Caution on the assessment of intestinal parasitic load in studying parasite-mediated sexual selection: The case of Blackbirds coccidiosis

The parasite-mediated sexual selection (PMSS) theory has led to an increasing number of experimental studies essentially focussed on blood parasites. Currently, more research is being carried out on intestinal parasites in relationship to this theory. Before testing the theory with gastrointestinal parasites, it is important: (i) to determine an optimal research methodology to obtain an accurate assessment of parasite burden and (ii) to have information about life-history traits of the parasite to interpret data appropriately. In this study, we present data on oocyst output of Isosporaturdi in the faeces of blackbirds (Turdus merula) that illustrate the importance of developing methods that are relevant for a particular model system, instead of relying on existing methods that may work in other systems. Our results show that: (i) a single droplet of faeces will accurately indicate the parasitic load in blackbirds, (ii) oocyst shedding varies greatly within and between days, (iii) the course of infection is characterised with two successive peaks of oocyst shedding, (iv) infection lasts approximately 1 month and (iv) there is no effect of sex, size of infective dose or re-infection on the course of infection. We discuss the practical implications of these results in determining the reliability of, and in avoiding erroneous conclusions about, PMSS when using intestinal parasites as models. In particular, we emphasise that numerous measurements must be performed on different days. In addition, faeces must be collected at a particular time of day because there is a strong temporal variation in oocyst shedding. Finally, a standardised methodology that has been developed for a particular host-parasite assemblage does not necessarily work with other biological models. Together, our results should encourage future investigators to identify an accurate methodology for assessing parasitic load as a first step before testing hypotheses associated with the PMSS theory.     

Theoretical study on the body form and swimming pattern of Anomalocaris based on hydrodynamic simulation

Anomalocarid arthropod is the largest known predatory animal of middle Cambrian. Studies on Anomalocaris have been piled up in the past two decades since the first reasonable reconstruction had achieved in 1980s. Recent finding of legs beneath lobes on Parapeytoia Yunnanensis shows arthropod affinities, however, many researchers believe that it must be a powerful swimmer by the use of developed lobes. In this work, we investigate swimming behaviour of Anomalocaris in water by performing hydrodynamical calculation. As a result of simulation using moving particle method possible swimming motion of Anomalocaris is obtained. In the computer we can change the morphology from known bauplan of Anomalocaris found as fossil record. It makes us possible to discuss on the variants of Anomalocaris at the intermediate state of evolution process. Such new methodology using computer reveals how and from where Anomalocaris evolved.     

Space as the final frontier in stochastic simulations of biological systems

Recent technological and theoretical advances are only now allowing the simulation of detailed kinetic models of biological systems that reflect the stochastic movement and reactivity of individual molecules within cellular compartments. The behavior of many systems could not be properly understood without this level of resolution, opening up new perspectives of using computer simulations to accelerate biological research. We review the modeling methodology applied to stochastic spatial models, also to the attention of non-expert potential users. Modeling choices, current limitations and perspectives of improvement of current general-purpose modeling/simulation platforms for biological systems are discussed.     

Prediction of the initial folding sites and the entire folding processes for Ig-like beta-sandwich proteins

Describing the whole story of protein folding is currently the main enigmatic problem in molecular bioinformatics study. Protein folding mechanisms have been intensively investigated with experimental as well as simulation techniques. Since a protein folds into its specific 3D structure from a unique amino acid sequence, it is interesting to extract as much information as possible from the amino acid sequence of a protein. Analyses based on inter-residue average distance statistics and a coarse-grained Gō-model simulation were conducted on Ig and FN3 domains of a titin protein to decode the folding mechanisms from their sequence data and native structure data, respectively. The central region of all domains was predicted to be an initial folding unit, that is, stable in an early state of folding. This common feature coincides well with the experimental results and underscores the significance of the β-sandwich proteins' common structure, namely, the key strands for folding and the Greek-key motif, which is located in the central region. We confirmed that our sequence-based techniques were able to predict the initial folding event just next to the denatured state and that a 3D-based Gō-model simulation can be used to investigate the whole process of protein folding.     

