Microfluidic Ruler-Readout and CRISPR Cas12a-Responded Hydrogel-Integrated Paper-Based Analytical Devices (μReaCH-PAD) for Visible Quantitative Point-of-Care Testing of Invasive Fungi.

Abstract

Invasive fungi (IF) have become a significant problem affecting human health. However, the culture-based assay of IF, known as the most commonly used clinical diagnostic method, suffers from time consumption, complicated operation, and the requirement of trained operators, which may cause the delay diagnosis of the disease. In this report, a microfluidic ruler-readout and CRISPR Cas12a-responded hydrogel-integrated paper-based analytical device (μReaCH-PAD) was established for visible and quantitative point-of-care testing of IF. Using the genus-conserved fragments of 18s rRNA as the detection target, this platform relied on a CRISPR Cas12a system for target recognition, a DNA hydrogel coupled with a cascade of enzymatic reactions for signal amplification and transduction, and paper-based microfluidic chips for visual quantitative readout by naked eyes. The 18s rRNA fragments of Candida or Aspergillus were employed as a model target and introduced with PAM sites for Cas12a-recognition during reverse transcription recombinase-aided amplification. Using μReaCH-PAD, as low as 10 CFU/mL Candida and Aspergillus were visually identified by unaided eyes. The calculated detection limits were 4.90 and 4.13 CFU/mL (in 1 mL samples), respectively. The quantitative detection results can be obtained in the range from 10 to 104 CFU/mL with reasonable specificity and accuracy compared with qRT-PCR. Furthermore, μReaCH-PAD can analyze complex biological samples by Candida, Aspergillus, and Cryptococcus detection systems and identify specific genera of different IF by naked eyes, indicating a good agreement with the culture-based assay and the advantages over G-testing and GM-testing systems. With the benefits of high sensitivity, selectivity, quantitative readout, low cost, and ease of operation, μReaCH-PAD is expected to provide a portable detection tool of IF in resource-limited settings by untrained personnel and technical support for early diagnosis.