Real-time reverse transcription-polymerase chain reaction assay panel for the detection of severe acute respiratory syndrome coronavirus 2 and its variants

The role of SARS-CoV-2 N protein in diagnosis and vaccination in the context of emerging variants: present status and prospects

Despite many countries rapidly revising their strategies to prevent contagions, the number of people infected with Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to surge. The emergent variants that can evade the immune response significantly affect the effectiveness of mainstream vaccines and diagnostic products based on the original spike protein. Therefore, it is essential to focus on the highly conserved nature of the nucleocapsid protein as a potential target in the field of vaccines and diagnostics. In this regard, our review initially discusses the structure, function, and mechanism of action of N protein. Based on this discussion, we summarize the relevant research on the in-depth development and application of diagnostic methods and vaccines based on N protein, such as serology and nucleic acid detection. Such valuable information can aid in designing more efficient diagnostic and vaccine tools that could help end the SARS-CoV-2 pandemic.

An Update on Detection Technologies for SARS-CoV-2 Variants of Concern

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus's genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.

Genetic algorithm based image reconstruction applying the digital holography process with the Discrete Orthonormal Stockwell Transform technique for diagnosis of COVID-19

World Health Organization has described the real-time reverse transcription-polymerase chain reaction test method for the diagnosis of the novel coronavirus disease (COVID-19). However, the limited number of test kits, the long-term results of the tests, the high probability of the disease spreading during the test and imaging without focused images necessitate the use of alternative diagnostic methods such as chest X-ray (CXR) imaging. The storage of data obtained for the diagnosis of the disease also poses a major problem. This causes misdiagnosis and delays treatment. In this work, we propose a hybrid 3D reconstruction method of CXR images (CXRI) to detect coronavirus pneumonia and prevent misdiagnosis on CXRI. We used the digital holography technique (DHT) for obtaining a priori information of CXRI stored in created digital hologram (CDH). In this way, the elimination of the storage problem that requires high space was revealed. In addition, Discrete Orthonormal S-Transform (DOST) is applied to the reconstructed CDH image obtained by using DHT. This method is called CDH_DHT_DOST. A multiresolution spatial-frequency representation of the lung images that belong to healthy people and diseased people with the COVID-19 virus is obtained by using the CDH_DHT_DOST. Moreover, the genetic algorithm (GA) is adopted for the reconstruction process for optimization of the CDH image and then DOST is applied. This hybrid method is called CDH_GA_DOST. Finally, we compare the results obtained from CDH_DHT_DOST and CDH_GA_DOST. The results show the feasibility of reconstructing CXRI with CDH_GA_DOST. The proposed method holds promises to meet demands for the detection of the COVID-19 virus.

Specific Detection of SARS-CoV-2 Variants B.1.1.7 (Alpha) and B.1.617.2 (Delta) Using a One-Step Quantitative PCR Assay

In this report, we describe the development of a reverse transcription-quantitative PCR (RT-qPCR) assay, termed Alpha-Delta assay, which can detect all severe acute respiratory syndrome coronavirus 2 (SC-2) variants and distinguish between the Alpha (B.1.1.7) and Delta (B.1.617.2) variants. The Alpha- and Delta-specific reactions in the assay target mutations that are strongly linked to the target variant. The Alpha reaction targets the D3L substitution in the N gene, and the Delta reaction targets the spike gene 156 to 158 mutations. Additionally, we describe a second Delta-specific assay that we use as a confirmatory test for the Alpha-Delta assay that targets the 119 to 120 deletion in the Orf8 gene. Both reactions have similar sensitivities of 15 to 25 copies per reaction, similar to the sensitivity of commercial SC-2 detection tests. The Alpha-Delta assay and the Orf8_119del assay were successfully used to classify clinical samples that were subsequently analyzed by whole-genome sequencing. Lastly, the capability of the Alpha-Delta assay and Orf8_119del assay to identify correctly the presence of Delta RNA in wastewater samples was demonstrated. This study provides a rapid, sensitive, and cost-effective tool for detecting and classifying two worldwide dominant SC-2 variants. It also highlights the importance of a timely diagnostic response to the emergence of new SC-2 variants with significant consequences on global health. IMPORTANCE The new assays described herein enable rapid, straightforward, and cost-effective detection of severe acute respiratory syndrome coronavirus 2 (SC-2) with immediate classification of the examined sample as Alpha, Delta, non-Alpha, or non-Delta variant. This is highly important for two main reasons: (i) it provides the scientific and medical community with a novel diagnostic tool to rapidly detect and classify any SC-2 sample of interest as Alpha, Delta, or none and can be applied to both clinical and environmental samples, and (ii) it demonstrates how to respond to the emergence of new variants of concern by developing a variant-specific assay. Such assays should improve our preparedness and adjust the diagnostic capacity to serve clinical, epidemiological, and research needs.

Identification of Hotspot Mutations in the N Gene of SARS-CoV-2 in Russian Clinical Samples That May Affect the Detection by Reverse Transcription-PCR

Sensitive and reliable diagnostic test systems based on real-time PCR are of great importance in the fight against the ongoing SARS-CoV-2 pandemic. The genetic variability of the SARS-CoV-2 virus leads to the accumulation of mutations, some of which may affect the sensitivity of modern PCR assays. The aim of this study was to search in Russian clinical samples for new mutations in SARS-CoV-2 gene N that can affect the detection by RT-PCR. In this study, the polymorphisms in the regions of the target gene N causing failed or poor detection of the target N in the RT-PCR assay on 12 selected samples were detected. Sequencing the entire N and E genes in these samples along with other 195 samples that were positive for both target regions was performed. Here, we identified a number of nonsynonymous mutations and one novel deletion in the N gene that affected the ability to detect a target in the N gene as well a few mutations in the E gene of SARS-CoV-2 that did not affect detection. Sequencing revealed that majority of the mutations in the N gene were located in the variable region between positions 193 and 235 aa, inside and nearby the phosphorylated serine-rich region of the protein N. This study highlights the importance of the further characterization of the genetic variability and evolution of gene N, the most common target for detecting SARS-CoV-2. The use of at least two targets for detecting SARS-CoV-2, including one for the E gene, will be necessary for reliable diagnostics.