HIV-1 reverse transcriptase connection domain mutations: dynamics of emergence and implications for success of combination antiretroviral therapy.

BACKGROUND: Factors promoting the emergence of human immunodeficiency virus type 1 (HIV-1) reverse transcriptase (RT) connection domain mutations and their effect on antiretroviral therapy (ART) are still largely undetermined. We investigated this matter by analyzing genotypic resistance tests covering 400 amino acid positions in the RT of HIV-1 subtype B viruses and corresponding treatment histories and laboratory measurements. METHODS: The emergence of connection domain mutations was studied in 334 patients receiving monotherapy or dual therapy with thymidine analogues at the time of the genotypic resistance test. Response to subsequent combination ART (cART) was analyzed using Cox regression for 291 patients receiving unboosted protease inhibitors. Response was defined by ever reaching an HIV RNA level <50 copies/mL during the first cART. RESULTS: The connection domain mutations N348I, R356K, R358K, A360V, and A371V were more frequently observed in ART-exposed than ART-naive patients, of which only N348I and A360V were nonpolymorphic (with a prevalence of <1.5% in untreated patients). N348I correlated with M184V and predominantly occurred in patients receiving lamivudine and zidovudine concomitantly. A360V was not associated with specific drug combinations and was found to emerge later than M184V or thymidine analogue mutations. Nonpolymorphic connection domain mutations were rarely detected in the absence of established drug resistance mutations in ART-exposed individuals (prevalence, <1%). None of the 5 connection domain mutations associated with treatment showed a statistically significant effect on response to cART. CONCLUSIONS: Despite their frequent emergence, connection domain mutations did not show large detrimental effects on response to cART. Currently, routine implementation of connection domain sequencing seems unnecessary for developed health care settings.

The emergence of new genes on the young therian X.

Recent studies have revealed that our sex chromosomes differentiated relatively recently from ancestral autosomes in the common ancestor of placental and marsupial mammals (therians). Here, we show that the therian X started to accumulate new retroduplicate genes with overall sex-biased expression upon therian sex chromosome differentiation. This process reached its peak within the first approximately 90 million years of sex chromosome evolution and then leveled off. Taken together, our observations suggest that the major sex-related functional remodeling of the X was completed relatively soon after the origination of therian sex chromosomes.

Factors associated with the emergence of K65R in patients with HIV-1 infection treated with combination antiretroviral therapy containing tenofovir.

BACKGROUND: The human immunodeficiency virus type 1 reverse-transcriptase mutation K65R is a single-point mutation that has become more frequent after increased use of tenofovir disoproxil fumarate (TDF). We aimed to identify predictors for the emergence of K65R, using clinical data and genotypic resistance tests from the Swiss HIV Cohort Study. METHODS: A total of 222 patients with genotypic resistance tests performed while receiving treatment with TDF-containing regimens were stratified by detectability of K65R (K65R group, 42 patients; undetected K65R group, 180 patients). Patient characteristics at start of that treatment were analyzed. RESULTS: In an adjusted logistic regression, TDF treatment with nonnucleoside reverse-transcriptase inhibitors and/or didanosine was associated with the emergence of K65R, whereas the presence of any of the thymidine analogue mutations D67N, K70R, T215F, or K219E/Q was protective. The previously undescribed mutational pattern K65R/G190S/Y181C was observed in 6 of 21 patients treated with efavirenz and TDF. Salvage therapy after TDF treatment was started for 36 patients with K65R and for 118 patients from the wild-type group. Proportions of patients attaining human immunodeficiency virus type 1 loads <50 copies/mL after 24 weeks of continuous treatment were similar for the K65R group (44.1%; 95% confidence interval, 27.2%-62.1%) and the wild-type group (51.9%; 95% confidence interval, 42.0%-61.6%). CONCLUSIONS: In settings where thymidine analogue mutations are less likely to be present, such as at start of first-line therapy or after extended treatment interruptions, combinations of TDF with other K65R-inducing components or with efavirenz or nevirapine may carry an enhanced risk of the emergence of K65R. The finding of a distinct mutational pattern selected by treatment with TDF and efavirenz suggests a potential fitness interaction between K65R and nonnucleoside reverse-transcriptase inhibitor-induced mutations.

Emergence of young human genes after a burst of retroposition in primates.

The origin of new genes through gene duplication is fundamental to the evolution of lineage- or species-specific phenotypic traits. In this report, we estimate the number of functional retrogenes on the lineage leading to humans generated by the high rate of retroposition (retroduplication) in primates. Extensive comparative sequencing and expression studies coupled with evolutionary analyses and simulations suggest that a significant proportion of recent retrocopies represent bona fide human genes. We estimate that at least one new retrogene per million years emerged on the human lineage during the past approximately 63 million years of primate evolution. Detailed analysis of a subset of the data shows that the majority of retrogenes are specifically expressed in testis, whereas their parental genes show broad expression patterns. Consistently, most retrogenes evolved functional roles in spermatogenesis. Proteins encoded by X chromosome-derived retrogenes were strongly preserved by purifying selection following the duplication event, supporting the view that they may act as functional autosomal substitutes during X-inactivation of late spermatogenesis genes. Also, some retrogenes acquired a new or more adapted function driven by positive selection. We conclude that retroduplication significantly contributed to the formation of recent human genes and that most new retrogenes were progressively recruited during primate evolution by natural and/or sexual selection to enhance male germline function.

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.

In vitro prevention of the emergence of daptomycin resistance in Staphylococcus aureus and enterococci following combination with amoxicillin/clavulanic acid or ampicillin.

Daptomycin is bactericidal against meticillin-resistant Staphylococcus aureus (MRSA), glycopeptide-intermediate-resistant S. aureus (GISA) and vancomycin-susceptible and -resistant enterococci. However, selection for daptomycin-resistant derivatives has occasionally been reported during therapy in humans. Here we evaluate whether selection for daptomycin-resistant S. aureus or enterococci could be prevented in vitro by combining daptomycin with amoxicillin/clavulanic acid, ampicillin, gentamicin or rifampicin. Six strains of S. aureus (four MRSA and two GISA) and four strains of enterococci (two Enterococcus faecalis and two Enterococcus faecium) were serially exposed in broth to two-fold stepwise increasing concentrations of daptomycin alone or in combination with a fixed concentration [0.25x minimum inhibitory concentration (MIC)] of either of the second agents. The daptomycin MIC was examined after each cycle. Exposure to daptomycin alone gradually selected for S. aureus and enterococci with an increased MIC. Gentamicin did not prevent the emergence of daptomycin-resistant bacteria. Rifampicin was also unable to prevent daptomycin resistance, although resistance was slightly delayed. In contrast, amoxicillin/clavulanic acid or ampicillin prevented or greatly delayed the selection of daptomycin-resistant mutants in S. aureus and enterococci, respectively. Addition of amoxicillin/clavulanic acid or ampicillin to daptomycin prevents, or greatly delays, daptomycin resistance in vitro. Future studies in animal models are needed to predict the utility of these combinations in humans.

Emergence of Cooperation on Static and Dynamic Networks

Game theory is a branch of applied mathematics used to analyze situation where two or more agents are interacting. Originally it was developed as a model for conflicts and collaborations between rational and intelligent individuals. Now it finds applications in social sciences, eco- nomics, biology (particularly evolutionary biology and ecology), engineering, political science, international relations, computer science, and philosophy. Networks are an abstract representation of interactions, dependencies or relationships. Net- works are extensively used in all the fields mentioned above and in many more. Many useful informations about a system can be discovered by analyzing the current state of a network representation of such system. In this work we will apply some of the methods of game theory to populations of agents that are interconnected. A population is in fact represented by a network of players where one can only interact with another if there is a connection between them. In the first part of this work we will show that the structure of the underlying network has a strong influence on the strategies that the players will decide to adopt to maximize their utility. We will then introduce a supplementary degree of freedom by allowing the structure of the population to be modified along the simulations. This modification allows the players to modify the structure of their environment to optimize the utility that they can obtain.