Wolbachia versus dengue: Evolutionary forecasts.

A novel form of biological control is being applied to the dengue virus. The agent is the maternally transmitted bacterium Wolbachia, naturally absent from the main dengue vector, the mosquito Aedes aegypti. Three Wolbachia-based control strategies have been proposed. One is suppression of mosquito populations by large-scale releases of males incompatible with native females; this intervention requires ongoing releases. The other interventions transform wild mosquito populations with Wolbachia that spread via the frequency-dependent fitness advantage of Wolbachia-infected females; those interventions potentially require just a single, local release for area-wide disease control. One of these latter strategies uses Wolbachia that shortens mosquito life, indirectly preventing viral maturation/transmission. The other strategy uses Wolbachia that block viral transmission. All interventions can be undermined by viral, bacterial or mosquito evolution; viral virulence in humans may also evolve. We examine existing theory, experiments and comparative evidence to motivate predictions about evolutionary outcomes. (i) The life-shortening strategy seems the most likely to be thwarted by evolution. (ii) Mosquito suppression has a reasonable chance of working locally, at least in the short term, but long-term success over large areas is challenging. (iii) Dengue blocking faces strong selection for viral resistance but may well persist indefinitely at some level. Virulence evolution is not mathematically predictable, but comparative data provide no precedent for Wolbachia increasing dengue virulence. On balance, our analysis suggests that the considerable possible benefits of these technologies outweigh the known negatives, but the actual risk is largely unknown

Optimal Foraging By Bacteriophages Through Host Avoidance

Optimal foraging theory explains diet restriction as an adaptation to best utilize an array of foods differing in quality, the poorest items not worth the lost opportunity of finding better ones. Although optimal foraging has traditionally been applied to animal behavior, the model is easily applied to viral host range, which is genetically determined. The usual perspective for bacteriophages ( bacterial viruses) is that expanding host range is always advantageous if fitness on former hosts is not compromised. However, foraging theory identifies conditions favoring avoidance of poor hosts even if larger host ranges have no intrinsic costs. Bacteriophage T7 rapidly evolved to discriminate among different Escherichia coli strains when one host strain was engineered to kill infecting phages but the other remained productive. After modifying bacteria to yield more subtle fitness effects on T7, we tested qualitative predictions of optimal foraging theory by competing broad and narrow host range phages against each other. Consistent with the foraging model, diet restriction was favored when good hosts were common or there was a large difference in host quality. Contrary to the model, the direction of selection was affected by the density of poor hosts because being able to discriminate was costly.Integrative Biolog

Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic val

An Autonomous Flight Safety System

The Autonomous Flight Safety System (AFSS) being developed by NASA s Goddard Space Flight Center s Wallops Flight Facility and Kennedy Space Center has completed two successful developmental flights and is preparing for a third. AFSS has been demonstrated to be a viable architecture for implementation of a completely vehicle based system capable of protecting life and property in event of an errant vehicle by terminating the flight or initiating other actions. It is capable of replacing current human-in-the-loop systems or acting in parallel with them. AFSS is configured prior to flight in accordance with a specific rule set agreed upon by the range safety authority and the user to protect the public and assure mission success. This paper discusses the motivation for the project, describes the method of development, and presents an overview of the evolving architecture and the current status

Aggregation dynamics explain vegetation patch-size distributions

Vegetation patch-size distributions have been an intense area of study for theoreticians and applied ecologists alike in recent years. Of particular interest is the seemingly ubiquitous nature of power-law patch-size distributions emerging in a number of diverse ecosystems. The leading explanation of the emergence of these power-laws is due to local facilitative mechanisms. There is also a common transition from power law to exponential distribution when a system is under global pressure, such as grazing or lack of rainfall. These phenomena require a simple mechanistic explanation. Here, we study vegetation patches from a spatially implicit, patch dynamic viewpoint. We show that under minimal assumptions a power-law patch-size distribution appears as a natural consequence of aggregation. A linear death term also leads to an exponential term in the distribution for any non-zero death rate. This work shows the origin of the breakdown of the power-law under increasing pressure and shows that in general, we expect to observe a power law with an exponential cutoff (rather than pure power laws). The estimated parameters of this distribution also provide insight into the underlying ecological mechanisms of aggregation and death

Evolution of phage with chemically ambiguous proteomes

BACKGROUND: The widespread introduction of amino acid substitutions into organismal proteomes has occurred during natural evolution, but has been difficult to achieve by directed evolution. The adaptation of the translation apparatus represents one barrier, but the multiple mutations that may be required throughout a proteome in order to accommodate an alternative amino acid or analogue is an even more daunting problem. The evolution of a small bacteriophage proteome to accommodate an unnatural amino acid analogue can provide insights into the number and type of substitutions that individual proteins will require to retain functionality. RESULTS: The bacteriophage Qβ initially grows poorly in the presence of the amino acid analogue 6-fluorotryptophan. After 25 serial passages, the fitness of the phage on the analogue was substantially increased; there was no loss of fitness when the evolved phage were passaged in the presence of tryptophan. Seven mutations were fixed throughout the phage in two independent lines of descent. None of the mutations changed a tryptophan residue. CONCLUSIONS: A relatively small number of mutations allowed an unnatural amino acid to be functionally incorporated into a highly interdependent set of proteins. These results support the 'ambiguous intermediate' hypothesis for the emergence of divergent genetic codes, in which the adoption of a new genetic code is preceded by the evolution of proteins that can simultaneously accommodate more than one amino acid at a given codon. It may now be possible to direct the evolution of organisms with novel genetic codes using methods that promote ambiguous intermediates

The domestication of the probiotic bacterium Lactobacillus acidophilus

Lactobacillus acidophilus is a Gram-positive lactic acid bacterium that has had widespread historical use in the dairy industry and more recently as a probiotic. Although L. acidophilus has been designated as safe for human consumption, increasing commercial regulation and clinical demands for probiotic validation has resulted in a need to understand its genetic diversity. By drawing on large, well-characterised collections of lactic acid bacteria, we examined L. acidophilus isolates spanning 92 years and including multiple strains in current commercial use. Analysis of the whole genome sequence data set (34 isolate genomes) demonstrated L. acidophilus was a low diversity, monophyletic species with commercial isolates essentially identical at the sequence level. Our results indicate that commercial use has domesticated L. acidophilus with genetically stable, invariant strains being consumed globally by the human population

Modelling the spread of American foulbrood in honeybees

We investigate the spread of American foulbrood (AFB), a disease caused by the bacterium Paenibacillus larvae, that affects bees and can be extremely damaging to beehives. Our dataset comes from an inspection period carried out during an AFB epidemic of honeybee colonies on the island of Jersey during the summer of 2010. The data include the number of hives of honeybees, location and owner of honeybee apiaries across the island. We use a spatial SIR model with an underlying owner network to simulate the epidemic and characterize the epidemic using a Markov chain Monte Carlo (MCMC) scheme to determine model parameters and infection times (including undetected ‘occult’ infections). Likely methods of infection spread can be inferred from the analysis, with both distance- and owner-based transmissions being found to contribute to the spread of AFB. The results of the MCMC are corroborated by simulating the epidemic using a stochastic SIR model, resulting in aggregate levels of infection that are comparable to the data. We use this stochastic SIR model to simulate the impact of different control strategies on controlling the epidemic. It is found that earlier inspections result in smaller epidemics and a higher likelihood of AFB extinction