In the age of superbugs and antibiotic resistance, it is more important than ever for patients with bacterial infections to be diagnosed and treated quickly and correctly. The overuse of broad spectrum antibiotics to treat patients with more resistant infections contributes to the emergence of drug-resistant microbes, which according to the CDC kills 35,000 Americans each year.
Current methods of identifying which drug will kill rare, specific, and dangerous bacterial pathogens takes days of culturing work in lab to yield results. This method of identifying bacteria results in overprescribing common antibiotics to treat sick patients while physicians are awaiting test results, to the point bacteria strains previously susceptible to weaker antibiotics develop resistance. This treatment strategy does not benefit patients.
However, a new diagnostic approach developed by scientists at the Broad Institute of MIT and Harvard and Massachusetts General Hospital (MGH) could help tackle this problem. Called GoPhAST-R, (Genotypic and Phenotypic AST through RNA detection), this newly developed screening assay allows physicians to accurately determine which (if any) antibiotic should be used to treat an infection within hours, instead of days. By saving time in diagnosis, physicians will not resort to “standby” methods of bacterial treatment, and bacterial strains would not have the opportunity to develop resistance to weaker antibiotics. This rapid test could potentially be applied to any bacterial infection and antibiotic.
“The ability to quickly and accurately identify the best antibiotic would greatly improve the care of patients with infection, while ensuring that our arsenal of antibiotics is deployed intelligently and efficiently,” said Dr. Deborah Hung, a core institute member at the Broad and MGH, and who helped lead the development of the test with Dr. Roby Bhattacharyya.
The current gold standard method of antibiotic susceptibility testing (AST) is called “phenotypic” and involves taking bacteria from a patient, growing spores in a petri dish in the presence of various antibiotics, and observing the results in lab to determine which drug can inhibit growth of the microbe. These growth-based assays are accurate, but take several days to return results. Newer “genotypic” methods that search bacterial DNA for mutations known to confer drug resistance are faster but less accurate, because antibiotic resistance can arise from genetic changes that aren’t included in the test. GoPhAST-R combines these two approaches and can provide results faster than both methods.
In their study published in Nature, the team of scientists developing GoPhAST-R found that just minutes after exposure to an antibiotic, drug-resistant and drug-sensitive versions of the bacteria in petri dishes showed distinct patterns of messenger RNA (mRNA) expression, reflecting differences in the activity of their genes. This information conveyed how much the antibiotics were preventing bacterial growth and replication. By looking for mRNA signatures of drug sensitivity, the Go-PhAST-R can quickly identify an organism’s sensitivity to certain drugs, regardless of the underlying genetic roots of resistance.
The scientists then deployed machine-learning algorithms to sequence and identify the mRNA transcripts that best distinguish drug-sensitive from drug-resistant organisms. Integrating this genotypic data with phenotypic expression-based data allows GoPhAST-R to be between 94 to 99% accurate in classifying bacterial strains. The GoPhAST-R assay uses a specialized, next-generation RNA detection platform to determine antibiotic susceptibility less than four hours after bacteria are positively detected in a blood culture, compared to 28-40 hours using standard clinical laboratory methods.
“If it is developed for clinical use, GoPhAST-R could help transform the diagnosis and treatment of infectious diseases, while helping to prevent the further emergence and spread of antibiotic-resistant superbugs,” said Bhattacharyya.
GoPhAST-R can identify susceptibility to three major antibiotic classes in clinical use today — carbapenems, fluoroquinolones, and aminoglycosides, to treat five pathogens that often become drug-resistant: E. coli, Klebsiella pneumoniae, Acinetobacter baumannii, Staphylococcus aureus, and Pseudomonas aeruginosa. GoPhAST-R can also rapidly determine ciprofloxacin susceptibility of pathogens, as demonstrated in patient samples from MGH’s clinical microbiology laboratory.