The emergence of antimicrobial resistance is one of the most serious health threats to our entire population. Infections from resistant bacteria are now too common, and some pathogens have become resistant to multiple antibiotic classes. The Centers for Disease Control and Prevention (CDC) recently estimated that drug-resistant bacteria account for more than 2 million illnesses and over 23,000 deaths every year in the U.S. With rising rates of drug-resistant infections, there is pressing need for new diagnostic methods that can rapidly determine the most effective therapy for an infection. Unfortunately, the current method for performing antibiotic susceptibility testing (AST) involves growing microorganisms from clinical samples and determining their sensitivity to antibiotics through cell growth. This ?gold standard? technique is extremely time-consuming (minimum 48-72 hours) and can result in significant delays in appropriate therapy, prolonged illness, greater risk of death, inappropriate antibiotic use, and increased spread of resistance. For some infections like gonorrhea, AST is not even performed in the clinic and instead inferred based on treatment failure. In short, it is imperative that new strategies are developed to rapidly diagnose and prevent the amplification of drug resistance. Antibiotic exposure can trigger the expression of a signature set of mRNAs in susceptible microbes in as rapidly as a few minutes, raising the exciting possibility of using RNA detection ? not cell growth ? as a new means for rapid, phenotype-based AST. We will develop innovative RNA sensor technology that evaluates these molecular signatures within a clinically-relevant, low-cost, and easy-to-use diagnostic platform. To achieve this, we will use synthetic biology approaches to engineer highly-sensitive genetic sensors of mRNA. These sensors will be deployed in cell-free expression systems that can be arrayed and freeze-dried onto low-cost, solid-state substrates like paper. The result will be a new class of antibiotic diagnostics with ideal performance, storage, and distribution characteristics. The RNA sensor technology will be developed and validated with high priority bacterial organisms. Notably, we will, for the first time, define RNA signatures of susceptibility for N. gonorrhoeae, which the CDC recently elevated as a major cause for concern in the U.S. and for which AST capabilities do not currently existing in the clinical setting. This work will usher in a new technology for rapidly diagnosing antibiotic resistance, with the potential to transform the management of today's growing antimicrobial resistance problem.

Public Health Relevance

The improper and excessive use of antibiotics in the past decades has led to an alarming increase in antimicrobial resistance. With rising rates of drug-resistant infections, there is pressing need for new diagnostic methods that can rapidly determine the most effective therapy for an infection. We are developing a novel diagnostic system based on rapid molecular sensor technologies to determine antibiotic susceptibilities of bacterial infections.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
NIH Director’s New Innovator Awards (DP2)
Project #
1DP2AI131083-01
Application #
9167953
Study Section
Special Emphasis Panel (ZRG1-MOSS-C (56)R)
Program Officer
Ritchie, Alec
Project Start
2016-09-30
Project End
2021-06-30
Budget Start
2016-09-30
Budget End
2021-06-30
Support Year
1
Fiscal Year
2016
Total Cost
$2,472,375
Indirect Cost
$972,375
Name
Boston University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
049435266
City
Boston
State
MA
Country
United States
Zip Code
02215
Newby, Gregory A; Kiriakov, Szilvia; Hallacli, Erinc et al. (2017) A Genetic Tool to Track Protein Aggregates and Control Prion Inheritance. Cell 171:966-979.e18