False alarms, real challenges--one university's communication response to the 2001 anthrax crisis

Considerable research exists on how government agencies at the federal, state, and local levels communicated during the fall 2001 anthrax attacks. However, there is little research on how other institutions handled this crisis, in terms of their response to potential anthrax contamination (aka "white powder scares") and their approach to disseminating important health and safety information. In this article, we investigate a major university's communication response to the anthrax crisis. First, we describe its communication experiences relating to a large white powder scare that occurred in October 2001. Second, we describe the university's broader communication efforts in terms of several important elements of risk communication research, including influence of source attributes, key messages, preferred channels, responses to information requests, and organizational influences. This study underlines that an institution does not have to be directly affected by a crisis to find itself on the communication "front lines." Moreover, other institutions may find it useful to learn from the experiences of this university, so that they may communicate more effectively during future crises.     

A career pathway in protein folding: from model peptides to postreductionist protein science

This review discusses the inherent challenge of linking "reductionist" approaches to decipher the information encoded in protein sequences with burgeoning efforts to explore protein folding in native environments-"postreductionist" approaches. Because the invitation to write this article came as a result of my selection to receive the 2010 Dorothy Hodgkin Award of the Protein Society, I use examples from my own work to illustrate the evolution from the reductionist to the postreductionist perspective. I am incredibly honored to receive the Hodgkin Award, but I want to emphasize that it is the combined effort, creativity, and talent of many students, postdoctoral fellows, and collaborators over several years that has led to any accomplishments on which this selection is based. Moreover, I do not claim to have unique insight into the topics discussed here; but this writing opportunity allows me to illustrate some threads in the evolution of protein folding research with my own experiences and to point out to those embarking on careers how the twists and turns in anyone's scientific path are influenced and enriched by the scientific context of our research. The path my own career has taken thus far has been shaped by the timing of discoveries in the field of protein science; together with our contemporaries, we become part of a knowledge evolution. In my own case, this has been an epoch of great discovery in protein folding and I feel very fortunate to have participated in it.     

Curvature in hand movements as a result of visual misjudgements of direction

The path that our hand takes when moving from one position to another is often slightly curved. Part of this curvature is caused by perceptual errors. We examine here whether this is so for the influence that a surface's orientation has on the approaching hand's path. When moving our hand towards a point on a surface we tend to follow a path that makes the final approach more orthogonal to the surface at that point. Doing so makes us less sensitive to imperfections in controlling our movements. Here we show that this tendency is also present when moving towards a point along an edge of a drawing of an oriented bar. The influence of the bar's orientation is no smaller when people are explicitly asked to move as straight as possible, than when they are instructed to move as fast as possible. The bar's orientation also influences perceptual judgements of a straight path, but this influence is only as large as it is on the curvature of the hand's path for judgements of the direction from the hand's initial position to the target. We conclude that the influence of the bar's orientation on the curvature of the hand's path is caused by a misperception of the initial direction in which the hand has to move to reach the target.     

Machine learning modeling of family wide enzyme-substrate specificity screens

Biocatalysis is a promising approach to sustainably synthesize pharmaceuticals, complex natural products, and commodity chemicals at scale. However, the adoption of biocatalysis is limited by our ability to select enzymes that will catalyze their natural chemical transformation on non-natural substrates. While machine learning and in silico directed evolution are well-posed for this predictive modeling challenge, efforts to date have primarily aimed to increase activity against a single known substrate, rather than to identify enzymes capable of acting on new substrates of interest. To address this need, we curate 6 different high-quality enzyme family screens from the literature that each measure multiple enzymes against multiple substrates. We compare machine learning-based compound-protein interaction (CPI) modeling approaches from the literature used for predicting drug-target interactions. Surprisingly, comparing these interaction-based models against collections of independent (single task) enzyme-only or substrate-only models reveals that current CPI approaches are incapable of learning interactions between compounds and proteins in the current family level data regime. We further validate this observation by demonstrating that our no-interaction baseline can outperform CPI-based models from the literature used to guide the discovery of kinase inhibitors. Given the high performance of non-interaction based models, we introduce a new structure-based strategy for pooling residue representations across a protein sequence. Altogether, this work motivates a principled path forward in order to build and evaluate meaningful predictive models for biocatalysis and other drug discovery applications.     

A brief history of the status of transposable elements: from junk DNA to major players in evolution

The idea that some genetic factors are able to move around chromosomes emerged more than 60 years ago when Barbara McClintock first suggested that such elements existed and had a major role in controlling gene expression and that they also have had a major influence in reshaping genomes in evolution. It was many years, however, before the accumulation of data and theories showed that this latter revolutionary idea was correct although, understandably, it fell far short of our present view of the significant influence of what are now known as "transposable elements" in evolution. In this article, I summarize the main events that influenced my thinking about transposable elements as a young scientist and the influence and role of these specific genomic elements in evolution over subsequent years. Today, we recognize that the findings about genomic changes affected by transposable elements have considerably altered our view of the ways in which genomes evolve and work.     

Origins of Life: Chemical and Philosophical Approaches

In this article we address selected important milestones of chemical evolution that led to life. The first such milestone could be achieved by Oparin’s model, which accounts for the early stages of chemical evolution. These occurred at the dawn of development of primitive chemical systems that were pre-RNA. Oparin’s model consists of spontaneous formation of coacervates that encapsulate chemical matter, undergo primitive self-replication, and provide a pathway to a primitive metabolism. We review the experimental updates of his model from our laboratory and discuss types of selection that could have occurred in these primitive systems. Another major milestone in chemical evolution is the transition from abiotic to biotic. This has occurred later, after the RNA world evolved. A controversy of what life is interferes with the efforts to elucidate this transition. Thus, we present various definitions of life, some of which specifically include the requirements and mechanisms for this transition. Self-replication is one of the major requirements for life. In this context we re-examine the question if viruses, which do not have capability to self-replicate, are alive. We draw on philosophy of Hegel, Aristotle, Rescher, Priest, and Fry to guide us in our endeavors. Specifically, we apply Hegel’s law on quantity-to-quality transition to abiotic-to-biotic transition, Aristotle’s philosophy to the definition of life, Priest’s dialetheism to the question if viruses are alive or not, Fry’s philosophy to the beginning of natural selection in chemical evolution, and Rescher’s philosophy to the possible cognitive bias toward simple definitions of life.     

A new bayesian method for fitting evolutionary models to comparative data with intraspecific variation

Phylogenetic comparative methods that incorporate intraspecific variability are relatively new and, so far, not especially widely used in empirical studies. In the present short article we will describe a new Bayesian method for fitting evolutionary models to comparative data that incorporates intraspecific variability. This method differs from an existing likelihood-based approach in that it requires no a priori inference about species means and variances; rather it takes phenotypic values from individuals and a phylogenetic tree as input, and then samples species means and variances, along with the parameters of the evolutionary model, from their joint posterior probability distribution. One of the most novel and intriguing attributes of this approach is that jointly sampling the species means with the evolutionary model parameters means that the model and tree can influence our estimates of species mean trait values, not just the reverse. In the present implementation, we first apply this method to the most widely used evolutionary model for continuously valued phenotypic trait data (Brownian motion). However, the general approach has broad applicability, which we illustrate by also fitting the λ model, another simple model for quantitative trait evolution on a phylogeny. We test our approach via simulation and by analyzing two empirical datasets obtained from the literature. Finally, we have implemented the methods described herein in a new function for the R statistical computing environment, and this function will be distributed as part of the 'phytools' R library.     

Repeated exposure to social stress alters the development of agonistic behavior in male golden hamsters

In male golden hamsters, exposure to social stress during puberty alters aggressive behavior. Interestingly, agonistic behavior undergoes two major transitions during puberty: a decline in attack frequency and a shift from play fighting to adult-like aggression. Based on previous observations, we developed an approach for characterizing offensive responses as play fighting or adult-like. The present studies had two aims. First, we validated our approach by looking at the development of attack types during puberty. Second, we looked at the effects of repeated social stress on the development of agonistic behavior by repeatedly exposing individuals to aggressive adults during puberty. In the first phase of the study, our results point to three different developmental periods. Initially, animals engage in agonistic behavior though attacks targeted at the face and cheeks. This period lasts from Postnatal Day 20 (P-20) to P-40 (early puberty). This phase corresponding to play fighting is followed by a transitional period characterized by attacks focused on the flanks (from P-40 to P-50, mid-puberty). Afterward, animals perform adult-like aggression characterized by attacks focused on the belly and rear. Our data also show that repeated exposure to aggressive adults has two separate effects on the development of agonistic behavior. Repeated social stress accelerated the onset of adult-like agonistic responses. Furthermore, attack frequency, while decreasing during puberty, remained at a higher level in early adulthood in stressed animals. These results show that repeated exposure to social stress during puberty alters the development of agonistic behavior both qualitatively and quantitatively.     

