As highlighted in the 'Bad Bugs, No Drugs' campaign by the Infectious Diseases Society of America, There simply aren't enough new drugs in the pharmaceutical pipeline to keep pace with drug-resistant bacterial infections, so-called 'superbugs'. Numerous hospitals worldwide have experienced outbreaks caused by multidrug-resistant (MDR) Pseudomonas aeruginosa, Acinetobacter baumannii and Klebsiella pneumoniae, three of the 6 top-priority dangerous ESKAPE pathogens that require the most urgent attention to discover new antibiotics. Sadly, no novel antibiotics against these Gram-negative 'superbugs' will be available for many years to come. Polymyxins (i.e. polymyxin B and colistin) are now being used as the last-line therapy for these very problematic MDR pathogens. Most unfortunately, the emergence of polymyxin resistance has been increasingly reported recently. In essence, resistance to polymyxins implies a total lack of antibiotics for treatment of life-threatening infections caused by these pandrug-resistant (PDR) Gram-negative bacteria. Research Design: This project will apply systems pharmacology to antibiotic pharmacokinetics/pharmacodynamics (PK/PD) to identify novel polymyxin combinations with FDA-approved nonantibiotic drugs against PDR P. aeruginosa, A. baumannii and K. pneumoniae. Our over-arching hypothesis is that the identified polymyxin-nonantibiotic combinations will synergistically kill Gram-negative 'superbugs' with minimal development of resistance, and integration of systems pharmacology with antimicrobial PK/PD modeling will elucidate the underlying mechanism(s) of the synergistic interaction between host-pathogen-drug.
Our specific aims are to: (1) Identify novel polymyxin-nonantibiotic combinations against pandrug-resistant P. aeruginosa, A. baumannii and K. pneumoniae; (2) Investigate the in vitro PK/PD of active polymyxin-nonantibiotic combinations; (3) Evaluate the synergistic killing and suppression of polymyxin resistance by the active combinations over 2-week treatment using hollow fiber infection model and conduct omics studies; (4) Demonstrate proof-of-concept for the most active combinations using mouse infection models and conduct integrated omics studies to understand the host-pathogen-drug interactions; and (5) Conduct systems pharmacology network analysis and PK/PD mathematical modeling on the polymyxin- nonantibiotic combinations. Transcriptomics, proteomics and metabolomics will be utilized to investigate the interaction between host, pathogen and drug. Together, these studies will identify the best polymyxin-nonantibiotic combination (plus one backup) for further pharmacological evaluations. Significance: This project holds great promise for development of novel polymyxin combinations. As all drugs have already been approved by FDA, our multi-disciplinary approach will provide a fast-track and cost-effective solution to combat these very problematic Gram-negative 'superbugs'. Overall, this project targets the urgent global unmet medical need, lack of new antibiotics.

Public Health Relevance

The world is facing an enormous and growing threat from the emergence of bacterial 'superbugs' Pseudomonas aeruginosa, Acinetobacter baumannii and Klebsiella pneumoniae that are resistant to all antibiotics, while no novel antibiotics are in current drug discovery pipeline. As described in the 'Bad Bugs, No Drugs' paper published by the Infectious Diseases Society of America, 'as antibiotic discovery stagnates, a public health crisis brews'. This project will employ antimicrobial PK/PD and systems pharmacology to develop novel polymyxin combinations and responds to the recent global call for discovery of new antibiotics: The 10 x '20 Initiative.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI111965-05
Application #
9459199
Study Section
Special Emphasis Panel (ZAI1)
Program Officer
Xu, Zuoyu
Project Start
2014-04-01
Project End
2019-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
5
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Monash University
Department
Type
DUNS #
753252691
City
Melbourne
State
Country
Australia
Zip Code
3800
Xu, Ying; Song, Jiangning; Wilson, Campbell et al. (2018) PhosContext2vec: a distributed representation of residue-level sequence contexts and its application to general and kinase-specific phosphorylation site prediction. Sci Rep 8:8240
Song, Jiangning; Li, Fuyi; Leier, André et al. (2018) PROSPERous: high-throughput prediction of substrate cleavage sites for 90 proteases with improved accuracy. Bioinformatics 34:684-687
Wang, Jiawei; Yang, Bingjiao; Leier, André et al. (2018) Bastion6: a bioinformatics approach for accurate prediction of type VI secreted effectors. Bioinformatics 34:2546-2555
Azad, Mohammad A K; Sivanesan, Sivashangarie; Wang, Jiping et al. (2018) Methionine Ameliorates Polymyxin-Induced Nephrotoxicity by Attenuating Cellular Oxidative Stress. Antimicrob Agents Chemother 62:
Tran, Thien B; Wang, Jiping; Doi, Yohei et al. (2018) Novel Polymyxin Combination With Antineoplastic Mitotane Improved the Bacterial Killing Against Polymyxin-Resistant Multidrug-Resistant Gram-Negative Pathogens. Front Microbiol 9:721
Dai, Chongshan; Xiao, Xilong; Li, Daowen et al. (2018) Chloroquine ameliorates carbon tetrachloride-induced acute liver injury in mice via the concomitant inhibition of inflammation and induction of apoptosis. Cell Death Dis 9:1164
Lin, Yu-Wei; Yu, Heidi H; Zhao, Jinxin et al. (2018) Polymyxin B in Combination with Enrofloxacin Exerts Synergistic Killing against Extensively Drug-Resistant Pseudomonas aeruginosa. Antimicrob Agents Chemother 62:
Shetty, Nivedita; Ahn, Patricia; Park, Heejun et al. (2018) Improved Physical Stability and Aerosolization of Inhalable Amorphous Ciprofloxacin Powder Formulations by Incorporating Synergistic Colistin. Mol Pharm 15:4004-4020
Huang, Jiayuan; Zhu, Yan; Han, Mei-Ling et al. (2018) Comparative analysis of phosphoethanolamine transferases involved in polymyxin resistance across 10 clinically relevant Gram-negative bacteria. Int J Antimicrob Agents 51:586-593
Wang, Huilin; Feng, Liubin; Webb, Geoffrey I et al. (2018) Critical evaluation of bioinformatics tools for the prediction of protein crystallization propensity. Brief Bioinform 19:838-852

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