Identification and Characterization of Circular Intronic RNAs Derived from Insulin Gene.

Circular RNAs (circRNAs) are a large family of noncoding RNAs that have emerged as novel regulators of gene expression. However, little is known about the function of circRNAs in pancreatic ß-cells. Here, transcriptomic analysis of mice pancreatic islet RNA-sequencing data identified 77 differentially expressed circRNAs between mice fed with a normal diet and a high-fat diet. Surprisingly, multiple circRNAs were derived from the intron 2 of the preproinsulin 2 (Ins2) gene and are termed as circular intronic (ci)-Ins2. The expression of ci-Ins2 transcripts in mouse pancreatic islets, and ßTC6 cells were confirmed by reverse transcription PCR, DNA sequencing, and RNase R treatment experiments. The level of ci-Ins2 was altered in ßTC6 cells upon exposure to elevated levels of palmitate and glucose. Computational analysis predicted the interaction of several RNA-binding proteins with ci-Ins2 and their flanking region, suggesting their role in the ci-Ins2 function or biogenesis. Additionally, bioinformatics analysis predicted the association of several microRNAs with ci-Ins2. Gene ontology and pathway analysis of genes targeted by miRNAs associated with ci-Ins2 suggested the regulation of several key biological processes. Together, our findings indicate that differential expression of circRNAs, especially ci-Ins2 transcripts, may regulate ß-cell function and may play a critical role in the development of diabetes.

PCIF1 is partly cytoplasmic, dynamically localizes to stress granules and binds mRNA coding regions upon oxidative stress.

PCIF1 (Phosphorylated CTD-Interacting Factor 1) is the mRNA (2'-O-methyladenosine-N(6)-)-methyltransferase that catalyzes the formation of cap-adjacent N6,2'-O-dimethyladenosine (m6Am) by methylating adenosines at the first transcribed position of capped mRNAs. While previous studies assumed that PCIF1 was nuclear, cell fractionation and immunofluorescence both show that a population of PCIF1 is localized to the cytoplasm. Further, PCIF1 redistributes to stress granules upon oxidative stress. Immunoprecipitation studies with stressed cells show that PCIF1 also physically interacts with G3BP and other stress granule components. In addition, PCIF1 behaves as a stress granule component as it disassociates from stress granules upon recovery from stress. Overexpressing full-length PCIF1 also inhibits stress granule formation, while knocking out PCIF1 slows stress granule disassembly. Next, our enhanced crosslinking and immunoprecipitation (eCLIP) data show that PCIF1 binds mRNAs in their coding sequences rather than cap-proximal regions. Further PCIF1's association with mRNAs increased upon NaAsO2 stress. In contrast to eCLIP data, ChIP-Seq experiments show that PCIF1 is predominantly associated with transcription start sites rather than gene bodies, indicating that PCIF1's association with mature mRNA is not co-transcriptional. Collectively, our data suggest that PCIF1 has cytoplasmic RNA surveillance role(s) independent of transcription-associated cap-adjacent mRNA modification, particularly during the stress response.

The Dawning of a New Enterprise: RNA Therapeutics for the Skin.

Despite being under development for decades, RNA therapeutics have only recently emerged as viable drug platforms. The COVID-19 mRNA vaccines have demonstrated the promise and power of the platform technology. In response, novel RNA drugs are entering clinical trials at an accelerating rate. As the skin is the largest and most accessible organ, it has always been a preferred target for drug discovery. This holds true for RNA therapies as well, and multiple candidate RNA-based drugs are currently in development for an array of skin conditions. In this mini review, we catalog the RNA therapies currently in clinical trials for different dermatological diseases. We summarize the main types of RNA-related drugs and use examples of drugs currently in development to illustrate their key mechanism of action.

Cancer-Associated circRNA-miRNA-mRNA Regulatory Networks: A Meta-Analysis.

Recent advances in sequencing technologies and the discovery of non-coding RNAs (ncRNAs) have provided new insights in the molecular pathogenesis of cancers. Several studies have implicated the role of ncRNAs, including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and recently discovered circular RNAs (circRNAs) in tumorigenesis and metastasis. Unlike linear RNAs, circRNAs are highly stable and closed-loop RNA molecules. It has been established that circRNAs regulate gene expression by controlling the functions of miRNAs and RNA-binding protein (RBP) or by translating into proteins. The circRNA-miRNA-mRNA regulatory axis is associated with human diseases, such as cancers, Alzheimer's disease, and diabetes. In this study, we explored the interaction among circRNAs, miRNAs, and their target genes in various cancers using state-of-the-art bioinformatics tools. We identified differentially expressed circRNAs, miRNAs, and mRNAs on multiple cancers from publicly available data. Furthermore, we identified many crucial drivers and tumor suppressor genes in the circRNA-miRNA-mRNA regulatory axis in various cancers. Together, this study data provide a deeper understanding of the circRNA-miRNA-mRNA regulatory mechanisms in cancers.

Identification of multipotent drugs for COVID-19 therapeutics with the evaluation of their SARS-CoV2 inhibitory activity.

The SARS-CoV2 is a highly contagious pathogen that causes COVID-19 disease. It has affected millions of people globally with an average lethality of ~3%. There is an urgent need of drugs for the treatment of COVID-19. In the current studies, we have used bioinformatics techniques to screen the FDA approved drugs against nine SARS-CoV2 proteins to identify drugs for repurposing. Additionally, we analyzed if the identified molecules can also affect the human proteins whose expression in lung changed during SARS-CoV2 infection. Targeting such genes may also be a beneficial strategy to curb disease manifestation. We have identified 74 molecules that can bind to various SARS-CoV2 and human host proteins. We experimentally validated our in-silico predictions using vero E6 cells infected with SARS-CoV2 virus. Interestingly, many of our predicted molecules viz. capreomycin, celecoxib, mefloquine, montelukast, and nebivolol showed good activity (IC50) against SARS-CoV2. We hope that these studies may help in the development of new therapeutic options for the treatment of COVID-19.