| Literature DB >> 34062939 |
Huifen Zhou1, Jen-Hui Tsou1, Molangur Chinthalapally2, Hongjie Liu3, Feng Jiang1.
Abstract
SARS-CoV-2, influenza, and respiratory syncytial viruses (RSVs) cause acute respiratory infections with similar symptoms. Since the treatments and outcomes of these infections are different, the early detection and accurate differentiation of the viruses are clinically important for the prevention and treatment of the diseases. We previously demonstrated that clustered regularly interspaced short palindromic repeats (CRISPR) could rapidly and precisely detect SARS-CoV-2. The objective of this study was to develop CRISPR as a test for simultaneously detecting and accurately distinguishing the viruses. The CRISPR assay with an RNA guide against each virus was performed in the reference standards of SARS-CoV-2, influenza A and B, and RSV. The CRISPR assay had a limit of detection of 1-100 copies/µL for specifically detecting SARS-CoV-2, influenza A and B, and RSV without cross-reaction with other respiratory viruses. The validation of the test in nasopharyngeal specimens showed that it had a 90-100% sensitivity and 100% specificity for the detection of SARS-CoV-2, influenza A and B, and RSV. The CRISPR assay could potentially be used for sensitive detection and specific differentiation of the respiratory viruses.Entities:
Keywords: SARS-CoV-2; detection; influenza; respiratory syncytial viruses
Year: 2021 PMID: 34062939 PMCID: PMC8147329 DOI: 10.3390/diagnostics11050823
Source DB: PubMed Journal: Diagnostics (Basel) ISSN: 2075-4418
Sequences for RPA primers.
| Primers for RT-RPA | |
|---|---|
| SARS-CoV2 N-F | TGATTACAAACATTGGCCGCAAATTGCACA |
| SARS-CoV2 N-R | AGGTCAACCACGTTCCCGAAGGTGTGACTT |
| Influenza A-F | CTCACTTTTCTAGCACGGT |
| Influenza A-R | CCACTGGCTACGGCAGGTC |
| Influenza B-F | GCCATTCGATTTATAGGAAGAGC |
| Influenza B-R | CACTTGATCAACTAGAGCCT |
| RSV-F | AGAAATGAAATTTGAAGTGT |
| RSV-R | GATTCTATCTCAATGTTGAT |
| RNase P gene-F | TGGAGCCAGAGACCGACACA |
| RNase P gene-R | ACATGGCTCTGGTCCGAGGT |
Abbreviations: RT-RPA = reverse transcription-recombinase polymerase amplification; F = forward primer; and R = reverse primer.
Figure 1The workflow of the plate-based CRISPR for detection and differentiation of viruses.
Figure 2The RT-RPA mix was loaded in a 24-well plate. A 10 µL reaction containing a primer set for each target, RNA, and reverse transcriptase was added in each well in quadruplicate. Abbreviations: SARS 2 = SARS-CoV-2; FLU = influenza; and RNP = RNase P gene.
Figure 3The specificity of CRISPR and RT-PCR for detection of the different viruses. (A) The results of CRISPR, represented by fluorescence intensity, were read by a fluorescence plate reader in 10 min. The X-axis shows the RNA sample of each virus. The Y-axis indicates the fluorescence intensity of each sample. The error bars represent the standard deviation from the mean of the fluorescence intensity generated from ten replicates per sample. (B) The results of CRISPR are read by a UV transilluminator in 10 min. (C) The results of RT-PCR analysis of the same specimens. The X-axis shows the RNA sample of each virus. The Y-axis shows the copy number of the virus RNA measured by RT-PCR in each sample. The error bars represent the standard deviation from the mean of the copy number generated from ten replicates per sample. * p < 0.0001.
Figure 4The sensitivity of CRISPR-Cas12a and RT-PCR for detecting SARS-CoV-2, influenza A and B, and RSV in serially diluted RNA standard samples. (A) The LOD of CRISPR for detecting the viruses was 1–100 copies/µL (* p < 0. 01). The X-axis shows the serially diluted concentrations (from 104 to 0.1 copies/µL) of the RNA standard samples that were tested. The Y-axis indicates the fluorescence intensity of each sample read on the fluorescence plate reader. The error bars represent the standard deviation from the mean of the fluorescence intensity generated from ten replicates in each sample. (B) Amplification curves of RT-P CR analysis of the serially diluted RNA samples. Amplification plots were created when the relative fluorescence unit (Y-axis) from each sample was plotted against the cycle number (X-axis). (C) The high linearity (R2 = 0.902–0.997) of all standard curves of the four types of viruses analyzed by RT-PCR. The X-axis indicates the serially diluted RNA samples that were tested. The Y-axis shows the cycle number of RT-PCR. The error bars represent the standard deviation from the mean of cycle number of RT-PCR generated from ten replicates in each sample. (D) Linear regression analysis shows that the CRSIPR and RT-PCR assays had great agreement for detection of the viruses (All R2 > 0.90, p < 0.01). The X-axis shows the serially diluted RNA samples tested. The Y-axis displays the copies of virus RNA per µL measured by CRSIP or RT-PCR in each of the serially diluted RNA samples. The error bars represent the standard deviation from the mean of copy number generated from ten replicates per concentration.
The diagnostic sensitivity and specificity of CRISPR-Cas12a for detection of the viruses.
| Target | The Number of Specimens Tested | The Number of Positive Results | Sensitivity * | Specificity * |
|---|---|---|---|---|
| SARS-CoV-2 | 10 | 10 | 100.0% | 100.0% |
| Influenza A | 16 | 16 | 100.0% | 100.0% |
| Influenza B | 13 | 13 | 100.0% | 100.0% |
| RSV | 10 | 9 | 90.0% | 100.0% |
* Clinical RT-PCR diagnostic testing was used as the gold standard.