Brain-protective mechanisms of autophagy associated circRNAs: Kick starting self-cleaning mode in brain cells via circRNAs as a potential therapeutic approach for neurodegenerative diseases

Altered autophagy is a hallmark of neurodegeneration but how autophagy is regulated in the brain and dysfunctional autophagy leads to neuronal death has remained cryptic. Being a key cellular waste-recycling and housekeeping system, autophagy is implicated in a range of brain disorders and altering autophagy flux could be an effective therapeutic strategy and has the potential for clinical applications down the road. Tight regulation of proteins and organelles in order to meet the needs of complex neuronal physiology suggests that there is distinct regulatory pattern of neuronal autophagy as compared to non-neuronal cells and nervous system might have its own separate regulator of autophagy. Evidence has shown that circRNAs participates in the biological processes of autophagosome assembly. The regulatory networks between circRNAs, autophagy, and neurodegeneration remains unknown and warrants further investigation. Understanding the interplay between autophagy, circRNAs and neurodegeneration requires a knowledge of the multiple steps and regulatory interactions involved in the autophagy pathway which might provide a valuable resource for the diagnosis and therapy of neurodegenerative diseases. In this review, we aimed to summarize the latest studies on the role of brain-protective mechanisms of autophagy associated circRNAs in neurodegenerative diseases (including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, Spinal Muscular Atrophy, Amyotrophic Lateral Sclerosis, and Friedreich’s ataxia) and how this knowledge can be leveraged for the development of novel therapeutics against them. Autophagy stimulation might be potential one-size-fits-all therapy for neurodegenerative disease as per considerable body of evidence, therefore future research on brain-protective mechanisms of autophagy associated circRNAs will illuminate an important feature of nervous system biology and will open the door to new approaches for treating neurodegenerative diseases

Mapping CircRNA–miRNA–mRNA regulatory axis identifies hsa_circ_0080942 and hsa_circ_0080135 as a potential theranostic agents for SARS-CoV-2 infection

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection

SARS-CoV-2 induced cytokine storm related circRNA-miRNA-mRNA regulatory axis.

SARS-CoV-2 induced cytokine storm related circRNA-miRNA-mRNA regulatory axis.</p

Using circRNA based therapeutics to mitigate cytokine storm syndrome induced by SARS-CoV-2.

Using circRNA based therapeutics to mitigate cytokine storm syndrome induced by SARS-CoV-2.</p

List of all softwares and tools utilized in the current study.

List of all softwares and tools utilized in the current study.</p

Gene ontology analysis of differentially expressed genes.

Top GO terms with lowest P-values in cellular component, molecular function, and biological process were shown, respectively.</p

Venn diagram of overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets.

a) Overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets (whole genes). b) Overlapped differentially expressed circRNAs among circRNAs of circRNA datasets, miRNA datasets and mRNA datasets (cytokine storm related mRNAs).</p

List of count of differentially expressed RNAs and their predicted targets.

List of count of differentially expressed RNAs and their predicted targets.</p

KEGG analysis of 15 cytokine storm related genes.

Non-coding RNAs (ncRNAs) can control the flux of genetic information; affect RNA stability and play crucial roles in mediating epigenetic modifications. A number of studies have highlighted the potential roles of both virus-encoded and host-encoded ncRNAs in viral infections, transmission and therapeutics. However, the role of an emerging type of non-coding transcript, circular RNA (circRNA) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has not been fully elucidated so far. Moreover, the potential pathogenic role of circRNA-miRNA-mRNA regulatory axis has not been fully explored as yet. The current study aimed to holistically map the regulatory networks driven by SARS-CoV-2 related circRNAs, miRNAs and mRNAs to uncover plausible interactions and interplay amongst them in order to explore possible therapeutic options in SARS-CoV-2 infection. Patient datasets were analyzed systematically in a unified approach to explore circRNA, miRNA, and mRNA expression profiles. CircRNA-miRNA-mRNA network was constructed based on cytokine storm related circRNAs forming a total of 165 circRNA-miRNA-mRNA pairs. This study implies the potential regulatory role of the obtained circRNA-miRNA-mRNA network and proposes that two differentially expressed circRNAs hsa_circ_0080942 and hsa_circ_0080135 might serve as a potential theranostic agents for SARS-CoV-2 infection. Collectively, the results shed light on the functional role of circRNAs as ceRNAs to sponge miRNA and regulate mRNA expression during SARS-CoV-2 infection.</div

The cytoHubba plug-in in Cytoscape was used to search the list of top 10 genes from the PPI network with node degrees indicating hub differentially expressed genes, including STAT1, RSAD2, IFIT1, IFIT3, IFIT2, DDX58, OAS2, MX2, IFI44 and IFI44L.

The cytoHubba plug-in in Cytoscape was used to search the list of top 10 genes from the PPI network with node degrees indicating hub differentially expressed genes, including STAT1, RSAD2, IFIT1, IFIT3, IFIT2, DDX58, OAS2, MX2, IFI44 and IFI44L.</p