Proyecto de Investigación: MECANISMOS MICROSCOPICOS TRAS LA EVOLUCION RAPIDA: PAISAJES ADAPTATIVOS, CARRERAS DE ARMAS Y REDES DE COMPARTICION DE GENES
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FIS2017-89773-P
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Intra-Population Competition during Adaptation to Increased Temperature in an RNA Bacteriophage
(Multidisciplinary Digital Publishing Institute (MDPI), 2021-06-24) Arribas, M.; Lázaro, E.; Agencia Estatal de Investigación (AEI); Lázaro, E. [0000-0001-7477-7822]; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
Evolution of RNA bacteriophages of the family Leviviridae is governed by the high error rates of their RNA-dependent RNA polymerases. This fact, together with their large population sizes, leads to the generation of highly heterogeneous populations that adapt rapidly to most changes in the environment. Throughout adaptation, the different mutants that make up a viral population compete with each other in a non-trivial process in which their selective values change over time due to the generation of new mutations. In this work we have characterised the intra-population dynamics of a well-studied levivirus, Qβ, when it is propagated at a higher-than-optimal temperature. Our results show that adapting populations experienced rapid changes that involved the ascent of particular genotypes and the loss of some beneficial mutations of early generation. Artificially reconstructed populations, containing a fraction of the diversity present in actual populations, fixed mutations more rapidly, illustrating how population bottlenecks may guide the adaptive pathways. The conclusion is that, when the availability of beneficial mutations under a particular selective condition is elevated, the final outcome of adaptation depends more on the occasional occurrence of population bottlenecks and how mutations combine in genomes than on the selective value of particular mutations.
Emergence of complex socioeconomic networks driven by individual and collective interests
(APS Physics, 2020-12-09) Iranzo, Jaime; Martí, Federico Pablo; Aguirre, Jacobo; Agencia Estatal de Investigacion (AEI); 0000-0003-2196-5103; [0000-0002-0633-6985; Centros de Excelencia Severo Ochoa, CENTRO NACIONAL DE BIOTECNOLOGIA (CNB), SEV-2017-0712; Centros de Excelencia Severo Ochoa, CENTRO DE BIOTECNOLOGIA Y GENOMICA DE PLANTAS (CBGP), SEV-2016-0672; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
The basic mechanisms that lead to the creation of complex socioeconomic structures remain poorly understood. A combination of network science and game theory can help explain them by examining how simple networks interact to build complex entities, both when connections among individuals are exclusively guided by self-interest or when they result from a mixture of individual and collective motivations. Here we present a theoretical framework where individuals or human groups from different communities connect to each other only if they increase their own eigenvector centrality, a topological measure of wide applications in many different contexts that quantifies the importance of a node within the network. Our analytical and numerical results show that the emergence of interconnected networks is catalyzed by the self-interest of peripheral agents, who are penalized in the long run but transiently benefit from establishing links with nodes from other communities. Moreover, the interconnection process leads to a hierarchical, assortative, and very efficient structure where links across networks involve nodes of the same importance. These findings are robust to the introduction of moderate levels of collective-oriented behavior and compatible with the interconnection dynamics observed in real-world socioeconomic networks.
The resumption of sports competitions after COVID-19 lockdown: The case of the Spanish football league
(Elsevier BV, 2020-06-04) Buldú, J. M.; Antequera, D. R.; Aguirre, Jacobo; Comunidad de Madrid; Agencia Estatal de Investigación (AEI); Budú, J. M. [0000-0002-9345-599X]; Jacobo, A. [0000-0003-2196-5103]; Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737
In this work, we present a stochastic discrete-time SEIR Susceptible-Exposed-Infectious-Recoveredmodel adapted to describe the propagation of COVID-19 during a football tournament. Specifically, we are concerned about the re-start of the Spanish national football league, La Liga, which is currently –May 2020– stopped with 11 fixtures remaining. Our model includes two additional states of an individual, confined and quarantined, which are reached when an individual presents COVID-19 symptoms or has undergone a virus test with a positive result. The model also accounts for the interaction dynamics of players, considering three different sources of infection: the player social circle, the contact with his/her team colleagues during training sessions, and the interaction with rivals during a match. Our results highlight the influence of the days between matches, the frequency of virus tests and their sensitivity on the number of players infected at the end of the season. Following our findings, we finally propose a variety of strategies to minimise the probability that COVID-19 propagates in case the season of La Liga was re-started after the current lockdown.
A Multiplex Immunosensor for Detecting Perchlorate-Reducing Bacteria for Environmental Monitoring and Planetary Exploration
(Extreme Microbiology, 2020-12-16) Gallardo Carreño, Ignacio; Moreno Paz, M.; Aguirre, Jacobo; Blanco, Yolanda; Alonso Pintado, Eduardo; Raymond Bouchard, Isabelle; Maggiori, Catherine; Rivas, Luis A.; Engelbrektson, Anna; Whyte, Lyle; Parro García, V.; Ministerio de Economía y Competitividad (MINECO); Agencia Estatal de Investigación (AEI); Ministerio de Ciencia e Innovación (MICINN); Unidad de Excelencia Científica María de Maeztu Centro de Astrobiología del Instituto Nacional de Técnica Aeroespacial y CSIC, MDM-2017-0737; Centros de Excelencia Severo Ochoa, CENTRO NACIONAL DE BIOTECNOLOGIA (CNB), SEV-2017-0712
Perchlorate anions are produced by chemical industries and are important contaminants in certain natural ecosystems. Perchlorate also occurs in some natural and uncontaminated environments such as the Atacama Desert, the high Arctic or the Antarctic Dry Valleys, and is especially abundant on the surface of Mars. As some bacterial strains are capable of using perchlorate as an electron acceptor under anaerobic conditions, their detection is relevant for environmental monitoring on Earth as well as for the search for life on Mars. We have developed an antibody microarray with 20 polyclonal antibodies to detect perchlorate-reducing bacteria (PRB) strains and two crucial and highly conserved enzymes involved in perchlorate respiration: perchlorate reductase and chlorite dismutase. We determined the cross-reactivity, the working concentration, and the limit of detection of each antibody individually and in a multiplex format by Fluorescent Sandwich Microarray Immunoassay. Although most of them exhibited relatively high sensitivity and specificity, we applied a deconvolution method based on graph theory to discriminate between specific signals and cross-reactions from related microorganisms. We validated the system by analyzing multiple bacterial isolates, crude extracts from contaminated reactors and salt-rich natural samples from the high Arctic. The PRB detecting chip (PRBCHIP) allowed us to detect and classify environmental isolates as well as to detect similar strains by using crude extracts obtained from 0.5 g even from soils with low organic-matter levels (<103 cells/g of soil). Our results demonstrated that PRBCHIP is a valuable tool for sensitive and reliable detection of perchlorate-reducing bacteria for research purposes, environmental monitoring and planetary exploration.
