The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has challenged the speed at which laboratories discover the viral composition and study health outcomes. The small ~30-kb ssRNA genome of coronaviruses makes them adept at cross-species spread, but also enable a robust understanding of all the proteins the viral genome encodes. We have employed protein modeling, molecular dynamic simulations, evolutionary mapping, and 3D printing to gain a full proteome- and dynamicome-level understanding of SARS-CoV-2. We established the Viral Integrated Structural Evolution Dynamic Database (VIStEDD at prokoplab.com/vistedd) to facilitate future discoveries and educational use. Here, we highlight the use of VIStEDD for nsp6, nucleocapsid (N), and spike (S) surface glycoprotein. For both nsp6 and N, we found highly conserved surface amino acids that likely drive protein–protein interactions. In characterizing viral S protein, we developed a quantitative dynamics cross-correlation matrix to gain insights into its interactions with the angiotensin I–converting enzyme 2 (ACE2)–solute carrier family 6 member 19 (SLC6A19) dimer. Using this quantitative matrix, we elucidated 47 potential functional missense variants from genomic databases within ACE2/SLC6A19/transmembrane serine protease 2 (TMPRSS2), warranting genomic enrichment analyses in SARS-CoV-2 patients. These variants had ultralow frequency but existed in males hemizygous for ACE2. Two ACE2 noncoding variants (rs4646118 and rs143185769) present in ~9% of individuals of African descent may regulate ACE2 expression and may be associated with increased susceptibility of African Americans to SARS-CoV-2. We propose that this SARS-CoV-2 database may aid research into the ongoing pandemic.

The immune response to COVID-19 infection is variable. How COVID-19 influences clinical outcomes in hospitalized patients needs to be understood through readily obtainable biological materials, such as blood. We hypothesized that a high-density analysis of host (and pathogen) blood RNA in hospitalized patients with SARS-CoV-2 would provide mechanistic insights into the heterogeneity of response amongst COVID-19 patients when combined with advanced multidimensional bioinformatics for RNA. We enrolled 36 hospitalized COVID-19 patients (11 died) and 15 controls, collecting 74 blood PAXgene RNA tubes at multiple timepoints, one early and in 23 patients after treatment with various therapies. Total RNAseq was performed at high-density, with >160 million paired-end, 150 base pair reads per sample, representing the most sequenced bases per sample for any publicly deposited blood PAXgene tube study. There are 770 genes significantly altered in the blood of COVID-19 patients associated with antiviral defense, mitotic cell cycle, type I interferon signaling, and severe viral infections. Immune genes activated include those associated with neutrophil mechanisms, secretory granules, and neutrophil extracellular traps (NETs), along with decreased gene expression in lymphocytes and clonal expansion of the acquired immune response. Therapies such as convalescent serum and dexamethasone reduced many of the blood expression signatures of COVID-19. Severely ill or deceased patients are marked by various secondary infections, unique gene patterns, dysregulated innate response, and peripheral organ damage not otherwise found in the cohort. High-density transcriptomic data offers shared gene expression signatures, providing unique insights into the immune system and individualized signatures of patients that could be used to understand the patient’s clinical condition. Whole blood transcriptomics provides patient-level insights for immune activation, immune repertoire, and secondary infections that can further guide precision treatment.

Ornithine decarboxylase 1 (ODC1 gene) has been linked through gain-of-function variants to a rare disease featuring developmental delay, alopecia, macrocephaly, and structural brain anomalies. ODC1 has been linked to additional diseases like cancer, with growing evidence for neurological contributions to schizophrenia, mood disorders, anxiety, epilepsy, learning, and suicidal behavior. The evidence of ODC1 connection to neural disorders highlights the need for a systematic analysis of ODC1 genotype-to-phenotype associations. An analysis of variants from ClinVar, Geno2MP, TOPMed, gnomAD, and COSMIC revealed an intellectual disability and seizure connected loss-of-function variant, ODC G84R (rs138359527, NC_000002.12:g.10444500C > T). The missense variant is found in ~1% of South Asian individuals and results in 2.5-fold decrease in enzyme function. Expression quantitative trait loci (eQTLs) reveal multiple functionally annotated, non-coding variants regulating ODC1 that associate with psychiatric/neurological phenotypes. Further dissection of RNA-Seq during fetal brain development and within cerebral organoids showed an association of ODC1 expression with cell proliferation of neural progenitor cells, suggesting gain-of-function variants with neural over-proliferation and loss-of-function variants with neural depletion. The linkage from the expression data of ODC1 in early neural progenitor proliferation to phenotypes of neurodevelopmental delay and to the connection of polyamine metabolites in brain function establish ODC1 as a bona fide neurodevelopmental disorder gene.

The SARS-CoV-2 pandemic, starting in 2019, has challenged the speed at which labs perform science, ranging from discoveries of the viral composition to handling health outcomes in humans. The small ~30kb single-stranded RNA genome of Coronaviruses makes them adept at cross species spread and drift, increasing their probability to cause pandemics. However, this small genome also allows for a robust understanding of all proteins coded by the virus. We employed protein modeling, molecular dynamic simulations, evolutionary mapping, and 3D printing to gain a full proteome and dynamicome understanding of SARS-CoV-2. The Viral Integrated Structural Evolution Dynamic Database (VIStEDD) has been established (prokoplab.com/vistedd), opening future discoveries and educational usage. In this paper, we highlight VIStEDD usage for nsp6, Nucleocapsid (N), and Spike (S) surface glycoprotein. For both nsp6 and N we reveal highly conserved surface amino acids that likely drive protein-protein interactions. In characterizing viral S protein, we have developed a quantitative dynamics cross correlation matrix insight into interaction with the ACE2/SLC6A19 dimer complex. From this quantitative matrix, we elucidated 47 potential functional missense variants from population genomic databases within ACE2/SLC6A19/TMPRSS2, warranting genomic enrichment analyses in SARS-CoV-2 patients. Moreover, these variants have ultralow frequency, but can exist as hemizygous in males for ACE2, which falls on the X-chromosome. Two noncoding variants (rs4646118 and rs143185769) found in ~9% of African descent individuals for ACE2 may regulate expression and be related to increased susceptibility of African Americans to SARS-CoV-2. This powerful database of SARS-CoV-2 can aid in research progress in the ongoing pandemic.

Introduction: The year 2020 was defined by the 29,903 base pairs of RNA that codes for the SARS-CoV-2 genome. SARS-CoV-2 infects humans to cause COVID-19, spreading from patient-to-patient yet impacts patients very divergently. Areas covered: Within this review, we address the known molecular mechanisms and supporting data for COVID-19 clinical course and pathology, clinical risk factors and molecular signatures, therapeutics of severe COVID-19, and reinfection/vaccination. Literature and published datasets were reviewed using PubMed, Google Scholar, and NCBI SRA tools. The combination of exaggerated cytokine signaling, pneumonia, NETosis, pyroptosis, thrombocytopathy, endotheliopathy, multiple organ dysfunction syndrome (MODS), and acute respiratory distress syndrome (ARDS) create a positive feedback loop of severe damage in patients with COVID-19 that impacts the entire body and may persist for months following infection. Understanding the molecular pathways of severe COVID-19 opens the door for novel therapeutic design. We summarize the current insights into pathology, risk factors, secondary infections, genetics, omics, and drugs being tested to treat severe COVID-19. Expert opinion : A growing level of support suggests the need for stronger integration of biomarkers and precision medicine to guide treatment strategies of severe COVID-19, where each patient has unique outcomes and thus require guided treatment.