<Emphasis Type="Italic">Drosophila</Emphasis> as models to understand the adaptive process during invasion

The last few decades have seen a growing number of species invasions globally, including many insect species. In drosophilids, there are several examples of successful invasions, i.e. Zaprionus indianus and Drosophila subobscura some decades ago, but the most recent and prominent example is the invasion of Europe and North America by the pest species, Drosophila suzukii. During the invasive process, species often encounter diverse environmental conditions that they must respond to, either through rapid genetic adaptive shifts or phenotypic plasticity, or by some combination of both. Consequently, invasive species constitute powerful models for investigating various questions related to the adaptive processes that underpin successful invasions. In this paper, we highlight how Drosophila have been and remain a valuable model group for understanding these underlying adaptive processes, and how they enable insight into key questions in invasion biology, including how quickly adaptive responses can occur when species are faced with new environmental conditions.     

Examples of Mathematical Modeling: Tales from the Crypt

Mathematical modeling is being increasingly recognized within the biomedical sciences as an important tool that can aid the understanding of biological systems. The heavily regulated cell renewal cycle in the colonic crypt provides a good example of how modeling can be used to find out key features of the system kinetics, and help to explain both the breakdown of homeostasis and the initiation of tumorigenesis.We use the cell population model by Johnston et al. (2007) Proc. Natl. Acad. Sci. USA 104, 4008-4013, to illustrate the power of mathematical modeling by considering two key questions about the cell population dynamics in the colonic crypt. We ask: how can a model describe both homeostasis and unregulated growth in tumorigenesis; and to which parameters in the system is the model most sensitive? In order to address these questions, we discuss what type of modeling approach is most appropriate in the crypt.We use the model to argue why tumorigenesis is observed to occur in stages with long lag phases between periods of rapid growth, and we identify the key parameters.     

Perceived Risk of Avian Influenza and Urbanization in Northern Vietnam

Decision-analytic models provide forecasts of how systems of interest will respond to management. These models can be parameterized using empirical data, but sometimes require information elicited from experts. When evaluating the effects of disease in species translocation programs, expert judgment is likely to play a role because complete empirical information will rarely be available. We illustrate development of a decision-analytic model built to inform decision-making regarding translocations and other management actions for the boreal toad (Anaxyrus boreas boreas), a species with declines linked to chytridiomycosis caused by Batrachochytrium dendrobatidis (Bd). Using the model, we explored the management implications of major uncertainties in this system, including whether there is a genetic basis for resistance to pathogenic infection by Bd, how translocation can best be implemented, and the effectiveness of efforts to reduce the spread of Bd. Our modeling exercise suggested that while selection for resistance to pathogenic infection by Bd could increase numbers of sites occupied by toads, and translocations could increase the rate of toad recovery, efforts to reduce the spread of Bd may have little effect. We emphasize the need to continue developing and parameterizing models necessary to assess management actions for combating chytridiomycosis-associated declines.     

Comparison of model selection technique performance in predicting the spread of newly invasive species: a case study with <Emphasis Type="Italic">Batrachochytrium salamandrivorans</Emphasis>

Species distribution models (SDMs) increasingly have been used to anticipate the spread of invasive species. However, these models are powerful conservation tools only if they are biologically relevant, and thus validation of these models is essential. Here, we evaluate four model selection frameworks for their ability to identify a best fit model of spread under low data conditions early in an invasion, specifically testing the efficacy of methods that utilize absence data in addition to presence data in evaluating models. We test this question using a simulation where we generated data with varying confidence in the accuracy of the absence data, as absences in early invasions may become presences in the future, and increasing quantity of observation data to test the models. We create these simulations based on a real-world example of a newly emergent, invasive fungal pathogen, Batrachochytrium salamandrivorans (Bsal). The simulation demonstrated that AIC and Likelihood consistently outperform both Kappa and AUC in selecting the true model as the best model when data are limited and absence data are low quality, with AIC providing the most conservative results due to penalties for overparameterization. With these results, we then used these techniques to compare five candidate models for predicting the spread of Bsal. Consistent with the simulation, the best fit model of the candidate models for Bsal was inconsistent across the four metrics. However, AIC, which performed best in the simulation study, suggested that the spread of Bsal into Western Europe was best predicted by a combination of bioclimatic suitability, salamander richness, and number of salamander imports. Our results highlight the difficulty in evaluating predictive models when data are limited and of low quality, as with a newly invasive species, but show that these challenges can be partially addressed with the appropriate model selection approach. Use of this approach is critical as SDMs of invasive species are often used to inform conservation policy and efforts before the invasion spreads, when limited data are available.     

