Dominance, Pleiotropy and Metabolic Structure

It is a common observation that most mutants have similar dominance relations for all the characters they are known to affect. As a model of pleiotropic effects we investigate a branched pathway where the two outputs represent two characters whose variation is affected by changes in any of the genetically specified enzymes in the system. We consider the effects on the phenotype (fluxes or intermediate metabolites) of substitutions at one locus represented by enzyme activities of the two homozygotes (mutant and wild type) and that of the heterozygote. Dominance indices for the characters pleiotropically connected by the metabolic system are calculated. We show that if enzymes behave 'linearly,' (first order), that is if saturation and feedback inhibition or other nonlinearities are absent, all fluxes and pools have identical dominance relations. The presence of such nonlinearity, however, leads to differences in dominance between different characters and we define the conditions where such differences can be important.     

How Predator Food Preference can Change the Destiny of Native Prey in Predator–Prey Systems

The aim of this work is to develop and analyse a mathematical model for a predator-2 preys system arising in insular environments. We are interested in the evolution of a native prey population without behavioural traits to cope with predation or competition, after the introduction of alien species. Here, we consider a long living bird population with low fertility rate. We point out the effects of the preference of the predator for either juvenile or adult stages. In addition, we study the impact of alien prey introduction in such a model. We use a reaction-diffusion system with a singular logistic right hand side. The aim of this work is to bring interesting dynamics to the fore. As a first example, oscillatory behaviour takes place in the model without alien preys and when predators have an average preference coefficient. Introduction of alien preys can lead to species extinction.     

Heteroclinic orbits indicate overexploitation in predator-prey systems with a strong Allee effect

Species establishment in a model system in a homogeneous environment can be dependent not only on the parameter setting, but also on the initial conditions of the system. For instance, predator invasion into an established prey population can fail and lead to system collapse, an event referred to as overexploitation. This phenomenon occurs in models with bistability properties, such as strong Allee effects. The Allee effect then prevents easy re-establishment of the prey species. In this paper, we deal with the bifurcation analyses of two previously published predator-prey models with strong Allee effects. We expand the analyses to include not only local, but also global bifurcations. We show the existence of a point-to-point heteroclinic cycle in these models, and discuss numerical techniques for continuation in parameter space. The continuation of such a cycle in two-parameter space forms the boundary of a region in parameter space where the system collapses after predator invasion, i.e. where overexploitation occurs. We argue that the detection and continuation of global bifurcations in these models are of vital importance for the understanding of the model dynamics.     

A mathematical modelling framework for understanding chemorepulsive signal transduction in Dictyostelium

Chemorepulsion is the process by which an organism or a cell moves in the direction of decreasing chemical concentration. While a few experimental studies have been performed, no mathematical models exist for this process. In this paper we have modelled gradient sensing, the first subprocess of chemorepulsion, in Dictyostelium discoideum-a well characterized model eukaryotic system. We take the first steps towards achieving a comprehensive mechanistic understanding of chemorepulsion in this system. We have used, as a basis, the biochemical network of the Keizer-Gunnink et al. (2007) to develop the mathematical modelling framework. This network describes the underlying pathways of chemorepellent gradient sensing in D. discoideum. Working within this modelling framework we address whether the postulated interactions of the pathways and species in this network can lead to a chemorepulsive response. We also analyse the possible role of additional regulatory effects (such as additional receptor regulation of enzymes in this network) and if this is necessary to achieve this behaviour. Thus we have investigated the receptor regulation of important enzymes and feedback effects in the network. This modelling framework generates important insights into and testable predictions regarding the role of key components and feedback loops in regulating chemorepulsive gradient sensing, and what factors might be important for generating a chemorepulsive response; it serves as a first step towards a comprehensive mechanistic understanding of this process.     

Simulations Show that Virus Assembly and Budding Are Facilitated by Membrane Microdomains

For many viruses, assembly and budding occur simultaneously during virion formation. Understanding the mechanisms underlying this process could promote biomedical efforts to block viral propagation and enable use of capsids in nanomaterials applications. To this end, we have performed molecular dynamics simulations on a coarse-grained model that describes virus assembly on a fluctuating lipid membrane. Our simulations show that the membrane can promote association of adsorbed subunits through dimensional reduction, but it also introduces thermodynamic and kinetic effects that can inhibit complete assembly. We find several mechanisms by which membrane microdomains, such as lipid rafts, reduce these effects, and thus, enhance assembly. We show how these predicted mechanisms can be experimentally tested. Furthermore, the simulations demonstrate that assembly and budding depend crucially on the system dynamics via multiple timescales related to membrane deformation, protein diffusion, association, and adsorption onto the membrane.     

