SAPHIR: a physiome core model of body fluid homeostasis and blood pressure regulation.

We present the current state of the development of the SAPHIR project (a Systems Approach for PHysiological Integration of Renal, cardiac and respiratory function). The aim is to provide an open-source multi-resolution modelling environment that will permit, at a practical level, a plug-and-play construction of integrated systems models using lumped-parameter components at the organ/tissue level while also allowing focus on cellular- or molecular-level detailed sub-models embedded in the larger core model. Thus, an in silico exploration of gene-to-organ-to-organism scenarios will be possible, while keeping computation time manageable. As a first prototype implementation in this environment, we describe a core model of human physiology targeting the short- and long-term regulation of blood pressure, body fluids and homeostasis of the major solutes. In tandem with the development of the core models, the project involves database implementation and ontology development.

SAPHIR - a multi-scale, multi-resolution modeling environment targeting blood pressure regulation and fluid homeostasis.

We present progress on a comprehensive, modular, interactive modeling environment centered on overall regulation of blood pressure and body fluid homeostasis. We call the project SAPHIR, for "a Systems Approach for PHysiological Integration of Renal, cardiac, and respiratory functions". The project uses state-of-the-art multi-scale simulation methods. The basic core model will give succinct input-output (reduced-dimension) descriptions of all relevant organ systems and regulatory processes, and it will be modular, multi-resolution, and extensible, in the sense that detailed submodules of any process(es) can be "plugged-in" to the basic model in order to explore, eg. system-level implications of local perturbations. The goal is to keep the basic core model compact enough to insure fast execution time (in view of eventual use in the clinic) and yet to allow elaborate detailed modules of target tissues or organs in order to focus on the problem area while maintaining the system-level regulatory compensations.

Construction, visualisation, and clustering of transcription networks from microarray expression data.

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express(3D).

Prediction of microRNA targets.

Recently, microRNAs (miRNAs) have been shown to be important regulators of genes in many organisms and have already been implicated in a growing number of diseases. MiRNAs are short (21-23 nucleotides) RNAs that bind to the 3' untranslated regions of target genes. This binding event causes translational repression of the target gene and, evidence now suggests, also stimulates rapid degradation of the target transcript. miRNAs represent a new species of regulator, controlling the levels of potentially large numbers of proteins, many of which might be important drug targets. The expression of miRNAs shows that they are highly differentially expressed, with specific miRNAs active in certain tissues at certain times. In many cancers, miRNA expression is significantly altered, and this has been shown to be a useful diagnostic tool. Several computational approaches have been developed for the prediction of miRNA targets.

Formal TCA cycle description based on elementary actions.

Many databases propose their own structure and format to provide data describing biological processes. This heterogeneity contributes to the difficulty of large systematic and automatic functional comparisons. To overcome these problems, we have used the BioPsi formal description scheme which allows multi-level representations of biological process information. Applied to the description of the tricarboxylic acid cycle (TCA), we show that BioPsi allows the formal integration of functional information existing in current databases and make them available for further automated analysis. In addition such a formal TCA cycle process description leads to a more accurate biological process annotation which takes in account the biological context. This enables us to perform an automated comparison of the TCA cycles for seven different species based on processes rather than protein sequences. From current databases, BioPsi is able to unravel information that are already known by the biologists but are not available for automated analysis tools and simulation software, because of the lack of formal process descriptions. This use of the BioPsi description scheme to describe the TCA cycle was a key step of the MitoScop project that aims to describe and simulate mitochondrial metabolism in silico.

Impact of RNA degradation on gene expression profiles: assessment of different methods to reliably determine RNA quality.

DNA microarray technology enables investigators to measure the expression of several 1000 mRNA species simultaneously in a biological specimen. However, the reliability of the microarray technology to detect transcriptional differences representative of the original samples is affected by the quality of the extracted RNA. Thus, it is of critical importance to standardize sample-handling protocols and to perform a quality assessment of RNA preparations. In this report, 59 human tissue samples were used to evaluate the relationships between RNA quality and gene expression. From Affymetrix GeneChip array data analysis of these samples, we compared the performance of the 28S/18S ratio, two computer methods (RIN and degradometer) and our in-house RNA quality scale (RQS) in assessing RNA quality. The optimal RNA reliability threshold was determined for each method using statistical discrimination measures. We showed that RQS, RIN and degradometer have a similar capacity to detect reliable RNA samples whereas the 28S/18S ratio leads to a misleading categorization. Furthermore, we developed a new approach, based on clustering analyses of full chip expression, to control RNA quality after hybridization experiments. The combination of these methods, allowing monitoring of RNA quality prior to and after the hybridization experiments, ensured reliable and reproducible microarray data.

Maps, books and other metaphors for systems biology.

We briefly review the use of metaphors in science and progressively focus on fields from biology and molecular biology to genomics and bioinformatics. We discuss how metaphors are both a tool for scientific exploration and a medium for public communication of complex subjects, by various short examples. Finally, we propose a metaphor for systems biology that provides an illuminating perspective for the ambitious goals of this field and delimits its current agenda.

A description scheme of biological processes based on elementary bricks of action.

With the fast growth of high-throughput strategies in Biology, there is a strong need to accelerate knowledge acquisition and organization of molecular functions. Unfortunately, although we know that there is a correlation between protein molecules and their functions, we are unable to clearly identify this link. Here, we revisit the current views of protein functions as well as their annotation, and we show that they are incompatible with unambiguous interpretations and the use of this knowledge. We describe herein a description scheme for biological processes based on elementary bricks of action that may be associated with biological molecules. To retrieve the descriptive quality found in annotations of other kinds of biological data, it was decided to develop a scheme involving four levels of abstraction: Basic Elements of Action, Biological Activities, Biological Functionalities and Biological Roles. This multi-level organization is a generic method; it allows for a description of biological processes by using a limited number of elementary bricks of action. Moreover, by using this description of biological processes, it should now be possible to clearly identify unambiguous relationships between the organization of biological processes and the structural or functional organizations of biological molecules.

Involvement of sphingosine in dexamethasone-induced thymocyte apoptosis.

It is generally accepted that ceramide plays an essential role in apoptosis. In this study we suggest that in thymocytes, dexamethasone-induced apoptosis is mediated by sphingosine rather than ceramide, through the activation of an aSMase and a cerase in a caspase-dependent manner.