Variation in temperature of peak trait performance constrains adaptation of arthropod populations to climatic warming.

The capacity of arthropod populations to adapt to long-term climatic warming is currently uncertain. Here we combine theory and extensive data to show that the rate of their thermal adaptation to climatic warming will be constrained in two fundamental ways. First, the rate of thermal adaptation of an arthropod population is predicted to be limited by changes in the temperatures at which the performance of four key life-history traits can peak, in a specific order of declining importance: juvenile development, adult fecundity, juvenile mortality and adult mortality. Second, directional thermal adaptation is constrained due to differences in the temperature of the peak performance of these four traits, with these differences expected to persist because of energetic allocation and life-history trade-offs. We compile a new global dataset of 61 diverse arthropod species which provides strong empirical evidence to support these predictions, demonstrating that contemporary populations have indeed evolved under these constraints. Our results provide a basis for using relatively feasible trait measurements to predict the adaptive capacity of diverse arthropod populations to geographic temperature gradients, as well as ongoing and future climatic warming.

Integrating gene annotation with orthology inference at scale.

Annotating coding genes and inferring orthologs are two classical challenges in genomics and evolutionary biology that have traditionally been approached separately, limiting scalability. We present TOGA (Tool to infer Orthologs from Genome Alignments), a method that integrates structural gene annotation and orthology inference. TOGA implements a different paradigm to infer orthologous loci, improves ortholog detection and annotation of conserved genes compared with state-of-the-art methods, and handles even highly fragmented assemblies. TOGA scales to hundreds of genomes, which we demonstrate by applying it to 488 placental mammal and 501 bird assemblies, creating the largest comparative gene resources so far. Additionally, TOGA detects gene losses, enables selection screens, and automatically provides a superior measure of mammalian genome quality. TOGA is a powerful and scalable method to annotate and compare genes in the genomic era.

Latent functional diversity may accelerate microbial community responses to temperature fluctuations.

How complex microbial communities respond to climatic fluctuations remains an open question. Due to their relatively short generation times and high functional diversity, microbial populations harbor great potential to respond as a community through a combination of strain-level phenotypic plasticity, adaptation, and species sorting. However, the relative importance of these mechanisms remains unclear. We conducted a laboratory experiment to investigate the degree to which bacterial communities can respond to changes in environmental temperature through a combination of phenotypic plasticity and species sorting alone. We grew replicate soil communities from a single location at six temperatures between 4°C and 50°C. We found that phylogenetically and functionally distinct communities emerge at each of these temperatures, with K-strategist taxa favored under cooler conditions and r-strategist taxa under warmer conditions. We show that this dynamic emergence of distinct communities across a wide range of temperatures (in essence, community-level adaptation) is driven by the resuscitation of latent functional diversity: the parent community harbors multiple strains pre-adapted to different temperatures that are able to 'switch on' at their preferred temperature without immigration or adaptation. Our findings suggest that microbial community function in nature is likely to respond rapidly to climatic temperature fluctuations through shifts in species composition by resuscitation of latent functional diversity.

Most ecosystems on Earth rely on dynamic communities of microorganisms which help to cycle nutrients in the environment. There is increasing concern that climate change may have a profound impact on these complex networks formed of large numbers of microbial species linked by intricate biochemical relationships. Any species within a microbial community can acclimate to new temperatures by quickly tweaking their biological processes, for example by activating genes that are more suited to warmer conditions. Over time, a species may acclimate or adapt to new conditions. However, the community as a whole can also respond to these changes, and often much faster, by simply altering the abundance or presence of its members through a process known as species sorting. It remains unclear exactly how acclimation, adaptation and species sorting each contribute to the community's response to a temperature shift ­ an increasingly common scenario under global climate change. To address this question, Smith et al. investigated how species sorting and acclimation may help whole soil bacterial communities to cope with lasting changes in temperature. To do so, soil samples from a single field site (and therefore featuring the same microbial community) were incubated for four weeks under six different temperatures. Genetic analyses revealed that, at the end of the experiments, distinct communities specific to a given temperature had emerged. They all differed in species composition and the types of biological functions they could perform. Further experiments showed that each community had been taken over by strains of bacteria which grew best at the new temperature that they had been exposed to, including extreme warming scenarios never seen in their native environment. This suggests that these organisms were already present in the original community. They had persisted even under temperatures which were not optimal for them, acting as a slumbering ('latent') 'reservoir' of traits and functional abilities that allowed species sorting to produce distinct and functionally capable communities in each novel thermal environment. This suggests that species sorting could help bacterial communities to cope with dramatic changes in their thermal environment. Smith et al.'s findings suggest that bacterial communities can cope with warming environments much better than has been previously thought. In the future, this work may help researchers to better predict how climate change could impact microbial community structure and functioning, and most crucially their contributions to the global carbon cycle.

