A rapid CRISPR-based nanodroplet assay enables direct clinical identification of mycobacteria species
The global incidence and mortality of nontuberculous mycobacterial infections have risen sharply with population aging. In some regions, they are now surpassing Mycobacterium tuberculosis complex infections, imposing a substantial clinical and economic burden. Because nontuberous mycobacteria exhibit species-level heterogeneity and require prolonged culture for identification, their diagnosis remains slow and is frequently inaccurate. Here, we describe a multiplexed clustered regularly interspaced short palindromic repeats (CRISPR)–assisted nanodroplet differential identification (CANDI) diagnostic platform that integrates species-agnostic target amplification with species-specific CRISPR-associated protein 12a (Cas12a) detection in fluorescence-barcoded nanodroplets. By spatially compartmentalizing CRISPR reactions into color-encoded nanodroplets, CANDI overcomes the multiplexing limitations of conventional CRISPR diagnostics and enables simultaneous interrogation of multiple mycobacterial targets in a single assay. We designed a 16-plex panel that distinguishes 15 clinically relevant Mycobacterium species and subspecies. CANDI achieved high analytical sensitivity and accurate discrimination in samples containing coinfections with multiple species or subspecies. When applied to 230 clinical specimens, including sputum, tracheal aspirates, and other respiratory fluids, CANDI delivered subspecies-level results within 3.5 hours, achieving 97.08% sensitivity and 99.7% specificity relative to culture-based identification. By combining multiplexed, high-specificity CRISPR detection with scalable droplet-based engineering, CANDI has the potential to overcome the culture dependency of current diagnostics and enable species- and subspecies-level identification across the genetically complex Mycobacterium genus, offering a clinically adaptable framework for rapid, precision diagnosis of mycobacterial infections.
Authors
- Courtney N. Dial (ORCID: https://orcid.org/0000-0003-0004-7418)
- Adrian M. Zelazny (ORCID: https://orcid.org/0000-0003-2847-7428)
- Taryn A. Miner (ORCID: https://orcid.org/0009-0009-9304-2413)
- Jia Fan (ORCID: https://orcid.org/0000-0003-3384-0834)
- Tony Hu (ORCID: https://orcid.org/0000-0002-5166-4937)
- Christopher J. Lyon (ORCID: https://orcid.org/0000-0003-2319-2933)
- Melissa B. Miller (ORCID: https://orcid.org/0000-0002-0296-3535)
- Bo Ning (ORCID: https://orcid.org/0000-0001-9437-7244)
- Seungyeon Seo
- Fangyou Yu (ORCID: https://orcid.org/0000-0003-4924-2484)
- Zhen Huang (ORCID: https://orcid.org/0000-0002-3990-7350)
- Xiaoli Zhu (ORCID: https://orcid.org/0000-0001-5497-4538)
- Duran Bao (ORCID: https://orcid.org/0000-0001-9049-1947)
- Mingyu Gan (ORCID: https://orcid.org/0009-0008-4405-092X)
- Shu Wang (ORCID: https://orcid.org/0000-0002-1751-1267)
- Long Chen (ORCID: https://orcid.org/0000-0002-1287-0404)
- Qingyun Liu (ORCID: https://orcid.org/0000-0002-2284-5050)
- Zhiyuan Wu (ORCID: https://orcid.org/0000-0003-3576-6244)
- Wenshu Zheng (ORCID: https://orcid.org/0000-0001-6726-1326)
- Gou Hongquan (ORCID: https://orcid.org/0000-0002-9890-4088)
- Kelly Eick (ORCID: https://orcid.org/0009-0009-0787-8063)
- Xiaocui Wu
- Sheila Mollin (ORCID: https://orcid.org/0009-0003-0576-8430)
- Duy Tran
Institutions
- University of North Carolina at Chapel Hill (US)
- Tulane University (US)
- Tongji University (CN)
- Shanghai Pulmonary Hospital (CN)
- Shanghai Tenth People's Hospital (CN)
- National Institutes of Health Clinical Center (US)
- Tsinghua University (CN)
Publication Details
- Journal
- Science Translational Medicine
- Published
- 2026-09-16
- DOI
- https://doi.org/10.1126/scitranslmed.aef2648
- Primary Topic
- Mycobacterium research and diagnosis
- Type
- article
- Field-Weighted Citation Impact
- 0.00