The COVID-19 pandemic, caused by SARS-CoV-2, highlighted inadequacies in existing diagnostic testing. While various molecular approaches exist (real-time RT-qPCR, isothermal methods, CRISPR), RT-qPCR offers advantages in simplicity, multiplexing potential, and sensitivity. However, many commercial RT-qPCR tests are slow (1-1.5 hours), less sensitive than achievable, and often target only two viral genes, increasing the risk of false negatives. The virus's potential to mutate also poses a challenge. False negatives can also stem from sampling issues, RNA recovery, PCR inhibitors, or human error. This necessitates a highly sensitive, specific, and rapid RT-qPCR assay with robust controls to minimize false negatives. The authors aimed to develop an RT-qPCR test that is both qualitative and quantitative, sensitive, specific, and fast, adhering to MIQE guidelines to ensure transparency and reproducibility. The need for rapid and reliable detection is crucial not only for accurate diagnosis but also for informed public health strategies.

The existing literature highlighted the need for improved SARS-CoV-2 diagnostic tests. Commercial assays often lacked sensitivity (e.g., detecting 500 viral copies per reaction), were time-consuming (1-1.5 hours), and typically targeted only two viral genes, potentially leading to false negatives. While streamlined assays with lower detection limits existed, they were often based on artificial spike-in experiments and still took around 2 hours to complete. The concern about SARS-CoV-2 mutations affecting primer binding sites and causing false negatives was also a significant factor in motivating the development of a more robust assay. Studies demonstrating the variability of Cq values between laboratories further highlighted the need for more reliable and standardized diagnostic testing. Previous work by the authors showed the potential for reducing PCR reaction times through optimization of denaturation and polymerisation steps.

The study employed a MIQE-compliant workflow for the design, optimization, and validation of CoV2-ID. The assay targets three SARS-CoV-2 genes (Nsp10, Nsp12, and N) to maximize specificity and minimize the impact of mutations. A human control (JUN) is included to confirm the presence of human cells, and an extraction and inhibition control artificial sequence (EICAS) monitors assay performance and detects potential inhibitors. The study optimized primer and probe concentrations, annealing temperatures, and PCR parameters using various techniques including ddPCR. Clinical samples (23 positive, 5 negative) were used for validation. The optimization included reducing RT and qPCR times. The methodology further explored multiple cycle fluorescence detection (MCFD) as an alternative to real-time detection to reduce assay time. A genotyping assay for the D614G mutation was also designed and applied to the clinical samples. Detailed methods were used for RNA extraction, primer/probe design, RT-qPCR and ddPCR experiments, and data analysis. Various qPCR instruments were used for comparing run times and assay performance under different conditions. Ethical considerations were addressed by using anonymized RNA samples and obtaining ethics approval.

CoV2-ID consistently detected two copies of viral RNA, with a limit of detection of a single copy. Validation on clinical samples showed 100% sensitivity and 100% specificity. The assay runtime was significantly reduced to approximately 15 minutes. The multiplexing approach, using the same fluorophore for multiple viral targets, enhanced sensitivity. The multiple cycle fluorescence detection (MCFD) protocol further reduced the assay time, while maintaining the ability to quantify viral load. All clinical samples from Chelmsford, UK, between mid-April and June 2020, showed the D614G mutation, while an Australian sample was wild-type. The addition of a third viral target (Nsp12), detected with the same fluorophore as two other targets, further increased the assay's sensitivity. Optimization of RT and qPCR conditions resulted in significant time reduction. Analysis revealed that the EICAS showed minimal inhibition, suggesting high RNA sample quality. Mutation analysis showed that the mutations did not significantly impact the assay’s performance, as long as the mutations were not at the 3’ end of the primers. The ddPCR provided quantitative data for the EICAS which acted as a quality control for RNA and allowed indirect viral load measurement. The MCFD protocol generated a 5-level diagnostic rating system, offering a fast, less subjective, and more interpretable result than traditional Cq values.

CoV2-ID addresses the limitations of existing SARS-CoV-2 detection assays by combining high sensitivity, specificity, and speed. The use of three viral targets and a multiplexing strategy with a single fluorophore minimizes the risk of false negatives due to mutations or other factors. The MCFD approach simplifies data interpretation by moving away from subjective Cq values and provides a more user-friendly rating system. This is particularly useful in high-throughput screening scenarios where rapid results are essential. The inclusion of controls for RNA quality and PCR inhibitors further improves the reliability of the assay. The ability to adapt CoV2-ID for both qualitative and quantitative applications makes it versatile for various diagnostic needs. The findings support the prevalence of the D614G mutation in the UK during the study period. The study highlights the limitations of using Cq values for precise viral load quantification. The use of EICAS quantification via ddPCR addresses this concern, providing a more reliable approach to assess viral load. The findings contribute to the development of more robust and efficient SARS-CoV-2 diagnostic tools, particularly for high-throughput settings.

CoV2-ID represents a significant advancement in SARS-CoV-2 detection, offering a rapid, sensitive, and specific assay suitable for various diagnostic applications. Its MIQE-compliant design, multiplexing strategy, and MCFD protocol contribute to its robustness and ease of use. Future research could focus on adapting CoV2-ID for point-of-care diagnostics and exploring its application in diverse settings, including environmental surveillance. Further investigation into the impact of emerging mutations on assay performance is also warranted.

The study utilized a limited number of samples for validation, and the results might not be fully generalizable to all geographical regions or viral strains. The quantitative aspects of the assay rely on the EICAS internal control, which requires validation in different laboratories. While the MCFD method reduces assay time, it might not be applicable to all qPCR instruments.