Metabolic plasticity can amplify ecosystem responses to global warming.

Organisms have the capacity to alter their physiological response to warming through acclimation or adaptation, but the consequence of this metabolic plasticity for energy flow through food webs is currently unknown, and a generalisable framework does not exist for modelling its ecosystem-level effects. Here, using temperature-controlled experiments on stream invertebrates from a natural thermal gradient, we show that the ability of organisms to raise their metabolic rate following chronic exposure to warming decreases with increasing body size. Chronic exposure to higher temperatures also increases the acute thermal sensitivity of whole-organismal metabolic rate, independent of body size. A mathematical model parameterised with these findings shows that metabolic plasticity could account for 60% higher ecosystem energy flux with just +2 °C of warming than a traditional model based on ecological metabolic theory. This could explain why long-term warming amplifies ecosystem respiration rates through time in recent mesocosm experiments, and highlights the need to embed metabolic plasticity in predictive models of global warming impacts on ecosystems.

Adaptive evolution shapes the present-day distribution of the thermal sensitivity of population growth rate.

Developing a thorough understanding of how ectotherm physiology adapts to different thermal environments is of crucial importance, especially in the face of global climate change. A key aspect of an organism's thermal performance curve (TPC)-the relationship between fitness-related trait performance and temperature-is its thermal sensitivity, i.e., the rate at which trait values increase with temperature within its typically experienced thermal range. For a given trait, the distribution of thermal sensitivities across species, often quantified as "activation energy" values, is typically right-skewed. Currently, the mechanisms that generate this distribution are unclear, with considerable debate about the role of thermodynamic constraints versus adaptive evolution. Here, using a phylogenetic comparative approach, we study the evolution of the thermal sensitivity of population growth rate across phytoplankton (Cyanobacteria and eukaryotic microalgae) and prokaryotes (bacteria and archaea), 2 microbial groups that play a major role in the global carbon cycle. We find that thermal sensitivity across these groups is moderately phylogenetically heritable, and that its distribution is shaped by repeated evolutionary convergence throughout its parameter space. More precisely, we detect bursts of adaptive evolution in thermal sensitivity, increasing the amount of overlap among its distributions in different clades. We obtain qualitatively similar results from evolutionary analyses of the thermal sensitivities of 2 physiological rates underlying growth rate: net photosynthesis and respiration of plants. Furthermore, we find that these episodes of evolutionary convergence are consistent with 2 opposing forces: decrease in thermal sensitivity due to environmental fluctuations and increase due to adaptation to stable environments. Overall, our results indicate that adaptation can lead to large and relatively rapid shifts in thermal sensitivity, especially in microbes for which rapid evolution can occur at short timescales. Thus, more attention needs to be paid to elucidating the implications of rapid evolution in organismal thermal sensitivity for ecosystem functioning.

Phytoplankton thermal responses adapt in the absence of hard thermodynamic constraints.

To better predict how populations and communities respond to climatic temperature variation, it is necessary to understand how the shape of the response of fitness-related rates to temperature evolves (the thermal performance curve). Currently, there is disagreement about the extent to which the evolution of thermal performance curves is constrained. One school of thought has argued for the prevalence of thermodynamic constraints through enzyme kinetics, whereas another argues that adaptation can-at least partly-overcome such constraints. To shed further light on this debate, we perform a phylogenetic meta-analysis of the thermal performance curves of growth rate of phytoplankton-a globally important functional group-controlling for environmental effects (habitat type and thermal regime). We find that thermodynamic constraints have a minor influence on the shape of the curve. In particular, we detect a very weak increase of maximum performance with the temperature at which the curve peaks, suggesting a weak "hotter-is-better" constraint. Also, instead of a constant thermal sensitivity of growth across species, as might be expected from strong constraints, we find that all aspects of the thermal performance curve evolve along the phylogeny. Our results suggest that phytoplankton thermal performance curves adapt to thermal environments largely in the absence of hard thermodynamic constraints.

