Anticipating the species jump: surveillance for emerging viral threats.

Zoonotic disease surveillance is typically triggered after animal pathogens have already infected humans. Are there ways to identify high-risk viruses before they emerge in humans? If so, then how and where can identifications be made and by what methods? These were the fundamental questions driving a workshop to examine the future of predictive surveillance for viruses that might jump from animals to infect humans. Virologists, ecologists and computational biologists from academia, federal government and non-governmental organizations discussed opportunities as well as obstacles to the prediction of species jumps using genetic and ecological data from viruses and their hosts, vectors and reservoirs. This workshop marked an important first step towards envisioning both scientific and organizational frameworks for this future capability. Canine parvoviruses as well as seasonal H3N2 and pandemic H1N1 influenza viruses are discussed as exemplars that suggest what to look for in anticipating species jumps. To answer the question of where to look, prospects for discovering emerging viruses among wildlife, bats, rodents, arthropod vectors and occupationally exposed humans are discussed. Finally, opportunities and obstacles are identified and accompanied by suggestions for how to look for species jumps. Taken together, these findings constitute the beginnings of a conceptual framework for achieving a virus surveillance capability that could predict future species jumps

Effective, Robust Design of Community Mitigation for Pandemic Influenza: A Systematic Examination of Proposed US Guidance

BACKGROUND: The US government proposes pandemic influenza mitigation guidance that includes isolation and antiviral treatment of ill persons, voluntary household member quarantine and antiviral prophylaxis, social distancing of individuals, school closure, reduction of contacts at work, and prioritized vaccination. Is this the best strategy combination? Is choice of this strategy robust to pandemic uncertainties? What are critical enablers of community resilience? METHODS AND FINDINGS: We systematically simulate a broad range of pandemic scenarios and mitigation strategies using a networked, agent-based model of a community of explicit, multiply-overlapping social contact networks. We evaluate illness and societal burden for alterations in social networks, illness parameters, or intervention implementation. For a 1918-like pandemic, the best strategy minimizes illness to <1% of the population and combines network-based (e.g. school closure, social distancing of all with adults' contacts at work reduced), and case-based measures (e.g. antiviral treatment of the ill and prophylaxis of household members). We find choice of this best strategy robust to removal of enhanced transmission by the young, additional complexity in contact networks, and altered influenza natural history including extended viral shedding. Administration of age-group or randomly targeted 50% effective pre-pandemic vaccine with 7% population coverage (current US H5N1 vaccine stockpile) had minimal effect on outcomes. In order, mitigation success depends on rapid strategy implementation, high compliance, regional mitigation, and rigorous rescinding criteria; these are the critical enablers for community resilience. CONCLUSIONS: Systematic evaluation of feasible, recommended pandemic influenza interventions generally confirms the US community mitigation guidance yields best strategy choices for pandemic planning that are robust to a wide range of uncertainty. The best strategy combines network- and case-based interventions; network-based interventions are paramount. Because strategies must be applied rapidly, regionally, and stringently for greatest benefit, preparation and public education is required for long-lasting, high community compliance during a pandemic

How to suppress undesired synchronization

It is delightful to observe the emergence of synchronization in the blinking of fireflies to attract partners and preys. Other charming examples of synchronization can also be found in a wide range of phenomena such as, e.g., neurons firing, lasers cascades, chemical reactions, and opinion formation. However, in many situations the formation of a coherent state is not pleasant and should be mitigated. For example, the onset of synchronization can be the root of epileptic seizures, traffic congestion in communication networks, and the collapse of constructions. Here we propose the use of contrarians to suppress undesired synchronization. We perform a comparative study of different strategies, either requiring local or total knowledge of the system, and show that the most efficient one solely requires local information. Our results also reveal that, even when the distribution of neighboring interactions is narrow, significant improvement in mitigation is observed when contrarians sit at the highly connected elements. The same qualitative results are obtained for artificially generated networks as well as two real ones, namely, the Routers of the Internet and a neuronal network

Whole-genome sequencing of Salmonella Mississippi and Typhimurium Definitive Type 160, Australia and New Zealand

