Emerging role of microRNAs and long non-coding RNAs in COVID-19 with implications to therapeutics.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection which is commonly known as COVID-19 (COronaVIrus Disease 2019) has creeped into the human population taking tolls of life and causing tremendous economic crisis. It is indeed crucial to gain knowledge about their characteristics and interactions with human host cells. It has been shown that the majority of our genome consists of non-coding RNAs. Non-coding RNAs including micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) display significant roles in regulating gene expression in almost all cancers and viral diseases. It is intriguing that miRNAs and lncRNAs remarkably regulate the function and expression of major immune components of SARS-CoV-2. MiRNAs act via RNA interference mechanism in which they bind to the complementary sequences of the viral RNA strand, inducing the formation of silencing complex that eventually degrades or inhibits the viral RNA and viral protein expression. LncRNAs have been extensively shown to regulate gene expression in cytokine storm and thus emerges as a critical target for COVID-19 treatment. These lncRNAs also act as competing endogenous RNAs (ceRNAs) by sponging miRNAs and thus affecting the expression of downstream targets during SARS-CoV-2 infection. In this review, we extensively discuss the role of miRNAs and lncRNAs, describe their mechanism of action and their different interacting human targets cells during SARS-CoV-2 infection. Finally, we discuss possible ways how an interference with their molecular function could be exploited for new therapies against SARS-CoV-2.

Noncoding RNome as Enabling Biomarkers for Precision Health.

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

Non-coding RNAs: the silent regulators of health and diseases.

Non-coding RNAs (ncRNAs) like miRNAs, siRNA, lncRNAs, circRNAs, piRNAs, snoRNAs, snRNAs etc. form a collective group of RNAs that is instrumental to the various functions of the genome. With the advent of cutting-edge molecular biology tools and techniques, scientists have unearthed several mechanisms through which these ncRNAs act. Although our understanding may still be limited, yet scientists have been able to establish ncRNAs as major regulators of genetic inter-plays that dictate various pathophysiological conditions. This special issue of Molecular Biology Reports features a collection of research and review articles on ncRNAs and their involvement in different pathophysiological conditions that include different types of cancers. It is expected that this special issue will motivate researchers in the field to delve deeper into the world of ncRNAs and attempt to develop new diagnostic and therapeutic interventions for challenging clinical conditions.

Tangled quest of post-COVID-19 infection-caused neuropathology and what 3P nano-bio-medicine can solve?

COVID-19-caused neurological problems are the important post-CoV-2 infection complications, which are recorded in ~ 40% of critically ill COVID-19 patients. Neurodegeneration (ND) is one of the most serious complications. It is necessary to understand its molecular mechanism(s), define research gaps to direct research to, hopefully, design new treatment modalities, for predictive diagnosis, patient stratification, targeted prevention, prognostic assessment, and personalized medical services for this type of complication. Individualized nano-bio-medicine combines nano-medicine (NM) with clinical and molecular biomarkers based on omics data to improve during- and post-illness management or post-infection prognosis, in addition to personalized dosage profiling and drug selection for maximum treatment efficacy, safety with least side-effects. This review will enumerate proteins, receptors, and enzymes involved in CoV-2 entrance into the central nervous system (CNS) via the blood-brain barrier (BBB), and list the repercussions after that entry, ranging from neuroinflammation to neurological symptoms disruption mechanism. Moreover, molecular mechanisms that mediate the host effect or viral detrimental effect on the host are discussed here, including autophagy, non-coding RNAs, inflammasome, and other molecular mechanisms of CoV-2 infection neuro-affection that are defined here as hallmarks of neuropathology related to COVID-19 infection. Thus, a couple of questions are raised; for example, "What are the hallmarks of neurodegeneration during COVID-19 infection?" and "Are epigenetics promising solution against post-COVID-19 neurodegeneration?" In addition, nano-formulas might be a better novel treatment for COVID-19 neurological complications, which raises one more question, "What are the challenges of nano-bio-based nanocarriers pre- or post-COVID-19 infection?" especially in the light of omics-based changes/challenges, research, and clinical practice in the framework of predictive preventive personalized medicine (PPPM / 3P medicine).

