ALBERT

Description: As internet technologies make their way into developing areas, so too does the possibility of education and training being delivered to the people living in those previously unserved areas. The growing catalogue of free, high quality courseware, when combined with the newly acquired means of delivery, creates the potential for millions of people in the developing world to acquire a good education. Yet a good education obviously requires more than simply delivering information; students must also receive high quality feedback on their assessments. They must be told how their performance compares with the ideal, and be shown how to close the gap between the two. However, delivering high quality feedback is labor-intensive, and therefore expensive, and has long been recognized as a problematic issue by educators. This paper outlines a case study that uses a Learning Management System (LMS) to efficiently deliver detailed feedback that is informed by the principles of best practice. We make the case that the efficiencies of this method allow for large-scale courses with thousands of enrolments that are accessible to developing and developed areas alike. We explore the question; is computer-mediated feedback delivery efficient and effective and might it be applied to large-scale courses at low-cost?

Description: Parasite host range can be influenced by physiological, behavioral, and ecological factors. Combining data sets on host–parasite associations with phylogenetic information of the hosts and the parasites involved can generate evolutionary hypotheses about the selective forces shaping host range. Here, we analyzed associations between the nest-parasitic flies in the genus Philornis and their host birds on Trinidad. Four of ten Philornis species were only reared from one species of bird. Of the parasite species with more than one host bird species, P. falsificus was the least specific and P. deceptivus the most specific attacking only Passeriformes. Philornis flies in Trinidad thus include both specialists and generalists , with varying degrees of specificity within the generalists. We used three quantities to more formally compare the host range of Philornis flies: the number of bird species attacked by each species of Philornis , a phylogenetically informed host specificity index (Poulin and Mouillot's S TD ), and a branch length-based S TD . We then assessed the phylogenetic signal of these measures of host range for 29 bird species. None of these measures showed significant phylogenetic signal, suggesting that clades of Philornis did not differ significantly in their ability to exploit hosts. We also calculated two quantities of parasite species load for the birds – the parasite species richness, and a variant of the S TD index based on nodes rather than on taxonomic levels – and assessed the signal of these measures on the bird phylogeny. We did not find significant phylogenetic signal for the parasite species load or the node-based S TD index. Finally, we calculated the parasite associations for all bird pairs using the Jaccard index and regressed these similarity values against the number of nodes in the phylogeny separating bird pairs. This analysis showed that Philornis on Trinidad tend to feed on closely related bird species more often than expected by chance. Host range, parasite species load, and community similarity are important descriptors of host-parasite interactions. We used a phylogenetic approach to explore host-associations between birds and their Philornis parasites on the island of Trinidad.

Description: We analyzed individual variation in work load (nest visit rate) during chick-rearing, and the consequences of this variation in terms of breeding productivity, in a highly synchronous breeder, the European starling ( Sturnus vulgaris ) focusing on female birds. There was marked (10- to 16-fold) variation in total, female and male nest visit rates, among individuals, but individual variation in female nest visit rate was independent of environment (rainfall, temperature) and metrics of individual quality (laying date, clutch size, amount of male provisioning help), and was only weakly associated with chick demand (i.e., day 6 brood size). Female nest visit rate was independent of date and experimentally delayed birds provisioned at the same rate as peak-nesting birds; supporting a lack of effect of date per se. Brood size at fledging was positively but weakly related to total nest visit rate (male + female), with 〉fivefold variation in nest visit rate for any given brood size, and in females brood size at fledging and chick mass at fledging were independent of female nest visit rate, that is, individual variation in workload was not associated with higher productivity. Nevertheless, nest visit rate in females was repeatable among consecutive days (6–8 posthatching), and between peak (first) and second broods, but not among years. Our data suggest that individual females behave as if committed to a certain level of parental care at the outset of their annual breeding attempt, but this varies among years, that is, behavior is not fixed throughout an individual's life but represents an annually variable decision. We suggest females are making predictable decisions about their workload during provisioning that maximizes their overall fitness based on an integration of information on their current environment (although these cues currently remain unidentified). Traditional metrics of parental workload vary considerably and we elucidate an uncoupling of female provisioning effort and fitness benefits. We suggest females are making predictable decisions about their workload during provisioning that maximizes their overall fitness based on an integration of information on their current environment.

Description: by Eliseo Ferrante, Ali Emre Turgut, Edgar Duéñez-Guzmán, Marco Dorigo, Tom Wenseleers Division of labor is ubiquitous in biological systems, as evidenced by various forms of complex task specialization observed in both animal societies and multicellular organisms. Although clearly adaptive, the way in which division of labor first evolved remains enigmatic, as it requires the simultaneous co-occurrence of several complex traits to achieve the required degree of coordination. Recently, evolutionary swarm robotics has emerged as an excellent test bed to study the evolution of coordinated group-level behavior. Here we use this framework for the first time to study the evolutionary origin of behavioral task specialization among groups of identical robots. The scenario we study involves an advanced form of division of labor, common in insect societies and known as “task partitioning”, whereby two sets of tasks have to be carried out in sequence by different individuals. Our results show that task partitioning is favored whenever the environment has features that, when exploited, reduce switching costs and increase the net efficiency of the group, and that an optimal mix of task specialists is achieved most readily when the behavioral repertoires aimed at carrying out the different subtasks are available as pre-adapted building blocks. Nevertheless, we also show for the first time that self-organized task specialization could be evolved entirely from scratch, starting only from basic, low-level behavioral primitives, using a nature-inspired evolutionary method known as Grammatical Evolution. Remarkably, division of labor was achieved merely by selecting on overall group performance, and without providing any prior information on how the global object retrieval task was best divided into smaller subtasks. We discuss the potential of our method for engineering adaptively behaving robot swarms and interpret our results in relation to the likely path that nature took to evolve complex sociality and task specialization.

Description: by Patrícia Santos-Oliveira, António Correia, Tiago Rodrigues, Teresa M Ribeiro-Rodrigues, Paulo Matafome, Juan Carlos Rodríguez-Manzaneque, Raquel Seiça, Henrique Girão, Rui D. M. Travasso Sprouting angiogenesis, where new blood vessels grow from pre-existing ones, is a complex process where biochemical and mechanical signals regulate endothelial cell proliferation and movement. Therefore, a mathematical description of sprouting angiogenesis has to take into consideration biological signals as well as relevant physical processes, in particular the mechanical interplay between adjacent endothelial cells and the extracellular microenvironment. In this work, we introduce the first phase-field continuous model of sprouting angiogenesis capable of predicting sprout morphology as a function of the elastic properties of the tissues and the traction forces exerted by the cells. The model is very compact, only consisting of three coupled partial differential equations, and has the clear advantage of a reduced number of parameters. This model allows us to describe sprout growth as a function of the cell-cell adhesion forces and the traction force exerted by the sprout tip cell. In the absence of proliferation, we observe that the sprout either achieves a maximum length or, when the traction and adhesion are very large, it breaks. Endothelial cell proliferation alters significantly sprout morphology, and we explore how different types of endothelial cell proliferation regulation are able to determine the shape of the growing sprout. The largest region in parameter space with well formed long and straight sprouts is obtained always when the proliferation is triggered by endothelial cell strain and its rate grows with angiogenic factor concentration. We conclude that in this scenario the tip cell has the role of creating a tension in the cells that follow its lead. On those first stalk cells, this tension produces strain and/or empty spaces, inevitably triggering cell proliferation. The new cells occupy the space behind the tip, the tension decreases, and the process restarts. Our results highlight the ability of mathematical models to suggest relevant hypotheses with respect to the role of forces in sprouting, hence underlining the necessary collaboration between modelling and molecular biology techniques to improve the current state-of-the-art.

Description: by Sayed-Rzgar Hosseini, Aditya Barve, Andreas Wagner All biological evolution takes place in a space of possible genotypes and their phenotypes. The structure of this space defines the evolutionary potential and limitations of an evolving system. Metabolism is one of the most ancient and fundamental evolving systems, sustaining life by extracting energy from extracellular nutrients. Here we study metabolism’s potential for innovation by analyzing an exhaustive genotype-phenotype map for a space of 10 15 metabolisms that encodes all possible subsets of 51 reactions in central carbon metabolism. Using flux balance analysis, we predict the viability of these metabolisms on 10 different carbon sources which give rise to 1024 potential metabolic phenotypes. Although viable metabolisms with any one phenotype comprise a tiny fraction of genotype space, their absolute numbers exceed 10 9 for some phenotypes. Metabolisms with any one phenotype typically form a single network of genotypes that extends far or all the way through metabolic genotype space, where any two genotypes can be reached from each other through a series of single reaction changes. The minimal distance of genotype networks associated with different phenotypes is small, such that one can reach metabolisms with novel phenotypes – viable on new carbon sources – through one or few genotypic changes. Exceptions to these principles exist for those metabolisms whose complexity (number of reactions) is close to the minimum needed for viability. Increasing metabolic complexity enhances the potential for both evolutionary conservation and evolutionary innovation.

Description: by Pengxing Cao, Ada W. C. Yan, Jane M. Heffernan, Stephen Petrie, Robert G. Moss, Louise A. Carolan, Teagan A. Guarnaccia, Anne Kelso, Ian G. Barr, Jodie McVernon, Karen L. Laurie, James M. McCaw Influenza is an infectious disease that primarily attacks the respiratory system. Innate immunity provides both a very early defense to influenza virus invasion and an effective control of viral growth. Previous modelling studies of virus–innate immune response interactions have focused on infection with a single virus and, while improving our understanding of viral and immune dynamics, have been unable to effectively evaluate the relative feasibility of different hypothesised mechanisms of antiviral immunity. In recent experiments, we have applied consecutive exposures to different virus strains in a ferret model, and demonstrated that viruses differed in their ability to induce a state of temporary immunity or viral interference capable of modifying the infection kinetics of the subsequent exposure. These results imply that virus-induced early immune responses may be responsible for the observed viral hierarchy. Here we introduce and analyse a family of within-host models of re-infection viral kinetics which allow for different viruses to stimulate the innate immune response to different degrees. The proposed models differ in their hypothesised mechanisms of action of the non-specific innate immune response. We compare these alternative models in terms of their abilities to reproduce the re-exposure data. Our results show that 1) a model with viral control mediated solely by a virus-resistant state, as commonly considered in the literature, is not able to reproduce the observed viral hierarchy; 2) the synchronised and desynchronised behaviour of consecutive virus infections is highly dependent upon the interval between primary virus and challenge virus exposures and is consistent with virus-dependent stimulation of the innate immune response. Our study provides the first mechanistic explanation for the recently observed influenza viral hierarchies and demonstrates the importance of understanding the host response to multi-strain viral infections. Re-exposure experiments provide a new paradigm in which to study the immune response to influenza and its role in viral control.

Description: The merger of formerly isolated lineages is hypothesized to occur in vertebrates under certain conditions. However, despite many demonstrated instances of introgression between taxa in secondary contact, examples of lineage mergers are rare. Preliminary mtDNA sequencing of a Malagasy passerine, Xanthomixis zosterops (Passeriformes: Bernieridae), indicated a possible instance of merging lineages. We tested the hypothesis that X . zosterops lineages are merging by comparing mtDNA sequence and microsatellite data, as well as mtDNA sequence data from host-specific feather lice in the genus Myrsidea (Phthiraptera: Menoponidae). Xanthomixis zosterops comprises four deeply divergent, broadly sympatric, cryptic mtDNA clades that likely began diverging approximately 3.6 million years ago. Despite this level of divergence, the microsatellite data indicate that the X . zosterops mtDNA clades are virtually panmictic. Three major phylogroups of Myrsidea were found, supporting previous allopatry of the X . zosterops clades. In combination, the datasets from X . zosterops and its Myrsidea document a potential merger of previously allopatric lineages that likely date to the Pliocene. This represents the first report of sympatric apparent hybridization among more than two terrestrial vertebrate lineages. Further, the mtDNA phylogeographic pattern of X . zosterops , namely the syntopy of more than two deeply divergent cryptic clades, appears to be a novel scenario among vertebrates. We highlight the value of gathering multiple types of data in phylogeographic studies to contribute to the study of vertebrate speciation. Xanthomixis zosterops comprises four deeply divergent, broadly sympatric, cryptic mtDNA clades that likely began diverging approximately 3.6 million years ago. Despite this level of divergence, microsatellite data indicate that the X . zosterops mtDNA clades are virtually panmictic. The presence of three distinct phylogroups of host-specific Myrsidea lice on X . zosterops support previous allopatry and potential lineage merger of the X . zosterops clades.

Description: Sexual signals are important in attracting and choosing mates; however, these signals and their associated preferences are often costly and frequently lost. Despite the prevalence of signaling system loss in many taxa, the factors leading to signal loss remain poorly understood. Here, we test the hypothesis that complexity in signal loss scenarios is due to the context-dependent nature of the many factors affecting signal loss itself. Using the Avida digital life platform, we evolved 50 replicates of ~250 lineages, each with a unique combination of parameters, including whether signaling is obligate or facultative; genetic linkage between signaling and receiving genes; population size; and strength of preference for signals. Each of these factors ostensibly plays a crucial role in signal loss, but was found to do so only under specific conditions. Under obligate signaling, genetic linkage, but not population size, influenced signal loss; under facultative signaling, genetic linkage does not have significant influence. Somewhat surprisingly, only a total loss of preference in the obligate signaling populations led to total signal loss, indicating that even a modest amount of preference is enough to maintain signaling systems. Strength of preference proved to be the strongest single force preventing signal loss, as it consistently overcame the potential effects of drift within our study. Our findings suggest that signaling loss is often dependent on not just preference for signals, population size, and genetic linkage, but also whether signals are required to initiate mating. These data provide an understanding of the factors (and their interactions) that may facilitate the maintenance of sexual signals. Sexual signals are important in attracting and choosing mates; however, these signals and their associated preferences are often costly and frequently lost. Here we used the Avida digital life platform to explore the conditions (population size, genetic linkage, strength of preference, and requirement of signal to initial mating) under which signal loss occurs. Our findings suggest that (1) signaling loss is often dependent on not just preference for signals, population size, and genetic linkage, but also whether signals are required to initiate mating, and (2) complete signal loss may be harder to obtain that previously thought.

Description: by Paul M. Harrison, Laurent Badel, Mark J. Wall, Magnus J. E. Richardson Models of neocortical networks are increasingly including the diversity of excitatory and inhibitory neuronal classes. Significant variability in cellular properties are also seen within a nominal neuronal class and this heterogeneity can be expected to influence the population response and information processing in networks. Recent studies have examined the population and network effects of variability in a particular neuronal parameter with some plausibly chosen distribution. However, the empirical variability and covariance seen across multiple parameters are rarely included, partly due to the lack of data on parameter correlations in forms convenient for model construction. To addess this we quantify the heterogeneity within and between the neocortical pyramidal-cell classes in layers 2/3, 4, and the slender-tufted and thick-tufted pyramidal cells of layer 5 using a combination of intracellular recordings, single-neuron modelling and statistical analyses. From the response to both square-pulse and naturalistic fluctuating stimuli, we examined the class-dependent variance and covariance of electrophysiological parameters and identify the role of the h current in generating parameter correlations. A byproduct of the dynamic I-V method we employed is the straightforward extraction of reduced neuron models from experiment. Empirically these models took the refractory exponential integrate-and-fire form and provide an accurate fit to the perisomatic voltage responses of the diverse pyramidal-cell populations when the class-dependent statistics of the model parameters were respected. By quantifying the parameter statistics we obtained an algorithm which generates populations of model neurons, for each of the four pyramidal-cell classes, that adhere to experimentally observed marginal distributions and parameter correlations. As well as providing this tool, which we hope will be of use for exploring the effects of heterogeneity in neocortical networks, we also provide the code for the dynamic I-V method and make the full electrophysiological data set available.