Modeling vertical coral connectivity and mesophotic refugia

Whether mesophotic reefs will behave as refugia for corals threatened by global climate change and coastal development depends on vertical exchange of larvae between diverse habitats. Here we use a biophysical model of larval dispersal to estimate vertical connectivity of a broadcasting (Orbicella faveolata) and a brooding (Porites astreoides) species of coral in the US Virgin Islands. Modeling predicts subsidy to shallow areas by mesophotic larvae of both species based on local hydrology, adult reproductive characteristics, larval traits, and a wide range of scenarios developed to test depth-sensitive factors, such as fertilization rates and post-settlement survivorship. In extreme model scenarios of reduced fertilization and post-settlement survivorship of mesophotic larvae, 1–10 % local mesophotic subsidy to shallow recruitment is predicted for both species, which are demographically significant. Although direct vertical connectivity is higher for the broadcaster, the brooder demonstrates higher local multigenerational vertical connectivity, which suggests that local P. astreoides populations are more resilient than those of O. faveolata, and corroborates field studies. As shallow habitat degrades, mesophotic–shallow subsidy is predicted to increase for both species. This study is the first of its kind to simulate larval dispersal and settlement between habitats of different depths, and these findings have local, regional, and global implications for predicting and managing coral reef persistence in a changing climate.     

What can a weevil teach a fly,and reciprocally? Interaction of host immune systems with endosymbionts in <Emphasis Type="Italic">Glossina</Emphasis> and <Emphasis Type="Italic">Sitophilus</Emphasis>

The tsetse fly (Glossina genus) is the main vector of African trypanosomes, which are protozoan parasites that cause human and animal African trypanosomiases in Sub-Saharan Africa. In the frame of the IAEA/FAO program ‘Enhancing Vector Refractoriness to Trypanosome Infection’, in addition to the tsetse, the cereal weevil Sitophilus has been introduced as a comparative system with regards to immune interactions with endosymbionts. The cereal weevil is an agricultural pest that destroys a significant proportion of cereal stocks worldwide. Tsetse flies are associated with three symbiotic bacteria, the multifunctional obligate Wigglesworthia glossinidia, the facultative commensal Sodalis glossinidius and the parasitic Wolbachia. Cereal weevils house an obligatory nutritional symbiosis with the bacterium Sodalis pierantonius, and occasionally Wolbachia. Studying insect host-symbiont interactions is highly relevant both for understanding the evolution of symbiosis and for envisioning novel pest control strategies. In both insects, the long co-evolution between host and endosymbiont has led to a stringent integration of the host-bacteria partnership. These associations were facilitated by the development of specialized host traits, including symbiont-housing cells called bacteriocytes and specific immune features that enable both tolerance and control of the bacteria. In this review, we compare the tsetse and weevil model systems and compile the latest research findings regarding their biological and ecological similarities, how the immune system controls endosymbiont load and location, and how host-symbiont interactions impact developmental features including cuticle synthesis and immune system maturation. We focus mainly on the interactions between the obligate symbionts and their host’s immune systems, a central theme in both model systems. Finally, we highlight how parallel studies on cereal weevils and tsetse flies led to mutual discoveries and stimulated research on each model, creating a pivotal example of scientific improvement through comparison between relatively distant models.     

Drosophila melanogaster as a model organism for Alzheimer’s disease

Drosophila melanogaster provides an important resource for in vivo modifier screens of neurodegenerative diseases. To study the underlying pathogenesis of Alzheimer’s disease, fly models that address Tau or amyloid toxicity have been developed. Overexpression of human wild-type or mutant Tau causes age-dependent neurodegeneration, axonal transport defects and early death. Large-scale screens utilizing a neurodegenerative phenotype induced by eye-specific overexpression of human Tau have identified several kinases and phosphatases, apoptotic regulators and cytoskeleton proteins as determinants of Tau toxicity in vivo. The APP ortholog of Drosophila (dAPPl) shares the characteristic domains with vertebrate APP family members, but does not contain the human Aβ42 domain. To circumvent this drawback, researches have developed strategies by either direct secretion of human Aβ42 or triple transgenic flies expressing human APP, β-secretase and Drosophila γ-secretase presenilin (dPsn). Here, we provide a brief overview of how fly models of AD have contributed to our knowledge of the pathomechanisms of disease.     