We used phylogenomic and risk factor data on isolates of Salmonella enterica serovars Mississippi and Typhimurium definitive type 160 (DT160) collected from human, animal, and environmental sources to elucidate their epidemiology and disease reservoirs in Australia and New Zealand. Sequence data suggested wild birds as a likely reservoir for DT160; animal and environmental sources varied more for Salmonella Mississippi than for Salmonella Typhimurium. Australia and New Zealand isolates sat in distinct clades for both serovars; the median single-nucleotide polymorphism distance for DT160 was 29 (range 8–66) and for Salmonella Mississippi, 619 (range 565–737). Phylogenomic data identified plausible sources of human infection from wildlife and environmental reservoirs and provided evidence supporting New Zealand–acquired DT160 in a group of travelers returning to Australia. Wider use of real-time whole-genome sequencing in new locations and for other serovars may identify sources and routes of transmission, thereby aiding prevention and control

Evolution of Robustness to Noise and Mutation in Gene Expression Dynamics

Phenotype of biological systems needs to be robust against mutation in order to sustain themselves between generations. On the other hand, phenotype of an individual also needs to be robust against fluctuations of both internal and external origins that are encountered during growth and development. Is there a relationship between these two types of robustness, one during a single generation and the other during evolution? Could stochasticity in gene expression have any relevance to the evolution of these robustness? Robustness can be defined by the sharpness of the distribution of phenotype; the variance of phenotype distribution due to genetic variation gives a measure of `genetic robustness' while that of isogenic individuals gives a measure of `developmental robustness'. Through simulations of a simple stochastic gene expression network that undergoes mutation and selection, we show that in order for the network to acquire both types of robustness, the phenotypic variance induced by mutations must be smaller than that observed in an isogenic population. As the latter originates from noise in gene expression, this signifies that the genetic robustness evolves only when the noise strength in gene expression is larger than some threshold. In such a case, the two variances decrease throughout the evolutionary time course, indicating increase in robustness. The results reveal how noise that cells encounter during growth and development shapes networks' robustness to stochasticity in gene expression, which in turn shapes networks' robustness to mutation. The condition for evolution of robustness as well as relationship between genetic and developmental robustness is derived through the variance of phenotypic fluctuations, which are measurable experimentally.Comment: 25 page

Accelerated search for biomolecular network models to interpret high-throughput experimental data

<p>Abstract</p> <p>Background</p> <p>The functions of human cells are carried out by biomolecular networks, which include proteins, genes, and regulatory sites within DNA that encode and control protein expression. Models of biomolecular network structure and dynamics can be inferred from high-throughput measurements of gene and protein expression. We build on our previously developed fuzzy logic method for bridging quantitative and qualitative biological data to address the challenges of noisy, low resolution high-throughput measurements, i.e., from gene expression microarrays. We employ an evolutionary search algorithm to accelerate the search for hypothetical fuzzy biomolecular network models consistent with a biological data set. We also develop a method to estimate the probability of a potential network model fitting a set of data by chance. The resulting metric provides an estimate of both model quality and dataset quality, identifying data that are too noisy to identify meaningful correlations between the measured variables.</p> <p>Results</p> <p>Optimal parameters for the evolutionary search were identified based on artificial data, and the algorithm showed scalable and consistent performance for as many as 150 variables. The method was tested on previously published human cell cycle gene expression microarray data sets. The evolutionary search method was found to converge to the results of exhaustive search. The randomized evolutionary search was able to converge on a set of similar best-fitting network models on different training data sets after 30 generations running 30 models per generation. Consistent results were found regardless of which of the published data sets were used to train or verify the quantitative predictions of the best-fitting models for cell cycle gene dynamics.</p> <p>Conclusion</p> <p>Our results demonstrate the capability of scalable evolutionary search for fuzzy network models to address the problem of inferring models based on complex, noisy biomolecular data sets. This approach yields multiple alternative models that are consistent with the data, yielding a constrained set of hypotheses that can be used to optimally design subsequent experiments.</p

