The Gram-negative bacteria Acinetobacter baumannii, Pseudomonas aeruginosa and Klebsiella pneumoniae are causing significant problems in the USA and other parts of the world. These bacteria are opportunistic pathogens that cause pneumonia and other serious infections in critically-ill patients and those with impaired immune systems. Because these bacteria are increasingly displaying high levels of resistance to almost all currently available antibiotics and because of the shortage of new antibiotics coming into clinical use, clinicians are often left with little option but to use colistin, which is an antibiotic of the polymyxin class. Colistin first came onto the market nearly 50 years ago and has been used relatively rarely, until recent times. Unfortunately, although the resistance rates to colistin are much lower than for other antibiotics, there is mounting evidence that resistance to colistin is increasing. Since colistin is, in essence, the 'last-line'antibiotic for treatment of many infections, resistance to it implies resistance to virtually all antibiotics. It has become clear that even bacteria that seem to be susceptible to colistin harbor a highly colistin-resistant sub-population. Exposure to colistin leads to death of the susceptible bacteria in the total population, but unfortunately this leads to a situation where the highly colistin-resistant bacteria multiply to much larger numbers. Although two or more antibiotics are often prescribed in an attempt to overcome antibiotic resistance, this has been an empiric clinical practice, based on little or no evidence. The central aim of the present project is to use a series of very systematic studies to identify antibiotics that can be prescribed together with colistin to kill all members of the total bacterial population. The research strategy starts with the novel approach of identifying other antibiotics that are most active against the colistin-resistant sub-population of bacteria, as there is good evidence that the sub-population may be much more susceptible than previously thought to other antibiotics. These experiments are followed by screening of combinations, involving colistin and many other antibiotics, to determine which combinations and relative concentrations result in the highest activity. Then, a systematic series of in vitro studies will be conducted to simulate the conditions of infection and drug concentrations in the human body to devise regimens that optimize the combination regimens (each involving colistin plus another antibiotic) that most effectively kill both the colistin-susceptible and the colistin-resistant bacteria. Finally, once an optimal regimen is determined in vitro, animal studies will be performed to provide proof of concept. Each progressive stage in the research plan provides key information to develop understanding of the combinations and is driven by the development of mathematical mechanistic models to guide the optimization process. The outcome will be identification and optimization of colistin combination regimens to prevent amplification of resistant sub- populations in the very troublesome Gram-negative bacteria above. The world is facing an enormous and growing threat from the emergence of bacteria that are resistant to almost all available antibiotics and in the past two decades there has been a marked decline in discovery of novel antibiotics. 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 highlights the relevance of the current project which aims to preserve the usefulness of colistin through the study of novel approaches in the fight against very difficult to treat infections caused by Gram-negative bacteria to minimize the emergence of resistance.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI079330-02
Application #
7656630
Study Section
Special Emphasis Panel (ZAI1-DDS-M (M1))
Program Officer
Taylor, Christopher E,
Project Start
2008-07-15
Project End
2012-06-30
Budget Start
2009-07-01
Budget End
2010-06-30
Support Year
2
Fiscal Year
2009
Total Cost
$605,890
Indirect Cost
Name
Monash University
Department
Type
DUNS #
753252691
City
Victoria
State
Country
Australia
Zip Code
3800
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