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Updated: Sep 18, 2026

Identification of Mycobacterium Species by DNA Microarray Chip Method
Published on: June 24, 2025
A rapid CRISPR-based nanodroplet assay enables direct clinical identification of mycobacteria species
Hongquan Gou1,2, Long Chen2,3, Kelly L Eick4,5
1Department of Clinical Laboratory Medicine, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, China.
Abstract:
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.
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