A novel CRISPR-based malaria diagnostic capable of Plasmodium detection, species differentiation, and drug-resistance genotyping

Background: CRISPR-based diagnostics are a new class of highly sensitive and specific assays with multiple applications in infectious disease diagnosis. SHERLOCK, or Specific High-Sensitivity Enzymatic Reporter UnLOCKing, is one such CRISPR-based diagnostic that combines recombinase polymerase pre-amplification, CRISPR-RNA base-pairing, and LwCas13a activity for nucleic acid detection. Methods: We developed SHERLOCK assays capable of detecting all Plasmodium species known to cause human malaria and species-specific detection of P. vivax and P. falciparum, the species responsible for the majority of malaria cases worldwide. We further tested these assays using a diverse panel of clinical samples from the Democratic Republic of the Congo, Uganda, and Thailand and pools of Anopheles mosquitoes from Thailand. In addition, we developed a prototype SHERLOCK assay capable of detecting the dihydropteroate synthetase (dhps) single nucleotide variant A581G associated with P. falciparum sulfadoxine resistance. Findings: The suite of Plasmodium assays achieved analytical sensitivities ranging from 2.5-18.8 parasites per reaction when tested against laboratory strain genomic DNA. When compared to real-time PCR, the P. falciparum assay achieved 94% sensitivity and 94% specificity during testing of 123 clinical samples. Compared to amplicon-based deep sequencing, the dhps SHERLOCK assay achieved 73% sensitivity and 100% specificity when applied to a panel of 43 clinical samples, with false-negative calls only at lower parasite densities. Interpretation: These novel SHERLOCK assays demonstrate the versatility of CRISPR-based diagnostics and their potential as a new generation of molecular tools for malaria diagnosis and surveillance. Funding: National Institutes of Health (T32GM007092, R21AI148579, K24AI134990, R01AI121558, UL1TR002489, P30CA016086) (c) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)