Mathematical modeling of combinatorial regulation suggests that apparent positive regulation of targets by miRNA could be an artifact resulting from competition for mRNA

MicroRNAs bind to and regulate the abundance and activity of target messenger RNA through sequestration, enhanced degradation, and suppression of translation. Although miRNA have a predominantly negative effect on the target protein concentration, several reports have demonstrated a positive effect of miRNA, i.e., increase in target protein concentration on miRNA overexpression and decrease in target concentration on miRNA repression. miRNA–target pair-specific effects such as protection of mRNA degradation owing to miRNA binding can explain some of these effects. However, considering such pairs in isolation might be an oversimplification of the RNA biology, as it is known that one miRNA interacts with several targets, and conversely target mRNA are subject to regulation by several miRNAs. We formulate a mathematical model of this combinatorial regulation of targets by multiple miRNA. Through mathematical analysis and numerical simulations of this model, we show that miRNA that individually have a negative effect on their targets may exhibit an apparently positive net effect when the concentration of one miRNA is experimentally perturbed by repression/overexpression in such a multi-miRNA multitarget situation. We show that this apparent unexpected effect is due to competition and will not be observed when miRNA interact noncompetitively with the target mRNA. This result suggests that some of the observed unusual positive effects of miRNA may be due to the combinatorial complexity of the system rather than due to any inherently unusual positive effect of the miRNA on its target.     

Phenotype‐associated inbreeding biases estimates of inbreeding depression in a wild bird population

Inbreeding depression is usually quantified by regressing individual phenotypic values on inbreeding coefficients, implicitly assuming there is no correlation between an individual's phenotype and the kinship coefficient to its mate. If such an association between parental phenotype and parental kinship exists, and if the trait of interest is heritable, estimates of inbreeding depression can be biased. Here we first derive the expected bias as a function of the covariance between mean parental breeding value and parental kinship. Subsequently, we use simulated data to confirm the existence of this bias, and show that it can be accounted for in a quantitative genetic animal model. Finally, we use long‐term individual‐based data for white‐throated dippers (Cinclus cinclus), a bird species in which inbreeding is relatively common, to obtain an empirical estimate of this bias. We show that during part of the study period, parents of inbred birds had shorter wings than those of outbred birds, and as wing length is heritable, inbred individuals were smaller, independent of any inbreeding effects. This resulted in the overestimation of inbreeding effects. Similarly, during a period when parents of inbred birds had longer wings, we found that inbreeding effects were underestimated. We discuss how such associations may have arisen in this system, and why they are likely to occur in others, too. Overall, we demonstrate how less biased estimates of inbreeding depression can be obtained within a quantitative genetic framework, and suggest that inbreeding and additive genetic effects should be accounted for simultaneously whenever possible.     

The role of TFIIB-RNA polymerase II interaction in start site selection in yeast cells

Previous studies have established a critical role of both TFIIB and RNA polymerase II (RNAPII) in start site selection in the yeast Saccharomyces cerevisiae. However, it remains unclear how the TFIIB–RNAPII interaction impacts on this process since such an interaction can potentially influence both preinitiation complex (PIC) stability and conformation. In this study, we further investigate the role of TFIIB in start site selection by characterizing our newly generated TFIIB mutants, two of which exhibit a novel upstream shift of start sites in vivo. We took advantage of an artificial recruitment system in which an RNAPII holoenzyme component is covalently linked to a DNA-binding domain for more direct and stable recruitment. We show that TFIIB mutations can exert their effects on start site selection in such an artificial recruitment system even though it has a relaxed requirement for TFIIB. We further show that these TFIIB mutants have normal affinity for RNAPII and do not alter the promoter melting/scanning step. Finally, we show that overexpressing the genetically isolated TFIIB mutant E62K, which has a reduced affinity for RNAPII, can correct its start site selection defect. We discuss a model in which the TFIIB–RNAPII interaction controls the start site selection process by influencing the conformation of PIC prior to or during PIC assembly, as opposed to PIC stability.     