Description: Species can adapt to new environmental conditions either through individual phenotypic plasticity, intraspecific genetic differentiation in adaptive traits, or both. Wild emmer wheat, Triticum dicoccoides , an annual grass with major distribution in Eastern Mediterranean region, is predicted to experience in the near future, as a result of global climate change, conditions more arid than in any part of the current species distribution. To understand the role of the above two means of adaptation, and the effect of population range position, we analyzed reaction norms, extent of plasticity, and phenotypic selection across two experimental environments of high and low water availability in two core and two peripheral populations of this species. We studied 12 quantitative traits, but focused primarily on the onset of reproduction and maternal investment, which are traits that are closely related to fitness and presumably involved in local adaptation in the studied species. We hypothesized that the population showing superior performance under novel environmental conditions will either be genetically differentiated in quantitative traits or exhibit higher phenotypic plasticity than the less successful populations. We found the core population K to be the most plastic in all three trait categories (phenology, reproductive traits, and fitness) and most successful among populations studied, in both experimental environments; at the same time, the core K population was clearly genetically differentiated from the two edge populations. Our results suggest that (1) two means of successful adaptation to new environmental conditions, phenotypic plasticity and adaptive genetic differentiation, are not mutually exclusive ways of achieving high adaptive ability; and (2) colonists from some core populations can be more successful in establishing beyond the current species range than colonists from the range extreme periphery with conditions seemingly closest to those in the new environment. Our results suggest that (1) two means of successful adaptation to new environmental conditions, phenotypic plasticity and adaptive genetic differentiation, are not mutually exclusive ways of achieving high adaptive ability; and (2) colonists from some core populations can be more successful in establishing beyond the current species range than colonists from the range extreme periphery with conditions seemingly closest to those in the new environment.

Description: by Ariel Afek, Hila Cohen, Shiran Barber-Zucker, Raluca Gordân, David B. Lukatsky Recent genome-wide experiments in different eukaryotic genomes provide an unprecedented view of transcription factor (TF) binding locations and of nucleosome occupancy. These experiments revealed that a large fraction of TF binding events occur in regions where only a small number of specific TF binding sites (TFBSs) have been detected. Furthermore, in vitro protein-DNA binding measurements performed for hundreds of TFs indicate that TFs are bound with wide range of affinities to different DNA sequences that lack known consensus motifs. These observations have thus challenged the classical picture of specific protein-DNA binding and strongly suggest the existence of additional recognition mechanisms that affect protein-DNA binding preferences. We have previously demonstrated that repetitive DNA sequence elements characterized by certain symmetries statistically affect protein-DNA binding preferences. We call this binding mechanism nonconsensus protein-DNA binding in order to emphasize the point that specific consensus TFBSs do not contribute to this effect. In this paper, using the simple statistical mechanics model developed previously, we calculate the nonconsensus protein-DNA binding free energy for the entire C . elegans and D . melanogaster genomes. Using the available chromatin immunoprecipitation followed by sequencing (ChIP-seq) results on TF-DNA binding preferences for ~100 TFs, we show that DNA sequences characterized by low predicted free energy of nonconsensus binding have statistically higher experimental TF occupancy and lower nucleosome occupancy than sequences characterized by high free energy of nonconsensus binding. This is in agreement with our previous analysis performed for the yeast genome. We suggest therefore that nonconsensus protein-DNA binding assists the formation of nucleosome-free regions, as TFs outcompete nucleosomes at genomic locations with enhanced nonconsensus binding. In addition, here we perform a new, large-scale analysis using in vitro TF-DNA preferences obtained from the universal protein binding microarrays (PBM) for ~90 eukaryotic TFs belonging to 22 different DNA-binding domain types. As a result of this new analysis, we conclude that nonconsensus protein-DNA binding is a widespread phenomenon that significantly affects protein-DNA binding preferences and need not require the presence of consensus (specific) TFBSs in order to achieve genome-wide TF-DNA binding specificity.

Description: This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. This study investigates whether commonly studied properties of network structure vary with spatial scale, using highly resolved empirical food webs for the marine intertidal of the Sanak Archipelago in the Eastern Aleutian Islands. We find through analyses using niche and power-law scaling models that although raw structural properties of networks vary systematically with sampling extent, across six orders of magnitude, many of these apparent sensitivities are attributable to the increasing richness and decreasing connectance of larger-scale food webs.

Description: Aboveground plant performance is strongly influenced by belowground microorganisms, some of which are pathogenic and have negative effects, while others, such as nitrogen-fixing bacteria and arbuscular mycorrhizal fungi, usually have positive effects. Recent research revealed that belowground interactions between plants and functionally distinct groups of microorganisms cascade up to aboveground plant associates such as herbivores and their natural enemies. However, while functionally distinct belowground microorganisms commonly co-occur in the rhizosphere, their combined effects, and relative contributions, respectively, on performance of aboveground plant-associated organisms are virtually unexplored. Here, we scrutinized and disentangled the effects of free-living nitrogen-fixing (diazotrophic) bacteria Azotobacter chroococcum (DB) and arbuscular mycorrhizal fungi Glomus mosseae (AMF) on host plant choice and reproduction of the herbivorous two-spotted spider mite Tetranychus urticae on common bean plants Phaseolus vulgaris . Additionally, we assessed plant growth, and AMF and DB occurrence and density as affected by each other. Both AMF alone and DB alone increased spider mite reproduction to similar levels, as compared to the control, and exerted additive effects under co-occurrence. These effects were similarly apparent in host plant choice, that is, the mites preferred leaves from plants with both AMF and DB to plants with AMF or DB to plants grown without AMF and DB. DB, which also act as AMF helper bacteria, enhanced root colonization by AMF, whereas AMF did not affect DB abundance. AMF but not DB increased growth of reproductive plant tissue and seed production, respectively. Both AMF and DB increased the biomass of vegetative aboveground plant tissue. Our study breaks new ground in multitrophic belowground–aboveground research by providing first insights into the fitness implications of plant-mediated interactions between interrelated belowground fungi–bacteria and aboveground herbivores. Our study provides a key example of the interrelated effects of two primarily plant-mutualistic microorganisms, mycorrhizal fungi and free-living nitrogen-fixing bacteria, on herbivorous spider mites feeding on aboveground plant parts. It breaks new ground in multi-trophic below-aboveground research by providing first insights into the implications of plant-mediated belowground fungi-bacteria interactions on fitness of aboveground herbivores.

Description: Whether or not baiting influences stickleback catch per unit effort (CPUE) remains a matter of debate among stickleback researchers: While the opinions about the impact of baiting on CPUE differ, supporting quantitative data are scarce. The effect of baiting and trap type on nine-spined stickleback ( Pungitius pungitius ) CPUE was studied in a field experiment conducted over four consecutive days in a small pond in northeastern Finland. The results show that baited traps yielded better (mean CPUE = 1.24 fish/trap/d) catches than unbaited traps (mean CPUE = 0.66); however, there were also differences in CPUE depending on the type of collapsible trap that was used. The trap type effect on CPUE seemed to differ among age classes – the finer meshed trap caught more young-of-the-year fish than the coarse-meshed one, whereas the opposite was true for the older and larger individuals. The results agree with those of an earlier more restricted study conducted in the same locality: Together, these results provide strong evidence for the positive impact of baiting on nine-spined stickleback CPUE. Whether or not baiting influences catch per unit effort (CPUE) in stickleback fisheries remains a matter of debate among researchers in lack of quantitative data. A field experiment conducted with nine-spined stickleback ( Pungitius pungitius ) shows that bating improves CPUE. CPUE is also influenced by trap type, and CPUE of different size and age classes of fish differ depending on the trap type.

Description: by The PLOS Computational Biology Staff

Description: Phylogenetic relationships are hotspots for orchid studies with controversial standpoints. Traditionally, the phylogenies of orchids are based on morphology and subjective factors. Although more reliable than classic phylogenic analyses, the current methods are based on a few gene markers and PCR amplification, which are labor intensive and cannot identify the placement of some species with degenerated plastid genomes. Therefore, a more efficient, labor-saving and reliable method is needed for phylogenic analysis. Here, we present a method of orchid phylogeny construction using transcriptomes. Ten representative species covering five subfamilies of Orchidaceae were selected, and 315 single-copy orthologous genes extracted from the transcriptomes of these organisms were applied to reconstruct a more robust phylogeny of orchids. This approach provided a rapid and reliable method of phylogeny construction for Orchidaceae, one of the most diversified family of angiosperms. We also showed the rigorous systematic position of holomycotrophic species, which has previously been difficult to determine because of the degenerated plastid genome. We concluded that the method presented in this study is more efficient and reliable than methods based on a few gene markers for phylogenic analyses, especially for the holomycotrophic species or those whose DNA sequences have been difficult to amplify. Meanwhile, a total of 315 single-copy orthologous genes of orchids are offered and more informative loci could be used in the future orchid phylogenetic studies. We offered an efficient and reliable method for orchid phylogenic analyses, especially for the holomycotrophic species or those whose DNA sequences have been difficult to amplify. Meanwhile, a total of 315 single-copy orthologous genes of orchids are offered for orchid phylogenetic studies.

Description: The seasonal availability of food resources is an important factor shaping the life-history strategies of organisms. During times of nutritional restriction, physiological trade-offs can induce periods of immune suppression, thereby increasing susceptibility to infectious disease. Our goal was to provide a conceptual framework describing how the endemic level bovine brucellosis ( Brucella abortus ) may be maintained in Yellowstone bison based on the seasonality of food resources and the life-history strategies of the host and pathogen. Our analysis was based on active B. abortus infection (measured via bacterial culture), nutritional indicators (measured as metabolites and hormones in plasma), and carcass measurements of 402 slaughtered bison. Data from Yellowstone bison were used to investigate (1) whether seasonal changes in diet quality affect nutritional condition and coincide with the reproductive needs of female bison; (2) whether active B. abortus infection and infection intensities vary with host nutrition and nutritional condition; and (3) the evidence for seasonal changes in immune responses, which may offer protection against B. abortus , in relation to nutritional condition. Female bison experienced a decline in nutritional condition during winter as reproductive demands of late gestation increased while forage quality and availability declined. Active B. abortus infection was negatively associated with bison age and nutritional condition, with the intensity of infection negatively associated with indicators of nutrition (e.g., dietary protein and energy) and body weight. Data suggest that protective cell-mediated immune responses may be reduced during the B. abortus transmission period, which coincides with nutritional insufficiencies and elevated reproductive demands during spring. Our results illustrate how seasonal food restriction can drive physiological trade-offs that suppress immune function and create infection and transmission opportunities for pathogens. Susceptibility to infectious disease may be influenced by the seasonal availability of food resources. In Yellowstone bison, active brucellosis infection was negatively associated with bison age and nutritional condition, with infection intensities most pronounced in young animals. Our results illustrate how seasonal food restriction might drive physiological trade-offs, which suppress immune function and create infection and transmission opportunities for pathogens.

Description: by James Tamerius, Cécile Viboud, Jeffrey Shaman, Gerardo Chowell While a relationship between environmental forcing and influenza transmission has been established in inter-pandemic seasons, the drivers of pandemic influenza remain debated. In particular, school effects may predominate in pandemic seasons marked by an atypical concentration of cases among children. For the 2009 A/H1N1 pandemic, Mexico is a particularly interesting case study due to its broad geographic extent encompassing temperate and tropical regions, well-documented regional variation in the occurrence of pandemic outbreaks, and coincidence of several school breaks during the pandemic period. Here we fit a series of transmission models to daily laboratory-confirmed influenza data in 32 Mexican states using MCMC approaches, considering a meta-population framework or the absence of spatial coupling between states. We use these models to explore the effect of environmental, school–related and travel factors on the generation of spatially-heterogeneous pandemic waves. We find that the spatial structure of the pandemic is best understood by the interplay between regional differences in specific humidity (explaining the occurrence of pandemic activity towards the end of the school term in late May-June 2009 in more humid southeastern states), school vacations (preventing influenza transmission during July-August in all states), and regional differences in residual susceptibility (resulting in large outbreaks in early fall 2009 in central and northern Mexico that had yet to experience fully-developed outbreaks). Our results are in line with the concept that very high levels of specific humidity, as present during summer in southeastern Mexico, favor influenza transmission, and that school cycles are a strong determinant of pandemic wave timing.

Description: by Alireza Alemi, Carlo Baldassi, Nicolas Brunel, Riccardo Zecchina Understanding the theoretical foundations of how memories are encoded and retrieved in neural populations is a central challenge in neuroscience. A popular theoretical scenario for modeling memory function is the attractor neural network scenario, whose prototype is the Hopfield model. The model simplicity and the locality of the synaptic update rules come at the cost of a poor storage capacity, compared with the capacity achieved with perceptron learning algorithms. Here, by transforming the perceptron learning rule, we present an online learning rule for a recurrent neural network that achieves near-maximal storage capacity without an explicit supervisory error signal, relying only upon locally accessible information. The fully-connected network consists of excitatory binary neurons with plastic recurrent connections and non-plastic inhibitory feedback stabilizing the network dynamics; the memory patterns to be memorized are presented online as strong afferent currents, producing a bimodal distribution for the neuron synaptic inputs. Synapses corresponding to active inputs are modified as a function of the value of the local fields with respect to three thresholds. Above the highest threshold, and below the lowest threshold, no plasticity occurs. In between these two thresholds, potentiation/depression occurs when the local field is above/below an intermediate threshold. We simulated and analyzed a network of binary neurons implementing this rule and measured its storage capacity for different sizes of the basins of attraction. The storage capacity obtained through numerical simulations is shown to be close to the value predicted by analytical calculations. We also measured the dependence of capacity on the strength of external inputs. Finally, we quantified the statistics of the resulting synaptic connectivity matrix, and found that both the fraction of zero weight synapses and the degree of symmetry of the weight matrix increase with the number of stored patterns.

Description: by Sander Land, Steven A. Niederer Biophysical models of cardiac tension development provide a succinct representation of our understanding of force generation in the heart. The link between protein kinetics and interactions that gives rise to high cooperativity is not yet fully explained from experiments or previous biophysical models. We propose a biophysical ODE-based representation of cross-bridge (XB), tropomyosin and troponin within a contractile regulatory unit (RU) to investigate the mechanisms behind cooperative activation, as well as the role of cooperativity in dynamic tension generation across different species. The model includes cooperative interactions between regulatory units (RU-RU), between crossbridges (XB-XB), as well more complex interactions between crossbridges and regulatory units (XB-RU interactions). For the steady-state force-calcium relationship, our framework predicts that: (1) XB-RU effects are key in shifting the half-activation value of the force-calcium relationship towards lower [Ca 2+ ], but have only small effects on cooperativity. (2) XB-XB effects approximately double the duty ratio of myosin, but do not significantly affect cooperativity. (3) RU-RU effects derived from the long-range action of tropomyosin are a major factor in cooperative activation, with each additional unblocked RU increasing the rate of additional RU’s unblocking. (4) Myosin affinity for short (1–4 RU) unblocked stretches of actin of is very low, and the resulting suppression of force at low [Ca 2+ ] is a major contributor in the biphasic force-calcium relationship. We also reproduce isometric tension development across mouse, rat and human at physiological temperature and pacing rate, and conclude that species differences require only changes in myosin affinity and troponin I/troponin C affinity. Furthermore, we show that the calcium dependence of the rate of tension redevelopment k tr is explained by transient blocking of RU’s by a temporary decrease in XB-RU effects.