Anthropogenic and Climatic Effects on the Distribution of <Emphasis Type="Italic">Eulemur</Emphasis> Species: An Ecological Niche Modeling Approach

Several factors can influence primate distributions, including evolutionary history, interspecific competition, climate, and anthropogenic impacts. In Madagascar, several small spatial scale studies have shown that anthropogenic habitat modification affects the density and distribution of many lemur species. Ecological niche models can be used to examine broad-scale influences of anthropogenic impacts on primate distributions. In this study, we examine how climate and anthropogenic factors influence the distribution of 11 Eulemur species using ecological niche models. Specifically, we created one set of models only using rainfall and temperature variables. We then created a second set of models that combined these climate variables with three anthropogenic factors: distance to dense settlements, villages, and croplands. We used MaxEnt to generate all the models. We found that the addition of anthropogenic variables improved the climate models. Also, most Eulemur species exhibited reduced predicted geographic distributions once anthropogenic factors were added to the model. Distance to dense settlements was the most important anthropogenic factor in most cases. We suggest that including anthropogenic variables in ecological niche models is important for understanding primate distributions, especially in regions with significant human impacts. In addition, we identify several Eulemur species that were most affected by anthropogenic factors and should be the focus of increased conservation efforts.     

An enzyme family reunion — similarities,differences and eccentricities in actions on <Emphasis Type="Italic">α</Emphasis>-glucans

α-Glucans in general, including starch, glycogen and their derived oligosaccharides are processed by a host of more or less closely related enzymes that represent wide diversity in structure, mechanism, specificity and biological role. Sophisticated three-dimensional structures continue to emerge hand-in-hand with the gaining of novel insight in modes of action. We are witnessing the “test of time” blending with remaining questions and new relationships for these enzymes. Information from both within and outside of ALAMY_3 Symposium will provide examples on what the family contains and outline some future directions. In 2007 a quantum leap crowned the structural biology by the glucansucrase crystal structure. This initiates the disclosure of the mystery on the organisation of the multidomain structure and the “robotics mechanism” of this group of enzymes. The central issue on architecture and domain interplay in multidomain enzymes is also relevant in connection with the recent focus on carbohydrate-binding domains as well as on surface binding sites and their long underrated potential. Other questions include, how different or similar are glycoside hydrolase families 13 and 31 and is the lid finally lifted off the disguise of the starch lyase, also belonging to family 31? Is family 57 holding back secret specificities? Will the different families be sporting new “eccentric” functions, are there new families out there, and why are crystal structures of “simple” enzymes still missing? Indeed new understanding and discovery of biological roles continuously emphasize value of the collections of enzyme models, sequences, and evolutionary trees which will also be enabling advancement in design for useful and novel applications.     

A comprehensive gene network for fine tuning floral development in poplar

Herbaceous model species, especially Arabidopsis has provided a wealth of information about the genes involved in floral induction and development of inflorescences and flowers. While the genus Populus is an important model system for the molecular biology of woody plant. These two genuses differ in many ways. This study was designed to improve understanding of flower development in poplar at a system level, as its regulatory pathway to a large extent remains poorly known, owing to the presently limited mutant pool. To address this issue, a poplar GeneChip was employed to detect genes expressed during the whole floral developmental process. Using the expressed floral genes, a systematic gene network was constructed with the aid of functional association with Arabidopsis. The results suggested that autonomous, gibberellin, vernalization, photoperiod, ethylene, brassinosteroid, stress-induced and floral suppression pathways are involved in poplar flowering. Modularity analysis revealed several pathways in common with Arabidopsis, such as autonomous, gibberellin, vernalization and photoperiod pathways. In addition, brassinosteroid, stress-induced and floral suppression pathways were implicated as additional novel pathways. Notably, a difference in vernalization between Arabidopsis and poplar was revealed. Autonomous, gibberellin, vernalization, photoperiod, ethylene, brassinosteroid, stress-induced and floral suppression pathways integrated into a systematic gene network in floral development of poplar. Compared to Arabidopsis, brassinosteroid, stress-induced and floral suppression pathways are additional in poplar, and FLC is absent in vernalization pathway in poplar. Preliminary conclusions drawn here provide a basis for both identification of key genes and elucidation of molecular mechanisms involved in poplar floral development.     

