Logo Logo
  • Home
  • Our Team Members
  • Publications
  • Contact

More Info

  • Email papinlab@virgina.edu
  • Phone Office: (434) 924-8195 Computational lab: (434) 982-6267 Wet lab: (434) 924-8640
  • Location 415 Lane Road, Room 2041 Charlottesville, VA 22903

Related Links

  • PubMed
    Aptekawroclaw.com
  • UVA Engineering

Connect With Us

Integrated Experimental and Computational Analyses Reveal Differential Metabolic Functionality in Antibiotic-Resistant Pseudomonas aeruginosa

  • Home
  • Blog Details
January 7 2019
  • Published Works

Cell Syst. 2019 Jan 23;8(1):3-14.e3. doi: 10.1016/j.cels.2018.12.002. Epub 2019 Jan 2.

ABSTRACT

Metabolic adaptations accompanying the development of antibiotic resistance in bacteria remain poorly understood. To study this relationship, we profiled the growth of lab-evolved antibiotic-resistant lineages of the opportunistic pathogen Pseudomonas aeruginosa across 190 unique carbon sources. Our data revealed that the evolution of antibiotic resistance resulted in systems-level changes to growth dynamics and metabolic phenotype. A genome-scale metabolic network reconstruction of P. aeruginosa was paired with whole-genome sequencing data to predict genes contributing to observed changes in metabolism. We experimentally validated computational predictions to identify mutations in resistant P. aeruginosa affecting loss of catabolic function. Finally, we found a shared metabolic phenotype between lab-evolved P. aeruginosa and clinical isolates with similar mutational landscapes. Our results build upon previous knowledge of antibiotic-induced metabolic adaptation and provide a framework for the identification of metabolic limitations in antibiotic-resistant pathogens.

PMID:30611675 | PMC:PMC6345604 | DOI:10.1016/j.cels.2018.12.002

Previous Post Next Post

Recent Posts

  • Internal Grant Review: A Pre-Submission Program for Early-Career Clinical and Translational Researchers
  • Integrative genome-scale metabolic model of GABAergic neurons reveals metabolic signatures across the mild cognitive impairment – Alzheimer disease continuum
  • Benchmarking biochemical networks generated by large language models
  • Integrating multi-omics data with network modeling to characterize Pseudomonas aeruginosa persister cell metabolism
  • Mucin-induced metabolic reprogramming in Pseudomonas aeruginosa clinical isolates
Logo

Computational Systems Biology Laboratory; The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia.

Related Links

  • PubMed
    Aptekawroclaw.com
  • UVA Engineering

Contact Info

The research group of Dr. Jason Papin in the Department of Biomedical Engineering at the University of Virginia

  • Email: papinlab@virginia.edu
  • Phone (434) 924-8195

  • Home
  • Our Team Members
  • Publications
  • Contact