Bacterial persisters tolerate antibiotic treatment, and underlie the propensity of biofilm infections to relapse. An improved understanding of persister physiology will lead to the development of more effective therapies against biofilm-utilizing pathogens such as Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus aureus. Persister metabolism is of particular importance, as it influences entry into, maintenance of, and exit from this antibiotic-tolerant state. Unfortunately, persisters are a minor, transient subpopulation whose physiology is easily obscured by more abundant phenotypes (e.g., viable but non-culturable cells (VBNCs)). Recent evidence suggests that current persister isolation techniques provide samples with many more VBNCs than persisters. Without improved isolation techniques, the distinguishing feature between VBNCs and persisters, growth- resumption on standard media, must be used to characterize persister physiology. Here we propose to develop a method to elucidate the metabolic abilities of persisters from survival data, and thus circumvent the present isolation difficulties. Recent work has demonstrated that persisters can catabolize carbon sources, remain non-replicative, and yet become susceptible to aminoglycosides. Here we propose to harness this phenomenon to chart the metabolic capabilities of persisters. To accomplish this goal, we will develop a rapid AG potentiation assay, develop a computational approach to analyze the resulting survival data and direct further experimentation, and finally, demonstrate the utility of our approach by charting the metabolic abilities of three persister populations. To develop a rapid AG potentiation assay, we will use phenotype arrays (each well contains a different nutrient) to simultaneously measure AG potentiation and the necessary controls from hundreds of separate nutrients. To analyze the resulting survival data, we will use mixed integer linear optimization to generate an ensemble of non-redundant minimal metabolic pathways capable of explaining the data. These pathways will be clustered, and the reactions that most significantly discriminate between competing clusters will be experimentally perturbed to determine the metabolic capabilities of persisters. To demonstrate the utility of our approach, we will use our technique to study the metabolic abilities of three persister populations: exponential phase persisters tolerant to ofloxacin, exponential phase persisters tolerant to ampicillin, and stationary persisters tolerant to ofloxacin. Results from this proposal will fill fundamental knowledge gaps in persister metabolism, identify new avenues for therapeutic intervention through disruption of persister maintenance or enhancement of persister awakening, and impact the fields of network biology, microbiology, and infectious disease.

Public Health Relevance

Sixty-five percent of hospital-treated infections are caused by biofilms, and bacterial persisters are responsible for the propensity of these films to cause chronic and recurrent infections. Persisters are bacteria that have a non-inherited ability to tolerate antibiotic treatment, and the physiology of these survivors is ill-defined. Persister metabolism is of particular importance, as it influences entry into, maintenance of, and exit from this antibiotic tolerant state. The research proposed here seeks to identify the metabolic capabilities of persisters in order to develop novel therapeutics against them.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21AI105342-01
Application #
8486859
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Korpela, Jukka K
Project Start
2013-02-01
Project End
2015-01-31
Budget Start
2013-02-01
Budget End
2014-01-31
Support Year
1
Fiscal Year
2013
Total Cost
$188,660
Indirect Cost
$63,660
Name
Princeton University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
002484665
City
Princeton
State
NJ
Country
United States
Zip Code
08544
Robinson, Jonathan L; Adolfsen, Kristin J; Brynildsen, Mark P (2014) Deciphering nitric oxide stress in bacteria with quantitative modeling. Curr Opin Microbiol 19:16-24
Amato, Stephanie M; Fazen, Christopher H; Henry, Theresa C et al. (2014) The role of metabolism in bacterial persistence. Front Microbiol 5:70
Orman, Mehmet A; Brynildsen, Mark P (2013) Dormancy is not necessary or sufficient for bacterial persistence. Antimicrob Agents Chemother 57:3230-9
Orman, Mehmet A; Brynildsen, Mark P (2013) Establishment of a method to rapidly assay bacterial persister metabolism. Antimicrob Agents Chemother 57:4398-409