A recurrent neural model for proto-object based contour integration and figure-ground segregation

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects (“proto-objects”) based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594–6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492–1499 2007; Chen et al. Neuron, 82(3), 682–694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.     

Performing abstraction: two ways of modelling<Emphasis Type="Italic"> Arabidopsis thaliana</Emphasis>

What is the best way to analyse abstraction in scientific modelling? I propose to focus on abstracting as an epistemic activity, which is achieved in different ways and for different purposes depending on the actual circumstances of modelling and the features of the models in question. This is in contrast to a more conventional use of the term ‘abstract’ as an attribute of models, which I characterise as black-boxing the ways in which abstraction is performed and to which epistemological advantage. I exemplify my claims through a detailed reconstruction of the practices involved in creating two types of models of the flowering plant Arabidopsis thaliana, currently the best-known model organism in plant biology. This leads me to distinguish between two types of abstraction processes: the ‘material abstracting’ required in the production of Arabidopsis specimens and the ‘intellectual abstracting’ characterising the elaboration of visual models of Arabidopsis genomics. Reflecting on the differences between these types of abstracting helps to pin down the epistemic skills and research commitments used by researchers to produce each model, thus clarifying how models are handled by researchers and with which epistemological implications.     

Development and characterization of 24 chloroplast microsatellite markers for two species of <Emphasis Type="Italic">Eranthis</Emphasis> (Ranunculaceae)

Chloroplast microsatellites for two Korean endemic species, Eranthis byunsanensis and E. pungdoensis (Ranunculaceae), were isolated to address the questions of their distributional patterns and evolutionary relationships, using next-generation sequencing. Twenty-four polymorphic chloroplast microsatellite markers for these two species were developed, and then characterized in 65 individuals (55 individuals of E. byunsanensis and 10 individuals of E. pungdoensis). The number of alleles per locus ranged from 2 to 9; the average number of alleles across all the loci scored 4.792. The unbiased diversity per locus ranged from 0.089 to 0.880; the unbiased diversity averaged over all the loci was 0.646. The developed markers were successfully amplified for three congeneric species, E. stellata, E. pinnatifida, and E. longistipitata. The markers developed in this study can provide a valuable and important tool for understanding genetic variations, population structures, evolutionary histories and phylogeography of E. byunsanensis, E. pungdoensis, and related species.     

From bedside to bench to clinic trials: identifying new treatments for severe asthma

Asthmatics with a severe form of the disease are frequently refractory to standard medications such as inhaled corticosteroids, underlining the need for new treatments to prevent the occurrence of potentially life-threatening episodes. A major obstacle in the development of new treatments for severe asthma is the heterogeneous pathogenesis of the disease, which involves multiple mechanisms and cell types. Furthermore, new therapies might need to be targeted to subgroups of patients whose disease pathogenesis is mediated by a specific pathway. One approach to solving the challenge of developing new treatments for severe asthma is to use experimental mouse models of asthma to address clinically relevant questions regarding disease pathogenesis. The mechanistic insights gained from mouse studies can be translated back to the clinic as potential treatment approaches that require evaluation in clinical trials to validate their effectiveness and safety in human subjects. Here, we will review how mouse models have advanced our understanding of severe asthma pathogenesis. Mouse studies have helped us to uncover the underlying inflammatory mechanisms (mediated by multiple immune cell types that produce Th1, Th2 or Th17 cytokines) and non-inflammatory pathways, in addition to shedding light on asthma that is associated with obesity or steroid unresponsiveness. We propose that the strategy of using mouse models to address clinically relevant questions remains an attractive and productive research approach for identifying mechanistic pathways that can be developed into novel treatments for severe asthma.     

