58 research outputs found
Optimal Economic Growth under Stochastic Environmental Impact: Sensitivity Analysis
In this work we present an approach toward the sensitivity analysis of optimal economic growth to a negative environmental impact driven by random natural hazards that damage the production output . We use a simplified model of the GDP whose growth leads to the increase of GHG in the atmosphere provided investment in cleaning is insufficient. The hypothesis of the Poisson probability distribution of the natural hazards is used at the first stage of the research. We apply the standard utility function - the discounted integral consumption and construct an optimal investment policy in production and cleaning together with optimal GDP trajectories. We calibrate the model in the global scale and analyze the sensitivity of obtained optimal growth scenarios with respect to uncertain parameters of the Poisson distribution
Canalization of the evolutionary trajectory of the human influenza virus
Since its emergence in 1968, influenza A (H3N2) has evolved extensively in
genotype and antigenic phenotype. Antigenic evolution occurs in the context of
a two-dimensional 'antigenic map', while genetic evolution shows a
characteristic ladder-like genealogical tree. Here, we use a large-scale
individual-based model to show that evolution in a Euclidean antigenic space
provides a remarkable correspondence between model behavior and the
epidemiological, antigenic, genealogical and geographic patterns observed in
influenza virus. We find that evolution away from existing human immunity
results in rapid population turnover in the influenza virus and that this
population turnover occurs primarily along a single antigenic axis. Thus,
selective dynamics induce a canalized evolutionary trajectory, in which the
evolutionary fate of the influenza population is surprisingly repeatable and
hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure
Predictability of evolutionary trajectories in fitness landscapes
Experimental studies on enzyme evolution show that only a small fraction of
all possible mutation trajectories are accessible to evolution. However, these
experiments deal with individual enzymes and explore a tiny part of the fitness
landscape. We report an exhaustive analysis of fitness landscapes constructed
with an off-lattice model of protein folding where fitness is equated with
robustness to misfolding. This model mimics the essential features of the
interactions between amino acids, is consistent with the key paradigms of
protein folding and reproduces the universal distribution of evolutionary rates
among orthologous proteins. We introduce mean path divergence as a quantitative
measure of the degree to which the starting and ending points determine the
path of evolution in fitness landscapes. Global measures of landscape roughness
are good predictors of path divergence in all studied landscapes: the mean path
divergence is greater in smooth landscapes than in rough ones. The
model-derived and experimental landscapes are significantly smoother than
random landscapes and resemble additive landscapes perturbed with moderate
amounts of noise; thus, these landscapes are substantially robust to mutation.
The model landscapes show a deficit of suboptimal peaks even compared with
noisy additive landscapes with similar overall roughness. We suggest that
smoothness and the substantial deficit of peaks in the fitness landscapes of
protein evolution are fundamental consequences of the physics of protein
folding.Comment: 14 pages, 7 figure
Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses
The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined
Contrasting Epidemic Histories Reveal Pathogen-Mediated Balancing Selection on Class II MHC Diversity in a Wild Songbird
The extent to which pathogens maintain the extraordinary polymorphism at vertebrate Major Histocompatibility Complex (MHC) genes via balancing selection has intrigued evolutionary biologists for over half a century, but direct tests remain challenging. Here we examine whether a well-characterized epidemic of Mycoplasmal conjunctivitis resulted in balancing selection on class II MHC in a wild songbird host, the house finch (Carpodacus mexicanus). First, we confirmed the potential for pathogen-mediated balancing selection by experimentally demonstrating that house finches with intermediate to high multi-locus MHC diversity are more resistant to challenge with Mycoplasma gallisepticum. Second, we documented sequence and diversity-based signatures of pathogen-mediated balancing selection at class II MHC in exposed host populations that were absent in unexposed, control populations across an equivalent time period. Multi-locus MHC diversity significantly increased in exposed host populations following the epidemic despite initial compromised diversity levels from a recent introduction bottleneck in the exposed host range. We did not observe equivalent changes in allelic diversity or heterozygosity across eight neutral microsatellite loci, suggesting that the observations reflect selection rather than neutral demographic processes. Our results indicate that a virulent pathogen can exert sufficient balancing selection on class II MHC to rescue compromised levels of genetic variation for host resistance in a recently bottlenecked population. These results provide evidence for Haldane's long-standing hypothesis that pathogens directly contribute to the maintenance of the tremendous levels of genetic variation detected in natural populations of vertebrates
Influenza A Gradual and Epochal Evolution: Insights from Simple Models
The recurrence of influenza A epidemics has originally been explained by a “continuous antigenic drift” scenario. Recently, it has been shown that if genetic drift is gradual, the evolution of influenza A main antigen, the haemagglutinin, is punctuated. As a consequence, it has been suggested that influenza A dynamics at the population level should be approximated by a serial model. Here, simple models are used to test whether a serial model requires gradual antigenic drift within groups of strains with the same antigenic properties (antigenic clusters). We compare the effect of status based and history based frameworks and the influence of reduced susceptibility and infectivity assumptions on the transient dynamics of antigenic clusters. Our results reveal that the replacement of a resident antigenic cluster by a mutant cluster, as observed in data, is reproduced only by the status based model integrating the reduced infectivity assumption. This combination of assumptions is useful to overcome the otherwise extremely high model dimensionality of models incorporating many strains, but relies on a biological hypothesis not obviously satisfied. Our findings finally suggest the dynamical importance of gradual antigenic drift even in the presence of punctuated immune escape. A more regular renewal of susceptible pool than the one implemented in a serial model should be part of a minimal theory for influenza at the population level
Molecular evolution of a gene cluster of serine proteases expressed in the Anopheles gambiae female reproductive tract
