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Integrating CRISPR-Cas12a into a Microfluidic Dual-Droplet Device Enables Simultaneous Detection of HPV16 and HPV18.

Yin ZhaoDongjuan ChenZhichen XuTao LiJiang ZhuRui HuGuoyong XuYing LiYunhuang YangMaili Liu
Published in: Analytical chemistry (2023)
Fast, simplified, and multiplexed detection of human papillomaviruses (HPVs) is of great importance for both clinical management and population screening. However, current HPV detection methods often require sophisticated instruments and laborious procedures to detect multiple targets. In this work, we developed a simple microfluidic dual-droplet device (M-D3) for the simultaneous detection of HPV16 and HPV18 by combining the CRISPR-Cas12a system and multiplexed recombinase polymerase amplification (RPA) assay. A new approach of combining pressure/vacuum was proposed for efficient droplet generation with minimal sample consumption. Two groups of droplets that separately encapsulate the relevant Cas12a/crRNA and the fluorescent green or red reporters are parallelly generated, followed by automatic imaging to discriminate the HPV subtypes based on the specific fluorescence of the droplets. The M-D3 platform performs with high sensitivity (∼0.02 nM for unamplified plasmids) and specificity in detecting HPV16 and HPV18 DNA. By combining the RPA and Cas12a assay, M-D3 allows on-chip detection of HPV16 and HPV18 DNA simultaneously within 30 min, reaching a detection limit of 10 -18 M (∼1 copy/reaction). Moreover, the outstanding performance of M-D3 was validated in testing 20 clinical patient samples with HPV infection risk, showing a sensitivity of 92.3% and a specificity of 100%. By integrating the dual-droplet generator, CRISPR-Cas12a, and multiplexed RPA, the M-D3 platform provides an efficient way to discriminate the two most harmful HPV subtypes and holds great potential in the applications of multiplexed nucleic acid testing.
Keyphrases
  • high grade
  • crispr cas
  • high throughput
  • single cell
  • genome editing
  • label free
  • cervical cancer screening
  • machine learning
  • real time pcr
  • circulating tumor cells
  • circulating tumor
  • deep learning
  • climate change