Modelling nutritional mutualisms: challenges and opportunities for data integration

Nutritional mutualisms are ancient, widespread, and profoundly influential in biological communities and ecosystems. Although much is known about these interactions, comprehensive answers to fundamental questions, such as how resource availability and structured interactions influence mutualism persistence, are still lacking. Mathematical modelling of nutritional mutualisms has great potential to facilitate the search for comprehensive answers to these and other fundamental questions by connecting the physiological and genomic underpinnings of mutualisms with ecological and evolutionary processes. In particular, when integrated with empirical data, models enable understanding of underlying mechanisms and generalisation of principles beyond the particulars of a given system. Here, we demonstrate how mathematical models can be integrated with data to address questions of mutualism persistence at four biological scales: cell, individual, population, and community. We highlight select studies where data has been or could be integrated with models to either inform model structure or test model predictions. We also point out opportunities to increase model rigour through tighter integration with data, and describe areas in which data is urgently needed. We focus on plant‐microbe systems, for which a wealth of empirical data is available, but the principles and approaches can be generally applied to any nutritional mutualism.     

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

Modeling of signal transduction pathways plays a major role in understanding cells'' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.     

A systems approach to morphogenesis in <Emphasis Type="Italic">Arabidopsis thaliana</Emphasis>: II. Modeling the regulation of shoot apical meristem structure

Two models of the mechanism maintaining a zonal structure in the shoot apical meristem (SAM) were built based on the analysis of experimental data on the interactions between CLV1, CLV2, CLV3, and WUS genes and the concepts of their role in this mechanism. The first model, a simple one-dimensional model with two morphogens, which is a variant of Wolpert’s French flag model [1], describes the regulation of zone distribution along the SAM vertical axis. Despite a number of simplifications, this model has stationary solutions with biologically meaningful interpretation. The simplifying assumptions were successively abandoned in constructing a two-dimensional model of the mechanism underlying the regulation of SAM structure. This model provides a better understanding of the distributed system that regulates the SAM structure, and allows more detailed formalization of the modern concepts and experimental data concerning this mechanism.     

Modeling the Dynamics of Paternal Influences on Children Over the Life Course

Modeling the Dynamics of Paternal Influences on Children over the Life Course Is a heuristic model, which identifies sets of variables that predict father involvement, variables that interact to predict involvement, and variables that influence father characteristics and thereby influence involvement. It also suggests moderators and mediators of pathways from predictors to father involvement and from father involvement to child outcomes. It is a dynamic model, assuming change over the life course, while retaining paternal influences from one developmental period to another. The model is rooted in the extant literature, although it is not circumscribed by that literature. As a heuristic model, it offers a framework from which measurement models can be derived to address research questions of interest.     

A Model for the Spread of an Invasive Weed, <Emphasis Type="Italic">Tradescantia fluminensis</Emphasis>

Tradescantia fluminensis is an invasive weed and a serious threat to native forests in eastern Australia and New Zealand. Current methods of eradication are often ineffective, so understanding the growth mechanisms of Tradescantia is important in formulating better control strategies. We present a partial differential equation (PDE) model for Tradescantia growth and spatial proliferation that accounts for Tradescantia’s particular creeping and branching morphology, and the impact of self-shading on plant growth. This is the first PDE model to represent a weed that spreads via a creeping growth habit rather than by seed dispersal. We use a travelling wave analysis to investigate how Tradescantia extends to colonise new territory. Numerical simulations and analysis show that the model provides a good qualitative representation of the behaviour of this plant. This model provides a foundation for assessing different control and eradication strategies for Tradescantia.     

A new transgenic mouse model for conditional overexpression of the Polycomb Group protein EZH2

The Polycomb Group protein EZH2 is upregulated in most prostate cancers, and its overexpression is associated with poor prognosis. Most insights into the functional role of EZH2 in prostate cancer have been gained using cell lines and EZH2 inactivation studies. However, the question remains whether overexpression of EZH2 can initiate prostate tumourigenesis or drive tumour progression. Appropriate transgenic mouse models that are required to answer such questions are lacking. We developed one such transgenic mouse model for conditional overexpression of Ezh2. In this transgene, Ezh2 and Luciferase are transcribed from a single open reading frame. The latter gene enables intravital bioluminescent imaging of tissues expressing this transgene, allowing the detection of tumour outgrowth and potential metastatic progression over time. Prostate-specific Ezh2 overexpression by crossbreeding with Probasin-Cre mice led to neoplastic prostate lesions at low incidence and with a long latency. Compounding a previously described Bmi1-transgene and Pten-deficiency prostate cancer mouse model with the Ezh2 transgene did not enhance tumour progression or drive metastasis formation. In conclusion, we here report the generation of a wildtype Ezh2 overexpression mouse model that allows for intravital surveillance of tissues with activated transgene. This model will be an invaluable tool for further unravelling the role of EZH2 in cancer.