森林-农业景观格局变化的社会-生态系统模拟模型方法进展

社会-生态系统(SES)模拟模型是景观格局分析和决策的有效工具,能表征景观格局变化的社会-生态效应及景观决策的复杂反馈机制。文献综述了森林-农业景观格局的SES模型方法进展发现:(1)多数模型对景观过程与社会经济决策的反馈关系分析不足;(2)应集成多种情景模拟和景观效应分析方法,完善现有SES模型的理论方法基础;(3)通过集成格局优化模型和自主体模型会有效改进SES模型功能,具体途径包括:集成情景-生态效应的景观格局模拟方法、完善景观决策的理论基础、加强集成模型的不确定性分析、降低模型复杂性和综合定性-定量数据等。研究结果有助于理解多尺度森林-农业景观格局在社会-生态系统中的重要作用,能更好地支持跨学科集成模型开发与应用。     

Protein-Induced Membrane Curvature Alters Local Membrane Tension

Adsorption of proteins onto membranes can alter the local membrane curvature. This phenomenon has been observed in biological processes such as endocytosis, tubulation, and vesiculation. However, it is not clear how the local surface properties of the membrane, such as membrane tension, change in response to protein adsorption. In this article, we show that the partial differential equations arising from classical elastic model of lipid membranes, which account for simultaneous changes in shape and membrane tension due to protein adsorption in a local region, cannot be solved for nonaxisymmetric geometries using straightforward numerical techniques; instead, a viscous-elastic formulation is necessary to fully describe the system. Therefore, we develop a viscous-elastic model for inhomogeneous membranes of the Helfrich type. Using the newly available viscous-elastic model, we find that the lipids flow to accommodate changes in membrane curvature during protein adsorption. We show that, at the end of protein adsorption process, the system sustains a residual local tension to balance the difference between the actual mean curvature and the imposed spontaneous curvature. We also show that this change in membrane tension can have a functional impact such as altered response to pulling forces in the presence of proteins.     

The challenge of predicting temperature effects on short-term predator–prey dynamics

Understanding how interacting species respond to changing temperatures is complicated because both inter- and intraspecific processes can be temperature-dependent, and because the dynamics of interest often occur over short time scales. While efforts to document and integrate inter- and intraspecific effects are ongoing, few broad conclusions have emerged. Here, we use a simple structured predator–prey model to explore whether some such conclusions can be reached with incomplete knowledge about initial population sizes or about how temperature alters predation rates. We find that, despite strong sensitivity of quantitative predictions to the model’s details, qualitative predictions for how predator–prey communities respond to temperature may still be possible. As a case study, we ask whether biological control of the herbivorous insect pea aphid will be strengthened or weakened by increasing temperatures. Our empirically derived parameter estimates suggest biological control will be strengthened, but we caution that this result is not inevitable given what we currently know about the effects of temperature in this system. Our work highlights the complex interaction between inter- and intraspecific effects of temperature in ecological communities.     

Protein-Induced Membrane Curvature Alters Local Membrane Tension

Adsorption of proteins onto membranes can alter the local membrane curvature. This phenomenon has been observed in biological processes such as endocytosis, tubulation, and vesiculation. However, it is not clear how the local surface properties of the membrane, such as membrane tension, change in response to protein adsorption. In this article, we show that the partial differential equations arising from classical elastic model of lipid membranes, which account for simultaneous changes in shape and membrane tension due to protein adsorption in a local region, cannot be solved for nonaxisymmetric geometries using straightforward numerical techniques; instead, a viscous-elastic formulation is necessary to fully describe the system. Therefore, we develop a viscous-elastic model for inhomogeneous membranes of the Helfrich type. Using the newly available viscous-elastic model, we find that the lipids flow to accommodate changes in membrane curvature during protein adsorption. We show that, at the end of protein adsorption process, the system sustains a residual local tension to balance the difference between the actual mean curvature and the imposed spontaneous curvature. We also show that this change in membrane tension can have a functional impact such as altered response to pulling forces in the presence of proteins.     

Nucleic Acid Scavenging Polymers Inhibit Extracellular DNA-Mediated Innate Immune Activation without Inhibiting Anti-Viral Responses

Toll-like receptor (TLR) family members, 3, 7 and 9 are key components in initiation and progression of autoimmune disorders such as systemic lupus erythematosus (SLE). These TLRs are often referred to as nucleic acid-sensing TLRs based on their ability to recognize DNAs or RNAs produced by pathogens or damaged cells. During autoimmune disease progression these receptors recognize self nucleic acids as well as self nucleic acid-containing complexes and contribute to inflammatory cytokine production and subsequent enhancement of serum autoantibody levels. We have recently discovered that nucleic-acid scavenging polymers (NASPs) can neutralize the proinflammatory effects of nucleic acids. Here, we begin to explore what effects such NASPs have on normal immune function. We show that such NASPs can inhibit TLR activation without affecting nucleic acid-independent T cell activation. Moreover, we observe that stimulation of immune cells by encapsulated nucleic acids, such as those found in viral particles, is unaffected by NASPs. Thus NASPs only limit the activation of the immune system by accessible extra-cellular nucleic acid and do not engender non-specific immune suppression. These important findings suggest that NASPs represent a new approach toward anti-inflammatory drug development as these agents can potentially be utilized to block overt autoimmune disorders and inflammation while allowing normal immune responses to occur.     

Predicting coexistence of plants subject to a tolerance-competition trade-off

Ecological trade-offs between species are often invoked to explain species coexistence in ecological communities. However, few mathematical models have been proposed for which coexistence conditions can be characterized explicitly in terms of a trade-off. Here we present a model of a plant community which allows such a characterization. In the model plant species compete for sites where each site has a fixed stress condition. Species differ both in stress tolerance and competitive ability. Stress tolerance is quantified as the fraction of sites with stress conditions low enough to allow establishment. Competitive ability is quantified as the propensity to win the competition for empty sites. We derive the deterministic, discrete-time dynamical system for the species abundances. We prove the conditions under which plant species can coexist in a stable equilibrium. We show that the coexistence conditions can be characterized graphically, clearly illustrating the trade-off between stress tolerance and competitive ability. We compare our model with a recently proposed, continuous-time dynamical system for a tolerance-fecundity trade-off in plant communities, and we show that this model is a special case of the continuous-time version of our model.     

Noise Genetics: Inferring Protein Function by Correlating Phenotype with Protein Levels and Localization in Individual Human Cells

To understand gene function, genetic analysis uses large perturbations such as gene deletion, knockdown or over-expression. Large perturbations have drawbacks: they move the cell far from its normal working point, and can thus be masked by off-target effects or compensation by other genes. Here, we offer a complementary approach, called noise genetics. We use natural cell-cell variations in protein level and localization, and correlate them to the natural variations of the phenotype of the same cells. Observing these variations is made possible by recent advances in dynamic proteomics that allow measuring proteins over time in individual living cells. Using motility of human cancer cells as a model system, and time-lapse microscopy on 566 fluorescently tagged proteins, we found 74 candidate motility genes whose level or localization strongly correlate with motility in individual cells. We recovered 30 known motility genes, and validated several novel ones by mild knockdown experiments. Noise genetics can complement standard genetics for a variety of phenotypes.     

Viral transformation for production of personalized type I interferons

Type I interferons (IFN) are cytokines with many functions and have been widely used to treat many human diseases such as hepatitis C virus infection. Using the viral transformation and priming properties of Epstein-Barr virus, we have developed a system that can produce high levels of “personalized” IFNs, which are produced from the cells of the patient to whom the IFNs are to be administrated. We demonstrate the feasibility of the system. This seems to be the first report for the establishment of a personalized IFN-production system. The personalized IFNs could have a longer circulation time, fewer side effects but higher efficacy. We anticipate that the system can provide an improved form of IFN for medical uses.     

