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Data released on February 22, 2018

Supporting data for "Genome-scale metabolic modelling of responses to polymyxins in Pseudomonas aeruginosa."

Zhu, Y; Czauderna, T; Zhao, J; Klapperstueck, M; Maifiah, M, H; Han, M, L; Lu, J; Sommer, B; Velkov, T; Lithgow, T; Song, J; Schreiber, F; Li, J (2018): Supporting data for "Genome-scale metabolic modelling of responses to polymyxins in Pseudomonas aeruginosa." GigaScience Database. http://dx.doi.org/10.5524/100414 RIS BibTeX Text

Pseudomonas aeruginosa often causes multidrug-resistant infections in immunocompromised patients and polymyxins are often used as the last-line therapy. Alarmingly, resistance to polymyxins has been increasingly reported worldwide recently. To rescue this last-resort class of antibiotics, it is necessary to systematically understand how P. aeruginosa alters its metabolism in response to polymyxin treatment, thereby facilitating the development of effective therapies. To this end, a genome-scale metabolic model (GSMM) was employed to analyse bacterial metabolic changes at the systems level.
A high-quality GSMM iPAO1 was constructed for P. aeruginosa PAO1 for antimicrobial pharmacological research. Model iPAO1 encompasses an additional periplasmic compartment and contains 3,022 metabolites, 4,265 reactions and 1,458 genes in total. Growth prediction on 190 carbon and 95 nitrogen sources achieved an accuracy of 89.1%, outperforming all reported P. aeruginosa models. Notably, prediction of the essential genes for growth achieved a high accuracy of 87.9%. Metabolic simulation showed that lipid A modifications associated with polymyxin resistance exerted a limited impact on bacterial growth and metabolism, but remarkably changed the physiochemical properties of the outer membrane. Modelling with transcriptomic constraints revealed a broad range of metabolic responses to polymyxin treatment, including reduced biomass synthesis, upregulated amino acids catabolism, induced flux through the tricarboxylic acid cycle, and increased redox turnover.
Overall, iPAO1 represents the most comprehensive GSMM constructed to date for Pseudomonas. It provides a powerful systems pharmacology platform for the elucidation of complex killing mechanisms of antibiotics.

Contact Submitter

Accessions (data included in GigaDB):

PROJECT: PRJNA414673
MTBLS: MTBLS630

Keywords:

genome-scale metabolic model pseudomonas aeruginosa outer membrane polymyxin lipid a modification 

Genomic, Transcriptomic

http://gigadb.org/images/data/cropped/100414.jpg

Funding:

  • Funding body - Mosash University
  • Awardee - Jian Li
  • Funding body - National Health and Medical Research Council
  • Award ID - APP1127948
  • Awardee - Jian Li
  • Funding body - National Institute of Allergy and Infectious Diseases
  • Award ID - R01 AI111965
  • Awardee - Jian Li
  • Funding body - National Health and Medical Research Council
  • Award ID - APP1086825
  • Awardee - Tony Velko
  • Funding body - National Health and Medical Research Council
  • Award ID - APP1063069
  • Awardee - Jian Li
  • Funding body - Australian Research Councill
  • Award ID - FL130100038
  • Awardee - Trevor Lithgow

Samples: Table Settings

Columns:

Common Name
Scienfic Name
Sample Attributes
Taxonomic ID
Genbank Name

Sample IDTaxonomic IDCommon NameGenbank NameScientific NameSample Attributes
SAMN07807133208964  Pseudomonas aeruginosa PAO1 Strain:PAO1
Description:RNA extract from Pseudomonas aeruginos...
Analyte type:RNA
...
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Displaying 1-1 of 1 Sample(s).

Files: (FTP site) Table Settings

Columns:

File Description
Sample ID
Data Type
File Format
Size
Release Date
Download Link
File Attributes

File NameSample IDData TypeFile FormatSizeRelease Date 
Mass Spectrometry dataTAR212.84 MB2018-02-20
Mass Spectrometry dataTAR256.19 MB2018-02-20
annotationTAR1.37 GB2018-02-20
Mass Spectrometry dataTAR641.14 MB2018-02-20
ReadmeTEXT2.52 KB2018-02-20
MD5sumTEXT0.07 KB2018-02-20
scriptUNKNOWN2.38 KB2018-02-20
Displaying 1-7 of 7 File(s).

History:

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