New Diagnostic Tool Could Transform Detection of Dangerous Hospital Fungus
Digital SHERLOCK Enables Faster, More Accurate Detection of Drug-resistant Candida auris in Health Care Settings
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The yeast fungus Candida auris (C. auris), which spreads easily and can survive on surfaces for months, has emerged as a major global health threat in health care settings, a challenge made even greater by its resistance to multiple drugs. A new diagnostic platform, digital SHERLOCK (dSHERLOCK), developed by a team of researchers from MIT and Harvard, as well as Vishnu Chaturvedi, Ph.D., professor of pathology, microbiology, and immunology and of medicine at New York Medical College, and described in a recent study in Nature Biomedical Engineering, has the potential to transform how C. auris is diagnosed.
“Today’s diagnostic tests often depend on centralized labs, costly equipment, and turnaround times that can take several days, delays that can slow down crucial decisions about infection control and treatment,” says Dr. Chaturvedi. “Just as concerning, early or hard-to-detect drug resistance can be missed by standard testing methods. In our study, we address these gaps by developing a fast, portable, and accurate diagnostic tool designed for real-world clinical and public health use.”
In the study, dSHERLOCK was shown to detect C. auris with high specificity in as little as 20 minutes, delivering precise quantification of the fungal load and genetic resistance markers within 40 minutes. Unlike traditional laboratory methods that are often slow and require specialized personnel, dSHERLOCK utilizes machine learning and real-time reaction monitoring to deliver highly accurate results directly from minimally processed patient swabs. Designed with global accessibility in mind, the platform uses commercially available materials and standard laboratory equipment, making it a scalable tool for hospitals worldwide to monitor, treat, and contain C. auris.
“Together, these findings demonstrate a single platform capable of answering three clinically relevant questions at once: Is C. auris present in the clinical sample? How much fungus is there? Is there any evidence of C. auris resistance?” says Dr. Chaturvedi. “In practical terms, clinicians could receive actionable diagnostic information during a single clinical shift, rather than days later.”
According to Dr. Chaturvedi, several important questions now remain: What level of drug resistance should prompt doctors to change a patient’s treatment plan? Does the test work reliably across a wider range of patients and health care settings? And can this same testing approach be adapted to detect drug resistance in other fungi, bacteria, or viruses?
“The clinical and public health implications of this platform are profound, particularly for managing outbreaks and optimizing patient care,” says Dr. Chaturvedi.