<p>Abstract</p> <p>Background</p> <p>Genes involved in post-mating processes of multiple mating organisms are known to evolve rapidly due to coevolution driven by sexual conflict among male-female interacting proteins. In the malaria mosquito <it>Anopheles gambiae </it>- a monandrous species in which sexual conflict is expected to be absent or minimal - recent data strongly suggest that proteolytic enzymes specifically expressed in the female lower reproductive tissues are involved in the processing of male products transferred to females during mating. In order to better understand the role of selective forces underlying the evolution of proteins involved in post-mating responses, we analysed a cluster of genes encoding for three serine proteases that are down-regulated after mating, two of which specifically expressed in the atrium and one in the spermatheca of <it>A. gambiae </it>females.</p> <p>Results</p> <p>The analysis of polymorphisms and divergence of these female-expressed proteases in closely related species of the <it>A. gambiae </it>complex revealed a high level of replacement polymorphisms consistent with relaxed evolutionary constraints of duplicated genes, allowing to rapidly fix novel replacements to perform new or more specific functions. Adaptive evolution was detected in several codons of the 3 genes and hints of episodic selection were also found. In addition, the structural modelling of these proteases highlighted some important differences in their substrate specificity, and provided evidence that a number of sites evolving under selective pressures lie relatively close to the catalytic triad and/or on the edge of the specificity pocket, known to be involved in substrate recognition or binding. The observed patterns suggest that these proteases may interact with factors transferred by males during mating (e.g. substrates, inhibitors or pathogens) and that they may have differently evolved in independent <it>A. gambiae </it>lineages.</p> <p>Conclusions</p> <p>Our results - also examined in light of constraints in the application of selection-inference methods to the closely related species of the <it>A. gambiae </it>complex - reveal an unexpectedly intricate evolutionary scenario. Further experimental analyses are needed to investigate the biological functions of these genes in order to better interpret their molecular evolution and to assess whether they represent possible targets for limiting the fertility of <it>Anopheles </it>mosquitoes in malaria vector control strategies.</p
Quantifying the Adaptive Potential of an Antibiotic Resistance Enzyme
For a quantitative understanding of the process of adaptation, we need to understand its “raw material,” that is, the frequency and fitness effects of beneficial mutations. At present, most empirical evidence suggests an exponential distribution of fitness effects of beneficial mutations, as predicted for Gumbel-domain distributions by extreme value theory. Here, we study the distribution of mutation effects on cefotaxime (Ctx) resistance and fitness of 48 unique beneficial mutations in the bacterial enzyme TEM-1 β-lactamase, which were obtained by screening the products of random mutagenesis for increased Ctx resistance. Our contributions are threefold. First, based on the frequency of unique mutations among more than 300 sequenced isolates and correcting for mutation bias, we conservatively estimate that the total number of first-step mutations that increase Ctx resistance in this enzyme is 87 [95% CI 75–189], or 3.4% of all 2,583 possible base-pair substitutions. Of the 48 mutations, 10 are synonymous and the majority of the 38 non-synonymous mutations occur in the pocket surrounding the catalytic site. Second, we estimate the effects of the mutations on Ctx resistance by determining survival at various Ctx concentrations, and we derive their fitness effects by modeling reproduction and survival as a branching process. Third, we find that the distribution of both measures follows a Fréchet-type distribution characterized by a broad tail of a few exceptionally fit mutants. Such distributions have fundamental evolutionary implications, including an increased predictability of evolution, and may provide a partial explanation for recent observations of striking parallel evolution of antibiotic resistance
The Population Genetics of dN/dS
Evolutionary pressures on proteins are often quantified by the ratio of substitution rates at non-synonymous and synonymous sites. The dN/dS ratio was originally developed for application to distantly diverged sequences, the differences among which represent substitutions that have fixed along independent lineages. Nevertheless, the dN/dS measure is often applied to sequences sampled from a single population, the differences among which represent segregating polymorphisms. Here, we study the expected dN/dS ratio for samples drawn from a single population under selection, and we find that in this context, dN/dS is relatively insensitive to the selection coefficient. Moreover, the hallmark signature of positive selection over divergent lineages, dN/dS>1, is violated within a population. For population samples, the relationship between selection and dN/dS does not follow a monotonic function, and so it may be impossible to infer selection pressures from dN/dS. These results have significant implications for the interpretation of dN/dS measurements among population-genetic samples
Experimental evolution of adaptive divergence under varying degrees of gene flow
Adaptive divergence is the key evolutionary process generating biodiversity by means of natural selection. Yet, the conditions under which it can arise in the presence of gene flow remain contentious. To address this question, we subjected 132 sexually reproducing fission yeast populations, sourced from two independent genetic backgrounds, to disruptive ecological selection and manipulated the level of migration between environments. Contrary to theoretical expectations, adaptive divergence was most pronounced when migration was either absent (allopatry) or maximal (sympatry), but was much reduced at intermediate rates (parapatry and local mating). This effect was apparent across central life-history components (survival, asexual growth and mating) but differed in magnitude between ancestral genetic backgrounds. The evolution of some fitness components was constrained by pervasive negative correlations (trade-off between asexual growth and mating), while others changed direction under the influence of migration (for example, survival and mating). In allopatry, adaptive divergence was mainly conferred by standing genetic variation and resulted in ecological specialization. In sympatry, divergence was mainly mediated by novel mutations enriched in a subset of genes and was characterized by the repeated emergence of two strategies: an ecological generalist and an asexual growth specialist. Multiple loci showed consistent evidence for antagonistic pleiotropy across migration treatments providing a conceptual link between adaptation and divergence. This evolve-and-resequence experiment shows that rapid ecological differentiation can arise even under high rates of gene flow. It further highlights that adaptive trajectories are governed by complex interactions of gene flow, ancestral variation and genetic correlations
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