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Extract-Free One-Pot Ambient RPA-CRISPR Detection of Plasmodium in Whole Blood

jiang, F.; Liao, J.; Su, Y.

2026-03-19 infectious diseases
10.64898/2026.03.17.26348654 medRxiv
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BackgroundMalaria caused by Plasmodium is a major global health burden. Rapid and accurate malaria detection is essential for effective disease control. However, most molecular diagnostics require DNA extraction, thermal cycling, and specialized infrastructure, limiting use in resource-limited settings. This study aimed to develop an extraction-free, one-pot CRISPR-based platform for rapid Plasmodium detection directly from whole blood under ambient conditions. MethodsCrude blood lysates were directly applied to a one-pot recombinase polymerase amplification (RPA)-CRISPR reaction coupled with lateral flow readout. Analytical sensitivity and specificity were evaluated using purified DNA and whole-blood lysates. Diagnostic performance was assessed using a clinical cohort comprising 116 malaria cases and 109 negative controls. ResultsThe extract-free RPA-CRISPR assay achieved an analytical limit of detection of 100 copies/{micro}L from crude blood lysates, corresponding approximately to 12-20 parasites/{micro}L. No cross-reactivity was observed across Plasmodium species. In clinical evaluation, the assay demonstrated strong concordance with reference PCR, achieving 93.1% sensitivity and 100% specificity. Sensitivity varied with parasite burden, reaching 97.8% for high-density infections, 95.1% for moderate density, and 82.8% for low-density infections. The whole workflow was completed within 40 minutes at room temperature without specialized instrumentation. ConclusionsAn extract-free, one-pot ambient-temperature RPA-CRISPR platform allows rapid detection of Plasmodium directly from whole blood with high specificity and sensitivity across parasite burdens, supporting its potential for decentralized malaria diagnostics. Larger multicenter field studies are needed to validate performance under real-world conditions.

Published in Journal of Microbiological Methods (predicted rank #13) · training set

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