Role of IL-15 in immune-mediated and infectious diseases

IL-15 has a broad spectrum of biological activities. It is crucial for the development, proliferation, survival and differentiation of multiple cells from both innate and adaptive immune systems. However, IL-15 up-regulation has a central role in the development of several autoimmune or chronic inflammatory disorders. Therefore, targeting IL-15 or its receptor may have a valuable impact on the treatment of immune-mediated diseases. On the other hand, in some infectious diseases, IL-15 production is compromised but IL-15 given exogenously can potentially enhance immune responses to pathogens. Here, we discuss the current understanding of IL-15 role in immune-mediated and infectious diseases as well as its therapeutic use.     

The layer-oriented approach to declarative languages for biological modeling

We present a new approach to modeling languages for computational biology, which we call the layer-oriented approach. The approach stems from the observation that many diverse biological phenomena are described using a small set of mathematical formalisms (e.g. differential equations), while at the same time different domains and subdomains of computational biology require that models are structured according to the accepted terminology and classification of that domain. Our approach uses distinct semantic layers to represent the domain-specific biological concepts and the underlying mathematical formalisms. Additional functionality can be transparently added to the language by adding more layers. This approach is specifically concerned with declarative languages, and throughout the paper we note some of the limitations inherent to declarative approaches. The layer-oriented approach is a way to specify explicitly how high-level biological modeling concepts are mapped to a computational representation, while abstracting away details of particular programming languages and simulation environments. To illustrate this process, we define an example language for describing models of ionic currents, and use a general mathematical notation for semantic transformations to show how to generate model simulation code for various simulation environments. We use the example language to describe a Purkinje neuron model and demonstrate how the layer-oriented approach can be used for solving several practical issues of computational neuroscience model development. We discuss the advantages and limitations of the approach in comparison with other modeling language efforts in the domain of computational biology and outline some principles for extensible, flexible modeling language design. We conclude by describing in detail the semantic transformations defined for our language.     

Parakeet: a digital twin software pipeline to assess the impact of experimental parameters on tomographic reconstructions for cryo-electron tomography

In cryo-electron tomography (cryo-ET) of biological samples, the quality of tomographic reconstructions can vary depending on the transmission electron microscope (TEM) instrument and data acquisition parameters. In this paper, we present Parakeet, a ‘digital twin’ software pipeline for the assessment of the impact of various TEM experiment parameters on the quality of three-dimensional tomographic reconstructions. The Parakeet digital twin is a digital model that can be used to optimize the performance and utilization of a physical instrument to enable in silico optimization of sample geometries, data acquisition schemes and instrument parameters. The digital twin performs virtual sample generation, TEM image simulation, and tilt series reconstruction and analysis within a convenient software framework. As well as being able to produce physically realistic simulated cryo-ET datasets to aid the development of tomographic reconstruction and subtomogram averaging programs, Parakeet aims to enable convenient assessment of the effects of different microscope parameters and data acquisition parameters on reconstruction quality. To illustrate the use of the software, we present the example of a quantitative analysis of missing wedge artefacts on simulated planar and cylindrical biological samples and discuss how data collection parameters can be modified for cylindrical samples where a full 180° tilt range might be measured.     

Single domain intracellular antibodies: a minimal fragment for direct in vivo selection of antigen-specific intrabodies

There is a major need in target validation and therapeutic applications for molecules that can interfere with protein function inside cells. Intracellular antibodies (intrabodies) can bind to specific targets in cells but isolation of intrabodies is currently difficult. Intrabodies are normally single chain Fv fragments comprising variable domains of the immunoglobulin heavy (VH) and light chains (VL). We now demonstrate that single VH domains have excellent intracellular properties of solubility, stability and expression within the cells of higher organisms and can exhibit specific antigen recognition in vivo. We have used this intracellular single variable domain (IDab) format, based on a previously characterised intrabody consensus scaffold, to generate diverse intrabody libraries for direct in vivo screening. IDabs were isolated using two distinct antigens and affinities of isolated IDabs ranged between 20 nM and 200 nM. Moreover, IDabs selected for binding to the RAS protein could inhibit RAS-dependent oncogenic transformation of NIH3T3 cells. The IDab format is therefore ideal for in vivo intrabody use. This approach to intrabodies obviates the need for phage antibody libraries, avoids the requirement for production of antigen in vitro and allows for direct selection of intrabodies in vivo.     

