This review discusses the current testing methodologies for COVID-19 diagnosis and explores next-generation sequencing (NGS) technology for the detection of SARS-CoV-2 and monitoring phylogenetic evolution in the current COVID-19 pandemic. The review addresses the development, fundamentals, assay quality control and bioinformatics processing of the NGS data. This article provides a comprehensive review of the obstacles and opportunities facing the application of NGS technologies for the diagnosis, surveillance, and study of SARS-CoV-2 and other infectious diseases. Further, we have contemplated the opportunities and challenges inherent in the adoption of NGS technology as a diagnostic test with real-world examples of its utility in the fight against COVID-19.

Colorectal cancer (CRC) is a high burden disease with several genes involved in tumor progression. The aim of the present study was to identify, generate and clinically validate a novel gene signature to improve prediction of overall survival (OS) to effectively manage colorectal cancer. We explored The Cancer Genome Atlas (TCGA), COAD and READ datasets (597 samples) from The Protein Atlas (TPA) database to extract a total of 595 candidate genes. In parallel, we identified 29 genes with perturbations in > 6 cancers which are also affected in CRC. These genes were entered in cBioportal to generate a 17 gene panel with highest perturbations. For clinical validation, this gene panel was tested on the FFPE tissues of colorectal cancer patients (88 patients) using Nanostring analysis. Using multivariate analysis, a high prognostic score (composite 4 gene signature—DPP7/2, YWHAB, MCM4 and FBXO46) was found to be a significant predictor of poor prognosis in CRC patients (HR: 3.42, 95% CI: 1.71–7.94, p < 0.001 *) along with stage (HR: 4.56, 95% CI: 1.35–19.15, p = 0.01 *). The Kaplan-Meier analysis also segregated patients on the basis of prognostic score (log-rank test, p = 0.001 *). The external validation using GEO dataset (GSE38832, 122 patients) corroborated the prognostic score (HR: 2.7, 95% CI: 1.99–3.73, p < 0.001 *). Additionally, higher score was able to differentiate stage II and III patients (130 patients) on the basis of OS (HR: 2.5, 95% CI: 1.78–3.63, p < 0.001 *). Overall, our results identify a novel 4 gene prognostic signature that has clinical utility in colorectal cancer.

Oxidative damage has been identified as a major causative factor in degenerative diseases of the retina; retinal pigment epithelial (RPE) cells are at high risk. Hence, identifying novel strategies for increasing the antioxidant capacity of RPE cells, the purpose of this study, is important. Specifically, we evaluated the influence of selenium in the form of selenomethionine (Se-Met) in cultured RPE cells on system xc- expression and functional activity and on cellular levels of glutathione, a major cellular antioxidant. ARPE-19 and mouse RPE cells were cultured with and without selenomethionine (Se-Met), the principal form of selenium in the diet. Promoter activity assay, uptake assay, RT-PCR, northern and western blots, and immunofluorescence were used to analyze the expression of xc-, Nrf2, and its target genes. Se-Met activated Nrf2 and induced the expression and function of xc- in RPE. Other target genes of Nrf2 were also induced. System xc- consists of two subunits, and Se-Met induced the subunit responsible for transport activity (SLC7A11). Selenocysteine also induced xc- but with less potency. The effect of Se-met on xc- was associated with an increase in maximal velocity and an increase in substrate affinity. Se-Met increased the cellular levels of glutathione in the control, an oxidatively stressed RPE. The Se-Met effect was selective; under identical conditions, taurine transport was not affected and Na+-coupled glutamate transport was inhibited. This study demonstrates that Se-Met enhances the antioxidant capacity of RPE by inducing the transporter xc- with a consequent increase in glutathione.