Recruitment of ubiquitin-activating enzyme UBA1 to DNA by poly(ADP-ribose) promotes ATR signalling.

The DNA damage response (DDR) ensures cellular adaptation to genotoxic insults. In the crowded environment of the nucleus, the assembly of productive DDR complexes requires multiple protein modifications. How the apical E1 ubiquitin activation enzyme UBA1 integrates spatially and temporally in the DDR remains elusive. Using a human cell-free system, we show that poly(ADP-ribose) polymerase 1 promotes the recruitment of UBA1 to DNA. We find that the association of UBA1 with poly(ADP-ribosyl)ated protein-DNA complexes is necessary for the phosphorylation replication protein A and checkpoint kinase 1 by the serine/threonine protein kinase ataxia-telangiectasia and RAD3-related, a prototypal response to DNA damage. UBA1 interacts directly with poly(ADP-ribose) via a solvent-accessible and positively charged patch conserved in the Animalia kingdom but not in Fungi. Thus, ubiquitin activation can anchor to poly(ADP-ribose)-seeded protein assemblies, ensuring the formation of functional ataxia-telangiectasia mutated and RAD3-related-signalling complexes.

Role of carbon allocation efficiency in the temperature dependence of autotroph growth rates.

Relating the temperature dependence of photosynthetic biomass production to underlying metabolic rates in autotrophs is crucial for predicting the effects of climatic temperature fluctuations on the carbon balance of ecosystems. We present a mathematical model that links thermal performance curves (TPCs) of photosynthesis, respiration, and carbon allocation efficiency to the exponential growth rate of a population of photosynthetic autotroph cells. Using experiments with the green alga, Chlorella vulgaris, we apply the model to show that the temperature dependence of carbon allocation efficiency is key to understanding responses of growth rates to warming at both ecological and longer-term evolutionary timescales. Finally, we assemble a dataset of multiple terrestrial and aquatic autotroph species to show that the effects of temperature-dependent carbon allocation efficiency on potential growth rate TPCs are expected to be consistent across taxa. In particular, both the thermal sensitivity and the optimal temperature of growth rates are expected to change significantly due to temperature dependence of carbon allocation efficiency alone. Our study provides a foundation for understanding how the temperature dependence of carbon allocation determines how population growth rates respond to temperature.

Use and misuse of temperature normalisation in meta-analyses of thermal responses of biological traits.

There is currently unprecedented interest in quantifying variation in thermal physiology among organisms, especially in order to understand and predict the biological impacts of climate change. A key parameter in this quantification of thermal physiology is the performance or value of a rate, across individuals or species, at a common temperature (temperature normalisation). An increasingly popular model for fitting thermal performance curves to data-the Sharpe-Schoolfield equation-can yield strongly inflated estimates of temperature-normalised rate values. These deviations occur whenever a key thermodynamic assumption of the model is violated, i.e., when the enzyme governing the performance of the rate is not fully functional at the chosen reference temperature. Using data on 1,758 thermal performance curves across a wide range of species, we identify the conditions that exacerbate this inflation. We then demonstrate that these biases can compromise tests to detect metabolic cold adaptation, which requires comparison of fitness or rate performance of different species or genotypes at some fixed low temperature. Finally, we suggest alternative methods for obtaining unbiased estimates of temperature-normalised rate values for meta-analyses of thermal performance across species in climate change impact studies.

Towards a theoretically informed policy against a rakghoul plague outbreak.

A long time ago in a galaxy far, far away, the Sith Lord Karness Muur engineered the rakghoul plague, a disease that transformed infected humans into near-mindless predatory rakghouls. At its peak, the disease infected millions of individuals, giving rise to armies of rakghouls on a number of planets. Whether rakghoul populations have persisted until this day is not known, making a rakghoul invasion on Earth not completely improbable. Further, a strategy for defence against an outbreak of the disease on Earth has not yet been proposed. To fill this glaring gap, we developed the first mathematical model of the population dynamics of humans and rakghouls during a rakghoul plague outbreak. Using New South Wales as a model site, we then obtained ensembles of model predictions for the outcome of the rakghoul plague in two different disease control strategy scenarios (population evacuation and military intervention), and in the absence thereof. Finally, based on these predictions, we propose a set of policy guidelines for successfully controlling and eliminating outbreaks of the rakghoul plague in Australian states.

Structuprint: a scalable and extensible tool for two-dimensional representation of protein surfaces.

