The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models

MOTIVATION: Molecular biotechnology now makes it possible to build elaborate systems models, but the systems biology community needs information standards if models are to be shared, evaluated and developed cooperatively. RESULTS: We summarize the Systems Biology Markup Language (SBML) Level 1, a free, open, XML-based format for representing biochemical reaction networks. SBML is a software-independent language for describing models common to research in many areas of computational biology, including cell signaling pathways, metabolic pathways, gene regulation, and others. AVAILABILITY: The specification of SBML Level 1 is freely available from http://www.sbml.org/     

A method for estimating stochastic noise in large genetic regulatory networks

MOTIVATION: Genetic regulatory networks are often affected by stochastic noise, due to the low number of molecules taking part in certain reactions. The networks can be simulated using stochastic techniques that model each reaction as a stochastic event. As models become increasingly large and sophisticated, however, the solution time can become excessive; particularly if one wishes to determine the effect on noise of changes to a series of parameters, or the model structure. Methods are therefore required to rapidly estimate stochastic noise. RESULTS: This paper presents an algorithm, based on error growth techniques from non-linear dynamics, to rapidly estimate the noise characteristics of genetic networks of arbitrary size. The method can also be used to determine analytical solutions for simple sub-systems. It is demonstrated on a number of cases, including a prototype model of the galactose regulatory pathway in yeast. AVAILABILITY: A software tool which incorporates the algorithm is available for use as part of the stochastic simulation package Dizzy. It is available for download at http://labs.systemsbiology.net/bolouri/software/Dizzy/ CONTACT: dorrell@systemsbiology.org SUPPLEMENTARY INFORMATION: A conceptual model of the regulatory part of the galactose utilization pathway in yeast, used as an example in the paper, is available at http://labs.systemsbiology.net/bolouri/models/galconcept.dizzy     

Evolution of 'design' principles in biochemical networks

Computer modelling and simulation are commonly used to analyse engineered systems. Biological systems differ in that they often cannot be accurately characterised, so simulations are far from exact. Nonetheless, we argue in this paper that evolution results in recurring, dynamic organisational principles in biological systems, and that simulation can help to identify them and analyse their dynamic properties. As a specific example, we present a dynamic model of the galactose utilisation pathway in yeast, and highlight several features of the model that embody such 'design principles'.     

Inflammatory-induced hibernation in the fetus: priming of fetal sheep metabolism correlates with developmental brain injury

Prenatal inflammation is considered an important factor contributing to preterm birth and neonatal mortality and morbidity. The impact of prenatal inflammation on fetal bioenergetic status and the correlation of specific metabolites to inflammatory-induced developmental brain injury are unknown. We used a global metabolomics approach to examine plasma metabolites differentially regulated by intrauterine inflammation. Preterm-equivalent sheep fetuses were randomized to i.v. bolus infusion of either saline-vehicle or LPS. Blood samples were collected at baseline 2 h, 6 h and daily up to 10 days for metabolite quantification. Animals were killed at 10 days after LPS injection, and brain injury was assessed by histopathology. We detected both acute and delayed effects of LPS on fetal metabolism, with a long-term down-regulation of fetal energy metabolism. Within the first 3 days after LPS, 121 metabolites were up-regulated or down-regulated. A transient phase (4-6 days), in which metabolite levels recovered to baseline, was followed by a second phase marked by an opposing down-regulation of energy metabolites, increased pO(2) and increased markers of inflammation and ADMA. The characteristics of the metabolite response to LPS in these two phases, defined as 2 h to 2 days and at 6-9 days, respectively, were strongly correlated with white and grey matter volumes at 10 days recovery. Based on these results we propose a novel concept of inflammatory-induced hibernation of the fetus. Inflammatory priming of fetal metabolism correlated with measures of brain injury, suggesting potential for future biomarker research and the identification of therapeutic targets.     

How to ensure threatened species monitoring leads to threatened species conservation

Monitoring is essential for effective conservation and management of threatened species and ecological communities. However, more often than not, threatened species monitoring is poorly implemented, meaning that conservation decisions are not informed by the best available knowledge. We outline challenges and provide best‐practice guidelines for threatened species monitoring, informed by the diverse perspectives of 26 conservation managers and scientists from a range of organisations with expertise across Australian species and ecosystems. Our collective expertise synthesised five key principles that aim to enhance the design, implementation and outcomes of threatened species monitoring. These principles are (i) integrate monitoring with management; (ii) design fit‐for‐purpose monitoring programs; (iii) engage people and organisations; (iv) ensure good data management; and (v) communicate the value of monitoring. We describe how to incorporate these principles into existing frameworks to improve current and future monitoring programs. Effective monitoring is essential to inform appropriate management and enable better conservation outcomes for our most vulnerable species and ecological communities.     

Cooperative interaction of antimicrobial peptides with the interrelated immune pathways in plants

Plants express a diverse repertoire of functionally and structurally distinct antimicrobial peptides (AMPs) which provide innate immunity by acting directly against a wide range of pathogens. AMPs are expressed in nearly all plant organs, either constitutively or in response to microbial infections. In addition to their direct activity, they also contribute to plant immunity by modulating defence responses resulting from pathogen‐associated molecular pattern/effector‐triggered immunity, and also interact with other AMPs and pathways involving mitogen‐activated protein kinases, reactive oxygen species, hormonal cross‐talk and sugar signalling. Such links among AMPs and defence signalling pathways are poorly understood and there is no clear model for their interactions. This article provides a critical review of the empirical data to shed light on the wider role of AMPs in the robust and resource‐effective defence responses of plants.     

Visualization, documentation, analysis, and communication of large-scale gene regulatory networks

Genetic regulatory networks (GRNs) are complex, large-scale, and spatially and temporally distributed. These characteristics impose challenging demands on software tools for building GRN models, and so there is a need for custom tools. In this paper, we report on our ongoing development of BioTapestry, an open source, freely available computational tool designed specifically for building GRN models. We also outline our future development plans, and give some examples of current applications of BioTapestry.     

Computational Challenges of Personal Genomics

It is widely predicted that cost and efficiency gains in sequencing will usher in an era of personal genomics and personalized, predictive, preventive, and participatory medicine within a decade. I review the computational challenges ahead and propose general and specific directions for research and development. There is an urgent need to develop semantic ontologies that span genomics, molecular systems biology, and medical data. Although the development of such ontologies would be costly and difficult, the benefits will far outweigh the costs. I argue that availability of such ontologies would allow a revolution in web-services for personal genomics and medicine.     

Robustness as a measure of plausibility in models of biochemical networks

Theory, experiment, and observation suggest that biochemical networks which are conserved across species are robust to variations in concentrations and kinetic parameters. Here, we exploit this expectation to propose an approach to model building and selection. We represent a model as a mapping from parameter space to behavior space, and utilize bifurcation analysis to study the robustness of each region of steady-state behavior to parameter variations. The hypothesis that potential errors in models will result in parameter sensitivities is tested by analysis of two models of the biochemical oscillator underlying the Xenopus cell cycle. Our analysis successfully identifies known weaknesses in the older model and suggests areas for further investigation in the more recent, more plausible model. It also correctly highlights why the more recent model is more plausible.