Reconstruction of the metabolic network of Pseudomonas aeruginosa to interrogate virulence factor synthesis
Virulence-linked pathways in opportunistic pathogens are putative therapeutic targets that may be associated with less potential for resistance than targets in growth-essential pathways. However, efficacy of virulence-linked targets may be affected by the contribution of virulence-related genes to metabolism. We evaluate the complex interrelationships between growth and virulence-linked pathways using a genome-scale metabolic network reconstruction […]
Read MoreMetDraw: automated visualization of genome-scale metabolic network reconstructions and high-throughput data
OP-CBIO130776 1327..1328 Motivation: Metabolic reaction maps allow visualization of genome- scale models and high-throughput data in a format familiar to many biologists. However, creating a map of a large metabolic model is a difficult and time-consuming process. MetDraw fully automates the map-drawing process for metabolic models containing hundreds to thousands of reactions. MetDraw can also […]
Read MoreComparative Metabolic Systems Analysis of Pathogenic Burkholderia
Burkholderia cenocepacia and Burkholderia multivorans are opportunistic drug-resistant pathogens that account for the major- ity of Burkholderia cepacia complex infections in cystic fibrosis patients and also infect other immunocompromised individuals. While they share similar genetic compositions, B. cenocepacia and B. multivorans exhibit important differences in pathogenesis. We have developed reconciled genome-scale metabolic network reconstructions of […]
Read MoreNovel Multiscale Modeling Tool Applied to Pseudomonas aeruginosa Biofilm Formation
Multiscale modeling is used to represent biological systems with increasing frequency and success. Multiscale models are often hybrids of different modeling frameworks and programming languages. We present the MATLAB- NetLogo extension (MatNet) as a novel tool for multiscale modeling. We demonstrate the utility of the tool with a multiscale model of Pseudomonas aeruginosa biofilm formation […]
Read MoreTIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks
Background: Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR) relationships […]
Read MoreReconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis
In the past decade, over 50 genome-scale metabolic reconstructions have been built for a variety of single- and multi- cellular organisms. These reconstructions have enabled a host of computational methods to be leveraged for systems- analysis of metabolism, leading to greater understanding of observed phenotypes. These methods have been sparsely applied to comparisons between multiple […]
Read MoreFunctional integration of a metabolic network model and expression data without arbitrary thresholding
Motivation: Flux balance analysis (FBA) has been used extensively to analyze genome-scale, constraint-based models of metabolism in a variety of organisms. The predictive accuracy of such models has recently been improved through the integration of high-throughput expression profiles of metabolic genes and proteins. However, extensions of FBA often require that such data be discretized a […]
Read MoreMetabolic network analysis integrated with transcript verification for sequenced genomes
With sequencing of thousands of organisms completed or in progress, there is a growing need to integrate gene prediction with metabolic network analysis. Using Chlamydomonas reinhardtii as a model, we describe a systems-level methodology bridging metabolic network reconstruction with experimental verification of enzyme encoding open reading frames. Our quantitative and predictive metabolic model and its […]
Read MoreFunctional States of the Genome-Scale Escherichia Coli Transcriptional Regulatory System
A transcriptional regulatory network (TRN) constitutes the collection of regulatory rules that link environmental cues to the transcription state of a cell’s genome. We recently proposed a matrix formalism that quantitatively represents a system of such rules (a transcriptional regulatory system [TRS]) and allows systemic characterization of TRS properties. The matrix formalism not only allows […]
Read MoreProteomic and network analysis characterize stage-specific metabolism in Trypanosoma cruzi
Background: Trypanosoma cruzi is a Kinetoplastid parasite of humans and is the cause of Chagas disease, a potentially lethal condition affecting the cardiovascular, gastrointestinal, and nervous systems of the human host. Constraint-based modeling has emerged in the last decade as a useful approach to integrating genomic and other high-throughput data sets with more traditional, experimental […]
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