The A-kinase anchoring protein (AKAP)-Lbc-signaling complex mediates alpha1 adrenergic receptor-induced cardiomyocyte hypertrophy.

In response to various pathological stresses, the heart undergoes a pathological remodeling process that is associated with cardiomyocyte hypertrophy. Because cardiac hypertrophy can progress to heart failure, a major cause of lethality worldwide, the intracellular signaling pathways that control cardiomyocyte growth have been the subject of intensive investigation. It has been known for more than a decade that the small molecular weight GTPase RhoA is involved in the signaling pathways leading to cardiomyocyte hypertrophy. Although some of the hypertrophic pathways activated by RhoA have now been identified, the identity of the exchange factors that modulate its activity in cardiomyocytes is currently unknown. In this study, we show that AKAP-Lbc, an A-kinase anchoring protein (AKAP) with an intrinsic Rho-specific guanine nucleotide exchange factor activity, is critical for activating RhoA and transducing hypertrophic signals downstream of alpha1-adrenergic receptors (ARs). In particular, our results indicate that suppression of AKAP-Lbc expression by infecting rat neonatal ventricular cardiomyocytes with lentiviruses encoding AKAP-Lbc-specific short hairpin RNAs strongly reduces both alpha1-AR-mediated RhoA activation and hypertrophic responses. Interestingly, alpha1-ARs promote AKAP-Lbc activation via a pathway that requires the alpha subunit of the heterotrimeric G protein G12. These findings identify AKAP-Lbc as the first Rho-guanine nucleotide exchange factor (GEF) involved in the signaling pathways leading to cardiomyocytes hypertrophy.

Movement, impacts and management of plant distributions in response to climate change: insights from invasions

A major challenge in this era of rapid climate change is to predict changes in species distributions and their impacts on ecosystems, and, if necessary, to recommend management strategies for maintenance of biodiversity or ecosystem services. Biological invasions, studied in most biomes of the world, can provide useful analogs for some of the ecological consequences of species distribution shifts in response to climate change. Invasions illustrate the adaptive and interactive responses that can occur when species are confronted with new environmental conditions. Invasion ecology complements climate change research and provides insights into the following questions: i) how will species distributions respond to climate change? ii) how will species movement affect recipient ecosystems? and iii) should we, and if so how can we, manage species and ecosystems in the face of climate change? Invasion ecology demonstrates that a trait-based approach can help to predict spread speeds and impacts on ecosystems, and has the potential to predict climate change impacts on species ranges and recipient ecosystems. However, there is a need to analyse traits in the context of life-history and demography, the stage in the colonisation process (e.g., spread, establishment or impact), the distribution of suitable habitats in the landscape, and the novel abiotic and biotic conditions under which those traits are expressed. As is the case with climate change, invasion ecology is embedded within complex societal goals. Both disciplines converge on similar questions of "when to intervene?" and "what to do?" which call for a better understanding of the ecological processes and social values associated with changing ecosystems.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

A coiled coil trigger site is essential for rapid binding of synaptobrevin to the SNARE acceptor complex.

Exocytosis from synaptic vesicles is driven by stepwise formation of a tight alpha-helical complex between the fusing membranes. The complex is composed of the three SNAREs: synaptobrevin 2, SNAP-25, and syntaxin 1a. An important step in complex formation is fast binding of vesicular synaptobrevin to the preformed syntaxin 1.SNAP-25 dimer. Exactly how this step relates to neurotransmitter release is not well understood. Here, we combined different approaches to gain insights into this reaction. Using computational methods, we identified a stretch in synaptobrevin 2 that may function as a coiled coil "trigger site." This site is also present in many synaptobrevin homologs functioning in other trafficking steps. Point mutations in this stretch inhibited binding to the syntaxin 1.SNAP-25 dimer and slowed fusion of liposomes. Moreover, the point mutations severely inhibited secretion from chromaffin cells. Altogether, this demonstrates that the trigger site in synaptobrevin is crucial for productive SNARE zippering.

Pivotal role for a tail subunit of the RNA polymerase II mediator complex CgMed2 in azole tolerance and adherence in Candida glabrata.

Antifungal therapy failure can be associated with increased resistance to the employed antifungal agents. Candida glabrata, the second most common cause of invasive candidiasis, is intrinsically less susceptible to the azole class of antifungals and accounts for 15% of all Candida bloodstream infections. Here, we show that C. glabrata MED2 (CgMED2), which codes for a tail subunit of the RNA polymerase II Mediator complex, is required for resistance to azole antifungal drugs in C. glabrata. An inability to transcriptionally activate genes encoding a zinc finger transcriptional factor, CgPdr1, and multidrug efflux pump, CgCdr1, primarily contributes to the elevated susceptibility of the Cgmed2Δ mutant toward azole antifungals. We also report for the first time that the Cgmed2Δ mutant exhibits sensitivity to caspofungin, a constitutively activated protein kinase C-mediated cell wall integrity pathway, and elevated adherence to epithelial cells. The increased adherence of the Cgmed2Δ mutant was attributed to the elevated expression of the EPA1 and EPA7 genes. Further, our data demonstrate that CgMED2 is required for intracellular proliferation in human macrophages and modulates survival in a murine model of disseminated candidiasis. Lastly, we show an essential requirement for CgMed2, along with the Mediator middle subunit CgNut1 and the Mediator cyclin-dependent kinase/cyclin subunit CgSrb8, for the high-level fluconazole resistance conferred by the hyperactive allele of CgPdr1. Together, our findings underscore a pivotal role for CgMed2 in basal tolerance and acquired resistance to azole antifungals.

Spatially-resolved eigenmode decomposition of red blood cells membrane fluctuations questions the role of ATP in flickering.

Red blood cells (RBCs) present unique reversible shape deformability, essential for both function and survival, resulting notably in cell membrane fluctuations (CMF). These CMF have been subject of many studies in order to obtain a better understanding of these remarkable biomechanical membrane properties altered in some pathological states including blood diseases. In particular the discussion over the thermal or metabolic origin of the CMF has led in the past to a large number of investigations and modeling. However, the origin of the CMF is still debated. In this article, we present an analysis of the CMF of RBCs by combining digital holographic microscopy (DHM) with an orthogonal subspace decomposition of the imaging data. These subspace components can be reliably identified and quantified as the eigenmode basis of CMF that minimizes the deformation energy of the RBC structure. By fitting the observed fluctuation modes with a theoretical dynamic model, we find that the CMF are mainly governed by the bending elasticity of the membrane and that shear and tension elasticities have only a marginal influence on the membrane fluctations of the discocyte RBC. Further, our experiments show that the role of ATP as a driving force of CMF is questionable. ATP, however, seems to be required to maintain the unique biomechanical properties of the RBC membrane that lead to thermally excited CMF.

Effects of immunosuppressive drugs on HIV infection: implications for solid-organ transplantation.

With the advent of highly active antiretroviral therapy (HAART), HIV infection has become a chronic disease. Various end-stage organ failures have now become common co-morbidities and are primary causes of mortality in HIV-infected patients. Solid-organ transplantation therefore has been proposed to these patients, as HIV infection is not anymore considered an absolute contraindication. The initial results of organ transplantation in HIV-infected patients are encouraging with no differences in patient and graft survival compared with non-HIV-infected patients. The use of immunosuppressive drug therapy in HIV-infected patients has so far not shown major detrimental effects, and some drugs in combination with HAART have even demonstrated possible beneficial effects for specific HIV settings. Nevertheless, organ transplantation in HIV-infected patients remains a complex intervention, and more studies will be required to clarify open questions such as long-term effects of drug interactions between antiretroviral and immunosuppressive drugs, outcome of recurrent HCV infection in HIV-infected patients, incidence of graft rejection, or long-term graft and patient survival. In this article, we first review the immunological pathogenesis of HIV infection and the rationale for using immunosuppression combined with HAART. We then discuss the most recent results of solid-organ transplantation in HIV-infected patients.

Error and attack tolerance of layered complex networks.

Many complex systems may be described by not one but a number of complex networks mapped on each other in a multi-layer structure. Because of the interactions and dependencies between these layers, the state of a single layer does not necessarily reflect well the state of the entire system. In this paper we study the robustness of five examples of two-layer complex systems: three real-life data sets in the fields of communication (the Internet), transportation (the European railway system), and biology (the human brain), and two models based on random graphs. In order to cover the whole range of features specific to these systems, we focus on two extreme policies of system's response to failures, no rerouting and full rerouting. Our main finding is that multi-layer systems are much more vulnerable to errors and intentional attacks than they appear from a single layer perspective.

