CellML 2.0.

We present here CellML 2.0, an XML-based language for describing and exchanging mathematical models of physiological systems. MathML embedded in CellML documents is used to define the underlying mathematics of models. Models consist of a network of reusable components, each with variables and equations giving relationships between those variables. Models may import other models to create systems of increasing complexity. CellML 2.0 is defined by the normative specification presented here, prescribing the CellML syntax and the rules by which it should be used. The normative specification is intended primarily for the developers of software tools which directly consume CellML syntax. Users of CellML models may prefer to browse the informative rendering of the specification (https://cellml.org/specifications/cellml_2.0/) which extends the normative specification with explanations of the rules combined with examples of their usage.

Harmonizing semantic annotations for computational models in biology.

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Modular modelling with Physiome standards.

KEY POINTS: The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. ABSTRACT: The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole-cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles.

The CellML Metadata Framework 2.0 Specification.

The CellML Metadata Framework 2.0 is a modular framework that describes how semantic annotations should be made about mathematical models encoded in the CellML (www.cellml.org) format, and their elements. In addition to the Core specification, there are several satellite specifications, each designed to cater for model annotation in a different context. Basic Model Information, Citation, License and Biological Annotation specifications are presented.

Culture and detection of primary cilia in endothelial cell models.

BACKGROUND: The primary cilium is a sensor of blood-induced forces in endothelial cells (ECs). Studies that have examined EC primary cilia have reported a wide range of cilia incidence (percentage of ciliated cells). We hypothesise that this variation is due to the diversity in culture conditions in which the cells are grown. We studied two EC types: human umbilical vein endothelial cells (HUVECs) and human microvascular endothelial cells (HMEC-1s). Both cell types were grown in media containing foetal bovine serum (FBS) at high (20 % FBS and 10 % FBS for HUVECs and HMEC-1s, respectively) or low (2 % FBS) concentrations. Cells were then either fixed at confluence, serum-starved or grown post-confluence for 5 days in corresponding expansion media (cobblestone treatment). For each culture condition, we quantified cilia incidence and length. RESULTS: HUVEC ciliogenesis is dependent on serum concentration during the growth phase; low serum (2 % FBS) HUVECs were not ciliated, whereas high serum (20 % FBS) confluent HUVECs have a cilia incidence of 2.1 ± 2.2 % (median ± interquartile range). We report, for the first time, the presence of cilia in the HMEC-1 cell type. HMEC-1s have between 2.2 and 3.5 times greater cilia incidence than HUVECs (p < 0.001). HMEC-1s also have shorter cilia compared to HUVECs (3.0 ± 1.0 µm versus 5.1 ± 2.4 µm, at confluence, p = 0.003). CONCLUSIONS: We demonstrate that FBS plays a role in determining the prevalence of cilia in HUVECs. In doing so, we highlight the importance of considering a commonly varied parameter (% FBS), in the experimental design. We recommend that future studies examining large blood vessel EC primary cilia use confluent HUVECs grown in high serum medium, as we found these cells to have a higher cilia incidence than low serum media HUVECs. For studies interested in microvasculature EC primary cilia, we recommend using cobblestone HMEC-1s grown in high serum medium, as these cells have a 19.5 ± 6.2 % cilia incidence.

Computational models of the primary cilium and endothelial mechanotransmission.

In endothelial cells (ECs), the mechanotransduction of fluid shear stress is partially dependent on the transmission of force from the fluid into the cell (mechanotransmission). The role of the primary cilium in EC mechanotransmission is not yet known. To motivate a framework towards quantifying cilia contribution to EC mechanotransmission, we have reviewed mechanical models of both (1) the primary cilium (three-dimensional and lower-dimensional) and (2) whole ECs (finite element, non-finite element, and tensegrity). Both the primary cilia and whole EC models typically incorporate fluid-induced wall shear stress and spatial geometry based on experimentally acquired images of cells. This paper presents future modelling directions as well as the major goals towards integrating primary cilium models into a multi-component EC mechanical model. Finally, we outline how an integrated cilium-EC model can be used to better understand mechanotransduction in the endothelium.

Distributed model construction with virtual parts.

Here three models for a simple genetic device are constructed using modular mathematical models. The models are stored in an online system (the Physiome Model Repository) with distributed source and access control, demonstrating a collaborative method for creating mathematical models from reusable components.

Multiscale modeling of intracranial aneurysms: cell signaling, hemodynamics, and remodeling.

The genesis, growth, and rupture of intracranial aneurysms (IAs) involve physics at the molecular, cellular, blood vessel, and organ levels that occur over time scales ranging from seconds to years. Comprehensive mathematical modeling of IAs, therefore, requires the description and integration of events across length and time scales that span many orders of magnitude. In this letter, we outline a strategy for mulstiscale modeling of IAs that involves the construction of individual models at each relevant scale and their subsequent combination into an integrative model that captures the overall complexity of IA development. An example of the approach is provided using three models operating at different length and time scales: 1) shear stress induced nitric oxide production; 2) smooth muscle cell apoptosis; and 3) fluid-structure-growth modeling. A computational framework for combining them is presented. We conclude with a discussion of the advantages and challenges of the approach.

Model annotation for synthetic biology: automating model to nucleotide sequence conversion.

MOTIVATION: The need for the automated computational design of genetic circuits is becoming increasingly apparent with the advent of ever more complex and ambitious synthetic biology projects. Currently, most circuits are designed through the assembly of models of individual parts such as promoters, ribosome binding sites and coding sequences. These low level models are combined to produce a dynamic model of a larger device that exhibits a desired behaviour. The larger model then acts as a blueprint for physical implementation at the DNA level. However, the conversion of models of complex genetic circuits into DNA sequences is a non-trivial undertaking due to the complexity of mapping the model parts to their physical manifestation. Automating this process is further hampered by the lack of computationally tractable information in most models. RESULTS: We describe a method for automatically generating DNA sequences from dynamic models implemented in CellML and Systems Biology Markup Language (SBML). We also identify the metadata needed to annotate models to facilitate automated conversion, and propose and demonstrate a method for the markup of these models using RDF. Our algorithm has been implemented in a software tool called MoSeC. AVAILABILITY: The software is available from the authors' web site http://research.ncl.ac.uk/synthetic_biology/downloads.html.

The Physiome Model Repository 2.

MOTIVATION: The Physiome Model Repository 2 (PMR2) software was created as part of the IUPS Physiome Project (Hunter and Borg, 2003), and today it serves as the foundation for the CellML model repository. Key advantages brought to the end user by PMR2 include: facilities for model exchange, enhanced collaboration and a detailed change history for each model. AVAILABILITY: PMR2 is available under an open source license at http://www.cellml.org/tools/pmr/; a fully functional instance of this software can be accessed at http://models.physiomeproject.org/.

A global sensitivity tool for cardiac cell modeling: Application to ionic current balance and hypertrophic signaling.

Cardiovascular diseases are the major cause of death in the developed countries. Identifying key cellular processes involved in generation of the electrical signal and in regulation of signal transduction pathways is essential for unraveling the underlying mechanisms of heart rhythm behavior. Computational cardiac models provide important insights into cardiovascular function and disease. Sensitivity analysis presents a key tool for exploring the large parameter space of such models, in order to determine the key factors determining and controlling the underlying physiological processes. We developed a new global sensitivity analysis tool which implements the Morris method, a global sensitivity screening algorithm, onto a Nimrod platform, which is a distributed resources software toolkit. The newly developed tool has been validated using the model of IP3-calcineurin signal transduction pathway model which has 30 parameters. The key driving factors of the IP3 transient behaviour have been calculated and confirmed to agree with previously published data. We next demonstrated the use of this method as an assessment tool for characterizing the structure of cardiac ionic models. In three latest human ventricular myocyte models, we examined the contribution of transmembrane currents to the shape of the electrical signal (i.e. on the action potential duration). The resulting profiles of the ionic current balance demonstrated the highly nonlinear nature of cardiac ionic models and identified key players in different models. Such profiling suggests new avenues for development of methodologies to predict drug action effects in cardiac cells.

Sensitivity of NFAT cycling to cytosolic calcium concentration: implications for hypertrophic signals in cardiac myocytes.

The nuclear factor of activated T-cell (NFAT) transcription factors play an important role in many biological processes, including pathological cardiac hypertrophy. Stimulated by calcium signals, NFAT is translocated to the nucleus where it can regulate hypertrophic genes (excitation-transcription coupling). In excitable cells, such as myocytes, calcium is a key second messenger for multiple signaling events, including excitation-contraction coupling. Whether the calcium signals due to excitation-contraction and excitation-transcription coupling coincide or how they can be differentiated is currently unclear. Here we construct a mathematical model of NFAT cycling fitted to skeletal myocyte and baby hamster kidney cell data. The model replicates key behavior with respect to sensitivity to calcineurin overexpression and to calcium oscillations. Finally, we measure the sensitivity of the system to a simulated hypertrophic calcium signal, against a background excitation-contraction coupling calcium oscillation. We find that NFAT cycling is sensitive to excitation-transcription coupling even when both calcium signals are in the same cellular compartment, thus showing that separation of the signals may not be necessary in vitro.