Optimized synthesis and characterization of N-acylethanolamines and O-acylethanolamines, important family of lipid-signalling molecules

The endocannabinoid anandamide (N-arachidonoylethanolamine, AEA), a physiologically occurring bioactive compound on CB1 and CB2 receptors, has multiple physiological functions. Since the discovery of AEA additional non-cannabinoid endogenous compounds such as N-palmitoylethanolamine (PEA), and N-oleoylethanolamine (OEA) have been identified from mammalian tissues. Virodhamine (O-arachidonoylethanolamine, VA) is the only identified new member of the endocannabinoid family that is characterised by an ester linkage between acylic acid and ethanolamine instead of the amide linkage found in AEA and others non-cannabinoid N-acylethanolamines. It has been reported, as a cautionary note for lipid analyses, that VA can be produced nonenzymatically from AEA (and vice versa) as consequence of O,N-acyl migrations. O,N-acyl migrations are well documented in synthetic organic chemistry literature, but are not well described or recognized with regard to methods in lipid isolation or lipid enzyme studies. We here report an economical and effective protocol for large scale synthesis and characterization of some N- and O-acylethanolamines that could be useful as reference standards in order to investigate their possible formation in biological membranes, with potentially interesting biological properties.     

Towards a structured approach to building qualitative reasoning models and simulations

Successful transfer and uptake of qualitative reasoning technology for modelling and simulation in a variety of domains has been hampered by the lack of a structured methodology to support formalisation of ideas. We present a framework that structures and supports the capture of conceptual knowledge about system behaviour using a qualitative reasoning approach. This framework defines a protocol for representing content that supports the development of a conceptual understanding of systems and how they behave. The framework supports modellers in two ways. First, it structures and explicates the work involved in building models. Second, it facilitates easier comparison and evaluation of intermediate and final results of modelling efforts. We show how this framework has been used in developing qualitative reasoning models about three case studies of sustainable development in different river systems.     

Determining Disease Intervention Strategies Using Spatially Resolved Simulations

Predicting efficacy and optimal drug delivery strategies for small molecule and biological therapeutics is challenging due to the complex interactions between diverse cell types in different tissues that determine disease outcome. Here we present a new methodology to simulate inflammatory disease manifestation and test potential intervention strategies in silico using agent-based computational models. Simulations created using this methodology have explicit spatial and temporal representations, and capture the heterogeneous and stochastic cellular behaviours that lead to emergence of pathology or disease resolution. To demonstrate this methodology we have simulated the prototypic murine T cell-mediated autoimmune disease experimental autoimmune encephalomyelitis, a mouse model of multiple sclerosis. In the simulation immune cell dynamics, neuronal damage and tissue specific pathology emerge, closely resembling behaviour found in the murine model. Using the calibrated simulation we have analysed how changes in the timing and efficacy of T cell receptor signalling inhibition leads to either disease exacerbation or resolution. The technology described is a powerful new method to understand cellular behaviours in complex inflammatory disease, permits rational design of drug interventional strategies and has provided new insights into the role of TCR signalling in autoimmune disease progression.     

The role of pre-release efficacy assessment in selecting classical biological control agents for weeds—applying the Anna Karenina principle

The goals in selecting classical biological control agents for weeds are to identify agents that will be both safe for release and effective in controlling their target plants. The release of ineffective agents should be avoided, as these add to the costs and risks of biological control without contributing to its benefits. While the principles of host-specificity testing and risk assessment for weed biological control agents have been extensively debated and refined, there has been less attention given to assessing the probable efficacy of agents prior to release. This reluctance to undertake pre-release efficacy assessment (PREA) is probably based on concerns that it will both add to the cost of screening biological control agents and introduce a risk of wrongly rejecting effective agents. We used a project simulation model to investigate the implications of using PREA as an additional filter in the agent selection process. The results suggest that, if it can be done at a lower cost than host-specificity testing, the use of PREA as the first filter can make agent selection more cost-effective than screening based on host-specificity alone. We discuss examples of PREA and potential approaches. The impact of biocontrol agents is a function of their range, abundance, and per-capita damage. While it will always be difficult to predict the post-release abundance of biological control agents from pre-release studies, some estimates of potential range can be obtained from studies of climatic adaptation. For agents that affect the vegetative growth or survival of their target weeds, experimental measurement of per-capita damage is feasible and can contribute to a reduction in the numbers of ineffective agents released. The Anna Karenina principle states that success in complex undertakings does not depend on a single factor but requires avoiding many separate causes of failure. We suggest that, in biological control of weeds, the use of agents that are not sufficiently damaging is one such cause that can be partially avoided by the use of pre-release efficacy assessment.     

