ArticleBMC systems biology2011
Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction.
Article in BMC systems biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Revealing interactions between microbes, metabolites, and dietary compounds using genome-scale analysis.Microbiome · 2026Article
- Article
- The Essential Genome of Burkholderia cenocepacia H111.Journal of bacteriology · 2017Article
- FOXO Transcriptional Factors and Long-Term Living.Oxidative medicine and cellular longevity · 2017Review
- PSAMM: A Portable System for the Analysis of Metabolic Models.PLoS computational biology · 2016Article
- Article
- Burkholderia cenocepacia and Salmonella enterica ArnT proteins that transfer 4-amino-4-deoxy-l-arabinose to lipopolysaccharide share membrane topology and functional amino acids.Scientific reports · 2015Article
- Potential of metabolomics to reveal Burkholderia cepacia complex pathogenesis and antibiotic resistance.Frontiers in microbiology · 2015Review
- Analysis of Genome-scale Expression Network in Four Major Bacterial Residents of Cystic Fibrosis Lung.Current genomics · 2014Article
- Comparative metabolic systems analysis of pathogenic Burkholderia.Journal of bacteriology · 2014Article
- Mechanistic systems modeling to guide drug discovery and development.Drug discovery today · 2013Review
- Predicting new molecular targets for rhein using network pharmacology.BMC systems biology · 2012Article
- A metabolic network approach for the identification and prioritization of antimicrobial drug targets.Trends in microbiology · 2012Review
- Article
- Long-term colonization of the cystic fibrosis lung by Burkholderia cepacia complex bacteria: epidemiology, clonal variation, and genome-wide expression alterations.Frontiers in cellular and infection microbiology · 2011Article
- Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance.mSystemsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBurkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF) or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets.
resultsWe reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets.
conclusionsAs the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.