Description: by Jonas Paulsen, Odin Gramstad, Philippe Collas The three-dimensional (3D) structure of the genome is important for orchestration of gene expression and cell differentiation. While mapping genomes in 3D has for a long time been elusive, recent adaptations of high-throughput sequencing to chromosome conformation capture (3C) techniques, allows for genome-wide structural characterization for the first time. However, reconstruction of "consensus" 3D genomes from 3C-based data is a challenging problem, since the data are aggregated over millions of cells. Recent single-cell adaptations to the 3C-technique, however, allow for non-aggregated structural assessment of genome structure, but data suffer from sparse and noisy interaction sampling. We present a manifold based optimization (MBO) approach for the reconstruction of 3D genome structure from chromosomal contact data. We show that MBO is able to reconstruct 3D structures based on the chromosomal contacts, imposing fewer structural violations than comparable methods. Additionally, MBO is suitable for efficient high-throughput reconstruction of large systems, such as entire genomes, allowing for comparative studies of genomic structure across cell-lines and different species.

Description: by Hiroo Kenzaki, Shoji Takada Nucleosomes, basic units of chromatin, are known to show spontaneous DNA unwrapping dynamics that are crucial for transcriptional activation, but its structural details are yet to be elucidated. Here, employing a coarse-grained molecular model that captures residue-level structural details up to histone tails, we simulated equilibrium fluctuations and forced unwrapping of single nucleosomes at various conditions. The equilibrium simulations showed spontaneous unwrapping from outer DNA and subsequent rewrapping dynamics, which are in good agreement with experiments. We found several distinct partially unwrapped states of nucleosomes, as well as reversible transitions among these states. At a low salt concentration, histone tails tend to sit in the concave cleft between the histone octamer and DNA, tightening the nucleosome. At a higher salt concentration, the tails tend to bound to the outer side of DNA or be expanded outwards, which led to higher degree of unwrapping. Of the four types of histone tails, H3 and H2B tail dynamics are markedly correlated with partial unwrapping of DNA, and, moreover, their contributions were distinct. Acetylation in histone tails was simply mimicked by changing their charges, which enhanced the unwrapping, especially markedly for H3 and H2B tails.

Description: by Sebastian Bitzer, Jelle Bruineberg, Stefan J. Kiebel Even for simple perceptual decisions, the mechanisms that the brain employs are still under debate. Although current consensus states that the brain accumulates evidence extracted from noisy sensory information, open questions remain about how this simple model relates to other perceptual phenomena such as flexibility in decisions, decision-dependent modulation of sensory gain, or confidence about a decision. We propose a novel approach of how perceptual decisions are made by combining two influential formalisms into a new model. Specifically, we embed an attractor model of decision making into a probabilistic framework that models decision making as Bayesian inference. We show that the new model can explain decision making behaviour by fitting it to experimental data. In addition, the new model combines for the first time three important features: First, the model can update decisions in response to switches in the underlying stimulus. Second, the probabilistic formulation accounts for top-down effects that may explain recent experimental findings of decision-related gain modulation of sensory neurons. Finally, the model computes an explicit measure of confidence which we relate to recent experimental evidence for confidence computations in perceptual decision tasks.

Description: Wild bees provide a free and potentially diverse ecosystem service to farmers growing pollination-dependent crops. While many crops benefit from insect pollination, soft fruit crops, including strawberries are highly dependent on this ecosystem service to produce viable fruit. However, as a result of intensive farming practices and declining pollinator populations, farmers are increasingly turning to commercially reared bees to ensure that crops are adequately pollinated throughout the season. Wildflower strips are a commonly used measure aimed at the conservation of wild pollinators. It has been suggested that commercial crops may also benefit from the presence of noncrop flowers; however, the efficacy and economic benefits of sowing flower strips for crops remain relatively unstudied. In a study system that utilizes both wild and commercial pollinators, we test whether wildflower strips increase the number of visits to adjacent commercial strawberry crops by pollinating insects. We quantified this by experimentally sowing wildflower strips approximately 20 meters away from the crop and recording the number of pollinator visits to crops with, and without, flower strips. Between June and August 2013, we walked 292 crop transects at six farms in Scotland, recording a total of 2826 pollinators. On average, the frequency of pollinator visits was 25% higher for crops with adjacent flower strips compared to those without, with a combination of wild and commercial bumblebees ( Bombus spp.) accounting for 67% of all pollinators observed. This effect was independent of other confounding effects, such as the number of flowers on the crop, date, and temperature. Synthesis and applications . This study provides evidence that soft fruit farmers can increase the number of pollinators that visit their crops by sowing inexpensive flower seed mixes nearby. By investing in this management option, farmers have the potential to increase and sustain pollinator populations over time. This study found increased pollinator visitation to crops can be achieved by sowing relatively small and inexpensive flower strips in the crop vicinity. The frequency of pollinator visits was 25% higher for crops with adjacent flower strips compared to those without, an effect independent of other confounding effects such as number of flowers on the crop, date and temperature.

Description: by Malachi Griffith, Jason R. Walker, Nicholas C. Spies, Benjamin J. Ainscough, Obi L. Griffith Massively parallel RNA sequencing (RNA-seq) has rapidly become the assay of choice for interrogating RNA transcript abundance and diversity. This article provides a detailed introduction to fundamental RNA-seq molecular biology and informatics concepts. We make available open-access RNA-seq tutorials that cover cloud computing, tool installation, relevant file formats, reference genomes, transcriptome annotations, quality-control strategies, expression, differential expression, and alternative splicing analysis methods. These tutorials and additional training resources are accompanied by complete analysis pipelines and test datasets made available without encumbrance at www.rnaseq.wiki.

Description: by Arjun Bharioke, Dmitri B. Chklovskii Neurons must faithfully encode signals that can vary over many orders of magnitude despite having only limited dynamic ranges. For a correlated signal, this dynamic range constraint can be relieved by subtracting away components of the signal that can be predicted from the past, a strategy known as predictive coding, that relies on learning the input statistics. However, the statistics of input natural signals can also vary over very short time scales e.g., following saccades across a visual scene. To maintain a reduced transmission cost to signals with rapidly varying statistics, neuronal circuits implementing predictive coding must also rapidly adapt their properties. Experimentally, in different sensory modalities, sensory neurons have shown such adaptations within 100 ms of an input change. Here, we show first that linear neurons connected in a feedback inhibitory circuit can implement predictive coding. We then show that adding a rectification nonlinearity to such a feedback inhibitory circuit allows it to automatically adapt and approximate the performance of an optimal linear predictive coding network, over a wide range of inputs, while keeping its underlying temporal and synaptic properties unchanged. We demonstrate that the resulting changes to the linearized temporal filters of this nonlinear network match the fast adaptations observed experimentally in different sensory modalities, in different vertebrate species. Therefore, the nonlinear feedback inhibitory network can provide automatic adaptation to fast varying signals, maintaining the dynamic range necessary for accurate neuronal transmission of natural inputs.

Description: Phenotypic selection is widely accepted as the primary cause of adaptive evolution in natural populations, but selection on complex functional properties linking physiology, behavior, and morphology has been rarely quantified. In ectotherms, correlational selection on thermal physiology, thermoregulatory behavior, and energy metabolism is of special interest because of their potential coadaptation. We quantified phenotypic selection on thermal sensitivity of locomotor performance (sprint speed), thermal preferences, and resting metabolic rate in captive populations of an ectothermic vertebrate, the common lizard, Zootoca vivipara . No correlational selection between thermal sensitivity of performance, thermoregulatory behavior, and energy metabolism was found. A combination of high body mass and resting metabolic rate was positively correlated with survival and negatively correlated with fecundity. Thus, different mechanisms underlie selection on metabolism in lizards with small body mass than in lizards with high body mass. In addition, lizards that selected the near average preferred body temperature grew faster that their congeners. This is one of the few studies that quantifies significant correlational selection on a proxy of energy expenditure and stabilizing selection on thermoregulatory behavior. The annual survival and total fecundity of common lizards were significantly influenced by correlational selection acting on body mass and resting metabolic rate, but with opposite directions for the two life history traits.

Description: by Murat Alp, Vipan K. Parihar, Charles L. Limoli, Francis A. Cucinotta In this work, a stochastic computational model of microscopic energy deposition events is used to study for the first time damage to irradiated neuronal cells of the mouse hippocampus. An extensive library of radiation tracks for different particle types is created to score energy deposition in small voxels and volume segments describing a neuron’s morphology that later are sampled for given particle fluence or dose. Methods included the construction of in silico mouse hippocampal granule cells from neuromorpho.org with spine and filopodia segments stochastically distributed along the dendritic branches. The model is tested with high-energy 56 Fe, 12 C, and 1 H particles and electrons. Results indicate that the tree-like structure of the neuronal morphology and the microscopic dose deposition of distinct particles may lead to different outcomes when cellular injury is assessed, leading to differences in structural damage for the same absorbed dose. The significance of the microscopic dose in neuron components is to introduce specific local and global modes of cellular injury that likely contribute to spine, filopodia, and dendrite pruning, impacting cognition and possibly the collapse of the neuron. Results show that the heterogeneity of heavy particle tracks at low doses, compared to the more uniform dose distribution of electrons, juxtaposed with neuron morphology make it necessary to model the spatial dose painting for specific neuronal components. Going forward, this work can directly support the development of biophysical models of the modifications of spine and dendritic morphology observed after low dose charged particle irradiation by providing accurate descriptions of the underlying physical insults to complex neuron structures at the nano-meter scale.

Description: by Brinda Vallat, Carlos Madrid-Aliste, Andras Fiser Predicting the three-dimensional structure of proteins from their amino acid sequences remains a challenging problem in molecular biology. While the current structural coverage of proteins is almost exclusively provided by template-based techniques, the modeling of the rest of the protein sequences increasingly require template-free methods. However, template-free modeling methods are much less reliable and are usually applicable for smaller proteins, leaving much space for improvement. We present here a novel computational method that uses a library of supersecondary structure fragments, known as Smotifs, to model protein structures. The library of Smotifs has saturated over time, providing a theoretical foundation for efficient modeling. The method relies on weak sequence signals from remotely related protein structures to create a library of Smotif fragments specific to the target protein sequence. This Smotif library is exploited in a fragment assembly protocol to sample decoys, which are assessed by a composite scoring function. Since the Smotif fragments are larger in size compared to the ones used in other fragment-based methods, the proposed modeling algorithm, SmotifTF, can employ an exhaustive sampling during decoy assembly. SmotifTF successfully predicts the overall fold of the target proteins in about 50% of the test cases and performs competitively when compared to other state of the art prediction methods, especially when sequence signal to remote homologs is diminishing. Smotif-based modeling is complementary to current prediction methods and provides a promising direction in addressing the structure prediction problem, especially when targeting larger proteins for modeling.

Description: Studies on elevation diversity gradients have covered a large number of taxa and regions throughout the world; however, studies of freshwater fish are scarce and restricted to examining their changes along a specific gradient. These studies have reported a monotonic decrease in species richness with increasing elevation, but ignore the high taxonomic differentiation of each headwater assemblage that may generate high β -diversity among them. Here, we analyzed how fish assemblages vary with elevation among regional elevation bands, and how these changes are related to four environmental clines and to changes in the distribution, habitat use, and the morphology of fish species. Using a standardized field sampling technique, we assessed three different diversity and two structural assemblage measures across six regional elevation bands located in the northern Andes (Colombia). Each species was assigned to a functional group based on its body shape, habitat use, morphological, and/or behavioral adaptations. Additionally, at each sampling site, we measured four environmental variables. Our analyses showed: (1) After a monotonic decrease in species richness, we detected an increase in richness in the upper part of the gradient; (2) diversity patterns vary depending on the diversity measure used; (3) diversity patterns can be attributed to changes in species distribution and in the richness and proportions of functional groups along the regional elevation gradient; and (4) diversity patterns and changes in functional groups are highly correlated with variations in environmental variables, which also vary with elevation. These results suggest a novel pattern of variation in species richness with elevation: Species richness increases at the headwaters of the northern Andes owing to the cumulative number of endemic species there. This highlights the need for large-scale studies and has important implications for the aquatic conservation of the region. We perform the first regional analysis of elevation diversity gradients in freshwater fish. For this we used 141 localities between 250 and 2533 m a.s.l. from seven sub-regions in the Northern Andes, Colombia. The results of our study suggest a novel pattern of variation in species richness with elevation: species richness increases at the headwaters of the Northern Andes owing to the cumulative number of endemic species there.

Description: Microbes are critical components of ecosystems and provide vital services (e.g., photosynthesis, decomposition, nutrient recycling). From the diverse roles microbes play in natural ecosystems, high levels of functional diversity result. Quantifying this diversity is challenging, because it is weakly associated with morphological differentiation. In addition, the small size of microbes hinders morphological and behavioral measurements at the individual level, as well as interactions between individuals. Advances in microbial community genetics and genomics, flow cytometry and digital analysis of still images are promising approaches. They miss out, however, on a very important aspect of populations and communities: the behavior of individuals. Video analysis complements these methods by providing in addition to abundance and trait measurements, detailed behavioral information, capturing dynamic processes such as movement, and hence has the potential to describe the interactions between individuals. We introduce BEMOVI, a package using the R and ImageJ software, to extract abundance, morphology, and movement data for tens to thousands of individuals in a video. Through a set of functions BEMOVI identifies individuals present in a video, reconstructs their movement trajectories through space and time, and merges this information into a single database. BEMOVI is a modular set of functions, which can be customized to allow for peculiarities of the videos to be analyzed, in terms of organisms features (e.g., morphology or movement) and how they can be distinguished from the background. We illustrate the validity and accuracy of the method with an example on experimental multispecies communities of aquatic protists. We show high correspondence between manual and automatic counts and illustrate how simultaneous time series of abundance, morphology, and behavior are obtained from BEMOVI. We further demonstrate how the trait data can be used with machine learning to automatically classify individuals into species and that information on movement behavior improves the predictive ability. Video analysis is a promising approach to quantify traits and abundances of species in an automated fashion. In addition, it provides detailed behavioral information, capturing dynamic processes such as movement, and hence has the potential to describe the interactions between individuals. We introduce BEMOVI, an R package to automatically extract such information from sets of videos and show the general validity and accuracy of the method using microcosms of aquatic microbes.

Description: by Po-Wei Chen, Luis L. Fonseca, Yusuf A. Hannun, Eberhard O. Voit The article demonstrates that computational modeling has the capacity to convert metabolic snapshots, taken sequentially over time, into a description of cellular, dynamic strategies. The specific application is a detailed analysis of a set of actions with which Saccharomyces cerevisiae responds to heat stress. Using time dependent metabolic concentration data, we use a combination of mathematical modeling, reverse engineering, and optimization to infer dynamic changes in enzyme activities within the sphingolipid pathway. The details of the sphingolipid responses to heat stress are important, because they guide some of the longer-term alterations in gene expression, with which the cells adapt to the increased temperature. The analysis indicates that all enzyme activities in the system are affected and that the shapes of the time trends in activities depend on the fatty-acyl CoA chain lengths of the different ceramide species in the system.

Description: Nighttime transpiration is a substantial portion of ecosystem water budgets, but few studies compare water use of closely related co-occurring species in a phylogenetic context. Nighttime transpiration can range up to 69% of daytime rates and vary between species, ecosystem, and functional type. We examined leaf-level daytime and nighttime gas exchange of five species of the genus Rubus co-occurring in the Pacific Northwest of western North America in a greenhouse common garden. Contrary to expectations, nighttime transpiration was not correlated to daytime water use. Nighttime transpiration showed pronounced phylogenetic signals, but the proportion of variation explained by different phylogenetic groupings varied across datasets. Leaf osmotic water potential, water potential at turgor loss point, stomatal size, and specific leaf area were correlated with phylogeny but did not readily explain variation in nighttime transpiration. Patterns in interspecific variation as well as a disconnect between rates of daytime and nighttime transpiration suggest that variation in nighttime water use may be at least partly driven by genetic factors independent of those that control daytime water use. Future work with co-occurring congeneric systems is needed to establish the generality of these results and may help determine the mechanism driving interspecific variation in nighttime water use. Nighttime transpiration was measured in a greenhouse common garden in five species of Rubus . A phylogenetic signal was detected in the data, while nighttime and daytime transpiration were not correlated across the genus. This suggests that interspecific differences may contribute to differences in nighttime water use.