Wall Lizards Modulate Refuge Use through Continuous Assessment of Predation Risk Level

Prey species might use several possible ways to assess predation risk when encountering a predator. Animals may consider the risk level estimated in a first encounter to remain unchanged across subsequent encounters (fixed risk response), or they may update and change their responses across encounters in accordance with short‐term changes in risk levels (flexible risk response). We examined in the field how wall lizards assess risk level by analyzing time spent in refuges after simulated predator attacks. We first examined how risk was assessed when multiple consecutive sources of risk were present simultaneously. The results suggest that wall lizards assess risk based on multiple cues, such as approach speed, directness, and persistence (measured as the distance of the predator to their refuge after an attack). When risk was high lizards remained longer in their refuges. The first decision to appear partly from the refuge depended on both approach speed and persistence, whereas the decision to emerge completely depended only on persistence and not on approach speed. This suggests that wall lizards update information on predator threat and adjusted their emergence accordingly. In a second experiment, we analyzed how short‐term changes in risk level of successive attacks affected refuge use. Successive emergence times varied as a function of current risk level of each repeated attack, independently of the risk level of previous attacks. This indicated that lizards could track short‐term changes in risk level through time and modify their initial responses when required. Fine adjustments of refuge use may help lizards to minimize costs of refuge use in unfavorable and variable environments where antipredatory responses are costly.     

A new type of radical-pair-based model for magnetoreception

Certain migratory birds can sense the Earth's magnetic field. The nature of this process is not yet properly understood. Here we offer a simple explanation according to which birds literally see the local magnetic field through the impact of a physical rather than a chemical signature of the radical pair: a transient, long-lived electric dipole moment. Based on this premise, our picture can explain recent surprising experimental data indicating long lifetimes for the radical pair. Moreover, there is a clear evolutionary path toward this field-sensing mechanism: it is an enhancement of a weak effect that may be present in many species.     

Efficient selection of branch-specific models of sequence evolution

The analysis of extant sequences shows that molecular evolution has been heterogeneous through time and among lineages. However, for a given sequence alignment, it is often difficult to uncover what factors caused this heterogeneity. In fact, identifying and characterizing heterogeneous patterns of molecular evolution along a phylogenetic tree is very challenging, for lack of appropriate methods. Users either have to a priori define groups of branches along which they believe molecular evolution has been similar or have to allow each branch to have its own pattern of molecular evolution. The first approach assumes prior knowledge that is seldom available, and the second requires estimating an unreasonably large number of parameters. Here we propose a convenient and reliable approach where branches get clustered by their pattern of molecular evolution alone, with no need for prior knowledge about the data set under study. Model selection is achieved in a statistical framework and therefore avoids overparameterization. We rely on substitution mapping for efficiency and present two clustering approaches, depending on whether or not we expect neighbouring branches to share more similar patterns of sequence evolution than distant branches. We validate our method on simulations and test it on four previously published data sets. We find that our method correctly groups branches sharing similar equilibrium GC contents in a data set of ribosomal RNAs and recovers expected footprints of selection through dN/dS. Importantly, it also uncovers a new pattern of relaxed selection in a phylogeny of Mantellid frogs, which we are able to correlate to life-history traits. This shows that our programs should be very useful to study patterns of molecular evolution and reveal new correlations between sequence and species evolution. Our programs can run on DNA, RNA, codon, or amino acid sequences with a large set of possible models of substitutions and are available at http://biopp.univ-montp2.fr/forge/testnh.     

Evolution in stage-structured populations

For many organisms, stage is a better predictor of demographic rates than age. Yet no general theoretical framework exists for understanding or predicting evolution in stage-structured populations. Here, we provide a general modeling approach that can be used to predict evolution and demography of stage-structured populations. This advances our ability to understand evolution in stage-structured populations to a level previously available only for populations structured by age. We use this framework to provide the first rigorous proof that Lande's theorem, which relates adaptive evolution to population growth, applies to stage-classified populations, assuming only normality and that evolution is slow relative to population dynamics. We extend this theorem to allow for different means or variances among stages. Our next major result is the formulation of Price's theorem, a fundamental law of evolution, for stage-structured populations. In addition, we use data from Trillium grandiflorum to demonstrate how our models can be applied to a real-world population and thereby show their practical potential to generate accurate projections of evolutionary and population dynamics. Finally, we use our framework to compare rates of evolution in age- versus stage-structured populations, which shows how our methods can yield biological insights about evolution in stage-structured populations.     