Dipolar couplings as a probe of molecular dynamics and structure in solution.

The introduction of residual dipolar coupling methodology has increased the scope of structural biological problems that can be addressed by NMR spectroscopy. Conformational changes, the relative orientation of domains, and intermolecular complexes can now be characterized accurately and rapidly using NMR. The development of residual dipolar coupling methodology for the rapid recognition of homologous protein folds and for studies of submillisecond timescale dynamics has also seen considerable progress.     

系统生物学(Systems Biology)的几大重要问题

近几年来,系统生物学从正式提出到受到普遍关注和研究,对生物学的研究发展起了革命性的变化。主要从系统生物学的发展及其内容进行分析,讨论了生物数据整合,模型建立和模拟分析等几点关键性的问题,并展望了系统生物学的研究。     

Algorithms in nature: the convergence of systems biology and computational thinking

Computer science and biology have enjoyed a long and fruitful relationship for decades. Biologists rely on computational methods to analyze and integrate large data sets, while several computational methods were inspired by the high‐level design principles of biological systems. Recently, these two directions have been converging. In this review, we argue that thinking computationally about biological processes may lead to more accurate models, which in turn can be used to improve the design of algorithms. We discuss the similar mechanisms and requirements shared by computational and biological processes and then present several recent studies that apply this joint analysis strategy to problems related to coordination, network analysis, and tracking and vision. We also discuss additional biological processes that can be studied in a similar manner and link them to potential computational problems. With the rapid accumulation of data detailing the inner workings of biological systems, we expect this direction of coupling biological and computational studies to greatly expand in the future.     

Participatory Development and Analysis of a Fuzzy Cognitive Map of the Establishment of a Bio-Based Economy in the Humber Region

Fuzzy Cognitive Mapping (FCM) is a widely used participatory modelling methodology in which stakeholders collaboratively develop a ‘cognitive map’ (a weighted, directed graph), representing the perceived causal structure of their system. This can be directly transformed by a workshop facilitator into simple mathematical models to be interrogated by participants by the end of the session. Such simple models provide thinking tools which can be used for discussion and exploration of complex issues, as well as sense checking the implications of suggested causal links. They increase stakeholder motivation and understanding of whole systems approaches, but cannot be separated from an intersubjective participatory context. Standard FCM methodologies make simplifying assumptions, which may strongly influence results, presenting particular challenges and opportunities. We report on a participatory process, involving local companies and organisations, focussing on the development of a bio-based economy in the Humber region. The initial cognitive map generated consisted of factors considered key for the development of the regional bio-based economy and their directional, weighted, causal interconnections. A verification and scenario generation procedure, to check the structure of the map and suggest modifications, was carried out with a second session. Participants agreed on updates to the original map and described two alternate potential causal structures. In a novel analysis all map structures were tested using two standard methodologies usually used independently: linear and sigmoidal FCMs, demonstrating some significantly different results alongside some broad similarities. We suggest a development of FCM methodology involving a sensitivity analysis with different mappings and discuss the use of this technique in the context of our case study. Using the results and analysis of our process, we discuss the limitations and benefits of the FCM methodology in this case and in general. We conclude by proposing an extended FCM methodology, including multiple functional mappings within one participant-constructed graph.     

Trichinella spiralis: modulation of experimental autoimmune encephalomyelitis in DA rats

Helminth infection has a potent systemic immunomodulatory effect on the host immune response, which also affects the development of autoimmune diseases. We investigated the dose-dependent influence of Trichinella spiralis infection on experimental autoimmune encephalomyelitis (EAE). Our model of concomitant T. spiralis infection and EAE demonstrates that established infection of Dark Agouti (DA) rats with the parasite causes amelioration of the clinical course of induced EAE in a dose-dependent way. Infection with T. spiralis L1 stage muscle larvae (TSL1) reduced the severity of the autoimmune disease as judged by lower maximal clinical score, cumulative index, duration of illness and degree of mononuclear cell infiltration in T. spiralis infected animals compared to control, EAE-induced group. This study provides a valuable model of worm infection to investigate helminth-induced regulatory mechanisms for optimal benefit to the host.