Computational tool to assess superbug's response to antibiotics
A collaboration led by Monash University scientists has resulted in the creation of a powerful tool for antimicrobial pharmacological research into one of the world’s most dangerous superbugs, Pseudomonas aeruginosa.
P. aeruginosa causes life-threatening infectious diseases worldwide and is increasingly resistant to all antibiotics, including the polymyxins used as a last-resort defence. The World Health Organization (WHO) lists P. aeruginosa as a ‘Critical’ priority and is urging the development of novel antibiotics to combat it.
With this in mind, a team led by Monash Professor Jian Li developed a genome-scale metabolic model (GSMM) revealing the complex responses of P. aeruginosa to antibiotic treatments. Described in the journal GigaScience, the computational model allows scientists to decipher the complex interplay of metabolic pathways involved in the bacterial responses to antibiotics.
First author Dr Yan Zhu said the GSMM model, called iPAO1, represents the most comprehensive metabolic reconstruction for P. aeruginosa to date. Understanding how P. aeruginosa alters its metabolism will allow optimised antibacterial treatments.
“The model accounts for the largest number of reactions and metabolites in this superbug so far and enables accurate predictions of bacterial metabolism,” he said.
“It can be employed as a tool, similar to the computer-aided design software frequently used by engineers, to facilitate antibiotic treatment.”
Professor Li added that the computational tool provides a shortcut to time-consuming and costly experimental work, saying, “We hope we can use this model as a systems platform for antimicrobial pharmacology.”
The researchers believe the tool could be used to facilitate antibiotic combination therapies for difficult-to-treat infections and provide valuable mechanistic insight for drug discovery. “Hopefully,” said Professor Li, “such a computational approach can paradigm shift current antimicrobial pharmacology.”
Computational biology is a new direction for Professor Li, who is recognised globally for his groundbreaking antimicrobial work into polymyxins and multidrug-resistant superbugs. Along with Dr Zhu, he collaborated on the model with Professor Trevor Lithgow and Dr Jiangning Song from the Monash Biomedicine Discovery Institute (BDI), Professor Falk Schreiber from the University of Konstanz, Germany (then working in Monash’s Faculty of Information Technology), and others.
“The team is the first to employ a GSMM to investigate antibiotic concentration-effect relationships,” said Dr Zhu.
The Australian-designed technology will enable young people living with haemophilia to view the...
ALLSorts software uses RNA sequencing data to identify a patient's subtype of acute...
AI systems can diagnose prostate cancer biopsies with the same level of accuracy as specialist...