BACKGROUND: The term 'molecular cartography' encompasses a family of computational methods for two-dimensional transformation of protein structures and analysis of their physicochemical properties. The underlying algorithms comprise multiple manual steps, whereas the few existing implementations typically restrict the user to a very limited set of molecular descriptors. RESULTS: We present Structuprint, a free standalone software that fully automates the rendering of protein surface maps, given - at the very least - a directory with a PDB file and an amino acid property. The tool comes with a default database of 328 descriptors, which can be extended or substituted by user-provided ones. The core algorithm comprises the generation of a mould of the protein surface, which is subsequently converted to a sphere and mapped to two dimensions, using the Miller cylindrical projection. Structuprint is partly optimized for multicore computers, making the rendering of animations of entire molecular dynamics simulations feasible. CONCLUSIONS: Structuprint is an efficient application, implementing a molecular cartography algorithm for protein surfaces. According to the results of a benchmark, its memory requirements and execution time are reasonable, allowing it to run even on low-end personal computers. We believe that it will be of use - primarily but not exclusively - to structural biologists and computational biochemists.

Adult Kawasaki disease in a European patient: a case report and review of the literature.

INTRODUCTION: Kawasaki disease is an acute necrotising vasculitis of the medium- and small-sized vessels, occurring mainly in Japanese and Korean babies and children, aged 6 months to 5 years. Its main complication is damage of coronary arteries, which has the potential to be fatal. Here we report a rare case of Kawasaki disease that occurred in a 20-year-old Greek adult. CASE PRESENTATION: A 20-year-old Greek man presented with high fever, appetite loss, nausea and vomiting, headache and significant malaise. He had an erythema of the palms and strikingly red lips and conjunctiva. As he did not respond to broad-spectrum antibiotics and after having excluded other possible diagnoses, the diagnosis of Kawasaki disease was set. He was treated with intravenous immunoglobulin and oral aspirin on the 10th day since the onset of the illness. His clinico-laboratory response was excellent and no coronary artery aneurysms were detected in coronary artery computed tomography performed 1 month later. CONCLUSIONS: This report of an adult case of European Kawasaki disease may be of benefit to physicians of various specialties, including primary care doctors, hospital internists, intensivists and cardiologists. It demonstrates that a case of prolonged fever, unresponsive to antibiotics, in the absence of other diagnoses may be an incident of Kawasaki disease. It is worth stressing that such a diagnosis should be considered, even if the patient is adult and not of Asian lineage.

Space constrained homology modelling: the paradigm of the RNA-dependent RNA polymerase of dengue (type II) virus.

Protein structure is more conserved than sequence in nature. In this direction we developed a novel methodology that significantly improves conventional homology modelling when sequence identity is low, by taking into consideration 3D structural features of the template, such as size and shape. Herein, our new homology modelling approach was applied to the homology modelling of the RNA-dependent RNA polymerase (RdRp) of dengue (type II) virus. The RdRp of dengue was chosen due to the low sequence similarity shared between the dengue virus polymerase and the available templates, while purposely avoiding to use the actual X-ray structure that is available for the dengue RdRp. The novel approach takes advantage of 3D space corresponding to protein shape and size by creating a 3D scaffold of the template structure. The dengue polymerase model built by the novel approach exhibited all features of RNA-dependent RNA polymerases and was almost identical to the X-ray structure of the dengue RdRp, as opposed to the model built by conventional homology modelling. Therefore, we propose that the space-aided homology modelling approach can be of a more general use to homology modelling of enzymes sharing low sequence similarity with the template structures.

Pinda: a web service for detection and analysis of intraspecies gene duplication events.

We present Pinda, a Web service for the detection and analysis of possible duplications of a given protein or DNA sequence within a source species. Pinda fully automates the whole gene duplication detection procedure, from performing the initial similarity searches, to generating the multiple sequence alignments and the corresponding phylogenetic trees, to bootstrapping the trees and producing a Z-score-based list of duplication candidates for the input sequence. Pinda has been cross-validated using an extensive set of known and bibliographically characterized duplication events. The service facilitates the automatic and dependable identification of gene duplication events, using some of the most successful bioinformatics software to perform an extensive analysis protocol. Pinda will prove of use for the analysis of newly discovered genes and proteins, thus also assisting the study of recently sequenced genomes. The service's location is http://orion.mbg.duth.gr/Pinda. The source code is freely available via https://github.com/dgkontopoulos/Pinda/.