Investigators from Mass General Brigham have found that a method originally designed for cancer detection can also identify and monitor even tiny amounts of SARS-CoV-2 intact viral particles in blood and other fluids from patients with acute COVID-19 infections, creating the potential for guiding future treatment of patients. The research is published in Science Advances.
"During the early days of the pandemic, we wanted to see if our approach for isolating small cancer vesicles could be adapted to isolate SARS-CoV-2 virus from biofluids like blood, stool, and saliva," said co–senior author Shannon L. Stott, PhD, a member of the faculty at the Center for Engineering in Medicine & Surgery at Massachusetts General Hospital (MGH), a founding member of the Mass General Brigham healthcare system. "We quickly built an interdisciplinary team of experts to adapt our technology to push the boundaries of intact virus detection."
Stott and colleagues in her lab, and the lab of Genevieve M. Boland, MD, PhD, surgical director of the Termeer Center for Targeted Therapies at MGH, found that their technique could detect as few as three viral particles in 1 milliliter of blood. When tested in more than 150 samples (103 plasma, 36 saliva, and 29 stool samples) from patients with COVID-19, the method accurately measured virus levels across time, with intact viral particles detected as far out as 50 days after an initial infection.
With clinical needs changing, the ability to serially monitor viral load in this manner has great potential for guiding the treatment of patients with long Covid. This versatile technology could also have widespread applications in viral monitoring for current and future infectious diseases."
Shannon L. Stott, PhD, member of the faculty, Center for Engineering in Medicine & Surgery, Massachusetts General Hospital
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Journal reference:
Rabe, D. C., et al. (2025). Ultrasensitive detection of intact SARS-CoV-2 particles in complex biofluids using microfluidic affinity capture. Science Advances. doi.org/10.1126/sciadv.adh1167.