Description: Here we used both microsatellites and mtCR (mitochondrial DNA control region) sequences as genetic markers to examine the genetic diversity and population structure of Penaeus monodon shrimp from six Indonesian regions. The microsatellite data showed that shrimp from the Indian and the Pacific Ocean were genetically distinct from each other. It has been reported previously that P. monodon mtCR sequences from the Indo-Pacific group into two major paralogous clades of unclear origin. Here we show that the population structure inferred from mtCR sequences matches the microsatellite-based population structure for one of these clades. This is consistent with the notion that this mtCR clade shares evolutionary history with nuclear DNA and may thus represent nuclear mitochondrial pseudogenes (Numts). While examining genetic diversity and population structure of Penaeus monodon shrimp in Indonesian waters. Similarities between mtCR sequences and microsatellite data for one mtCR clade are discovered. Evidence points towards nuclear DNA as source of this mtCR clade.

Description: Bees are important pollinators of agricultural crops, and bee diversity has been shown to be closely associated with pollination, a valuable ecosystem service. Higher functional diversity and species richness of bees have been shown to lead to higher crop yield. Bees simultaneously represent a mega-diverse taxon that is extremely challenging to sample thoroughly and an important group to understand because of pollination services. We sampled bees visiting apple blossoms in 28 orchards over 6 years. We used species rarefaction analyses to test for the completeness of sampling and the relationship between species richness and sampling effort, orchard size, and percent agriculture in the surrounding landscape. We performed more than 190 h of sampling, collecting 11,219 specimens representing 104 species. Despite the sampling intensity, we captured 〈75% of expected species richness at more than half of the sites. For most of these, the variation in bee community composition between years was greater than among sites. Species richness was influenced by percent agriculture, orchard size, and sampling effort, but we found no factors explaining the difference between observed and expected species richness. Competition between honeybees and wild bees did not appear to be a factor, as we found no correlation between honeybee and wild bee abundance. Our study shows that the pollinator fauna of agroecosystems can be diverse and challenging to thoroughly sample. We demonstrate that there is high temporal variation in community composition and that sites vary widely in the sampling effort required to fully describe their diversity. In order to maximize pollination services provided by wild bee species, we must first accurately estimate species richness. For researchers interested in providing this estimate, we recommend multiyear studies and rarefaction analyses to quantify the gap between observed and expected species richness. Extensive sampling in New York apple orchards demonstrates that the bee fauna of this crop is incredibly diverse, but also very difficult to fully characterize. We recommend multi-year sampling in order to fully describe the bee fauna of agricultural crops.

Description: The endangered plant species Dianthus gratianopolitanus exhibits a highly fragmented distribution range comprising many isolated populations. Based upon this pattern of distribution, we selected a study region in Switzerland with a lower magnitude of isolation (Swiss Jura) and another study region in Germany with a higher degree of isolation (Franconian Jura). In each region, we chose ten populations to analyze population structure, reproduction, and genetic variation in a comparative approach. Therefore, we determined population density, cushion size, and cushion density to analyze population structure, investigated reproductive traits, including number of flowers, capsules, and germination rate, and analyzed amplified fragment length polymorphisms to study genetic variation. Population and cushion density were credibly higher in German than in Swiss populations, whereas reproductive traits and genetic variation within populations were similar in both study regions. However, genetic variation among populations and isolation by distance were stronger in Germany than in Switzerland. Generally, cushion size and density as well as flower and capsule production increased with population size and density, whereas genetic variation decreased with population density. In contrast to our assumptions, we observed denser populations and cushions in the region with the higher magnitude of isolation, whereas reproductive traits and genetic variation within populations were comparable in both regions. This corroborates the assumption that stronger isolation must not necessarily result in the loss of fitness and genetic variation. Furthermore, it supports our conclusion that the protection of strongly isolated populations contributes essentially to the conservation of a species' full evolutionary potential. We analysed the population structure, reproduction and genetic variation of the endangered plant species Dianthus gratianopolitanus from two geographic regions with a different magnitude of isolation. We observed differences in population structure but similar reproduction and genetic variation. We concluded that the isolation of populations of naturally rare species must not necessarily result in the loss of fitness and genetic variation.

Description: This paper proposes a discussion concerning the use of social media-related geographic information in the context of the strategic environmental assessment (SEA) of Sardinian Municipal masterplans (MMPs). We show that this kind of information improves, substantially, the SEA process since it provides planners, evaluators, and the local communities with information retrieved from social media that would have not been available otherwise. This information integrates authoritative data collection, which comes from official sources, and enlightens tastes and preferences of the users of services and infrastructure, and their expectations concerning their spatial organization. A methodological approach related to the collection of social media-related geographic information is implemented and discussed with reference to the urban context of the city of Cagliari (Sardinia, Italy). The results are very effective in terms of provision of information, which may possibly increase the spatial knowledge available for planning policy definition and implementation. In this perspective, this kind of information discloses opportunities for building analytical scenarios related to urban and regional planning and it offers useful suggestions for sustainable development based on tourism strategies.

Description: by Pengyi Yang, Xiaofeng Zheng, Vivek Jayaswal, Guang Hu, Jean Yee Hwa Yang, Raja Jothi Cell signaling underlies transcription/epigenetic control of a vast majority of cell-fate decisions. A key goal in cell signaling studies is to identify the set of kinases that underlie key signaling events. In a typical phosphoproteomics study, phosphorylation sites (substrates) of active kinases are quantified proteome-wide. By analyzing the activities of phosphorylation sites over a time-course, the temporal dynamics of signaling cascades can be elucidated. Since many substrates of a given kinase have similar temporal kinetics, clustering phosphorylation sites into distinctive clusters can facilitate identification of their respective kinases. Here we present a knowledge-based CLUster Evaluation (CLUE) approach for identifying the most informative partitioning of a given temporal phosphoproteomics data. Our approach utilizes prior knowledge, annotated kinase-substrate relationships mined from literature and curated databases, to first generate biologically meaningful partitioning of the phosphorylation sites and then determine key kinases associated with each cluster. We demonstrate the utility of the proposed approach on two time-series phosphoproteomics datasets and identify key kinases associated with human embryonic stem cell differentiation and insulin signaling pathway. The proposed approach will be a valuable resource in the identification and characterizing of signaling networks from phosphoproteomics data.

Description: Because parental care is costly, a sexual conflict between parents over parental investment is expected to arise. Parental care behavior is an adaptive decision, involving trade-offs between remating, and consequently desertion of the brood, and continuing parental effort. If the main advantage of desertion is remating, then this will be a time constraint, because the deserting individual will require a certain minimum period of time to breed again in the same breeding season. So, a short breeding season should force certain individuals to desert the first brood to have enough time to successfully complete their second breeding attempt. The rock sparrow, Petronia petronia , is an unusual species in which brood desertion can occur in both sexes and the breeding season is quite short so it is a good species to investigate the role of time constraint on brood desertion. For 3 years, I investigated the brood desertion modality of the rock sparrow. Then, for 2 years, I removed a group of experimental nest boxes during the autumn. Later, I re-installed the experimental nest boxes after the start of the breeding season (2 weeks after the first egg was laid), mimicking a shortening of the breeding season for the (experimental) pairs that used experimental nest boxes. I found that in the experimental pairs, the percentage of deserting individuals was significantly higher than in the control groups, and the deserting individuals were older females. This experiment adds to our knowledge of timing of reproduction effects on individual decisions to desert by showing that a short and delayed breeding season may have different effects on males and females. To my knowledge, this is the first experimental study that demonstrates a direct link between time constraint and brood desertion. If the main advantage of brood desertion is remating, then this will be a time constraint, because the deserting individual will require a certain minimum period of time to breed again in the same breeding season. I experimentally created two groups of pairs: the control pairs that started to breed as soon as they were ready and the experimental pairs that were forced to postpone their breeding phase because the breeding sites were available later. As predicted, I found that in the experimental pairs the percentage of deserting individuals was significantly higher than in the control groups. To my knowledge, this is the first experimental study that demonstrates a direct link between time constraint and brood desertion.

Description: by Deborah A. Striegel, Manami Hara, Vipul Periwal Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets.

Description: The island rule refers to the tendency of small vertebrates to become larger when isolated on islands and the frequent dwarfing of large forms. It implies genetic control, and a necessary linkage, of size and body-mass differences between insular and mainland populations. To examine the island rule, we compared body size and mass of gray jays ( Perisoreus canadensis ) on Anticosti Island, Québec, located in the Gulf of St. Lawrence, with three mainland populations (2 in Québec and 1 in Ontario). Although gray jays on Anticosti Island were ca 10% heavier, they were not structurally larger, than the three mainland populations. This suggests that Anticosti jays are not necessarily genetically distinct from mainland gray jays and that they may have achieved their greater body masses solely through packing more mass onto mainland-sized body frames. As such, they may be the first-known example of a proposed, purely phenotypic initial step in the adherence to the island rule by an insular population. Greater jay body mass is probably advantageous in Anticosti's high-density, intensely competitive social environment that may have resulted from the island's lack of mammalian nest predators. The island-rule proposes that small animals become larger when isolated on islands whereas large animals tend towards dwarfism. We found that gray jays ( Perisoreus canadensis ) on Anticosti Island, Québec were ca 10% heavier but not structurally larger, than three mainland populations, suggesting suggests that Anticosti jays are not necessarily genetically distinct from mainland gray jays and that they may achieve their greater body masses solely through packing more mass onto mainland-sized body frames. This is the first known example of a proposed, purely phenotypic initial step in the adherence to the island-rule by an insular population.

Description: While the mechanisms by which adult terrestrial plants deploy constitutive and induced responses to grazing pressure are well known, the means by which young aquatic plants defend themselves from herbivory are little studied. This study addresses nitrogen transport in the aquatic angiosperm Myriophyllum spicatum in response to herbivore exposure. Nitrogen tracers were used to monitor nitrogen uptake and reallocation in young plants in response to grazing by the generalist insect herbivore Acentria ephemerella . Total nitrogen content (N%) and patterns of nitrogen uptake and allocation (δ 15 N) were assessed in various plant tissues after 24 and 48 h. Following 24 h exposure to herbivore damage (Experiment 1), nitrogen content of plant apices was significantly elevated. This rapid early reaction may be an adaptation allowing the grazer to be sated as fast as possible, or indicate the accumulation of nitrogenous defense chemicals. After 48 h (Experiment 2), plants' tips showed depletion in nitrogen levels of ca. 60‰ in stem sections vulnerable to grazing. In addition, nitrogen uptake by grazed and grazing-prone upper plant parts was reduced and nutrient allocation into the relatively secure lower parts increased. The results point to three conclusions: (1) exposure to an insect herbivore induces a similar response in immature M. spicatum as previously observed in mature terrestrial species, namely a rapid (within 48 h) reduction in the nutritional value (N%) of vulnerable tissues, (2) high grazing intensity (100% of growing tips affected) did not limit the ability of young plants to induce resistance; and (3) young plants exposed to herbivory exhibit different patterns of nutrient allocation in vulnerable and secure tissues. These results provide evidence of induced defense and resource reallocation in immature aquatic macrophytes which is in line with the responses shown for mature aquatic macrophytes and terrestrial plants. The means by which young aquatic plants defend themselves from herbivory are little studied. This study addresses this gap in knowledge. Nitrogen tracers were used in two mesocosm experiments investigating the response of young Myriophyllum spicatum plants to grazing by the generalist insect herbivore Acentria ephemerella. Results indicate (1) exposure to an insect herbivore induces a rapid (within 48 h) reduction in the nutritional value of vulnerable tissues, (2) high level grazing intensity did not limit the ability of young plants to induce resistance; (3) young plants exposed to herbivory exhibit differential patterns of nutrient allocation in vulnerable and secure tissues.

Description: by Ghanim Ullah, Yina Wei, Markus A Dahlem, Martin Wechselberger, Steven J Schiff Cell volume changes are ubiquitous in normal and pathological activity of the brain. Nevertheless, we know little of how cell volume affects neuronal dynamics. We here performed the first detailed study of the effects of cell volume on neuronal dynamics. By incorporating cell swelling together with dynamic ion concentrations and oxygen supply into Hodgkin-Huxley type spiking dynamics, we demonstrate the spontaneous transition between epileptic seizure and spreading depression states as the cell swells and contracts in response to changes in osmotic pressure. Our use of volume as an order parameter further revealed a dynamical definition for the experimentally described physiological ceiling that separates seizure from spreading depression, as well as predicted a second ceiling that demarcates spreading depression from anoxic depolarization. Our model highlights the neuroprotective role of glial K buffering against seizures and spreading depression, and provides novel insights into anoxic depolarization and the relevant cell swelling during ischemia. We argue that the dynamics of seizures, spreading depression, and anoxic depolarization lie along a continuum of the repertoire of the neuron membrane that can be understood only when the dynamic ion concentrations, oxygen homeostasis,and cell swelling in response to osmotic pressure are taken into consideration. Our results demonstrate the feasibility of a unified framework for a wide range of neuronal behaviors that may be of substantial importance in the understanding of and potentially developing universal intervention strategies for these pathological states.

Description: by John R. Houser, Craig Barnhart, Daniel R. Boutz, Sean M. Carroll, Aurko Dasgupta, Joshua K. Michener, Brittany D. Needham, Ophelia Papoulas, Viswanadham Sridhara, Dariya K. Sydykova, Christopher J. Marx, M. Stephen Trent, Jeffrey E. Barrick, Edward M. Marcotte, Claus O. Wilke How do bacteria regulate their cellular physiology in response to starvation? Here, we present a detailed characterization of Escherichia coli growth and starvation over a time-course lasting two weeks. We have measured multiple cellular components, including RNA and proteins at deep genomic coverage, as well as lipid modifications and flux through central metabolism. Our study focuses on the physiological response of E . coli in stationary phase as a result of being starved for glucose, not on the genetic adaptation of E . coli to utilize alternative nutrients. In our analysis, we have taken advantage of the temporal correlations within and among RNA and protein abundances to identify systematic trends in gene regulation. Specifically, we have developed a general computational strategy for classifying expression-profile time courses into distinct categories in an unbiased manner. We have also developed, from dynamic models of gene expression, a framework to characterize protein degradation patterns based on the observed temporal relationships between mRNA and protein abundances. By comparing and contrasting our transcriptomic and proteomic data, we have identified several broad physiological trends in the E . coli starvation response. Strikingly, mRNAs are widely down-regulated in response to glucose starvation, presumably as a strategy for reducing new protein synthesis. By contrast, protein abundances display more varied responses. The abundances of many proteins involved in energy-intensive processes mirror the corresponding mRNA profiles while proteins involved in nutrient metabolism remain abundant even though their corresponding mRNAs are down-regulated.

Description: by Shaun S. Sanders, Dale D. O. Martin, Stefanie L. Butland, Mathieu Lavallée-Adam, Diego Calzolari, Chris Kay, John R. Yates, Michael R. Hayden Palmitoylation involves the reversible posttranslational addition of palmitate to cysteines and promotes membrane binding and subcellular localization. Recent advancements in the detection and identification of palmitoylated proteins have led to multiple palmitoylation proteomics studies but these datasets are contained within large supplemental tables, making downstream analysis and data mining time-consuming and difficult. Consequently, we curated the data from 15 palmitoylation proteomics studies into one compendium containing 1,838 genes encoding palmitoylated proteins; representing approximately 10% of the genome. Enrichment analysis revealed highly significant enrichments for Gene Ontology biological processes, pathway maps, and process networks related to the nervous system. Strikingly, 41% of synaptic genes encode a palmitoylated protein in the compendium. The top disease associations included cancers and diseases and disorders of the nervous system, with Schizophrenia, HD, and pancreatic ductal carcinoma among the top five, suggesting that aberrant palmitoylation may play a pivotal role in the balance of cell death and survival. This compendium provides a much-needed resource for cell biologists and the palmitoylation field, providing new perspectives for cancer and neurodegeneration.

Description: by Liat Rockah-Shmuel, Ágnes Tóth-Petróczy, Dan S. Tawfik Systematic mappings of the effects of protein mutations are becoming increasingly popular. Unexpectedly, these experiments often find that proteins are tolerant to most amino acid substitutions, including substitutions in positions that are highly conserved in nature. To obtain a more realistic distribution of the effects of protein mutations, we applied a laboratory drift comprising 17 rounds of random mutagenesis and selection of M.HaeIII, a DNA methyltransferase. During this drift, multiple mutations gradually accumulated. Deep sequencing of the drifted gene ensembles allowed determination of the relative effects of all possible single nucleotide mutations. Despite being averaged across many different genetic backgrounds, about 67% of all nonsynonymous, missense mutations were evidently deleterious, and an additional 16% were likely to be deleterious. In the early generations, the frequency of most deleterious mutations remained high. However, by the 17th generation, their frequency was consistently reduced, and those remaining were accepted alongside compensatory mutations. The tolerance to mutations measured in this laboratory drift correlated with sequence exchanges seen in M.HaeIII’s natural orthologs. The biophysical constraints dictating purging in nature and in this laboratory drift also seemed to overlap. Our experiment therefore provides an improved method for measuring the effects of protein mutations that more closely replicates the natural evolutionary forces, and thereby a more realistic view of the mutational space of proteins.

Description: Monitoring and predicting evolutionary changes underlying current environmental modifications are complex challenges. Recent approaches to achieve these objectives include assessing the genetic variation and effects of candidate genes on traits indicating adaptive potential. In birds, for example, short tandem repeat polymorphism at four candidate genes (CLOCK, NPAS2, ADCYAP1, and CREB1) has been linked to variation in phenological traits such as laying date and timing of migration. However, our understanding of their importance as evolutionary predictors is still limited, mainly because the extent of genotype–environment interactions (GxE) related to these genes has yet to be assessed. Here, we studied a population of Tree swallow ( Tachycineta bicolor ) over 4 years in southern Québec (Canada) to assess the relationships between those four candidate genes and two phenological traits related to reproduction (laying date and incubation duration) and also determine the importance of GxE in this system. Our results showed that NPAS2 female genotypes were nonrandomly distributed across the study system and formed a longitudinal cline with longer genotypes located to the east. We observed relationships between length polymorphism at all candidate genes and laying date and/or incubation duration, and most of these relationships were affected by environmental variables (breeding density, latitude, or temperature). In particular, the positive relationships detected between laying date and both CLOCK and NPAS2 female genotypes were variable depending on breeding density. Our results suggest that all four candidate genes potentially affect timing of breeding in birds and that GxE are more prevalent and important than previously reported in this context. Monitoring and predicting evolutionary changes underlying current environmental modifications are complex challenges and these objectives can be achieved by assessing the genetic variation and effects of candidate genes on traits indicating adaptive potential. Here, we studied a population of Tree swallow ( Tachycineta bicolor ) to assess the relationships between four candidate genes (CLOCK, NPAS2, ADCYAP1, CREB1) and two phenological traits related to reproduction (laying date and incubation duration), and also determine the importance of GxE in this system. Our results suggest that all four candidate genes potentially affect timing of breeding in birds and that gene-environment interactions (GxE) are more prevalent and important than previously reported in this context.

Description: by Shuai Yuan, H. Richard Johnston, Guosheng Zhang, Yun Li, Yi-Juan Hu, Zhaohui S. Qin With rapid decline of the sequencing cost, researchers today rush to embrace whole genome sequencing (WGS), or whole exome sequencing (WES) approach as the next powerful tool for relating genetic variants to human diseases and phenotypes. A fundamental step in analyzing WGS and WES data is mapping short sequencing reads back to the reference genome. This is an important issue because incorrectly mapped reads affect the downstream variant discovery, genotype calling and association analysis. Although many read mapping algorithms have been developed, the majority of them uses the universal reference genome and do not take sequence variants into consideration. Given that genetic variants are ubiquitous, it is highly desirable if they can be factored into the read mapping procedure. In this work, we developed a novel strategy that utilizes genotypes obtained a priori to customize the universal haploid reference genome into a personalized diploid reference genome. The new strategy is implemented in a program named RefEditor. When applying RefEditor to real data, we achieved encouraging improvements in read mapping, variant discovery and genotype calling. Compared to standard approaches, RefEditor can significantly increase genotype calling consistency (from 43% to 61% at 4X coverage; from 82% to 92% at 20X coverage) and reduce Mendelian inconsistency across various sequencing depths. Because many WGS and WES studies are conducted on cohorts that have been genotyped using array-based genotyping platforms previously or concurrently, we believe the proposed strategy will be of high value in practice, which can also be applied to the scenario where multiple NGS experiments are conducted on the same cohort. The RefEditor sources are available at https://github.com/superyuan/refeditor.

Description: In 2010, the American pika ( Ochotona princeps fenisex ) was denied federal protection based on limited evidence of persistence in low-elevation environments. Studies in nonalpine areas have been limited to relatively few environments, and it is unclear whether patterns observed elsewhere (e.g., Bodie, CA) represent other nonalpine habitats. This study was designed to establish pika presence in a new location, determine distribution within the surveyed area, and evaluate influences of elevation, vegetation, lava complexity, and distance to habitat edge on pika site occupancy. In 2011 and 2012, we conducted surveys for American pika on four distinct subalpine lava flows of Newberry National Volcanic Monument, Oregon, USA. Field surveys were conducted at predetermined locations within lava flows via silent observation and active searching for pika sign. Site habitat characteristics were included as predictors of occupancy in multinomial regression models. Above and belowground temperatures were recorded at a subsample of pika detection sites. Pika were detected in 26% (2011) and 19% (2012) of survey plots. Seventy-four pika were detected outside survey plot boundaries. Lava complexity was the strongest predictor of pika occurrence, where pika were up to seven times more likely to occur in the most complicated lava formations. Pika were two times more likely to occur with increasing elevation, although they were found at all elevations in the study area. This study expands the known distribution of the species and provides additional evidence for persistence in nonalpine habitats. Results partially support the predictive occupancy model developed for pika at Craters of the Moon National Monument, another lava environment. Characteristics of the lava environment clearly influence pika site occupancy, but habitat variables reported as important in other studies were inconclusive here. Further work is needed to gain a better understanding of the species’ current distribution and ability to persist under future climate conditions. This study documents persistence of a newly discovered population of American pika at elevations below those predicted as optimal for the species. Like other lava environments where pika have been recently documented, lava flows at NNVM appear to be serving as thermal refugia for pika, despite summer temperatures which regularly exceed thermal maxima for the species. It is likely that pika inhabit other low-elevation lava flows in areas that have never been surveyed.

Description: Many plants are grown outside their natural ranges. Plantings adjacent to native ranges provide an opportunity to monitor community assembly among associated insects and their parasitoids in novel environments, to determine whether gradients in species richness emerge and to examine their consequences for host plant reproductive success. We recorded the fig wasps (Chalcidoidea) associated with a single plant resource (ovules of Ficus microcarpa ) along a 1200 km transect in southwest China that extended for 1000 km beyond the tree's natural northern range margin. The fig wasps included the tree's agaonid pollinator and other species that feed on the ovules or are their parasitoids. Phytophagous fig wasps (12 species) were more numerous than parasitoids (nine species). The proportion of figs occupied by fig wasps declined with increasing latitude, as did the proportion of utilized ovules in occupied figs. Species richness, diversity, and abundance of fig wasps also significantly changed along both latitudinal and altitudinal gradients. Parasitoids declined more steeply with latitude than phytophages. Seed production declined beyond the natural northern range margin, and at high elevation, because pollinator fig wasps became rare or absent. This suggests that pollinator climatic tolerances helped limit the tree's natural distribution, although competition with another species may have excluded pollinators at the highest altitude site. Isolation by distance may prevent colonization of northern sites by some fig wasps and act in combination with direct and host-mediated climatic effects to generate gradients in community composition, with parasitoids inherently more sensitive because of declines in the abundance of potential hosts. The fig wasps associated with a single plant resource (ovules of Ficus microcarpa) along a 1200 km transect in SW China that extended for 1000 km beyond the tree's natural northern range margin were recorded. The proportion of figs utilized by any fig wasps declined with increasing latitude, as did the proportion of ovules that were occupied and the species richness, diversity and abundance of fig wasps. Parasitoids declined more steeply with latitude than phytophages.

Description: Evaluating trade-offs in life-history traits of plant pathogens is essential to understand the evolution and epidemiology of diseases. In particular, virulence costs when the corresponding host resistance gene is lacking play a major role in the adaptive biology of pathogens and contribute to the maintenance of their genetic diversity. Here, we investigated whether life-history traits directly linked to the establishment of plant–nematode interactions, that is, ability to locate and move toward the roots of the host plant, and to invade roots and develop into mature females, are affected in Meloidogyne incognita lines virulent against the tomato Mi-1.2 resistance gene. Virulent and avirulent near-isogenic lines only differing in their capacity to reproduce or not on resistant tomatoes were compared in single inoculation or pairwise competition experiments. Data highlighted (1) a global lack of trade-off in traits associated with unnecessary virulence with respect to the nematode ability to successfully infest plant roots and (2) variability in these traits when the genetic background of the nematode is considered irrespective of its (a)virulence status. These data suggest that the variation detected here is independent from the adaptation of M. incognita to host resistance, but rather reflects some genetic polymorphism in this asexual organism. Evaluating trade-offs in life-history traits of plant pathogens is essential to understand the evolution and epidemiology of diseases. Here, we designed experiments to investigate whether traits directly linked to the establishment of host–parasite interactions, that is, ability to locate and move toward the roots of the host plant, and to invade roots and develop into mature females, are affected in an asexual nematode adapted to plant resistance.

Description: by Alexey A. Gritsenko, Marc Hulsman, Marcel J. T. Reinders, Dick de Ridder Translation of RNA to protein is a core process for any living organism. While for some steps of this process the effect on protein production is understood, a holistic understanding of translation still remains elusive. In silico modelling is a promising approach for elucidating the process of protein synthesis. Although a number of computational models of the process have been proposed, their application is limited by the assumptions they make. Ribosome profiling (RP), a relatively new sequencing-based technique capable of recording snapshots of the locations of actively translating ribosomes, is a promising source of information for deriving unbiased data-driven translation models. However, quantitative analysis of RP data is challenging due to high measurement variance and the inability to discriminate between the number of ribosomes measured on a gene and their speed of translation. We propose a solution in the form of a novel multi-scale interpretation of RP data that allows for deriving models with translation dynamics extracted from the snapshots. We demonstrate the usefulness of this approach by simultaneously determining for the first time per-codon translation elongation and per-gene translation initiation rates of Saccharomyces cerevisiae from RP data for two versions of the Totally Asymmetric Exclusion Process (TASEP) model of translation. We do this in an unbiased fashion, by fitting the models using only RP data with a novel optimization scheme based on Monte Carlo simulation to keep the problem tractable. The fitted models match the data significantly better than existing models and their predictions show better agreement with several independent protein abundance datasets than existing models. Results additionally indicate that the tRNA pool adaptation hypothesis is incomplete, with evidence suggesting that tRNA post-transcriptional modifications and codon context may play a role in determining codon elongation rates.

Description: Negative density dependence (NDD) and niche partitioning have been perceived as important mechanisms for the maintenance of species diversity. However, little is known about their relative contributions to seedling survival. We examined the effects of biotic and abiotic neighborhoods and the variations of biotic neighborhoods among species using survival data for 7503 seedlings belonging to 22 woody species over a period of 2 years in three different forest types, a half-mature forest (HF), a mature forest (MF), and an old-growth forest (OGF), each of these representing a specific successional stage in a temperate forest ecosystem in northeastern China. We found a convincing evidence for the existence of NDD in temperate forest ecosystems. The biotic and abiotic variables affecting seedlings survival change with successional stage, seedling size, and age. The strength of NDD for the smaller (〈20 cm in height) and younger seedlings (1–2 years) as well as all seedlings combined varies significantly among species. We found no evidence that a community compensatory trend (CCT) existed in our study area. The results of this study demonstrate that the relative importance of NDD and habitat niche partitioning in driving seedling survival varies with seedling size and age and that the biotic and abiotic factors affecting seedlings survival change with successional stage. The results of this study demonstrate that NDD and habitat niche partitioning simultaneously operate in driving seedling survival in temperate forests, while the strength and importance of these processes vary with successional stage, seedling size and age.

Description: Interspecific hybridization, especially when regularly followed by backcrossing (i.e., introgressive hybridization), conveys a substantial risk for many endangered organisms. This is particularly true for narrow endemics occurring within distributional ranges of widespread congeners. An excellent example is provided by the plant genus Knautia (Caprifoliaceae): Locally endemic K .  carinthiaca is reported from two isolated populations in southern Austria situated within an area predominantly occupied by widespread K .  arvensis . While K .  carinthiaca usually inhabits low-competition communities on rocky outcrops, K .  arvensis occurs mainly in dry to mesic managed grasslands, yet both species can coexist in marginal environments and were suspected to hybridize. Flow cytometry revealed that diploid K .  carinthiaca only occurs at its locus classicus, whereas the second locality is inhabited by the morphologically similar but tetraploid K .  norica . In the, therefore, single population of K .  carinthiaca, flow cytometry and AFLP fingerprinting showed signs of introgressive hybridization with diploid K .  arvensis . Hybridization patterns were also reflected in intermediate habitat preferences and morphology of the hybrids. Environmental barriers to gene flow seem to prevent genetic erosion of K .  carinthiaca individuals from the core ecological niches, restricting most introgressed individuals to peripheral habitats. Efficient conservation of K. carinthiaca will require strict protection of its habitat and ban on forest clear cuts in a buffer zone to prevent invasion of K. arvensis . We demonstrate the large potential of multidisciplinary approaches combining molecular, cytometric, and ecological tools for a reliable inventory and threat assessment of rare species. Interspecific hybridization and/or introgression may convey a substantial threat for narrow endemics occurring within distributional ranges of their widespread congeners. We tested this assumption on an exemplary model system provided by the plant genus Knautia (Caprifoliaceae). By employing several complementary approaches, we determined the current distribution of locally endemic K. carinthiaca , estimated the hybridization risk and proposed necessary conservation actions.

Description: In dioecious species with both sexual and asexual reproduction, the spatial distribution of individual clones affects the potential for sexual reproduction and local adaptation. The seaweed Fucus radicans , endemic to the Baltic Sea, has separate sexes, but new attached thalli may also form asexually. We mapped the spatial distribution of clones (multilocus genotypes, MLGs) over macrogeographic (〉500 km) and microgeographic (〈100 m) scales in the Baltic Sea to assess the relationship between clonal spatial structure, sexual recruitment, and the potential for natural selection. Sexual recruitment was predominant in some areas, while in others asexual recruitment dominated. Where clones of both sexes were locally intermingled, sexual recruitment was nevertheless low. In some highly clonal populations, the sex ratio was strongly skewed due to dominance of one or a few clones of the same sex. The two largest clones (one female and one male) were distributed over 100–550 km of coast and accompanied by small and local MLGs formed by somatic mutations and differing by 1–2 mutations from the large clones. Rare sexual events, occasional long-distance migration, and somatic mutations contribute new genotypic variation potentially available to natural selection. However, dominance of a few very large (and presumably old) clones over extensive spatial and temporal scales suggested that either these have superior traits or natural selection has only been marginally involved in the structuring of genotypes. The seaweed Fucus radicans , endemic to the Baltic Sea, has separate sexes but all thalli may also form new attached thalli asexually. We mapped clones (genotypes) and their spatial distribution over macrogeographic (the species' distribution in northern and eastern Baltic) and microgeographic (〈100 m) scales. Rare sexual events, occasional long-distance migration and somatic mutations contribute new genotypic variation in northern and western populations of this brown algae, nevertheless the same few clones have resisted environmental changes and have dominated much of the species' distribution over extensive periods of time, which suggests that the distribution of clones of F. radicans cannot solely be ascribed to natural selection.

