Scientists develop new computational tool to decipher antibiotic action against ‘superbug’

Clockwise: Professor Jian Li, Dr Yan Zhu, Professor Trevor Lithgow and Dr Jiangning Song.

A multi-disciplinary team led by Monash University’sBiomedicine Discovery Institute (BDI)has created a powerful tool for antimicrobial pharmacological research into one of the world’s most dangerous ‘superbugs’,Pseudomonas aeruginosa.

The research was published today in GigaScience, a premier journal on ‘Big Data’ research from the life and biomedical sciences.

The team, led by Professor Jian Li, developed a genome-scale metabolic model (GSMM) revealing the complex responses of P. aeruginosa to antibiotic treatments. 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.

The computational model allows scientists to decipher the complex interplay of metabolic pathways involved in the bacterial responses to antibiotics. Understanding how P. aeruginosa alters its metabolism will allow optimised antibacterial treatments.

First author Dr Yan Zhu said the GSMM model, called iPAO1, represents the most comprehensive metabolic reconstruction for P. aeruginosa to date.

Professor Li, a world-leading researcher in polymyxin pharmacology, said the computational tool provides a short-cut to time-consuming and costly experimental work.

“We hope we can use this model as a systems platform for antimicrobial pharmacology,” Professor Li said.

It could be used to facilitate antibiotic combination therapies for difficult-to-treat infections and provide valuable mechanistic insight for drug discovery.

“Hopefully, such a computational approach can paradigm shift current antimicrobial pharmacology,” he said.

The model was developed as an interdisciplinary collaboration including Professor Li, Dr Yan Zhu, Professor Trevor Lithgow and Dr Jiangning Song from Monash BDI, and Professor Falk Schreiber (University of Konstanz, Germany) then working in Monash’s Faculty of Information Technology, and others. This research direction was initiated four years ago by a Monash Major Interdisciplinary Research (IDR) Grant and led to an NHMRC project grant in late 2016.

“The model accounts for the largest number of reactions and metabolites in this ‘superbug’ so far and enables accurate predictions of bacterial metabolism,” Dr Zhu said.

“It can be employed as a tool, similar to the Computer-Aided Design software frequently used by engineers, to facilitate antibiotic treatment. The team is the first to employ a GSMM to investigate antibiotic concentration-effect relationships,” he said.

Computational biology, a high priority for the Monash BDI, is a new direction for Professor Li who is recognised globally for his ground-breaking antimicrobial work into polymyxins and multidrug-resistant ‘superbugs’.

Professor Li was responding to a call by Monash University for new IDR projects. IDR is a key pillar of Monash University's Research Strategy.

“I think this is a showcase for IDR; research really needs cross-disciplinary approaches now,” he said.

This research was funded by a Monash Major IDR Grant and an NHMRC Project Grant.


Read the full paper in GigaScience titled Genome-scale metabolic modelling of responses to polymyxins in Pseudomonas aeruginosa.