Institute for Systems Biology

About: Institute for Systems Biology is a nonprofit organization based out in Seattle, Washington, United States. It is known for research contribution in the topics: Population & Proteomics. The organization has 1277 authors who have published 2777 publications receiving 353165 citations.

Transcriptional regulatory cascades in development: Initial rates, not steady state, determine network kinetics

Abstract: A model was built to examine the kinetics of regulatory cascades such as occur in developmental gene networks. The model relates occupancy of cis-regulatory target sites to transcriptional initiation rate, and thence to RNA and protein output. The model was used to simulate regulatory cascades in which genes encoding transcription factors are successively activated. Using realistic parameter ranges based on extensive earlier measurements in sea urchin embryos, we find that transitions of regulatory states occur sharply in these simulations, with respect to time or changing transcription factor concentrations. As is often observed in developing systems, the simulated regulatory cascades display a succession of gene activations separated by delays of some hours. The most important causes of this behavior are cooperativity in the assembly of cis-regulatory complexes and the high specificity of transcription factors for their target sites. Successive transitions in state occur long in advance of the approach to steady-state levels of the molecules that drive the process. The kinetics of such developmental systems thus depend mainly on the initial output rates of genes activated in response to the advent of new transcription factors.

Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

Abstract: The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us.

Structural and Genetic Diversity of Group B Streptococcus Capsular Polysaccharides

Abstract: Group B Streptococcus (GBS) is an important pathogen of neonates, pregnant women, and immunocompromised individuals. GBS isolates associated with human infection produce one of nine antigenically distinct capsular polysaccharides which are thought to play a key role in virulence. A comparison of GBS polysaccharide structures of all nine known GBS serotypes together with the predicted amino acid sequences of the proteins that direct their synthesis suggests that the evolution of serotype-specific capsular polysaccharides has proceeded through en bloc replacement of individual glycosyltransferase genes with DNA sequences that encode enzymes with new linkage specificities. We found striking heterogeneity in amino acid sequences of synthetic enzymes with very similar functions, an observation that supports horizontal gene transfer rather than stepwise mutagenesis as a mechanism for capsule variation. Eight of the nine serotypes appear to be closely related both structurally and genetically, whereas serotype VIII is more distantly related. This similarity in polysaccharide structure strongly suggests that the evolutionary pressure toward antigenic variation exerted by acquired immunity is counterbalanced by a survival advantage conferred by conserved structural motifs of the GBS polysaccharides.

Selecting differentially expressed genes from microarray experiments.

Abstract: Les technologies a haut debit, telles les puces a ADN et la spectrometrie de masse, permettent d'evaluer simultanement iles milliers de biomarqueurs potentiels qui distinguent differents types de tissus. Ces techniques sont particulierement interessantes dans la comparaison entre tissus cancereux et tissus normaux. Nous etudions des methodes statistiques pour classer les genes (ou les proteines) en fonction de leur differentiel d'expression dans les tissus. Nous etudions differentes mesures statistiques et nous soutenons que deux mesures liees a la courbe ROC (receiver operating characteristic) sont particulierement adaptees a cet objectif. Nous proposons aussi de quantifier la variabilite entre echantillons dans les classements de genes et nous suggerons d'utiliser la'fonction de probabilite de selection', la distribution de probabilite des classements pour chaque gene, estimee par bootstrap. Nous analysons un jeu de donnees reel obtenu a partir des resultats d'expression genique de 23 tissus ovariens normaux et de 30 tissus cancereux. Des etudes de simulation sont aussi utilisees pour etudier le comportement de differentes mesures statistiques de classement de genes et notre quantification de la variabilite entre echantillons. Notre approche conduit naturellement a une procedure de calcul de taille d'echantillon appropriee a des etudes exploratoires visant a identifier des genes a expression differentielle.

Comparative functional analysis of the Caenorhabditis elegans and Drosophila melanogaster proteomes.

Abstract: The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance.