A proposed molecular mechanism for pathogenesis of severe RNA-viral pulmonary infections

The effect of mesenchymal stem cells administration on DNA repair gene expressions in critically ill COVID-19 patients: prospective controlled study

When the studies are evaluated, immunomodulatory effect of MSCs, administration in critically ill patients, obstacle situations in use and side effects, pulmonary fibrosis prevention, which stem cells and their products, regeneration effect, administration route, and dosage are listed under the main heading like. The effect of MSC administration on DNA repair genes in COVID-19 infection is unknown. Our aim is to determine the effect of mesenchymal stem cells (MSCs) therapy applied in critically ill patients with coronavirus infection on DNA repair pathways and genes associated with those pathways. Patients (n = 30) divided into two equal groups. Group-1: Patients in a critically ill condition, Group-2: Patients in critically ill condition and transplanted MSCs. The mechanism was investigated in eleven genes of five different pathways; Base excision repair: PARP1, Nucleotide excision repair (NER): RAD23B and ERCC1, Homologous recombinational repair (HR): ATM, RAD51, RAD52 and WRN, Mismatch repair (MMR): MLH1, MSH2, and MSH6, Direct reversal repair pathway: MGMT. It was found that MSCs application had a significant effect on 6 genes located in 3 different DNA damage response pathways. These are NER pathway genes; RAD23 and ERCC1, HR pathway genes; ATM and RAD51, MMR pathway genes; MSH2 and MSH6 (p < 0.05). Two main points were shown. First, as a result of cellular damage in critical patients with COVID-19, DNA damage occurs and then DNA repair pathways and genes are activated in reaction to this situation. Second, administration of MSC to patients with COVID-19 infection plays a positive role by increasing the expression of DNA repair genes located in DNA damage pathways.

The consequences of viral infection on host DNA damage response: a focus on SARS-CoVs

DNA damage and genome instability in host cells are introduced by many viruses during their life cycles. Severe acute respiratory syndrome coronaviruses (SARS-CoVs) manipulation of DNA damage response (DDR) is an important area of research that is still understudied. Elucidation of the direct and indirect interactions between SARS-CoVs and DDR not only provides important insights into how the viruses exploit DDR pathways in host cells but also contributes to our understanding of their pathogenicity. Here, we present the known interactions of both SARS-CoV and SARS-CoV-2 with DDR pathways of the host cells, to further understand the consequences of infection on genome integrity. Since this area of research is in its early stages, we try to connect the unlinked dots to speculate and propose different consequences on DDR mechanisms. This review provides new research scopes that can be further investigated in vitro and in vivo, opening new avenues for the development of anti-SARS-CoV-2 drugs.

Targeting CK2 mediated signaling to impair/tackle SARS-CoV-2 infection: a computational biology approach

BACKGROUND

Similarities in the hijacking mechanisms used by SARS-CoV-2 and several types of cancer, suggest the repurposing of cancer drugs to treat Covid-19. CK2 kinase antagonists have been proposed for cancer treatment. A recent study in cells infected with SARS-CoV-2 found a significant CK2 kinase activity, and the use of a CK2 inhibitor showed antiviral responses. CIGB-300, originally designed as an anticancer peptide, is an antagonist of CK2 kinase activity that binds to the CK2 phospho-acceptor sites. Recent preliminary results show the antiviral activity of CIGB-300 using a surrogate model of coronavirus. Here we present a computational biology study that provides evidence, at the molecular level, of how CIGB-300 may interfere with the SARS-CoV-2 life cycle within infected human cells.

METHODS

Sequence analyses and data from phosphorylation studies were combined to predict infection-induced molecular mechanisms that can be interfered by CIGB-300. Next, we integrated data from multi-omics studies and data focusing on the antagonistic effect on the CK2 kinase activity of CIGB-300. A combination of network and functional enrichment analyses was used.

RESULTS

Firstly, from the SARS-CoV studies, we inferred the potential incidence of CIGB-300 in SARS-CoV-2 interference on the immune response. Afterwards, from the analysis of multiple omics data, we proposed the action of CIGB-300 from the early stages of viral infections perturbing the virus hijacking of RNA splicing machinery. We also predicted the interference of CIGB-300 in virus-host interactions that are responsible for the high infectivity and the particular immune response to SARS-CoV-2 infection. Furthermore, we provided evidence of how CIGB-300 may participate in the attenuation of phenotypes related to muscle, bleeding, coagulation and respiratory disorders.

CONCLUSIONS

Our computational analysis proposes putative molecular mechanisms that support the antiviral activity of CIGB-300.

Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures

PURPOSE

Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning (ML) based signatures (with 8-20% misclassification rates). These signatures can quantify therapeutically relevant as well as accidental radiation exposures. The prodromal symptoms of acute radiation syndrome (ARS) overlap those present in influenza and dengue fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

METHODS

This study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-neoplastic blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to ML-based classifiers to predict radiation exposure in other hematological conditions.

RESULTS

Except for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8-54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thrombosis, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death or extrusion of DNA fragments. Riboviral infections (e.g. influenza or dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

CONCLUSIONS

This approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures.