Scalable Drug-Resistance Profiling of Tuberculosis and Malaria Using mCARMEN

Cameron Myhrvold of Princeton University and Mireille Kamariza of the University of California, Los Angeles, both in the U.S., will develop an assay to rapidly detect multiple drug resistance mutations in Plasmodium falciparum and Mycobacterium tuberculosis for malaria and tuberculosis (TB) surveillance, respectively. Malaria and TB are two of the world's deadliest infectious diseases. Rapid and accurate drug resistance testing can save lives but current assays are slow or difficult to scale. Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN) is a CRISPR-based diagnostic test that detects nucleic acid biomarkers, such as those in pathogens, with high specificity and throughput. They have developed microfluidic CARMEN (mCARMEN), which produces results in under five hours, and will use an algorithm to design assays that detect the top ten drug-resistant P. falciparum mutations from blood samples, and M. tuberculosis mutations from saliva samples that confer resistance to two first-line TB drugs.