A Faster Diagnosis of Infections
Investigators have developed a device that substantially shortens the time needed to detect pathogens that are responsible for health-care-related infections in hospitals and other facilities.
The team of Massachusetts General Hospital (MGH) researchers said the device has shortened the diagnosis time from a couple of days to a matter of hours. Additionally, they said, the device would allow “point-of-care diagnosis,” meaning that it does not require the facilities and expertise available only in hospital laboratories.
“Health-care-associated infections are a major problem that affects more than 600,000 patients each year, more than 10 percent of whom will die, and incurs more $100 billion in related costs,” says Ralph Weissleder, MD, PhD, director of the MGH Center for Systems Biology, Thrall Family Professor of Radiology at Harvard Medical School (HMS) and co-senior author of the report, which appears in the journal Science Advances. “Rapid and efficient diagnosis of the pathogen is a critical first step in choosing the appropriate antibiotic regimen, and this system could provide that information in a physician’s office in less than two hours.”
While considered the gold standard for diagnosing bacterial infections, traditional culture-based diagnosis can take several days and requires specialized equipment, trained laboratory personnel and procedures that vary depending on the particular pathogen. Emerging genetic approaches that identify bacterial species by their nucleic acid sequences are powerful but still require complex equipment and workflows, restricting such testing to specialized hospital laboratories.
The system developed by the MGH team, dubbed PAD for Polarization Anisotropy Diagnostics, allows for accurate genetic testing in a simple device. Bacterial RNA is extracted from a sample in a small, disposable plastic cartridge. Following polymerase chain reaction amplification of the RNA, the material is loaded into a 2-cm plastic cube containing optical components that detect target RNAs based on the response to a light signal of sequence-specific detection probes. These optical cubes are placed on an electronic base station that transmits data to a smartphone or computer where the results can be displayed.