ArticleJournal of bacteriology2010
Metabolic network analysis of Pseudomonas aeruginosa during chronic cystic fibrosis lung infection.
Article in Journal of bacteriology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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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.
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Who cites it
57 citing papers in PubMed, 95 citations in OpenAlex.
- Trial
- Article
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- Article
- Machine learning from Pseudomonas aeruginosa transcriptomes identifies independently modulated sets of genes associated with known transcriptional regulators.Nucleic acids research · 2022Article
- A Computational Framework for Studying Gut-Brain Axis in Autism Spectrum Disorder.Frontiers in physiology · 2022Article
- Personalized Genome-Scale Metabolic Models Identify Targets of Redox Metabolism in Radiation-Resistant Tumors.Cell systems · 2021Article
- Pseudomonas aeruginosa reverse diauxie is a multidimensional, optimized, resource utilization strategy.Scientific reports · 2021Article
- A Systematic Strategy to Find Potential Therapeutic Targets forFrontiers in molecular biosciences · 2021Article
- Antibiotic resistance: Time of synthesis in a post-genomic age.Computational and structural biotechnology journal · 2021Review
- Multi-scale models of lung fibrosis.Matrix biology : journal of the International Society for Matrix Biology · 2020Review
- Pseudomonad reverse carbon catabolite repression, interspecies metabolite exchange, and consortial division of labor.Cellular and molecular life sciences : CMLS · 2020Review
- FindTargetsWEB: A User-Friendly Tool for Identification of Potential Therapeutic Targets in Metabolic Networks of Bacteria.Frontiers in genetics · 2019Article
- Network-Based Metabolism-Centered Screening of Potential Drug Targets inFrontiers in cellular and infection microbiology · 2019Article
- Genome-scale metabolic modeling of responses to polymyxins in Pseudomonas aeruginosa.GigaScience · 2018Article
- Novel Plasmodium falciparum metabolic network reconstruction identifies shifts associated with clinical antimalarial resistance.BMC genomics · 2017Article
- Managing uncertainty in metabolic network structure and improving predictions using EnsembleFBA.PLoS computational biology · 2017Article
- Chronic obstructive pulmonary disease candidate gene prioritization based on metabolic networks and functional information.PloS one · 2017Article
- Bridging the gap between clinicians and systems biologists: from network biology to translational biomedical research.Journal of translational medicine · 2016Review
- Reactive oxygen species drive evolution of pro-biofilm variants in pathogens by modulating cyclic-di-GMP levels.Open biology · 2016Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
System-level modeling is beginning to be used to decipher high throughput data in the context of disease. In this study, we present an integration of expression microarray data with a genome-scale metabolic reconstruction of Pseudomonas aeruginosa in the context of a chronic cystic fibrosis (CF) lung infection. A genome-scale reconstruction of P. aeruginosa metabolism was tailored to represent the metabolic states of two clonally related lineages of P. aeruginosa isolated from the lungs of a CF patient at different points over a 44-month time course, giving a mechanistic glimpse into how the bacterial metabolism adapts over time in the CF lung. Metabolic capacities were analyzed to determine how tradeoffs between growth and other important cellular processes shift during disease progression. Genes whose knockouts were either significantly growth reducing or lethal in silico were also identified for each time point and serve as hypotheses for future drug targeting efforts specific to the stages of disease progression.
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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.