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DNA Melting Curves Could Speed Blood-Borne Pathogen Detection

Scientists from the University of California, San Diego (UCSD), and elsewhere have described a method of detecting blood-borne pathogens faster and more accurately than traditional blood cultures. The method, called digital DNA melting analysis, produces results in under six hours, much shorter than traditional cultures which can require 15 hours to several days depending on the pathogen. 

Details of the method and results from a clinical pilot using blood samples from pediatric patients are provided in the Journal of Molecular Diagnostics in a paper titled, “Universal digital high resolution melt analysis for the diagnosis of bacteremia.” Results from the pilot study showed that their DNA melting approach matched results of blood cultures collected for sepsis testing. They were also able to quantify how much of the pathogen was present in the samples using DNA melting. 

The approach to testing relies on universal digital high-resolution DNA melting (U-dHRM), where DNA is heated until it splits—at about 120 to 190 degrees—and then analyzed. Each sequence has a specific signature during melting, which can be detected with a special dye. The dye causes the unwinding process to give off fluorescent light, creating a melting curve—the unique signature for each type of pathogen.

Those signatures are analyzed by a machine learning algorithm which determines the type of DNA present and identifies the pathogens present. Specifically, the algorithm can reliably detect the difference between melt curves from the pathogens and background noise by matching the curves to a database of known DNA melt curves. It’s also able to detect curves created by organisms that are not in this database, which could show up in a sample if it contains rare or emerging pathogens.   

The current study marks “the first time this method has been tested on whole blood from patients suspected of having sepsis. So this study is a more realistic preview of how the technology could perform in real clinical scenarios,” said Stephanie Fraley, PhD, the paper’s senior author and a professor in UCSD’s department of bioengineering. 

Sepsis-related complications account for one out of every five deaths worldwide. About 41% of these deaths occur in children. Early detection is critical for sepsis survival as mortality risk rises rapidly as the infection goes undiagnosed or improperly treated. Physicians typically treat sepsis cases with antibiotics while waiting for results from blood cultures. 

“The bottom line is, we’re not treating based on evidence,” Fraley said. “And the more we treat without evidence, the more we can cause unintended problems. Sometimes, we’re treating patients who have fungal or viral infections with antibacterials. This can cause antibiotic resistance and alter the patient’s microbiome in a significant way.” 

For the pilot, the researchers collected a milliliter of blood from 17 infants and toddlers along with samples for blood cultures for comparison. The results from DNA melting not only matched the results from blood cultures; the method is also much less likely to generate false positives compared to other types of tests that rely on nucleic acid amplification and next-generation sequencing.

“Our test has incorporated sample preparation processes, assay design techniques, and algorithms that ensure we only detect DNA from intact organisms, which is clinically relevant,” Mridu Sinha, a former PhD student in Fraley’s lab and one of the authors on the paper, noted. 

For their next steps, the researchers plan to conduct a broader clinical study, as well as expand the method to adult patients. Fraley and Sinha have since licensed the U-dHRM technology from UCSD and co-founded the startup Melio to commercialize it. They plan to work first on testing for newborns.

Reference Abstract

Fast and accurate diagnosis of bloodstream infection is necessary to inform treatment decisions for septic patients, who face hourly increases in mortality risk. Blood culture remains the gold standard test but typically requires approximately 15 hours to detect the presence of a pathogen. Here, the potential for universal digital high-resolution melt (U-dHRM) analysis to accomplish faster broad-based bacterial detection, load quantification, and species-level identification directly from whole blood is assessed. Analytical validation studies demonstrated strong agreement between U-dHRM load measurement and quantitative blood culture, indicating that U-dHRM detection is highly specific to intact organisms. In a pilot clinical study of 17 whole blood samples from pediatric patients undergoing simultaneous blood culture testing, U-dHRM achieved 100% concordance when compared with blood culture and 88% concordance when compared with clinical adjudication. Moreover, U-dHRM identified the causative pathogen to the species level in all cases where the organism was represented in the melt curve database. These results were achieved with a 1-mL sample input and sample-to-answer time of 6 hours. Overall, this pilot study suggests that U-dHRM may be a promising method to address the challenges of quickly and accurately diagnosing a bloodstream infection.

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