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Integrated CRISPR-based detection of HIV, tuberculosis, malaria, and resistance-associated variants

Jain, A. S.; Si, A.; Yap, J.; Schwartz, L. A.; Susilo, C.; Balamurugan, A.; Neal, A.; Le Roch, K. G.; Yang, O.; Garner, O.; Kamariza, M.

2026-09-29 infectious diseases
10.64898/2026.09.26.26364094 medRxiv
Show abstract

HIV, tuberculosis (TB) and malaria are major infectious diseases that frequently co-circulate in high-burden settings, yet their diagnostic pathways remain largely disease-specific, complicating detection of coinfection and integration of antimicrobial-resistance testing. Here we developed HTM CARMEN, a highly multiplexed CRISPR-Cas13a molecular-testing framework that integrates detection of HIV-1, HIV-2, four Plasmodium species and Mycobacterium tuberculosis (Mtb) with detection of isoniazid-resistance-associated inhA and katG variants. We find that HTM CARMEN retained target selectivity and single-nucleotide discrimination across in vitro experiments and clinically relevant sample matrices, including whole blood, serum, sputum and dried blood spots. Across 20 contrived samples for each condition, the HTM panel supported detection of low-abundance targets across multiple matrices and frequently detected greater number of low-input samples as positive than qPCR under the conditions tested. In contrived P. falciparum/HIV-1 and Mtb/HIV-1 coinfections, both pathogens were simultaneously detected across a range of relative target concentrations. Using confirmed-positive clinical samples, HTM CARMEN achieved positive percent agreement of 95% for malaria (19/20), 95% for HIV-1 (19/20) and 100% for Mtb (30/30), with 100% negative percent agreement for each target in the confirmed-negative samples. Both HIV-1 and Mtb were additionally detected in all nine confirmed-positive HIV-TB coinfection specimens. These findings establish the feasibility of integrating pathogen detection, species differentiation, resistance-associated variant interrogation and coinfection detection within a programmable molecular-testing platform, providing a framework for high-throughput integrated testing in co-endemic settings.

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