotype size, reproductive capability and topology of the genotype network affect the fitness of a phenotype? And, assuming that evolution is only able to access large phenotypes, what is the range of unattainable fitness values? In order to address these questions, we quantify the adaptive advantage of phenotypes of varying size and spectral radius in a two-peak landscape. We derive analytical relationships between the three variables (size, topology, and replicative ability) which are then tested through analysis of genotype-phenotype maps and simulations of population dynamics on such maps. Finally, we analytically show that the fraction of attainable phenotypes decreases with the length of the genotype, though its absolute number increases. The fact that most phenotypes are not visible to evolution very likely forbids the attainment of the highest peak in the landscape. Nevertheless, our results indicate that the relative fitness loss due to this limited accessibility is largely inconsequential for adaptation.Comment: 25 pages, 10 figures, uses iopart.cls, iopart10.clo, iopart12.clo, iopams.sty, setstack.st