Dissection of the complex phenotype in cuticular mutants of Arabidopsis reveals a role of SERRATE as a mediator.

Mutations in LACERATA (LCR), FIDDLEHEAD (FDH), and BODYGUARD (BDG) cause a complex developmental syndrome that is consistent with an important role for these Arabidopsis genes in cuticle biogenesis. The genesis of their pleiotropic phenotypes is, however, poorly understood. We provide evidence that neither distorted depositions of cutin, nor deficiencies in the chemical composition of cuticular lipids, account for these features, instead suggesting that the mutants alleviate the functional disorder of the cuticle by reinforcing their defenses. To better understand how plants adapt to these mutations, we performed a genome-wide gene expression analysis. We found that apparent compensatory transcriptional responses in these mutants involve the induction of wax, cutin, cell wall, and defense genes. To gain greater insight into the mechanism by which cuticular mutations trigger this response in the plants, we performed an overlap meta-analysis, which is termed MASTA (MicroArray overlap Search Tool and Analysis), of differentially expressed genes. This suggested that different cell integrity pathways are recruited in cesA cellulose synthase and cuticular mutants. Using MASTA for an in silico suppressor/enhancer screen, we identified SERRATE (SE), which encodes a protein of RNA-processing multi-protein complexes, as a likely enhancer. In confirmation of this notion, the se lcr and se bdg double mutants eradicate severe leaf deformations as well as the organ fusions that are typical of lcr and bdg and other cuticular mutants. Also, lcr does not confer resistance to Botrytis cinerea in a se mutant background. We propose that there is a role for SERRATE-mediated RNA signaling in the cuticle integrity pathway.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Volatile transport during the crystallization of anatectic melts: Oxygen, boron and hydrogen stable isotope study on the metamorphic complex of Naxos, Greece

Crystallization of anatectic melts in high-temperature metamorphic terrains releases volatile-rich magmas that can be transported into adjacent lithologies. This study addresses the variations in the oxygen, boron and hydrogen isotopic composition of aplite-pegmatite dikes that formed during the crystallization of anatectic melts in regional high-temperature metamorphism on the island of Naxos, Greece, and propagated upward into the overlying sequences of metamorphic schist. The transport distance of these dikes was increased through a significant horizontal component of travel that was imposed by contemporaneous low-angle extensional shearing. Laser fluorination oxygen isotope analyses of quartz, tourmaline, garnet, and biotite mineral separates from the aplite-pegmatite dikes show a progressive rise in delta(18)O values with increasing distance from the core. Oxygen isotope fractionations among quartz, tourmaline, and garnet show temperature variations from > 700degreesC down to similar to400degreesC. This range is considered to reflect isotopic fractionation beginning with crystallization at high temperatures in water-undersaturated conditions and then evolving through lower temperature crystallization and retrograde sub-solidus exchange. Two processes are examined for the cause of the progressive increase in delta(18)O values: (1) heterogeneous delta(18)O sources and (2) fluid-rock exchange between the aplite/pegmatite magmas and their host rock. Although the former process cannot be ruled out, there is as yet no evidence in the exposed sequences on Naxos for the presence of a suitable high delta(18)O magma source. In contrast, a tendency for the delta(18)O of quartz in the aplite/pegmatite dikes to approach that of the quartz in the metamorphic rock suggests that fluid-rock exchange with the host rock may potentially be an important process. Advection of fluid into the magma is examined based on Darcian fluid flow into an initially water-undersaturated buoyantly propagating aplitic dike magma. It is shown that such advective flow could only account for part of the O-18-enrichment, unless it were amplified by repeated injection of magma pulses, fluid recycling, and deformation-assisted post-crystallization exchange. The mechanism is, however, adequate to account for hydrogen isotope equilibration between dike and host rock. In contrast, variations in the delta(11)B values of tourmalines suggest that B-11/B-10 fractionation during crystallization and/or magma degassing was the major control of boron geochemistry rather than fluid-rock interaction and that the boron isotopic system was decoupled from that of oxygen. Copyright (C) 2003 Elsevier Ltd.