Rapid CRISPR Test Identifies Nontuberculous Mycobacteria Species from Respiratory Samples

These infections may affect as many as 300,000 Americans annually, with five-year mortality approaching 18%. Identifying the causative species typically requires slow culture workflows that can take four to six weeks, prolonging uncertainty and delaying appropriate therapy. To accelerate this process, researchers have developed a CRISPR-based platform that identifies mycobacterial species directly from respiratory samples within hours.

Tulane University (New Orleans, LA, USA) researchers developed CANDI (CRISPR-assisted Nanodroplet Differential Identification) to accelerate species-level diagnosis of NTM lung disease. The platform uses mucus from the lungs and other respiratory fluids to simultaneously test for up to 15 clinically relevant NTM species and subspecies. By design, it provides definitive species identification in a matter of hours, rather than the four to six weeks required by conventional culture-based workflows.

In a study evaluating 230 clinical samples, CANDI correctly identified NTM species and subspecies with 97.3% accuracy. The approach was developed to distinguish among a broad range of environmental mycobacteria that can cause chronic, tuberculosis-like infections, supporting clinicians in selecting appropriate regimens. The authors describe the method and findings in Science Translational Medicine on September 16, 2026.

Because symptoms overlap with tuberculosis and treatment requirements differ, misdiagnosis can delay appropriate care for months. The disease disproportionately affects older adults, people with underlying lung conditions, and immunocompromised patients. Trends also point to higher and increasing prevalence in the southern United States as temperatures and humidity rise, underscoring the need for faster, multiplexed species identification.

The platform’s novelty may enable expansion beyond NTM to other hard-to-diagnose infections, according to the team. Details of the assay and validation were published in Science Translational Medicine on September 16, 2026.

“Diagnosing NTM lung disease is very slow, and patients are left with a significant physical and emotional burden because they don't know the answer or what the treatment plan should be. Clinicians need a faster test that will allow them to accurately identify the specific type of bacteria that is causing the patient's lung disease,” said lead investigator Bo Ning, assistant professor of molecular biology at Tulane University School of Medicine.

“NTM lung disease is becoming more and more common, and the current detection approach is so difficult that patients end up suffering. This new method will help clinicians get patients started on the right treatment faster,” Ning said.

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