Activity and inhibition of the SARS-CoV-2 Omicron nsp13 R392C variant using RNA duplex unwinding assays.

SARS-CoV-2 nsp13 helicase is an essential enzyme for viral replication and a promising target for antiviral drug development. This study compares the double-stranded RNA (dsRNA) unwinding activity of nsp13 and the Omicron nsp13R392C variant, which is predominant in currently circulating lineages. Using in vitro gel- and fluorescence-based assays, we found that both nsp13 and nsp13R392C have dsRNA unwinding activity with equivalent kinetics. Furthermore, the R392C mutation had no effect on the efficiency of the nsp13-specific helicase inhibitor SSYA10-001. We additionally confirmed the activity of several other helicase inhibitors against nsp13, including punicalagin that inhibited dsRNA unwinding at nanomolar concentrations. Overall, this study reveals the utility of using dsRNA unwinding assays to screen small molecules for antiviral activity against nsp13 and the Omicron nsp13R392C variant. Continual monitoring of newly emergent variants will be essential for considering resistance profiles of lead compounds as they are advanced towards next-generation therapeutic development.

Evolution of the Umbilical Cord Blood Proteome Across Gestational Development.

Neonatal health is dependent on early risk stratification, diagnosis, and timely management of potentially devastating conditions, particularly in the setting of prematurity. Many of these conditions are poorly predicted in real-time by clinical data and current diagnostics. Umbilical cord blood may represent a novel source of molecular signatures that provides a window into the state of the fetus at birth. In this study, we comprehensively characterized the cord blood proteome of infants born between 24 to 42 weeks using untargeted mass spectrometry and functional enrichment analysis. We determined that the cord blood proteome at birth varies significantly across gestational development. Proteins that function in structural development and growth (e.g., extracellular matrix organization, lipid particle remodeling, and blood vessel development) are more abundant earlier in gestation. In later gestations, proteins with increased abundance are in immune response and inflammatory pathways, including complements and calcium-binding proteins. Furthermore, these data contribute to the knowledge of the physiologic state of neonates across gestational age, which is crucial to understand as we strive to best support postnatal development in preterm infants, determine mechanisms of pathology causing adverse health outcomes, and develop cord blood biomarkers to help tailor our diagnosis and therapeutics for critical neonatal conditions.

Integration of individualized and population-level molecular epidemiology data to model COVID-19 outcomes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants with enhanced transmissibility and immune escape have emerged periodically throughout the coronavirus disease 2019 (COVID-19) pandemic, but the impact of these variants on disease severity has remained unclear. In this single-center, retrospective cohort study, we examined the association between SARS-CoV-2 clade and patient outcome over a two-year period in Chicago, Illinois. Between March 2020 and March 2022, 14,252 residual diagnostic specimens were collected from SARS-CoV-2-positive inpatients and outpatients alongside linked clinical and demographic metadata, of which 2,114 were processed for viral whole-genome sequencing. When controlling for patient demographics and vaccination status, several viral clades were associated with risk for hospitalization, but this association was negated by the inclusion of population-level confounders, including case count, sampling bias, and shifting standards of care. These data highlight the importance of integrating non-virological factors into disease severity and outcome models for the accurate assessment of patient risk.

Serodominant SARS-CoV-2 Nucleocapsid Peptides Map to Unstructured Protein Regions.

The SARS-CoV-2 nucleocapsid (N) protein is highly immunogenic, and anti-N antibodies are commonly used as markers for prior infection. While several studies have examined or predicted the antigenic regions of N, these have lacked consensus and structural context. Using COVID-19 patient sera to probe an overlapping peptide array, we identified six public and four private epitope regions across N, some of which are unique to this study. We further report the first deposited X-ray structure of the stable dimerization domain at 2.05 Å as similar to all other reported structures. Structural mapping revealed that most epitopes are derived from surface-exposed loops on the stable domains or from the unstructured linker regions. An antibody response to an epitope in the stable RNA binding domain was found more frequently in sera from patients requiring intensive care. Since emerging amino acid variations in N map to immunogenic peptides, N protein variation could impact detection of seroconversion for variants of concern. IMPORTANCE As SARS-CoV-2 continues to evolve, a structural and genetic understanding of key viral epitopes will be essential to the development of next-generation diagnostics and vaccines. This study uses structural biology and epitope mapping to define the antigenic regions of the viral nucleocapsid protein in sera from a cohort of COVID-19 patients with diverse clinical outcomes. These results are interpreted in the context of prior structural and epitope mapping studies as well as in the context of emergent viral variants. This report serves as a resource for synthesizing the current state of the field toward improving strategies for future diagnostic and therapeutic design.

Challenges and Opportunities for Global Genomic Surveillance Strategies in the COVID-19 Era.

Global SARS-CoV-2 genomic surveillance efforts have provided critical data on the ongoing evolution of the virus to inform best practices in clinical care and public health throughout the pandemic. Impactful genomic surveillance strategies generally follow a multi-disciplinary pipeline involving clinical sample collection, viral genotyping, metadata linkage, data reporting, and public health responses. Unfortunately, current limitations in each of these steps have compromised the overall effectiveness of these strategies. Biases from convenience-based sampling methods can obfuscate the true distribution of circulating variants. The lack of standardization in genotyping strategies and bioinformatic expertise can create bottlenecks in data processing and complicate interpretation. Limitations and inconsistencies in clinical and demographic data collection and sharing can slow the compilation and limit the utility of comprehensive datasets. This likewise can complicate data reporting, restricting the availability of timely data. Finally, gaps and delays in the implementation of genomic surveillance data in the public health sphere can prevent officials from formulating effective mitigation strategies to prevent outbreaks. In this review, we outline current SARS-CoV-2 global genomic surveillance methods and assess roadblocks at each step of the pipeline to identify potential solutions. Evaluating the current obstacles that impede effective surveillance can improve both global coordination efforts and pandemic preparedness for future outbreaks.