Irrigation and its effect on polyphagous shot hole borer attack

Polyphagous shot hole borer (PSHB), Euwallacea whitfordiodendrus (Schedl) (Coleoptera: Curculionidae, Scolytinae), is an ambrosia beetle that has recently invaded southern California, USA. This beetle successfully attacks and reproduces in a multitude of tree species. As direct control methods are limited, we investigated cultural management options, and sought to determine whether irrigation affects the number of attacks host trees experienced. If irrigation plays a role, cultural control methods could be recommended to managers and growers. Three separate experiments were conducted that monitored the number of attacks on trees with different levels of irrigation. Two experiments examined PSHB attacks in established landscape trees where irrigation was either present or absent. A third experiment used young potted box elder with irrigation controlled with timed emitters. In all three experiments, the level of irrigation received by the trees did not affect the number of attacks. The results suggest that changes in irrigation practices do not affect risk from PSHB attack.     

Modelling evolutionary cell behaviour using neural networks: Application to tumour growth

In this paper, we present a modelling framework for cellular evolution that is based on the notion that a cell’s behaviour is driven by interactions with other cells and its immediate environment. We equip each cell with a phenotype that determines its behaviour and implement a decision mechanism to allow evolution of this phenotype. This decision mechanism is modelled using feed-forward neural networks, which have been suggested as suitable models of cell signalling pathways. The environmental variables are presented as inputs to the network and result in a response that corresponds to the phenotype of the cell. The response of the network is determined by the network parameters, which are subject to mutations when the cells divide. This approach is versatile as there are no restrictions on what the input or output nodes represent, they can be chosen to represent any environmental variables and behaviours that are of importance to the cell population under consideration. This framework was implemented in an individual-based model of solid tumour growth in order to investigate the impact of the tissue oxygen concentration on the growth and evolutionary dynamics of the tumour. Our results show that the oxygen concentration affects the tumour at the morphological level, but more importantly has a direct impact on the evolutionary dynamics. When the supply of oxygen is limited we observe a faster divergence away from the initial genotype, a higher population diversity and faster evolution towards aggressive phenotypes. The implementation of this framework suggests that this approach is well suited for modelling systems where evolution plays an important role and where a changing environment exerts selection pressure on the evolving population.     

To the Final Goal: Can We Predict and Suggest Mutations for Protein to Develop Desired Phenotype?

Directed evolution of proteins is a good approach to develop desired phenotypes from existing proteins. Fully experimental protein evolution usually utilizes randomization of a given protein sequence by error-prone PCR or gene shuffling followed by high-throughput selection or timeconsuming screening method. However, these random methods create mutant library full of deleterious mutations. In addition, they need high-throughput screening or selection method to search for positive clones from an enormous size of mutant library. Construction of a mutant library while retaining the original function is important for efficient protein evolution because it greatly reduces time and effort for the identification of positive mutants. Therefore, researchers have tried to reduce the size of mutant library by minimizing the occurrence of deleterious mutants. Such efforts have led to the creation of a concept of ‘small but smart library’. For this goal, neutral drift theory has been applied. Although smart library greatly reduces the library size, it is still the beyond the capacity of low-throughput assay. In parallel, computational analysis of protein structure and efforts to discriminate mutatable residues from all residues of a given protein have been consistently pursued. Accumulated knowledge of protein evolution through random mutation and selection has improved our understanding of functions of amino acids in protein structure. Protein evolution by rational design is being developed based on such understanding. In this review, we describe how the use of semi-rationally designed library rather than completely random one has impacted the overall procedure of directed evolution. We also describe efforts made to evaluate the effect of single mutation. Such efforts will bring lazy boys to the final goal - computational mutation suggestion system.     

Evolutionary crossroads in developmental biology: Cnidaria

There is growing interest in the use of cnidarians (corals, sea anemones, jellyfish and hydroids) to investigate the evolution of key aspects of animal development, such as the formation of the third germ layer (mesoderm), the nervous system and the generation of bilaterality. The recent sequencing of the Nematostella and Hydra genomes, and the establishment of methods for manipulating gene expression, have inspired new research efforts using cnidarians. Here, we present the main features of cnidarian models and their advantages for research, and summarize key recent findings using these models that have informed our understanding of the evolution of the developmental processes underlying metazoan body plan formation.     

Tracing the geographical origin of Megastigmus transvaalensis (Hymenoptera: Torymidae): an African wasp feeding on a South American plant in North America

Determining the geographical origin of an introduced organism can be critical to understanding or managing a non-native species, but is often difficult when the organism is small or inconspicuous. We used a phylogeographical approach to identify the region of endemism and determine the geographical origin of world populations of the seed-feeding wasp Megastigmus transvaalensis (Hussey). This wasp feeds on African Rhus species and South American Schinus species in various locations around the world. Because it is present both in Africa and in South America, it is unclear whether the wasp was originally an African Rhus-feeder that has begun feeding on Schinus or a South American Schinus-feeder that has started feeding on Rhus. Phylogenetic analysis of 800 bp of mitochondrial cytochrome oxidase I sequence data found extensive variation and phylogeographical structure within African M. transvaalensis. Specimens from other locations around the world were all identical in COI sequence and were phylogenetically nested within the African samples. We conclude that M. transvaalensis was originally an African Rhus-feeder that readily attacks Schinus. We evaluate potential pathways of introduction of this wasp to the New World, and we discuss implications of our results for biocontrol efforts against invasive Schinus populations.     

The likelihood node density effect and consequences for evolutionary studies of molecular rates

Many molecular phylogenies show longer root-to-tip path lengths in species-rich groups, encouraging hypotheses linking cladogenesis with accelerated molecular evolution. However, the pattern can also be caused by an artifact called the node density effect (NDE): this effect occurs when the method used to reconstruct a tree underestimates multiple hits that would have been revealed by extra nodes, leading to longer root-to-tip path lengths in clades with more terminal taxa. Here we use a twofold approach to demonstrate that maximum likelihood and Bayesian methods also suffer from the NDE known to affect parsimony. First, simulations deliberately mismatching the simulation and reconstruction models show that the greater the model disparity, the greater the gap between actual and reconstructed tree lengths, and the greater the NDE. Second, taxon sampling manipulation with empirical data shows that NDE can still be present when using optimized models: across 12 datasets, 70 out of 109 sister path comparisons showed significant evidence of NDE. Unless the model fairly accurately reconstructs the real tree length-and given the complexity of real sequence evolution this may be uncommon -- it will consistently produce a node density artifact. At commonly encountered divergence levels, a 10% underestimation of tree length results in > or = 80% of simulated phylogenies showing a positive NDE. Bayesian trees have a slight but consistently stronger effect. This pervasive methodological artifact increases apparent rate heterogeneity, and can compromise investigations of factors influencing molecular evolutionary rate that use path lengths in topologically asymmetric trees.     

Toward a more trait-centered approach to diffuse (co)evolution

How species evolve depends on the communities in which they are embedded. Here, we briefly review the ideas underlying concepts of diffuse coevolution, evolution, and selection. We discuss criteria to identify when evolution will be diffuse. We advocate a more explicitly trait-oriented approach to diffuse (co)evolution, and discuss how considering effects of interacting species on fitness alone tells us little about evolution. We endorse the view that diffuse evolution occurs whenever the response to selection by one interacting species on a given trait is altered by the presence of a second interacting species. Building on the work of others, we clarify and expand the criteria for diffuse evolution and present a simple experimental design that will allow the detection of diffuse selection. We argue that a greater focus on selection on specific traits and the evolutionary response to that selection will improve our conceptual understanding of how communities affect the evolution of species embedded within them.     

Free radicals in aging: causal complexity and its biomedical implications

Superoxide generated adventitiously by the mitochondrial respiratory chain can give rise to much more reactive radicals, resulting in random oxidation of all classes of macromolecules. Harman's 1956 suggestion that this process might drive aging has been a leading strand of biogerontological thinking since the discovery of superoxide dismutase. However, it has become apparent that the many downstream consequences of free radical damage can also be caused by processes not involving oxidation. Moreover, free radicals have been put to use by evolution to such an extent that their wholesale elimination would certainly be fatal. This multiplicity of parallel pathways and side-effects illustrates why attempts to postpone aging by "cleaning up" metabolism will surely fail for the foreseeable future: we simply understand metabolism too poorly. This has led me to pursue the alternative, "repair and maintenance" approach that sidesteps our ignorance of metabolism and may be feasible relatively soon.