Description: To date, the implications of the predicted greater intra-annual variability and extremes in precipitation on ecosystem functioning have received little attention. This study presents results on leaf-level physiological responses of five species covering the functional groups grasses, forbs, and legumes in the understorey of a Mediterranean oak woodland, with increasing precipitation variability, without altering total annual precipitation inputs. Although extending the dry period between precipitation events from 3 to 6 weeks led to increased soil moisture deficit, overall treatment effects on photosynthetic performance were not observed in the studied species. This resilience to prolonged water stress was explained by different physiological and morphological strategies to withstand periods below the wilting point, that is, isohydric behavior in Agrostis , Rumex, and Tuberaria , leaf succulence in Rumex , and taproots in Tolpis . In addition, quick recovery upon irrigation events and species-specific adaptations of water-use efficiency with longer dry periods and larger precipitation events contributed to the observed resilience in productivity of the annual plant community. Although none of the species exhibited a change in cover with increasing precipitation variability, leaf physiology of the legume Ornithopus exhibited signs of sensitivity to moisture deficit, which may have implications for the agricultural practice of seeding legume-rich mixtures in Mediterranean grassland-type systems. This highlights the need for long-term precipitation manipulation experiments to capture possible directional changes in species composition and seed bank development, which can subsequently affect ecosystem state and functioning. This study presents results on leaf-level physiological responses of five species in the understorey of a Mediterranean oak woodland. The previous reported resilience of productivity in this ecosystem with increasing precipitation variability is explained by different physiological and morphological strategies to withstand periods below the wilting point.

Description: The scale-eating cichlid fish, Perissodus microlepis , from Lake Tanganyika are a well-known example of an asymmetry dimorphism because the mouth/head is either left-bending or right-bending. However, how strongly its pronounced morphological laterality is affected by genetic and environmental factors remains unclear. Using quantitative assessments of mouth asymmetry, we investigated its origin by estimating narrow-sense heritability ( h 2 ) using midparent–offspring regression. The heritability estimates [field estimate: h 2  = 0.22 ± 0.06, P  =   0.013; laboratory estimate: h 2  = 0.18 ± 0.05, P  =   0.004] suggest that although variation in laterality has some additive genetic component, it is strongly environmentally influenced. Family-level association analyses of a putative microsatellite marker that was claimed to be linked to gene(s) for laterality revealed no association of this locus with laterality. Moreover, the observed phenotype frequencies in offspring from parents of different phenotype combinations were not consistent with a previously suggested single-locus two-allele model, but they neither were able to reject with confidence a random asymmetry model. These results reconcile the disputed mechanisms for this textbook case of mouth asymmetry where both genetic and environmental factors contribute to this remarkable case of morphological asymmetry. Using quantitative assessments of mouth asymmetry of scale-eating cichlid fish Perissodus microlepis, we investigated its origin by estimating narrow-sense heritability ( h 2 ) using midparent-offspring regression. The heritability estimates [field-estimate: h 2  = 0.22 ± 0.06, P  = 0.013; laboratory-estimate: h 2  = 0.18 ± 0.05, P  = 0.004] suggest that although variation in laterality has some additive genetic component, it is strongly environmentally influenced. These results reconcile the disputed mechanisms for this textbook case of mouth asymmetry where both genetic and environmental factors contribute to this remarkable case of morphological asymmetry.

Description: To monitor multiple environmental factors of henhouses in modern chicken farms, a henhouse online monitoring system based on wireless sensor network was developed using wireless sensor technology and computer network technology. Sensor data compensation and correction were designed to be achieved using software and data fitting methods, data reliable transmission achieved using a data loss recovery strategy, and data missing during monitoring addressed using a self-decision and online filling method. Operation test of the system showed that: The system was economic and reliable; it enabled wireless monitoring and Web display of the environmental factors of a henhouse; and the root mean square errors (RMSEs) between the estimated values from the self-decision and on-line filling method and experimental values of the four environmental factors were 0.1698, 3.0859, 77 and 0.094, respectively, indicative of high estimation accuracy. The system can provide support for modern management of henhouses and can be transplanted to related monitoring scenarios in the agricultural field.

Description: by Santiago Schnell

Description: The Crassulacean genus Aeonium is a well-known example for plant species radiation on oceanic archipelagos. However, while allopatric speciation among islands is documented for this genus, the role of intra-island speciation due to population divergence by topographical isolation or ecological heterogeneity has not yet been addressed. The aim of this study was to investigate intraspecific genetic structures and to identify spatial and ecological drivers of genetic population differentiation on the island scale. We analyzed inter simple sequence repeat variation within two island-endemic Aeonium species of La Palma: one widespread generalist that covers a large variety of different habitat types ( Ae. davidbramwellii ) and one narrow ecological specialist ( Ae. nobile ), in order to assess evolutionary potentials on this island. Gene pool differentiation and genetic diversity patterns were associated with major landscape structures in both species, with phylogeographic implications. However, overall levels of genetic differentiation were low. For the generalist species, outlier loci detection and loci–environment correlation approaches indicated moderate signatures of divergent selection pressures linked to temperature and precipitation variables, while the specialist species missed such patterns. Our data point to incipient differentiation among populations, emphasizing that ecological heterogeneity and topographical structuring within the small scales of an island can foster evolutionary processes. Very likely, such processes have contributed to the radiation of Aeonium on the Canary Islands. There is also support for different evolutionary mechanisms between generalist and specialist species. We analysed range-wide population genetic variation within two ecologically different single-island endemics of Aeonium on La Palma, Canary Islands. Population differentiation was moderate for both species but was clearly influenced by landscape structures and, within the generalist species covering a large variety of different habitats, some signatures of divergent selection due to climatic parameters were observable. Our study shows that topographical and ecological heterogeneity within single islands are probable drivers of evolution in this iconic example of plant species radiations.

Description: Populations occurring at species' range edges can be locally adapted to unique environmental conditions. From a species' perspective, range-edge environments generally have higher severity and frequency of extreme climatic events relative to the range core. Under future climates, extreme climatic events are predicted to become increasingly important in defining species' distributions. Therefore, range-edge genotypes that are better adapted to extreme climates relative to core populations may be essential to species' persistence during periods of rapid climate change. We use relatively simple conceptual models to highlight the importance of locally adapted range-edge populations (leading and trailing edges) for determining the ability of species to persist under future climates. Using trees as an example, we show how locally adapted populations at species' range edges may expand under future climate change and become more common relative to range-core populations. We also highlight how large-scale habitat destruction occurring in some geographic areas where many species range edge converge, such as biome boundaries and ecotones (e.g., the arc of deforestation along the rainforest-cerrado ecotone in the southern Amazonia), can have major implications for global biodiversity. As climate changes, range-edge populations will play key roles in helping species to maintain or expand their geographic distributions. The loss of these locally adapted range-edge populations through anthropogenic disturbance is therefore hypothesized to reduce the ability of species to persist in the face of rapid future climate change. We synthesize conservation, biogeographic, genetic, and climate change literature to provide a novel conceptual framework of the disproportionately important role that range-edge populations will have in determining species' responses to climate change.

Description: by Alexander Ullrich, Mathias A. Böhme, Johannes Schöneberg, Harald Depner, Stephan J. Sigrist, Frank Noé Synaptic vesicle fusion is mediated by SNARE proteins forming in between synaptic vesicle (v-SNARE) and plasma membrane (t-SNARE), one of which is Syntaxin-1A. Although exocytosis mainly occurs at active zones, Syntaxin-1A appears to cover the entire neuronal membrane. By using STED super-resolution light microscopy and image analysis of Drosophila neuro-muscular junctions, we show that Syntaxin-1A clusters are more abundant and have an increased size at active zones. A computational particle-based model of syntaxin cluster formation and dynamics is developed. The model is parametrized to reproduce Syntaxin cluster-size distributions found by STED analysis, and successfully reproduces existing FRAP results. The model shows that the neuronal membrane is adjusted in a way to strike a balance between having most syntaxins stored in large clusters, while still keeping a mobile fraction of syntaxins free or in small clusters that can efficiently search the membrane or be traded between clusters. This balance is subtle and can be shifted toward almost no clustering and almost complete clustering by modifying the syntaxin interaction energy on the order of only 1 k B T. This capability appears to be exploited at active zones. The larger active-zone syntaxin clusters are more stable and provide regions of high docking and fusion capability, whereas the smaller clusters outside may serve as flexible reserve pool or sites of spontaneous ectopic release.

Description: by Stephan Köhler, Friederike Schmid, Giovanni Settanni Fibrinogen is a serum multi-chain protein which, when activated, aggregates to form fibrin, one of the main components of a blood clot. Fibrinolysis controls blood clot dissolution through the action of the enzyme plasmin, which cleaves fibrin at specific locations. Although the main biochemical factors involved in fibrin formation and lysis have been identified, a clear mechanistic picture of how these processes take place is not available yet. This picture would be instrumental, for example, for the design of improved thrombolytic or anti-haemorrhagic strategies, as well as, materials with improved biocompatibility. Here, we present extensive molecular dynamics simulations of fibrinogen which reveal large bending motions centered at a hinge point in the coiled-coil regions of the molecule. This feature, likely conserved across vertebrates according to our analysis, suggests an explanation for the mechanism of exposure to lysis of the plasmin cleavage sites on fibrinogen coiled-coil region. It also explains the conformational variability of fibrinogen observed during its adsorption on inorganic surfaces and it is supposed to play a major role in the determination of the hydrodynamic properties of fibrinogen. In addition the simulations suggest how the dynamics of the D region of fibrinogen may contribute to the allosteric regulation of the blood coagulation cascade through a dynamic coupling between the a- and b-holes, important for fibrin polymerization, and the integrin binding site P1.

Description: by Sergei Maslov, Kim Sneppen Populations of species in ecosystems are often constrained by availability of resources within their environment. In effect this means that a growth of one population, needs to be balanced by comparable reduction in populations of others. In neutral models of biodiversity all populations are assumed to change incrementally due to stochastic births and deaths of individuals. Here we propose and model another redistribution mechanism driven by abrupt and severe reduction in size of the population of a single species freeing up resources for the remaining ones. This mechanism may be relevant e.g. for communities of bacteria, with strain-specific collapses caused e.g. by invading bacteriophages, or for other ecosystems where infectious diseases play an important role. The emergent dynamics of our system is characterized by cyclic ‘‘diversity waves’’ triggered by collapses of globally dominating populations. The population diversity peaks at the beginning of each wave and exponentially decreases afterwards. Species abundances have bimodal time-aggregated distribution with the lower peak formed by populations of recently collapsed or newly introduced species while the upper peak - species that has not yet collapsed in the current wave. In most waves both upper and lower peaks are composed of several smaller peaks. This self-organized hierarchical peak structure has a long-term memory transmitted across several waves. It gives rise to a scale-free tail of the time-aggregated population distribution with a universal exponent of 1.7. We show that diversity wave dynamics is robust with respect to variations in the rules of our model such as diffusion between multiple environments, species-specific growth and extinction rates, and bet-hedging strategies.

Description: by Hannah Edwards, Charlotte M. Deane Several protein structure classification schemes exist that partition the protein universe into structural units called folds. Yet these schemes do not discuss how these units sit relative to each other in a global structure space. In this paper we construct networks that describe such global relationships between folds in the form of structural bridges. We generate these networks using four different structural alignment methods across multiple score thresholds. The networks constructed using the different methods remain a similar distance apart regardless of the probability threshold defining a structural bridge. This suggests that at least some structural bridges are method specific and that any attempt to build a picture of structural space should not be reliant on a single structural superposition method. Despite these differences all representations agree on an organisation of fold space into five principal community structures: all- α , all- β sandwiches, all- β barrels, α / β and α + β . We project estimated fold ages onto the networks and find that not only are the pairings of unconnected folds associated with higher age differences than bridged folds, but this difference increases with the number of networks displaying an edge. We also examine different centrality measures for folds within the networks and how these relate to fold age. While these measures interpret the central core of fold space in varied ways they all identify the disposition of ancestral folds to fall within this core and that of the more recently evolved structures to provide the peripheral landscape. These findings suggest that evolutionary information is encoded along these structural bridges. Finally, we identify four highly central pivotal folds representing dominant topological features which act as key attractors within our landscapes.

Description: by Ayal Lavi, Omri Perez, Uri Ashery Neuronal microcircuits generate oscillatory activity, which has been linked to basic functions such as sleep, learning and sensorimotor gating. Although synaptic release processes are well known for their ability to shape the interaction between neurons in microcircuits, most computational models do not simulate the synaptic transmission process directly and hence cannot explain how changes in synaptic parameters alter neuronal network activity. In this paper, we present a novel neuronal network model that incorporates presynaptic release mechanisms, such as vesicle pool dynamics and calcium-dependent release probability, to model the spontaneous activity of neuronal networks. The model, which is based on modified leaky integrate-and-fire neurons, generates spontaneous network activity patterns, which are similar to experimental data and robust under changes in the model's primary gain parameters such as excitatory postsynaptic potential and connectivity ratio. Furthermore, it reliably recreates experimental findings and provides mechanistic explanations for data obtained from microelectrode array recordings, such as network burst termination and the effects of pharmacological and genetic manipulations. The model demonstrates how elevated asynchronous release, but not spontaneous release, synchronizes neuronal network activity and reveals that asynchronous release enhances utilization of the recycling vesicle pool to induce the network effect. The model further predicts a positive correlation between vesicle priming at the single-neuron level and burst frequency at the network level; this prediction is supported by experimental findings. Thus, the model is utilized to reveal how synaptic release processes at the neuronal level govern activity patterns and synchronization at the network level.

Description: by Michael A. Cerullo

Description: by Jasmine Foo, Lin L Liu, Kevin Leder, Markus Riester, Yoh Iwasa, Christoph Lengauer, Franziska Michor The traditional view of cancer as a genetic disease that can successfully be treated with drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in many human cancer types. However, only a subset of mutations found within the genomic landscape of cancer is likely to provide a fitness advantage to the cell. Distinguishing such “driver” mutations from innocuous “passenger” events is critical for prioritizing the validation of candidate mutations in disease-relevant models. We design a novel statistical index, called the Hitchhiking Index, which reflects the probability that any observed candidate gene is a passenger alteration, given the frequency of alterations in a cross-sectional cancer sample set, and apply it to a mutational data set in colorectal cancer. Our methodology is based upon a population dynamics model of mutation accumulation and selection in colorectal tissue prior to cancer initiation as well as during tumorigenesis. This methodology can be used to aid in the prioritization of candidate mutations for functional validation and contributes to the process of drug discovery.

Description: by Héctor García Martín, Vinay Satish Kumar, Daniel Weaver, Amit Ghosh, Victor Chubukov, Aindrila Mukhopadhyay, Adam Arkin, Jay D. Keasling Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13 C labeling experiments and genome-scale models. The data from 13 C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13 C labeling data. A comparison shows that the results of this new method are similar to those found through 13 C Metabolic Flux Analysis ( 13 C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems.

