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Genome-scale metabolic modeling of responses to polymyxins in Pseudomonas aeruginosa

Zhu, Yan and Czauderna, Tobias and Zhao, Jinxin and Klapperstueck, Matthias and Maifiah, Mohd Hafidz Mahamad and Han, Mei-Ling and Lu, Jing and Sommer, Björn and Velkov, Tony and Lithgow, Trevor and Song, Jiangning and Schreiber, Falk and Li, Jian (2018) Genome-scale metabolic modeling of responses to polymyxins in Pseudomonas aeruginosa. GigaScience, 7 (4). pp. 1-18. ISSN 2047-217X

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Background: 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 used to analyze bacterial metabolic changes at the systems level. Findings: A high-quality GSMM iPAO1 was constructed for P. aeruginosa PAO1 for antimicrobial pharmacological research. Model iPAO1 encompasses an additional periplasmic compartment and contains 3022 metabolites, 4265 reactions, and 1458 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 exert a limited impact on bacterial growth and metabolism but remarkably change the physiochemical properties of the outer membrane. Modeling with transcriptomics constraints revealed a broad range of metabolic responses to polymyxin treatment, including reduced biomass synthesis, upregulated amino acid catabolism, induced flux through the tricarboxylic acid cycle, and increased redox turnover. Conclusions: 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.

Item Type: Article (Journal)
Additional Information: 8219/65380
Uncontrolled Keywords: genome-scale metabolic model; Pseudomonas aeruginosa; polymyxin; lipid A modification; outer membrane
Subjects: Q Science > QR Microbiology
R Medicine > RM Therapeutics. Pharmacology
R Medicine > RM Therapeutics. Pharmacology > RM300 Drugs and their action
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): International Institute for Halal Research and Training (INHART)
Depositing User: Dr Mohd Hafidz Mahamad Maifiah
Date Deposited: 27 Aug 2018 16:18
Last Modified: 27 Aug 2018 16:18
URI: http://irep.iium.edu.my/id/eprint/65380

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