Genome-scale model of Pseudomonas aeruginosa metabolism unveils virulence and drug potentiation.

Pseudomonas aeruginosa is one of the leading causes of hospital-acquired infections. To decipher the metabolic mechanisms associated with virulence and antibiotic resistance, we have developed an updated genome-scale model (GEM) of P. aeruginosa. The model (iSD1509) is an extensively curated, three-compartment, and mass-and-charge balanced BiGG model containing 1509 genes, the largest gene content for any P. aeruginosa GEM to date. It is the most accurate with prediction accuracies as high as 92.4% (gene essentiality) and 93.5% (substrate utilization). In iSD1509, we newly added a recently discovered pathway for ubiquinone-9 biosynthesis which is required for anaerobic growth. We used a modified iSD1509 to demonstrate the role of virulence factor (phenazines) in the pathogen survival within biofilm/oxygen-limited condition. Further, the model can mechanistically explain the overproduction of a drug susceptibility biomarker in the P. aeruginosa mutants. Finally, we use iSD1509 to demonstrate the drug potentiation by metabolite supplementation, and elucidate the mechanisms behind the phenotype, which agree with experimental results.

Inferring statin-induced gene regulatory relationships in primary human hepatocytes.

MOTIVATION: Statins are the most widely used cholesterol-lowering drugs. The primary target of statins is HMG-CoA reductase, a key enzyme in cholesterol synthesis. However, statins elicit pleitropic responses including beneficial as well as adverse effects in the liver or other organs. Today, the regulatory mechanisms that cause these pleiotropic effects are not sufficiently understood. RESULTS: In this work, genome-wide RNA expression changes in primary human hepatocytes of six individuals were measured at up to six time points upon atorvastatin treatment. A computational analysis workflow was applied to reconstruct regulatory mechanisms based on these drug-response data and available knowledge about transcription factor (TF) binding specificities and protein-drug interactions. Several previously unknown TFs were predicted to be involved in atorvastatin-responsive gene expression. The novel relationships of nuclear receptors NR2C2 and PPARA on CYP3A4 were successfully validated in wet-lab experiments. AVAILABILITY: Microarray data are available at the Gene Expression Omnibus (GEO) database at www.ncbi.nlm.nih.gov/geo/, under accession number GSE29868. CONTACT: andreas.zell@uni-tuebingen.de; adrian.schroeder@uni-tuebingen.de SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.