Innovative CRISPR-Based Mouth Swab Test Promises Easier Tuberculosis Detection

A revolutionary CRISPR-based mouth swab test developed by Tulane University offers a faster, simpler, and non-invasive method for tuberculosis detection, enabling wider community screening and early diagnosis.
Researchers at Tulane University have developed a groundbreaking tuberculosis (TB) testing method utilizing an enhanced CRISPR-based assay that can detect TB from a simple tongue swab. This advancement has the potential to revolutionize TB screening by enabling easier, faster, and more accessible testing, especially in low-resource settings. Traditional TB diagnostics rely on sputum samples, which can be difficult to collect, particularly in children, HIV patients, and individuals with extrapulmonary TB. These limitations have resulted in an estimated 4 million undiagnosed cases annually.
To address this challenge, Tulane scientists refined their CRISPR assay to detect very low levels of TB bacteria in various samples, including stool, spinal fluid, and especially tongue swabs. In clinical evaluations, the new test demonstrated significantly improved detection rates, with 74% sensitivity in tongue swabs compared to 56% for conventional methods. It showed high accuracy across different sample types, such as respiratory specimens, pediatric stool, and adult spinal fluid, making it highly suitable for vulnerable populations.
The innovative test, called ActCRISPR-TB, amplifies and detects TB DNA rapidly, providing results in under an hour. It employs a simple "one pot" process, akin to COVID-19 rapid tests, where a swab sample is added to a pre-loaded tube with reagents. After incubation, color changes on the test strip indicate the presence of TB bacteria. This streamlined approach eliminates the need for specialized lab equipment or trained medical staff, opening new avenues for large-scale community screening.
This development aligns with efforts to move TB diagnostics beyond traditional methods. The research highlights the importance of accessible, non-invasive testing tools that can be deployed in remote areas, potentially reducing the number of undiagnosed cases. Tuane researchers also aim to incorporate artificial intelligence for resistance testing and further speed up diagnosis, forming a comprehensive strategy to combat TB worldwide.
"To end TB, we must deploy tools that can reach out to the communities where the disease spreads most," stated Dr. Tony Hu, the study’s lead author. The study, published in Nature Communications, marks a significant step toward more effective TB detection and treatment, ultimately aiming to save millions of lives.
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