SBML Level 3: an extensible format for the exchange and reuse of biological models

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction-based models and packages that extend the core with features suited to other model types including constraint-based models, reaction-diffusion models, logical network models, and rule-based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single-cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution

Temporal organization of cellular growth in Saccharomyces cerevisiae

Wenn Bäckerhefe in flüssigem Nährmedium kultiviert wird, stellen sich oft stabile rhythmische Muster der Atmungsaktivität ein (metabolische oder Atmungsoszillation). Die Perioden dieser Oszillation schwanken sehr stark, von 40 min bis 12 h und mehr, aber werden generell kürzer mit steigender Wachstumsrate. Verschiedene methodische und biologische Aspekte dieses Phänomens wurden in fünf Publikationen untersucht, mit einem Schwerpunkt auf periodische Muster der RNA Transkription und Chromatinstruktur. Dabei wurden bereits publizierte Daten systematisch miteinander verglichen. Es zeigt sich ein hoch-konserviertes Programm der Genexpression, welches in allen Experimenten, unabhängig von der Oszillationsperiode, zu beobachten ist. Ein Programm in relativ konstantem Zeitrahmen von 30 min bis 1 h startet mit Beginn erhöhter Atmungsaktivität, und führt von Expression zytoplasmatischer Ribosomen, über Aminosäuresynthesewege zu Expression mitochondrialer Ribosomen. Das Ende dieses Zellwachstumsprogramms geht mit Abbau von Speicherzuckern, transienter Fermentation und, in Zellen die dazu bereit sind, Einleitung der DNA Replikation einher ("metabolic S-phase gating"). Dieses Ende liegt an variabler Position innerhalb des globalen Rahmens der Atmungsoszillation, noch vor oder überlappend mit der Phase niedriger Atmungsaktivität. In letzterer Phase werden wiederum Gene des Katabolismus, der Autophagie und der zellulären Stressantwort exprimiert. Die relative Expression dieser Gengruppen ändert sich auch in herkömmlicher exponentieller Wachstumsphase, die also entgegen allgemeiner Annahme nicht als Fließgleichgewicht betrachtet werden kann, und korreliert generell mit der Wachstumsrate, was zu einer in vielen Mikroorganismen beobachteten Optimierung der ribosomalen Biomassefraktion führt. Die Oszillationen `kollabieren' bei der Wachstumsrate, bei der Fermentation einsetzt; der sogenannte Crabtree-Effekt, verwandt dem Warburg-Effekt. Mechanistische und empirische Modelle für die beobachtete Dynamik werden vorgeschlagen

The dynamics of cellular energetics during continuous yeast culture

A plethora of data is accumulating from high throughput methods on metabolites, coenzymes, proteins, and nucleic acids and their interactions as well as the signalling and regulatory functions and pathways of the cellular network. The frozen moment viewed in a single discrete time sample requires frequent repetition and updating before any appreciation of the dynamics of component interaction becomes possible. Even then in a sample derived from a cell population, time-averaging of processes and events that occur in out-of-phase individuals blur the detailed complexity of single cell organization. Continuously-grown cultures of yeast can become spontaneously self-synchronized, thereby enabling resolution of far more detailed temporal structure. Continuous on-line monitoring by rapidly responding sensors (O2 electrode and membrane-inlet mass spectrometry for O2, CO2 and H2S; direct fluorimetry for NAD(P)H and flavins) gives dynamic information from time-scales of minutes to hours. Supplemented with capillary electophoresis and gas chromatography mass spectrometry and transcriptomics the predominantly oscillatory behaviour of network components becomes evident, with a 40 min cycle between a phase of increased respiration (oxidative phase) and decreased respiration (reductive phase). Highly pervasive, this ultradian clock provides a coordinating function that links mitochondrial energetics and redox balance to transcriptional regulation, mitochondrial structure and organelle remodelling, DNA duplication and cell division events. Ultimately, this leads to a global partitioning of anabolism and catabolism and the enzymes involved, mediated by a relatively simple ATP feedback loop on chromatin architecture

The SBML ODE Solver Library: A native API for symbolic and fast numerical analysis of reaction networks

The SBML ODE Solver Library (SOSlib) is a programming library for symbolic and numerical analysis of chemical reaction network models encoded in the Systems Biology Markup Language (SBML). It is written in ISO C and distributed under the open source LGPL license. The package employs libSBML structures for formula representation and associated functions to construct a system of ordinary differential equations, their Jacobian matrix and other derivatives. SUNDIALS' CVODES is incorporated for numerical integration and sensitivity analysis. Preliminary benchmarking results give a rough overview on the behavior of different tools and are discussed in the Supplementary Material. The native application program interface provides fine-grained interfaces to all internal data structures, symbolic operations and numerical routines, enabling the construction of very efficient analytic applications and hybrid or multi-scale solvers with interfaces to SBML and non SBML data sources. Optional modules based on XMGrace and Graphviz allow quick inspection of structure and dynamics. 2006 Oxford University Press

Controlled vocabularies and semantics in systems biology

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments.ISSN:1744-429

Controlled vocabularies and semantics in systems biology

The use of computational modeling to describe and analyze biological systems is at the heart of systems biology. Model structures, simulation descriptions and numerical results can be encoded in structured formats, but there is an increasing need to provide an additional semantic layer. Semantic information adds meaning to components of structured descriptions to help identify and interpret them unambiguously. Ontologies are one of the tools frequently used for this purpose. We describe here three ontologies created specifically to address the needs of the systems biology community. The Systems Biology Ontology (SBO) provides semantic information about the model components. The Kinetic Simulation Algorithm Ontology (KiSAO) supplies information about existing algorithms available for the simulation of systems biology models, their characterization and interrelationships. The Terminology for the Description of Dynamics (TEDDY) categorizes dynamical features of the simulation results and general systems behavior. The provision of semantic information extends a model's longevity and facilitates its reuse. It provides useful insight into the biology of modeled processes, and may be used to make informed decisions on subsequent simulation experiments