Description: Many studies have explored the value of using more sophisticated coastal impact models and higher resolution elevation data in sea-level rise (SLR) adaptation planning. However, we know little about to what extent the improved models and data could actually lead to better conservation outcomes under SLR. This is important to know because high-resolution data are likely to not be available in some data-poor coastal areas in the world and running more complicated coastal impact models is relatively time-consuming, expensive, and requires assistance by qualified experts and technicians. We address this research question in the context of identifying conservation priorities in response to SLR. Specifically, we investigated the conservation value of using more accurate light detection and ranging (Lidar)-based digital elevation data and process-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple “bathtub” models based on the relatively coarse National Elevation Dataset (NED) in a coastal region of northeast Florida. We compared conservation outcomes identified by reserve design software (Zonation) using three different model dataset combinations (Bathtub–NED, Bathtub–Lidar, and SLAMM–Lidar). The comparisons show that the conservation priorities are significantly different with different combinations of coastal impact models and elevation dataset inputs. The research suggests that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because this model–dataset combination could improve conservation outcomes under SLR. Less accurate coastal impact models, including ones created using coarser Digital Elevation Model (DEM) data can still be useful when better data and models are not available or feasible, but results need to be appropriately assessed and communicated. A future research priority is to investigate how conservation priorities may vary among different SLR scenarios when different combinations of model-data inputs are used. We know little about to what extent the improved models and data could actually lead to better conservation outcomes for adaptation to sea-level rise (SLR). We investigated the value of using more accurate light detection and ranging (Lidar)-based digital elevation data and rules-based coastal land-cover change models (Sea Level Affecting Marshes Model, SLAMM) to identify conservation priorities versus simple “bathtub” models based on the relatively coarse National Elevation Dataset in a coastal region of northeast Florida. The comparison shows that it is valuable to invest in more accurate coastal impact models and elevation datasets in SLR adaptive conservation planning because the less accurate models and elevation datasets could fail to identify areas of high conservation value under a 1-m SLR scenario.

Description: How much should an individual invest in immunity as it grows older? Immunity is costly and its value is likely to change across an organism's lifespan. A limited number of studies have focused on how personal immune investment changes with age in insects, but we do not know how social immunity, immune responses that protect kin, changes across lifespan, or how resources are divided between these two arms of the immune response. In this study, both personal and social immune functions are considered in the burying beetle, Nicrophorus vespilloides . We show that personal immune function declines (phenoloxidase levels) or is maintained (defensin expression) across lifespan in nonbreeding beetles but is maintained (phenoloxidase levels) or even upregulated (defensin expression) in breeding individuals. In contrast, social immunity increases in breeding burying beetles up to middle age, before decreasing in old age. Social immunity is not affected by a wounding challenge across lifespan, whereas personal immunity, through PO, is upregulated following wounding to a similar extent across lifespan. Personal immune function may be prioritized in younger individuals in order to ensure survival until reproductive maturity. If not breeding, this may then drop off in later life as state declines. As burying beetles are ephemeral breeders, breeding opportunities in later life may be rare. When allowed to breed, beetles may therefore invest heavily in “staying alive” in order to complete what could potentially be their final reproductive opportunity. As parental care is important for the survival and growth of offspring in this genus, staying alive to provide care behaviors will clearly have fitness payoffs. This study shows that all immune traits do not senesce at the same rate. In fact, the patterns observed depend upon the immune traits measured and the breeding status of the individual. Multiple immune responses have evolved to protect the individual (personal) or their kin (social). Several studies have considered how personal immunity changes with age, but this is the first study to consider how social immunity changes with age. We found that in virgins, personal immunity declined or was maintained with age, while in breeders, it was maintained or even increased with age. Social immunity increased to middle age before falling in old age. We discuss the potential reasons for these differing responses to aging.

Description: The expression of male secondary sexual traits can be dynamic, changing size, shape, color, or structure over the course of different seasons. However, the factors underlying such changes are poorly understood. In male Anolis carolinensis lizards, a morphological secondary sexual signal called the dewlap changes size seasonally within individuals. Here, we test the hypothesis that seasonal changes in male dewlap size are driven by increased use and extension of the dewlap in spring and summer, when males are breeding, relative to the winter and fall. We captured male green anole lizards prior to the onset of breeding and constrained the dewlap in half of them such that it could not be extended. We then measured dewlap area in the spring, summer, and winter, and dewlap skin and belly skin elasticity in summer and winter. Dewlaps in unconstrained males increase in area from spring to summer and then shrink in the winter, whereas the dewlaps of constrained males consistently shrink from spring to winter. Dewlap skin is significantly more elastic than belly skin, and skin overall is more elastic in the summer relative to winter. These results show that seasonal changes in dewlap size are a function of skin elasticity and display frequency, and suggest that the mechanical properties of signaling structures can have important implications for signal evolution and design. Male Anolis carolinensis dewlaps used for display change size over the course of a breeding season. Here we show that this size change is likely a consequence of dewlap elasticity, which causes the dewlap to stretch out when it is displayed frequently.

Description: by Julia C. Quindlen, Victor K. Lai, Victor H. Barocas Cutaneous mechanoreceptors transduce different tactile stimuli into neural signals that produce distinct sensations of touch. The Pacinian corpuscle (PC), a cutaneous mechanoreceptor located deep within the dermis of the skin, detects high frequency vibrations that occur within its large receptive field. The PC is comprised of lamellae that surround the nerve fiber at its core. We hypothesized that a layered, anisotropic structure, embedded deep within the skin, would produce the nonlinear strain transmission and low spatial sensitivity characteristic of the PC. A multiscale finite-element model was used to model the equilibrium response of the PC to indentation. The first simulation considered an isolated PC with fiber networks aligned with the PC’s surface. The PC was subjected to a 10 μm indentation by a 250 μm diameter indenter. The multiscale model captured the nonlinear strain transmission through the PC, predicting decreased compressive strain with proximity to the receptor’s core, as seen experimentally by others. The second set of simulations considered a single PC embedded epidermally (shallow) or dermally (deep) to model the PC’s location within the skin. The embedded models were subjected to 10 μm indentations at a series of locations on the surface of the skin. Strain along the long axis of the PC was calculated after indentation to simulate stretch along the nerve fiber at the center of the PC. Receptive fields for the epidermis and dermis models were constructed by mapping the long-axis strain after indentation at each point on the surface of the skin mesh. The dermis model resulted in a larger receptive field, as the calculated strain showed less indenter location dependence than in the epidermis model.

Description: Ecological and environmental heterogeneity can produce genetic differentiation in highly mobile species. Accordingly, local adaptation may be expected across comparatively short distances in the presence of marked environmental gradients. Within the European continent, wolves ( Canis lupus ) exhibit distinct north–south population differentiation. We investigated more than 67-K single nucleotide polymorphism (SNP) loci for signatures of local adaptation in 59 unrelated wolves from four previously identified population clusters (northcentral Europe n  = 32, Carpathian Mountains n  = 7, Dinaric-Balkan n  = 9, Ukrainian Steppe n  = 11). Our analyses combined identification of outlier loci with findings from genome-wide association study of individual genomic profiles and 12 environmental variables. We identified 353 candidate SNP loci. We examined the SNP position and neighboring megabase (1 Mb, one million bases) regions in the dog ( C. lupus familiaris ) genome for genes potentially under selection, including homologue genes in other vertebrates. These regions included functional genes for, for example, temperature regulation that may indicate local adaptation and genes controlling for functions universally important for wolves, including olfaction, hearing, vision, and cognitive functions. We also observed strong outliers not associated with any of the investigated variables, which could suggest selective pressures associated with other unmeasured environmental variables and/or demographic factors. These patterns are further supported by the examination of spatial distributions of the SNPs associated with universally important traits, which typically show marked differences in allele frequencies among population clusters. Accordingly, parallel selection for features important to all wolves may eclipse local environmental selection and implies long-term separation among population clusters. We investigated 〉67 K single nucleotide polymorphism (SNP) loci for signatures of local adaptation in 59 unrelated wolves ( Canis lupus ) from four previously identified population clusters and identified 353 candidate loci. The neighbouring megabase regions in the dog ( C. lupus familiaris ) genome included functional genes for e.g. temperature regulation that may indicate local adaptation and genes controlling for universally important functions, including olfaction, hearing, vision and cognition. Single nucleotide polymorphisms associated with universally important traits typically show marked differences in allele frequencies among population clusters, and parallel selection for features important to all wolves may eclipse local environmental selection and implies long-term separation among population clusters.

Description: by Vipin Narang, Muhamad Azfar Ramli, Amit Singhal, Pavanish Kumar, Gennaro de Libero, Michael Poidinger, Christopher Monterola Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.

Description: by Jianfei Hu, Johnathan Neiswinger, Jin Zhang, Heng Zhu, Jiang Qian Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.

Description: by Vassilios Christopoulos, Paul R. Schrater Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation.

Description: by Chakravarthy Marella, Andrew E. Torda, Dominik Schwudke A lipidome is the set of lipids in a given organism, cell or cell compartment and this set reflects the organism’s synthetic pathways and interactions with its environment. Recently, lipidomes of biological model organisms and cell lines were published and the number of functional studies of lipids is increasing. In this study we propose a homology metric that can quantify systematic differences in the composition of a lipidome. Algorithms were developed to 1. consistently convert lipids structure into SMILES, 2. determine structural similarity between molecular species and 3. describe a lipidome in a chemical space model. We tested lipid structure conversion and structure similarity metrics, in detail, using sets of isomeric ceramide molecules and chemically related phosphatidylinositols. Template-based SMILES showed the best properties for representing lipid-specific structural diversity. We also show that sequence analysis algorithms are best suited to calculate distances between such template-based SMILES and we adjudged the Levenshtein distance as best choice for quantifying structural changes. When all lipid molecules of the LIPIDMAPS structure database were mapped in chemical space, they automatically formed clusters corresponding to conventional chemical families. Accordingly, we mapped a pair of lipidomes into the same chemical space and determined the degree of overlap by calculating the Hausdorff distance. We named this metric the ‘Lipidome jUXtaposition (LUX) score’. First, we tested this approach for estimating the lipidome similarity on four yeast strains with known genetic alteration in fatty acid synthesis. We show that the LUX score reflects the genetic relationship and growth temperature better than conventional methods although the score is based solely on lipid structures. Next, we applied this metric to high-throughput data of larval tissue lipidomes of Drosophila. This showed that the LUX score is sufficient to cluster tissues and determine the impact of nutritional changes in an unbiased manner, despite the limited information on the underlying structural diversity of each lipidome. This study is the first effort to define a lipidome homology metric based on structures that will enrich functional association of lipids in a similar manner to measures used in genetics. Finally, we discuss the significance of the LUX score to perform comparative lipidome studies across species borders.

Description: The genitalia of internally fertilizing taxa represent a striking example of rapid morphological evolution. Although sexual selection can shape variation in genital morphology, it has been difficult to test whether multiple sexual selection pressures combine to drive the rapid evolution of individual genital structures. Here, we test the hypothesis that both pre- and postcopulatory sexual selection can act in concert to shape complex structural variation in secondary genital morphology. We genetically modified the size and shape of the posterior lobes of Drosophila melanogaster males and tested the consequences of morphological variation on several reproductive measures. We found that the posterior lobes are necessary for genital coupling and that they are also the targets of multiple postcopulatory processes that shape quantitative variation in morphology, even though these structures make no direct contact with the external female genitalia or internal reproductive organs during mating. We also found that males with smaller and less structurally complex posterior lobes suffer substantial fitness costs in competitive fertilization experiments. Our results show that sexual selection mechanisms can combine to shape the morphology of a single genital structure and that the posterior lobes of D. melanogaster are the targets of multiple postcopulatory selection pressures. Pre- and post-copulatory sexual selection are thought to target genital structures that differ functionally during copulation, and with different strengths. We find that both selective forces combine to shape complex morphology of a single structure that is not directly involved with insemination during mating.

Description: Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques. Species distribution models (SDM) are becoming increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. but are rarely validated with independent data. Here we use independent data to test how the predictive performance of SDMs constructed to predict wild bee distributions depends on species traits, habitat type, and sampling technique. We conclude that, as a conservation tool, SDMs are best suited to modelling rarer, specialist species than more generalist species and will be most useful in long-term stable habitats.

Description: Despite the scientific method's central tenets of reproducibility (the ability to obtain similar results when repeated) and repeatability (the ability to replicate an experiment based on methods described), published ecological research continues to fail to provide sufficient methodological detail to allow either repeatability of verification. Recent systematic reviews highlight the problem, with one example demonstrating that an average of 13% of studies per year (±8.0 [SD]) failed to report sample sizes. The problem affects the ability to verify the accuracy of any analysis, to repeat methods used, and to assimilate the study findings into powerful and useful meta-analyses. The problem is common in a variety of ecological topics examined to date, and despite previous calls for improved reporting and metadata archiving, which could indirectly alleviate the problem, there is no indication of an improvement in reporting standards over time. Here, we call on authors, editors, and peer reviewers to consider repeatability as a top priority when evaluating research manuscripts, bearing in mind that legacy and integration into the evidence base can drastically improve the impact of individual research reports. Despite the widely accepted need to ensure that scientific research is both reproducible and repeatable, currently published ecological research still fails to provide sufficient methodological detail. Recent systematic reviews highlight the extent of the problem, which affects the ability to verify the accuracy and assess the reliability of any analysis, to repeat methods used, and to assimilate the study findings into powerful and useful meta-analyses. We call on authors, editors and peer-reviewers to consider repeatability as a top priority when evaluating research manuscripts, bearing in mind that legacy and integration into the evidence base can drastically improve the impact of individual research reports.

Description: The soil CO 2 emission is recognized as one of the largest fluxes in the global carbon cycle. Small errors in its estimation can result in large uncertainties and have important consequences for climate model predictions. Monte Carlo approach is efficient for estimating and reducing spatial scale sampling errors. However, that has not been used in soil CO 2 emission studies. Here, soil respiration data from 51 PVC collars were measured within farmland cultivated by maize covering 25 km 2 during the growing season. Based on Monte Carlo approach, optimal sample sizes of soil temperature, soil moisture, and soil CO 2 emission were determined. And models of soil respiration can be effectively assessed: Soil temperature model is the most effective model to increasing accuracy among three models. The study demonstrated that Monte Carlo approach may improve soil respiration accuracy with limited sample size. That will be valuable for reducing uncertainties of global carbon cycle. Monte Carlo approach can effectively optimize sample size and filter model; A small plot with enough sample size can introduce similar optimal error; Monte Carlo method identified W may be a greater source of variability in scaling up.

Description: In recent decades, alpine grasslands have been seriously degraded on the Tibetan Plateau and grazing exclusion by fencing has been widely adopted to restore degraded grasslands since 2004. To elucidate how alpine grasslands carbon (C), nitrogen (N), and phosphorus (P) storage responds to this management strategy, three types of alpine grassland in nine counties in Tibet were selected to investigate C, N, and P storage in the environment by comparing free grazing (FG) and grazing exclusion (GE) treatments, which had run for 6–8 years. The results revealed that there were no significant differences in total ecosystem C, N, and P storage, as well as the C, N, and P stored in both total biomass and soil (0–30 cm) fractions between FG and GE grasslands. However, precipitation played a key role in controlling C, N, and P storage and distribution. With grazing exclusion, C and N stored in aboveground biomass significantly increased by 5.7 g m −2 and 0.1 g m −2 , respectively, whereas the C and P stored in the soil surface layer (0–15 cm) significantly decreased by 862.9 g m −2 and 13.6 g m −2 , respectively. Furthermore, the storage of the aboveground biomass C, N, and P was positively correlated with vegetation cover and negatively correlated with the biodiversity index, including Pielou evenness index, Shannon–Wiener diversity index, and Simpson dominance index. The storage of soil surface layer C, N, and P was positively correlated with soil silt content and negatively correlated with soil sand content. Our results demonstrated that grazing exclusion had no impact on total C, N, and P storage, as well as C, N, and P in both total biomass and soil (0–30 cm) fractions in the alpine grassland ecosystem. However, grazing exclusion could result in increased aboveground biomass C and N pools and decreased soil surface layer (0–15 cm) C and P pools. In recent decades, alpine grasslands have been seriously degraded on the Tibetan Plateau and grazing exclusion by fencing has been widely adopted to restore degraded grasslands since 2004. This article investigates how alpine grasslands carbon (C), nitrogen (N) and phosphorus (P) storage response to this management strategy by comparing free grazing (FG) and grazing exclusion (GE) treatments. Our results demonstrated that this short-term grazing exclusion had no impact on total C, N, and P storage, as well as C, N, and P in both total biomass and soil fractions in the alpine grassland ecosystem.

