Emergence of the Omicron SARS-CoV-2 subvariants during the COVID-19 pandemic

In silico analyses identify sequence contamination thresholds for Nanopore-generated SARS-CoV-2 sequences

The SARS-CoV-2 pandemic has brought molecular biology and genomic sequencing into the public consciousness and lexicon. With an emphasis on rapid turnaround, genomic data informed both diagnostic and surveillance decisions for the current pandemic at a previously unheard-of scale. The surge in the submission of genomic data to publicly available databases proved essential as comparing different genome sequences offers a wealth of knowledge, including phylogenetic links, modes of transmission, rates of evolution, and the impact of mutations on infection and disease severity. However, the scale of the pandemic has meant that sequencing runs are rarely repeated due to limited sample material and/or the availability of sequencing resources, resulting in the upload of some imperfect runs to public repositories. As a result, it is crucial to investigate the data obtained from these imperfect runs to determine whether the results are reliable prior to depositing them in a public database. Numerous studies have identified a variety of sources of contamination in public next-generation sequencing (NGS) data as the number of NGS studies increases along with the diversity of sequencing technologies and procedures. For this study, we conducted an in silico experiment with known SARS-CoV-2 sequences produced from Oxford Nanopore Technologies sequencing to investigate the effect of contamination on lineage calls and single nucleotide variants (SNVs). A contamination threshold below which runs are expected to generate accurate lineage calls and maintain genome-relatedness and integrity was identified. Together, these findings provide a benchmark below which imperfect runs may be considered robust for reporting results to both stakeholders and public repositories and reduce the need for repeat or wasted runs.

SARS-CoV-2 Infection-Dependent Modulation in Vital Components of the Serum Profile of Severely SARS-CoV-2 Infected Patients

Background

COVID-19 modulates many serological biomarkers during the progress of disease severity. The study aimed to determine COVID-19 severity-associated perturbance in the serum profile.

Methods

A retrospective study including COVID-19-positive individuals (n = 405) was accomplished. The serum profile of COVID-19 participants was mined from laboratory records. Severity-associated alteration in the serum profile was evaluated using Pearson correlation, regression, VCramer, Bayesian posterior VCramer, and bias factor using R-base-RStudio-version-3.3.0 with a significant cut-off of p < 0.05.

Results

Significantly different mean ± standard deviation (SD) (highly versus moderately severe) of C-reactive protein (CRP), ferritin, neutrophil-lymphocyte ratio (NLR), D-dimer, platelets, prothrombin time (PT), partial prothrombin time (PTT), troponin 1, lactate dehydrogenase (LDH), aspartate-aminotransferase (AST), alanine aminotransferase (ALT), and AST/ALT ratio was observed (p < 0.001). Highly severe COVID-19 associated with CRP, ferritin, NLR, in D-dimer, PT, PTT, troponin 1, AST/ALT ratio, AST and ALT (adjusted odds ratio (AOR): 1.346, 1.05, 1.46, 1.33, 1.42, 1.23, 4.07, 3.9, 1.24, 1.45, p < 0.001). CRP with ferritin (r = 0.743), NLR (r = 0.77), white blood cells (WBC) (r = 0.8), troponin1 with LDH (r = 0.757), and D-dimer with platelets (r = -0.81) were highly correlated. X2pearson (p < 0.001), VCramer (0.71), Bayesian-VCramer (0.7), and bias-factor (-125) for troponin 1 indicate the strong association of troponin 1 level and with COVID-19 severity. X2pearson (p < 0.001), VCramer (1), Bayesian-VCramer (0.98), and bias-factor (-266.3) for NLR exhibited a very strong association of pathologic conditions with the high severity of the disease.

Conclusion

These biomarkers of inflammation (CRP, Ferritin, NLR), coagulation disorders (D-dimer, PT, and PTT) cardiac abnormality (troponin 1), and liver injury (AST/ALT) could be crucial in low-medical resource settings as potential prognosticator/predictors of the COVID-19 severity and clinical outcomes. Moreover, the outcome of this study could be leveraged for the early prediction of disease severity during SARS-CoV or Middle East Respiratory Coronavirus (MERS-CoV) infection.

GRT-R910: a self-amplifying mRNA SARS-CoV-2 vaccine boosts immunity for ≥6 months in previously-vaccinated older adults

SARS-CoV-2 has resulted in high levels of morbidity and mortality world-wide, and severe complications can occur in older populations. Humoral immunity induced by authorized vaccines wanes within 6 months, and frequent boosts may only offer transient protection. GRT-R910 is an investigational self-amplifying mRNA (samRNA)-based SARS-CoV-2 vaccine delivering full-length Spike and selected conserved non-Spike T cell epitopes. This study reports interim analyses for a phase I open-label dose-escalation trial evaluating GRT-R910 in previously vaccinated healthy older adults (NCT05148962). Primary endpoints of safety and tolerability were assessed. Most solicited local and systemic adverse events (AEs) following GRT-R910 dosing were mild to moderate and transient, and no treatment-related serious AEs were observed. The secondary endpoint of immunogenicity was assessed via IgG binding assays, neutralization assays, interferon-gamma ELISpot, and intracellular cytokine staining. Neutralizing antibody titers against ancestral Spike and variants of concern were boosted or induced by GRT-R910 and, contrasting to authorized vaccines, persisted through at least 6 months after the booster dose. GRT-R910 increased and/or broadened functional Spike-specific T cell responses and primed functional T cell responses to conserved non-Spike epitopes. This study is limited due to small sample size, and additional data from ongoing studies will be required to corroborate these interim findings.