Effects of biodiversity in agricultural landscapes on the protective microbiome of insects – a review

Symbiotic bacteria in herbivorous insects can have strong beneficial impacts on their host's survival, including conferring resistance to natural enemies such as parasitoid wasps or pathogens, while also imposing energetic costs on the host, resulting in cost‐benefit trade‐offs. Whether these trade‐offs favour the hosting of symbionts depends on the growth environment of the herbivore. Long‐term experimental grassland studies have shown that increasing plant species richness leads to an increased diversity of associated herbivores and their natural enemies. Such a change in natural enemy diversity, related to changes in plant diversity, could also drive changes in the community of symbionts hosted by the herbivorous insects. Aphids are one model system for studying symbionts in insects, and effects of host‐plant species and diversity on aphid‐symbiont interactions have been documented. Yet, we still understand little of the mechanisms underlying such effects. We review the current state of knowledge of how biodiversity can impact aphid‐symbiont communities and the underlying drivers. Then, we discuss this in the framework of sustainable agriculture, where increased plant biodiversity, in the form of wildflower strips, is used to recruit natural enemies to crop fields for their pest control services. Although aphid symbionts have the potential to reduce biological control effectiveness through conferring protection for the host insect, we discuss how increasing plant and natural enemy biodiversity can mitigate these effects and identify future research opportunities. Understanding how to promote beneficial interactions in ecological systems can help in the development of more sustainable agricultural management strategies.     

In vitro Cell Culture Model for Toxic Inhaled Chemical Testing

Cell cultures are indispensable to develop and study efficacy of therapeutic agents, prior to their use in animal models. We have the unique ability to model well differentiated human airway epithelium and heart muscle cells. This could be an invaluable tool to study the deleterious effects of toxic inhaled chemicals, such as chlorine, that can normally interact with the cell surfaces, and form various byproducts upon reacting with water, and limiting their effects in submerged cultures. Our model using well differentiated human airway epithelial cell cultures at air-liqiuid interface circumvents this limitation as well as provides an opportunity to evaluate critical mechanisms of toxicity of potential poisonous inhaled chemicals. We describe enhanced loss of membrane integrity, caspase release and death upon toxic inhaled chemical such as chlorine exposure. In this article, we propose methods to model chlorine exposure in mammalian heart and airway epithelial cells in culture and simple tests to evaluate its effect on these cell types.     

Zero-inflated Poisson models with measurement error in the response

Zero-inflated count data arise frequently from genomics studies. Analysis of such data is often based on a mixture model which facilitates excess zeros in combination with a Poisson distribution, and various inference methods have been proposed under such a model. Those analysis procedures, however, are challenged by the presence of measurement error in count responses. In this article, we propose a new measurement error model to describe error-contaminated count data. We show that ignoring the measurement error effects in the analysis may generally lead to invalid inference results, and meanwhile, we identify situations where ignoring measurement error can still yield consistent estimators. Furthermore, we propose a Bayesian method to address the effects of measurement error under the zero-inflated Poisson model and discuss the identifiability issues. We develop a data-augmentation algorithm that is easy to implement. Simulation studies are conducted to evaluate the performance of the proposed method. We apply our method to analyze the data arising from a prostate adenocarcinoma genomic study.     

Dynamics from a predator-prey-quarry-resource-scavenger model

Allochthonous resources can be found in many foodwebs and can influence both the structure and stability of an ecosystem. In order to better understand the role of how allochthonous resources are transferred as quarry from one predator-prey system to another, we propose a predator-prey-quarry-resource-scavenger (PPQRS) model, which is an extension of an existing model for quarry-resource-scavenger (a predator-prey-subsidy (PPS) model). Instead of taking the allochthonous resource input rate as a constant, as has been done in previous theoretical work, we explicitly incorporated the underlying predator-prey relation responsible for the input of quarry. The most profound differences between PPS and PPQRS system are found when the predator-prey system has limit cycles, resulting in a periodic rather than constant influx of quarry (the allochthonous resource) into the scavenger-resource interactions. This suggests that the way in which allochthonous resources are input into a predator-prey system can have a strong influence over the population dynamics. In order to understand the role of seasonality, we incorporated non-autonomous terms and showed that these terms can either stabilize or destabilize the dynamics, depending on the parameter regime. We also considered the influence of spatial motion (via diffusion) by constructing a continuum partial differential equation (PDE) model over space. We determine when such spatial dynamics essentially give the same information as the ordinary differential equation (ODE) system, versus other cases where there are strong spatial differences (such as spatial pattern formation) in the populations. In situations where increasing the carrying capacity in the ODE model drives the amplitude of the oscillations up, we found that a large carrying capacity in the PDE model results in a very small variation in average population size, showing that spatial diffusion is stabilizing for the PPQRS model.