Description: The self-organizing nature of the Mobile Ad hoc Networks (MANETs) provide a communication channel anywhere, anytime without any pre-existing network infrastructure. However, it is exposed to various vulnerabilities that may be exploited by the malicious nodes. One such malicious behavior is introduced by blackhole nodes, which can be easily introduced in the network and, in turn, such nodes try to crumble the working of the network by dropping the maximum data under transmission. In this paper, a new protocol is proposed which is based on the widely used Ad hoc On-Demand Distance Vector (AODV) protocol, Enhanced Secure Trusted AODV (ESTA), which makes use of multiple paths along with use of trust and asymmetric cryptography to ensure data security. The results, based on NS-3 simulation, reveal that the proposed protocol is effectively able to counter the blackhole nodes in three different scenarios.

Description: by Noah Ollikainen, René M. de Jong, Tanja Kortemme Interactions between small molecules and proteins play critical roles in regulating and facilitating diverse biological functions, yet our ability to accurately re-engineer the specificity of these interactions using computational approaches has been limited. One main difficulty, in addition to inaccuracies in energy functions, is the exquisite sensitivity of protein–ligand interactions to subtle conformational changes, coupled with the computational problem of sampling the large conformational search space of degrees of freedom of ligands, amino acid side chains, and the protein backbone. Here, we describe two benchmarks for evaluating the accuracy of computational approaches for re-engineering protein-ligand interactions: (i) prediction of enzyme specificity altering mutations and (ii) prediction of sequence tolerance in ligand binding sites. After finding that current state-of-the-art “fixed backbone” design methods perform poorly on these tests, we develop a new “coupled moves” design method in the program Rosetta that couples changes to protein sequence with alterations in both protein side-chain and protein backbone conformations, and allows for changes in ligand rigid-body and torsion degrees of freedom. We show significantly increased accuracy in both predicting ligand specificity altering mutations and binding site sequences. These methodological improvements should be useful for many applications of protein – ligand design. The approach also provides insights into the role of subtle conformational adjustments that enable functional changes not only in engineering applications but also in natural protein evolution.

Description: by Pete Riley, Michal Ben-Nun, Jon A. Linker, Angelia A. Cost, Jose L. Sanchez, Dylan George, David P. Bacon, Steven Riley The potential rapid availability of large-scale clinical episode data during the next influenza pandemic suggests an opportunity for increasing the speed with which novel respiratory pathogens can be characterized. Key intervention decisions will be determined by both the transmissibility of the novel strain (measured by the basic reproductive number R 0 ) and its individual-level severity. The 2009 pandemic illustrated that estimating individual-level severity, as described by the proportion p C of infections that result in clinical cases, can remain uncertain for a prolonged period of time. Here, we use 50 distinct US military populations during 2009 as a retrospective cohort to test the hypothesis that real-time encounter data combined with disease dynamic models can be used to bridge this uncertainty gap. Effectively, we estimated the total number of infections in multiple early-affected communities using the model and divided that number by the known number of clinical cases. Joint estimates of severity and transmissibility clustered within a relatively small region of parameter space, with 40 of the 50 populations bounded by: p C , 0.0133–0.150 and R 0 , 1.09–2.16. These fits were obtained despite widely varying incidence profiles: some with spring waves, some with fall waves and some with both. To illustrate the benefit of specific pairing of rapidly available data and infectious disease models, we simulated a future moderate pandemic strain with p C approximately ×10 that of 2009; the results demonstrating that even before the peak had passed in the first affected population, R 0 and p C could be well estimated. This study provides a clear reference in this two-dimensional space against which future novel respiratory pathogens can be rapidly assessed and compared with previous pandemics.

Description: by Gang Li, Karen E. Ross, Cecilia N. Arighi, Yifan Peng, Cathy H. Wu, K. Vijay-Shanker MicroRNAs (miRNAs) regulate a wide range of cellular and developmental processes through gene expression suppression or mRNA degradation. Experimentally validated miRNA gene targets are often reported in the literature. In this paper, we describe miRTex, a text mining system that extracts miRNA-target relations, as well as miRNA-gene and gene-miRNA regulation relations. The system achieves good precision and recall when evaluated on a literature corpus of 150 abstracts with F-scores close to 0.90 on the three different types of relations. We conducted full-scale text mining using miRTex to process all the Medline abstracts and all the full-length articles in the PubMed Central Open Access Subset. The results for all the Medline abstracts are stored in a database for interactive query and file download via the website at http://proteininformationresource.org/mirtex. Using miRTex, we identified genes potentially regulated by miRNAs in Triple Negative Breast Cancer, as well as miRNA-gene relations that, in conjunction with kinase-substrate relations, regulate the response to abiotic stress in Arabidopsis thaliana . These two use cases demonstrate the usefulness of miRTex text mining in the analysis of miRNA-regulated biological processes.

Description: by Greg Jensen, Fabian Muñoz, Yelda Alkan, Vincent P. Ferrera, Herbert S. Terrace Transitive inference (the ability to infer that B 〉 D given that B 〉 C and C 〉 D ) is a widespread characteristic of serial learning, observed in dozens of species. Despite these robust behavioral effects, reinforcement learning models reliant on reward prediction error or associative strength routinely fail to perform these inferences. We propose an algorithm called betasort , inspired by cognitive processes, which performs transitive inference at low computational cost. This is accomplished by (1) representing stimulus positions along a unit span using beta distributions, (2) treating positive and negative feedback asymmetrically, and (3) updating the position of every stimulus during every trial, whether that stimulus was visible or not. Performance was compared for rhesus macaques, humans, and the betasort algorithm, as well as Q -learning, an established reward-prediction error (RPE) model. Of these, only Q -learning failed to respond above chance during critical test trials. Betasort’s success (when compared to RPE models) and its computational efficiency (when compared to full Markov decision process implementations) suggests that the study of reinforcement learning in organisms will be best served by a feature-driven approach to comparing formal models.

Description: This paper is based on the experience of introducing wireless sensor networks (WSNs) into the building industry in Denmark and in a rural area of Greenland. There are very real advantages in the application of the technology and its consequences for the life cycle operation of the building sector. Sensor networks can be seen as an important part of the Internet of Things and may even constitute an Internet of Sensors, since the communication layers can differ from the Internet standards. The current paper describes the case for application, followed by a discussion of the observed adaptive advantages and consequences of the technology. Essentially, WSNs constitute a highly sophisticated technology that is more robust in a rural context due to its extremely simple installation procedures (plug and play) allowing the use of local less-skilled labour, and the possibility of reconfiguring and repurposing its use remotely.

Description: Understanding the mechanisms underlying the movements and spread of a species over time and space is a major concern of ecology. Here, we assessed the effects of an individual's sex and the density and sex ratio of conspecifics in the local and neighboring environment on the movement probability of the banana weevil, Cosmopolites sordidus . In a “two patches” experiment, we used radiofrequency identification tags to study the C. sordidus movement response to patch conditions. We showed that local and neighboring densities of conspecifics affect the movement rates of individuals but that the density-dependent effect can be either positive or negative depending on the relative densities of conspecifics in local and neighboring patches. We demonstrated that sex ratio also influences the movement of C. sordidus , that is, the weevil exhibits nonfixed sex-biased movement strategies. Sex-biased movement may be the consequence of intrasexual competition for resources (i.e., oviposition sites) in females and for mates in males. We also detected a high individual variability in the propensity to move. Finally, we discuss the role of demographic stochasticity, sex-biased movement, and individual heterogeneity in movement on the colonization process. This article presents an empirical approach to understand how the decision to move is influenced by relationships between individual phenotype (sex) and the population density, and sex ratio of the local and neighboring patches. We prove that movement depends on the dynamics of population density and sex ratio of both the local patch and the neighboring patch. We show that sex-biased dispersal is highly dependent on the interactions between the sex of the individual and the patch conditions (sex ratio and density).

Description: by Alberto Romagnoni, Jérôme Ribot, Daniel Bennequin, Jonathan Touboul The layout of sensory brain areas is thought to subtend perception. The principles shaping these architectures and their role in information processing are still poorly understood. We investigate mathematically and computationally the representation of orientation and spatial frequency in cat primary visual cortex. We prove that two natural principles, local exhaustivity and parsimony of representation, would constrain the orientation and spatial frequency maps to display a very specific pinwheel-dipole singularity. This is particularly interesting since recent experimental evidences show a dipolar structures of the spatial frequency map co-localized with pinwheels in cat. These structures have important properties on information processing capabilities. In particular, we show using a computational model of visual information processing that this architecture allows a trade-off in the local detection of orientation and spatial frequency, but this property occurs for spatial frequency selectivity sharper than reported in the literature. We validated this sharpening on high-resolution optical imaging experimental data. These results shed new light on the principles at play in the emergence of functional architecture of cortical maps, as well as their potential role in processing information.

Description: by Kimberly Glass, Michelle Girvan The Gene Ontology (GO) provides biologists with a controlled terminology that describes how genes are associated with functions and how functional terms are related to one another. These term-term relationships encode how scientists conceive the organization of biological functions, and they take the form of a directed acyclic graph (DAG). Here, we propose that the network structure of gene-term annotations made using GO can be employed to establish an alternative approach for grouping functional terms that captures intrinsic functional relationships that are not evident in the hierarchical structure established in the GO DAG. Instead of relying on an externally defined organization for biological functions, our approach connects biological functions together if they are performed by the same genes, as indicated in a compendium of gene annotation data from numerous different sources. We show that grouping terms by this alternate scheme provides a new framework with which to describe and predict the functions of experimentally identified sets of genes.

Description: by Robert P. Jenkins, Anja Hanisch, Cristian Soza-Ried, Erik Sahai, Julian Lewis The somite segmentation clock is a robust oscillator used to generate regularly-sized segments during early vertebrate embryogenesis. It has been proposed that the clocks of neighbouring cells are synchronised via inter-cellular Notch signalling, in order to overcome the effects of noisy gene expression. When Notch-dependent communication between cells fails, the clocks of individual cells operate erratically and lose synchrony over a period of about 5 to 8 segmentation clock cycles (2–3 hours in the zebrafish). Here, we quantitatively investigate the effects of stochasticity on cell synchrony, using mathematical modelling, to investigate the likely source of such noise. We find that variations in the transcription, translation and degradation rate of key Notch signalling regulators do not explain the in vivo kinetics of desynchronisation. Rather, the analysis predicts that clock desynchronisation, in the absence of Notch signalling, is due to the stochastic dissociation of Her1/7 repressor proteins from the oscillating her1/7 autorepressed target genes. Using in situ hybridisation to visualise sites of active her1 transcription, we measure an average delay of approximately three minutes between the times of activation of the two her1 alleles in a cell. Our model shows that such a delay is sufficient to explain the in vivo rate of clock desynchronisation in Notch pathway mutant embryos and also that Notch-mediated synchronisation is sufficient to overcome this stochastic variation. This suggests that the stochastic nature of repressor/DNA dissociation is the major source of noise in the segmentation clock.

Description: The Yucatán Peninsula in Mexico contains some of the largest breeding groups of the globally distributed and critically endangered hawksbill turtle ( Eretmochelys imbricata ). An improved understanding of the breeding system of this species and how its genetic variation is structured among nesting areas is required before the threats to its survival can be properly evaluated. Here, we genotype 1195 hatchlings and 41 nesting females at 12 microsatellite loci to assess levels of multiple paternity, genetic variation and whether individual levels of homozygosity are associated with reproductive success. Of the 50 clutches analyzed, only 6% have multiple paternity. The distribution of pairwise relatedness among nesting localities (rookeries) was not random with elevated within-rookery relatedness, and declining relatedness with geographic distance indicating some natal philopatry. Although there was no strong evidence that particular rookeries had lost allelic variation via drift, younger turtles had significantly lower levels of genetic variation than older turtles, suggesting some loss of genetic variation. At present there is no indication that levels of genetic variation are associated with measures of reproductive success such as clutch size, hatching success, and frequency of infertile eggs. We genotype critically endangered hawksbill turtle ( Eretmochelys imbricata ) hatchlings and nesting females at 12 microsatellite loci from the Yucatan Peninsula to assess levels of multiple paternity, genetic variation and it relation with reproductive success. We found very low multiple paternity levels; relatedness among rookeries was not random and decrease with geographic distance indicating natal philopatry; and there is no indication that levels of genetic variation are associated with reproductive success.

Description: by Maciej Jan Ejsmond, Jacek Radwan Major Histocompatibility Complex (MHC) genes code for proteins involved in the incitation of the adaptive immune response in vertebrates, which is achieved through binding oligopeptides (antigens) of pathogenic origin. Across vertebrate species, substitutions of amino acids at sites responsible for the specificity of antigen binding (ABS) are positively selected. This is attributed to pathogen-driven balancing selection, which is also thought to maintain the high polymorphism of MHC genes, and to cause the sharing of allelic lineages between species. However, the nature of this selection remains controversial. We used individual-based computer simulations to investigate the roles of two phenomena capable of maintaining MHC polymorphism: heterozygote advantage and host-pathogen arms race (Red Queen process). Our simulations revealed that levels of MHC polymorphism were high and driven mostly by the Red Queen process at a high pathogen mutation rate, but were low and driven mostly by heterozygote advantage when the pathogen mutation rate was low. We found that novel mutations at ABSs are strongly favored by the Red Queen process, but not by heterozygote advantage, regardless of the pathogen mutation rate. However, while the strong advantage of novel alleles increased the allele turnover rate, under a high pathogen mutation rate, allelic lineages persisted for a comparable length of time under Red Queen and under heterozygote advantage. Thus, when pathogens evolve quickly, the Red Queen is capable of explaining both positive selection and long coalescence times, but the tension between the novel allele advantage and persistence of alleles deserves further investigation.

Description: by Manuel Schottdorf, Wolfgang Keil, David Coppola, Leonard E. White, Fred Wolf The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1’s intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.

Description: by Jordi Fonollosa, Emre Neftci, Mikhail Rabinovich We often learn and recall long sequences in smaller segments, such as a phone number 858 534 22 30 memorized as four segments. Behavioral experiments suggest that humans and some animals employ this strategy of breaking down cognitive or behavioral sequences into chunks in a wide variety of tasks, but the dynamical principles of how this is achieved remains unknown. Here, we study the temporal dynamics of chunking for learning cognitive sequences in a chunking representation using a dynamical model of competing modes arranged to evoke hierarchical Winnerless Competition (WLC) dynamics. Sequential memory is represented as trajectories along a chain of metastable fixed points at each level of the hierarchy, and bistable Hebbian dynamics enables the learning of such trajectories in an unsupervised fashion. Using computer simulations, we demonstrate the learning of a chunking representation of sequences and their robust recall. During learning, the dynamics associates a set of modes to each information-carrying item in the sequence and encodes their relative order. During recall, hierarchical WLC guarantees the robustness of the sequence order when the sequence is not too long. The resulting patterns of activities share several features observed in behavioral experiments, such as the pauses between boundaries of chunks, their size and their duration. Failures in learning chunking sequences provide new insights into the dynamical causes of neurological disorders such as Parkinson’s disease and Schizophrenia.