Theoretical Analysis of S, M and N Structural Proteins by the Protein-RNA Recognition Code Leads to Genes/proteins that Are Relevant to the SARS-CoV-2 Life Cycle and Pathogenesis

1-L Transcription of SARS-CoV-2 Spike Protein S1 Subunit

The COVID-19 pandemic prompted rapid research on SARS-CoV-2 pathogenicity. Consequently, new data can be used to advance the molecular understanding of SARS-CoV-2 infection. The present bioinformatics study discusses the "spikeopathy" at the molecular level and focuses on the possible post-transcriptional regulation of the SARS-CoV-2 spike protein S1 subunit in the host cell/tissue. A theoretical protein-RNA recognition code was used to check the compatibility of the SARS-CoV-2 spike protein S1 subunit with mRNAs in the human transcriptome (1-L transcription). The principle for this method is elucidated on the defined RNA binding protein GEMIN5 (gem nuclear organelle-associated protein 5) and RNU2-1 (U2 spliceosomal RNA). Using the method described here, it was shown that 45% of the genes/proteins identified by 1-L transcription of the SARS-CoV-2 spike protein S1 subunit are directly linked to COVID-19, 39% are indirectly linked to COVID-19, and 16% cannot currently be associated with COVID-19. The identified genes/proteins are associated with stroke, diabetes, and cardiac injury.

SARS-CoV-2 Covid-19 Infection During Pregnancy and Differential DNA Methylation in Human Cord Blood Cells From Term Neonates

Background

The global pandemic of coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). About 18.4% of total Covid-19 cases were reported in children. Even though vertical transmission from mother to infant is likely to occur at a low rate, exposure to COVID-19 during fetal life may alter DNA methylation patterns with potential long-term effects.

Objective

To determine if COVID-19 infection during pregnancy alters the DNA methylation patterns in umbilical cord blood cells from term infants and to identify potential pathways and genes affected by exposure to COVID-19 infection.

Methods

Umbilical cord blood was collected from 8 infants exposed to COVID-19 during pregnancy and 8 control infants with no COVID-19 exposure. Genomic DNA was isolated from umbilical cord blood cells and genome-wide DNA methylation was performed using Illumina Methylation EPIC Array.

Results

119 differentially methylated loci were identified at the FDR level of 0.20 (64 hypermethylated loci and 55 hypomethylated loci) in umbilical cord blood cells of COVID-19 exposed neonates compared to the control group. Important canonical pathways identified by Ingenuity Pathway Analysis (IPA) were related to stress response (corticotropin releasing hormone signaling, glucocorticoid receptor signaling, and oxytocin in brain signaling pathway), and cardiovascular disease and development (nitric oxide signaling in the cardiovascular system, apelin cardiomyocyte signaling pathways, factors promoting cardiogenesis, and renin-angiotensin signaling). The genes affected by the differential methylations were associated with cardiac, renal, hepatic, neurological diseases, developmental and immunological disorders.

Conclusions

COVID-19 induces differential DNA methylation in umbilical cord blood cells. The differentially methylated genes may contribute to hepatic, renal, cardiac, developmental and immunological disorders in offspring born to mothers with COVID-19 infection during pregnancy, and their developmental regulation.

1-L Transcription in Alzheimer's Disease

Alzheimer's disease is a very complex disease and better explanations and models are needed to understand how neurons are affected and microglia are activated. A new model of Alzheimer's disease is presented here, the β-amyloid peptide is considered an important RNA recognition/binding peptide. 1-L transcription revealed compatible sequences with AAUAAA (PAS signal) and UUUC (class III ARE rich in U) in the Aβ peptide, supporting the peptide-RNA regulatory model. When a hypothetical model of fibril selection with the prionic character of amyloid assemblies is added to the peptide-RNA regulatory model, the downregulation of the PI3K-Akt pathway and the upregulation of the PLC-IP3 pathway are well explained. The model explains why neurons are less protected from inflammation and why microglia are activated; why mitochondria are destabilized; why the autophagic flux is destabilized; and why the post-transcriptional attenuation of the axonal signal "noise" is interrupted. For example, the model suggests that Aβ peptide may post-transcriptionally control ELAVL2 (ELAV-like RNA binding protein 2) and DCP2 (decapping mRNA protein 2), which are known to regulate RNA processing, transport, and stability.

Transcription of the Envelope Protein by 1-L Protein-RNA Recognition Code Leads to Genes/Proteins That Are Relevant to the SARS-CoV-2 Life Cycle and Pathogenesis

The theoretical protein-RNA recognition code was used in this study to research the compatibility of the SARS-CoV-2 envelope protein (E) with mRNAs in the human transcriptome. According to a review of the literature, the spectrum of identified genes showed that the virus post-transcriptionally promotes or represses the genes involved in the SARS-CoV-2 life cycle. The identified genes/proteins are also involved in adaptive immunity, in the function of the cilia and wound healing (EMT and MET) in the pulmonary epithelial tissue, in Alzheimer's and Parkinson's disease and in type 2 diabetes. For example, the E-protein promotes BHLHE40, which switches off the IL-10 inflammatory "brake" and inhibits antiviral THαβ cells. In the viral cycle, E supports the COPII-SCAP-SREBP-HSP90α transport complex by the lowering of cholesterol in the ER and by the repression of insulin signaling, which explains the positive effect of HSP90 inhibitors in COVID-19 (geldanamycin), and E also supports importin α/β-mediated transport to the nucleus, which explains the positive effect of ivermectin, a blocker of importins α/β. In summary, transcription of the envelope protein by the 1-L protein-RNA recognition code leads to genes/proteins that are relevant to the SARS-CoV-2 life cycle and pathogenesis.