Two serious public health challenges have emerged in the current COVID-19 pandemic namely, deficits in SARS-CoV-2 variant monitoring and neglect of other co-circulating respiratory viruses. Additionally, accurate assessment of the evolution, extent, and dynamics of the outbreak is required to understand the transmission of the virus. To address these challenges, we evaluated 533 samples using a high-throughput next-generation sequencing (NGS) respiratory viral panel (RVP) that includes 40 viral pathogens. The performance metrics revealed a PPA, NPA, and accuracy of 95.98%, 85.96%, and 94.4%, respectively. The clade for pangolin lineage B that contains certain distant variants, including P4715L in ORF1ab, Q57H in ORF3a, and S84L in ORF8 covarying with the D614G spike protein mutation, were the most prevalent early in the pandemic in Georgia, USA. The isolates from the same county formed paraphyletic groups, indicating virus transmission between counties. The study demonstrates the clinical and public health utility of the NGS-RVP to identify novel variants that can provide actionable information to prevent or mitigate emerging viral threats and models that provide insights into viral transmission patterns and predict transmission/resurgence of regional outbreaks as well as providing critical information on co-circulating respiratory viruses that might be independent factors contributing to the global disease burden.

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is an infectious virus that causes coronavirus disease 2019 (COVID-19) transmitted mainly through droplets and aerosol affecting the respiratory tract and lungs. Little is known regarding why some individuals are more susceptible than others and develop severe symptoms. In this study, we analyzed the nasopharyngeal microbiota profile of aged patients with COVID-19 (asymptomatic vs. symptomatic) vs. healthy individuals. We examined the nasopharynx swab of 84 aged-matched patients, out of which 27 were negative asymptomatic (NegA), 30 were positive asymptomatic (PA), and 27 patients were positive symptomatic (PSY). Our analysis revealed the presence of abundant Cyanobacterial taxa at phylum level in PA (p-value = 0.0016) and PSY (p-value = 0.00038) patients along with an upward trend in the population of Litoricola, Amylibacter, Balneola, and Aeromonas at the genus level. Furthermore, to know the relationship between the nasal microbiota composition and severity of COVID-19, we compared PA and PSY groups. Our data show that the nasal microbiota of PSY patients was significantly enriched with the signatures of two bacterial taxa: Cutibacterium (p-value = 0.045) and Lentimonas (p-value = 0.007). Furthermore, we also found a significantly lower abundance of five bacterial taxa, namely: Prevotellaceae (p-value = 7 × 10⁻⁶), Luminiphilus (p-value = 0.027), Flectobacillus (p-value = 0.027), Comamonas (p-value = 0.048), and Jannaschia (p-value = 0.012) in PSY patients. The dysbiosis of the nasal microbiota in COVID-19 positive patients might have a role in contributing to the severity of COVID-19. The findings of our study show that there is a strong correlation between the composition of the nasal microbiota and COVID-19 severity. Further studies are needed to validate our finding in large-scale samples and to correlate immune response (cytokine Strome) and nasal microbiota to identify underlying mechanisms and develop therapeutic strategies against COVID-19.

Objectives: Limitations of widespread current COVID-19 diagnostic testing exist in both the pre-analytical and analytical stages. To alleviate these limitations, we developed a universal saliva processing protocol (SalivaSTAT) that would enable an extraction-free RT-PCR test using commercially available RT-PCR kits. Methods: We optimized saliva collection devices, heat-shock treatment, and homogenization. Saliva samples (879) previously tested using the FDA-EUA method were reevaluated with the optimized SalivaSTAT protocol using two widely available commercial RT-PCR kits. A five-sample pooling strategy was evaluated as per FDA guidelines. Results: Saliva collection (done without any media) showed performance comparable to that of the FDA-EUA method. The SalivaSTAT protocol was optimized by incubating saliva samples at 95 °C for 30-min and homogenization, followed by RT-PCR assay. The clinical sample evaluation of 630 saliva samples using the SalivaSTAT protocol with PerkinElmer (600-samples) and CDC (30-samples) RT-PCR assay achieved positive (PPA) and negative percent agreements (NPAs) of 95.0% and 100%, respectively. The LoD was established as ~60–180 copies/mL by absolute quantification. Furthermore, a five-sample-pooling evaluation using 250 saliva samples achieved a PPA and NPA of 92% and 100%, respectively. Conclusion: We have optimized an extraction-free RT-PCR assay for saliva samples that demonstrates comparable performance to FDA-EUA assay (Extraction and RT-PCR).