Time domains of the hypoxic ventilatory response in ectothermic vertebrates

Over a decade has passed since Powell et al. (Respir Physiol 112:123–134, 1998) described and defined the time domains of the hypoxic ventilatory response (HVR) in adult mammals. These time domains, however, have yet to receive much attention in other vertebrate groups. The initial, acute HVR of fish, amphibians and reptiles serves to minimize the imbalance between oxygen supply and demand. If the hypoxia is sustained, a suite of secondary adjustments occur giving rise to a more long-term balance (acclimatization) that allows the behaviors of normal life. These secondary responses can change over time as a function of the nature of the stimulus (the pattern and intensity of the hypoxic exposure). To add to the complexity of this process, hypoxia can also lead to metabolic suppression (the hypoxic metabolic response) and the magnitude of this is also time dependent. Unlike the original review of Powell et al. (Respir Physiol 112:123–134, 1998) that only considered the HVR in adult animals, we also consider relevant developmental time points where information is available. Finally, in amphibians and reptiles with incompletely divided hearts the magnitude of the ventilatory response will be modulated by hypoxia-induced changes in intra-cardiac shunting that also improve the match between O2 supply and demand, and these too change in a time-dependent fashion. While the current literature on this topic is reviewed here, it is noted that this area has received little attention. We attempt to redefine time domains in a more ‘holistic’ fashion that better accommodates research on ectotherms. If we are to distinguish between the genetic, developmental and environmental influences underlying the various ventilatory responses to hypoxia, however, we must design future experiments with time domains in mind

Extended 2D myotube culture recapitulates postnatal fibre type plasticity

Background: The traditional problems of performing skeletal muscle cell cultures derived from mammalian or avian species are limited myotube differentiation, and transient myotube persistence which greatly restricts the ability of myotubes to undergo phenotypic maturation. We report here on a major technical breakthrough in the establishment of a simple and effective method of extended porcine myotube cultures (beyond 50 days) in two-dimension (2D) that recapitulates key features of postnatal fibre types. Results: Primary porcine muscle satellite cells (myoblasts) were isolated from the longissimus dorsi of 4 to 6 weeks old pigs for 2D cultures to optimise myotube formation, improve surface adherence and characterise myotube maturation. Over 95 % of isolated cells were myoblasts as evidenced by the expression of Pax3 and Pax7. Our relatively simple approach, based on modifications of existing surface coating reagents (Maxgel), and of proliferation and differentiation (Ultroser G) media, typically achieved by 5 days of differentiation fusion index of around 80 % manifested in an abundance of discrete myosin heavy chain (MyHC) slow and fast myotubes. There was little deterioration in myotube viability over 50 days, and the efficiency of myotube formation was maintained over seven myoblast passages. Regular spontaneous contractions of myotubes were frequently observed throughout culture. Myotubes in extended cultures were able to undergo phenotypic adaptation in response to different culture media, including the adoption of a dominant postnatal phenotype of fast-glycolytic MyHC 2x and 2b expression by about day 20 of differentiation. Furthermore, fast-glycolytic myotubes coincided with enhanced expression of the putative porcine long intergenic non-coding RNA (linc-MYH), which has recently been shown to be a key coordinator of MyHC 2b expression in vivo. Conclusions: Our revised culture protocol allows the efficient differentiation and fusion of porcine myoblasts into myotubes and their prolonged adherence to the culture surface. Furthermore, we are able to recapitulate in 2D the maturation process of myotubes to resemble postnatal fibre types which represent a major technical advance in opening access to the in vitro study of coordinated postnatal muscle gene expression

Genesis of a Fungal Non-Self Recognition Repertoire

Conspecific allorecognition, the ability for an organism to discriminate its own cells from those of another individual of the same species, has been developed by many organisms. Allorecognition specificities are determined by highly polymorphic genes. The processes by which this extreme polymorphism is generated remain largely unknown. Fungi are able to form heterokaryons by fusion of somatic cells, and somatic non self-recognition is controlled by heterokaryon incompatibility loci (het loci). Herein, we have analyzed the evolutionary features of the het-d and het-e fungal allorecognition genes. In these het genes, allorecognition specificity is determined by a polymorphic WD-repeat domain. We found that het-d and het-e belong to a large gene family with 10 members that all share the WD-repeat domain and show that repeats of all members of the family undergo concerted evolution. It follows that repeat units are constantly exchanged both within and between members of the gene family. As a consequence, high mutation supply in the repeat domain is ensured due to the high total copy number of repeats. We then show that in each repeat four residues located at the protein/protein interaction surface of the WD-repeat domain are under positive diversifying selection. Diversification of het-d and het-e is thus ensured by high mutation supply, followed by reshuffling of the repeats and positive selection for favourable variants. We also propose that RIP, a fungal specific hypermutation process acting specifically on repeated sequences might further enhance mutation supply. The combination of these evolutionary mechanisms constitutes an original process for generating extensive polymorphism at loci that require rapid diversification