Description
04 April 2018

Antimicrobial resistant ‘superbugs’ have an arsenal of molecular weapons designed to help them survive the body’s immune defences. Now a collaboration led by Monash Biomedicine Discovery Institute (BDI) researchers has developed a new computational tool that may help disarm a key part of this weaponry.
‘Bastion6’ can accurately predict deadly proteins that are injected into human cells by what’s called the ‘type 6 secretion system’ (T6SS) in bacteria. These secreted proteins – small molecules called ‘effectors’ – play a vital role in the survival of bacterial populations, including the deadly gram-negative bacteria that are increasingly resisting antibiotics.
Antimicrobial resistance is a global problem.
Until now, there was no universal method available to predict T6SS secreted proteins and very few of them were known.
The study, which was published in the leading journal Bioinformatics on 4 April, was led by senior authors Professor Trevor Lithgow from the Department of Microbiology and Dr Jiangning Song from the Department of Biochemistry & Molecular Biology.
First author, PhD student Jiawei Wang from the Lithgow lab, said the Bastion6 paper had already generated wide interest since its informal publishing on 14 March, with its web server receiving more than 1000 visits across 17 countries.
“Bastion6 can be viewed as a milestone in our secreted effector identification project, and is a natural result of more than two years’ work in a great team with international support,” Mr Wang said.
Mr Wang said the study, which involved 54,212 protein sequences, identified 94 effector candidates that can now be investigated further. The publicly accessible Bastion6 server could help users perform preliminary screenings of potential type 6 secreted effectors for further experimental validation by using its prediction function.
“It’s very important to understand and identify the effectors, but to date experimental validation has been labor-intensive and time-consuming, making it impossible to directly identify effectors from genome-scale protein sequences,” he said.
Professor Lithgow expanded on Mr Wang’s comments.
“Knowing the identity of the effectors, and thereby understanding what they are doing to immune cells, is the key knowledge to provide ‘immune boost’ treatments to circumvent the action of the effectors,” Professor Lithgow said.
Mr Wang was also first author on two previous papers leading up to this study.
“This one is like a mountain, but it’s not the end of the peaks – we still have some ongoing work,” Mr Wang said.
Professor Lithgow spoke highly of Mr Wang’s work on this topic.
“Discovery of secreted effector proteins has been one of the toughest nuts to crack in protein targeting research, and Jiawei has succeeded through very clever use of machine-learning technology,” Professor Lithgow said.
“Jiawei is furthering the Monash BDI vision in two important areas of discovery research: Infection & Immunity and Computational Biology,” he said.
Remarkably, Mr Wang is yet to complete the first year of his PhD.
“My supervisors Professor Lithgow and Dr Song have given me the supervision, support, guidance and freedom to make this progress,” Mr Wang said.
Mr Wang is the recipient of the prestigious Monash Graduate Scholarship awarded to the top-ranked student recruited, university-wide, each year. He also holds the Monash International Postgraduate Research Scholarship and Faculty Postgraduate Excellence Award, as well as having previously won a number of scholarships, awards and achievements in his home country, China.
He is assisting Professor Lithgow in building the computational biology arm of the Wenzhou-Monash BDI Joint Institute, an initiative of the Monash BDI and clinicians and researchers at the Wenzhou Medical University (WMU) and its affiliated hospitals in Zhejiang province, China. Professor Lithgow has been appointed Scientific Director of the new joint WMU-Monash BDI Biomedical Research Centre, where antimicrobial resistance and infection control are in prime focus.
Mr Wang said he was grateful that Monash University had recognised him as a top student and offered him the chance to conduct his doctorate here.
“And for giving me the inspiration to undertake this research,” Mr Wang said.
Read the full paper in Bioinformatics titled Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors.
Period | 4 Apr 2018 |
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Media contributions
1Media contributions
Title New computational tool to defend against the molecular weapons of ‘superbugs’ Media name/outlet Monash Biomedicine Discovery Institute Country/Territory Australia Date 4/04/18 URL https://www.monash.edu/discovery-institute/news-and-events/news/new-computational-tool-to-defend-against-the-molecular-weapons-of-superbugs Persons Jiawei Wang, Jiangning Song, Trevor Lithgow
Keywords
- Bioinformatics
- Computational tool
- Defence
- Superbugs
- Molecular weapon
- Type 6 secretion system
- Bastion6
- Machine learning
Related content
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Outputs
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Bastion6: A bioinformatics approach for accurate prediction of type VI secreted effectors
Research output: Contribution to journal › Article › Research › peer-review