UnCovid: A versatile, low-cost, and open-source protocol for SARS-CoV-2 RNA detection

Abstract

Here, we describe a detailed step-by-step protocol to detect SARS-CoV-2 RNA using RT-PCR-mediated amplification and CRISPR/Cas-based visualization. The optimized assay uses basic molecular biology equipment such as conventional thermocyclers and transilluminators for qualitative detection. Alternatively, a fluorescence plate reader can be used for quantitative measurements. The protocol detects two regions of the SARS-CoV-2 genome in addition to the human RNaseP sample control. Aiming to reach remote regions, this work was developed to use the portable molecular workstation from BentoLab. For complete details on the use and execution of this protocol, please refer to Alcántara et al., 2021.

Keywords: Biotechnology and bioengineering; CRISPR; Clinical Protocol; Immunology; Microbiology; Molecular Biology.

Graphical abstract

Figure 1

Recommended plate layout for 32 reactions to be processed in the BentoLab

Figure 2

RT-PCR products from positive and negative controls for ORF1ab, N and RNAseP targets The amplification products were run on a 5% agarose gel at 70 V for 60 min. AmpliSize Molecular Ruler (Cat. No. 1708200, Bio-Rad) was used as ladder. Products were visualized using SafeGreen (Cat. No. G108-G, abm) in the loading buffer TriTrack DNA loading dye 6× (Cat. No. R1161, ThermoFisher).

Figure 3

Recommended plate layout for CRISPR/Cas reactions in a 96-well microplate For each target 32 reactions are included (28 unknown samples + duplicates of positive controls, negative extraction, and no template controls).

Figure 4

Fluorescence ratio distribution for clinical samples in this example Data from 50 SARS-CoV-2 positive and 50 negative samples are shown. (A) Fluorescence distribution for SARS-CoV-2 positive samples sorted by viral RNA load for the ORF1ab and N targets. (B) Fluorescence distribution for SARS-CoV-2 positive and negative samples for the two targets (ORF1ab, N). (C) RNaseP fluorescence ratio distribution for SARS-CoV-2 samples, sorted by viral RNA load, positive and, negative controls. Tukey boxplots in A-C indicate the median, 25%, and 75% percentiles. Whiskers indicate minimun and maximun values excluding outliers (full circles).

Figure 5

Fluorescence ratio for positive and negative controls Fluorescence ratio data represent the mean of five independent experiments. Error bars show standard deviation.

Figure 6

Visual detection of the amplified N target using CRISPR/Cas12a-dependent fluorescence signal RT-PCR products of positive and negative SARS-CoV-2 samples were observed in a blue light LED transilluminator.

Figure 7

Test decision scheme Cut-off values were calculated by a Receiver Operating Characteristic (ROC) curve analysis (Hanley and McNeil, 1982). The selected cut-off values were those that reported the highest percentage of correctly classified samples according to a ROC curve analysis with 100 samples (Alcántara et al., 2021). ∗ Test again if symptoms occur. If symptoms already present RT-qPCR recommended. ∗∗ If an invalid result is obtained, see troubleshooting section – problem 5.