Long noncoding RNA HULC is an independent predictor of COVID-19 severity and mortality in relation to microRNA-9 and IL-6

LncRNA HULC regulates inflammation in vascular endothelial cells resulting in their dysfunction. Endothelial dysfunction contributes to severe COVID-19. lncRNA HULC targets miRNA-9 that play roles in the pathogenesis and progression of COVID-19 through the acute inflammatory response mediated by IL-6. This study aimed to evaluate the role of IncRNA HULC, miRNA-9, and IL-6 in estimating the severity and predicting the prognosis of COVID-19. There were 38 non-severe, 38 severe COVID-19 patients, and 38 healthy controls enrolled in this study. Expression of lncRNA HULC and miRNA-9 was performed using RT-qPCR. ELISA was utilized to measure serum IL-6. Expression of lncRNA HULC and IL-6 level were increased in severe patients compared to non-severe patients and controls (p < 0.001). MiRNA-9 showed the lowest expression levels in the severe patients in comparison with non-severe patients and controls (p < 0.001) lncRNA HULC was negatively correlated with miRNA-9 (p < 0.001, r = -0.582) and positively correlated with IL-6 (p < 0.001, r = 0.567). Furthermore, miRNA-9 showed a negative correlation with IL-6 (p < 0.001, r = -0.0466). For severity prediction, lncRNA HULC expression had an adjusted OR of 52.5 (95% CI: 1.43-192.2, p = 0.031). The lncRNA HULC had an adjusted mortality hazard ratio of 1.9 (95% CI: 1.02-3.56, p = 0.043) after the adjustment of IL-6. So, in COVID-19 patients, the lncRNA HULC had a positive correlation with IL-6 and a negative correlation with miRNA-9. The COVID-19 severity and mortality appear to be predicted independently by the lncRNA HULC.

A novel microfluidic RNA chip for direct, single-nucleotide specific, rapid and partially-degraded RNA detection.

Direct RNA detection is critical for providing the RNA insights into gene expression profiling, noncoding RNAs, RNA-associated diseases and pathogens, without reverse transcription. However, classical RNA analysis usually requires RT-PCR, which can cause bias amplification and quantitation errors. To address this challenge, herein we report a microfluidic RNA chip (the microchip prototype) for direct RNA detection, which is primarily based on RNA extension and labeling with DNA polymerase. This detection strategy is of high specificity (discriminating against single-nucleotide differences), rapidity, accuracy, nuclease resistance, and reusability. Further, we have successfully detected disease-associated RNAs in clinical samples, demonstrating its great potentials in biomedical research and clinical diagnosis.

Genome interaction of the virus and the host genes and non-coding RNAs in SARS-CoV-2 infection.

In this review, we highlight the interaction of SARS-CoV-2 virus and host genomes, reporting the current studies on the sequence analysis of SARS-CoV-2 isolates and host genomes from diverse world populations. The main genetic variants that are present in both the virus and host genomes were particularly focused on the ACE2 and TMPRSS2 genes, and their impact on the patients' susceptibility to the virus infection and severity of the disease. Finally, the interaction of the virus and host non-coding RNAs is described in relation to their regulatory roles in target genes and/or signaling pathways critically associated with SARS-CoV-2 infection. Altogether, these studies provide a significant contribution to the knowledge of SARS-CoV-2 mechanisms of infection and COVID-19 pathogenesis. The described genetic variants and molecular factors involved in host/virus genome interactions have significantly contributed to defining patient risk groups, beyond those based on patients' age and comorbidities, and they are promising candidates to be potentially targeted in treatment strategies for COVID-19 and other viral infectious diseases.

VADR: validation and annotation of virus sequence submissions to GenBank.

BACKGROUND: GenBank contains over 3 million viral sequences. The National Center for Biotechnology Information (NCBI) previously made available a tool for validating and annotating influenza virus sequences that is used to check submissions to GenBank. Before this project, there was no analogous tool in use for non-influenza viral sequence submissions. RESULTS: We developed a system called VADR (Viral Annotation DefineR) that validates and annotates viral sequences in GenBank submissions. The annotation system is based on the analysis of the input nucleotide sequence using models built from curated RefSeqs. Hidden Markov models are used to classify sequences by determining the RefSeq they are most similar to, and feature annotation from the RefSeq is mapped based on a nucleotide alignment of the full sequence to a covariance model. Predicted proteins encoded by the sequence are validated with nucleotide-to-protein alignments using BLAST. The system identifies 43 types of "alerts" that (unlike the previous BLAST-based system) provide deterministic and rigorous feedback to researchers who submit sequences with unexpected characteristics. VADR has been integrated into GenBank's submission processing pipeline allowing for viral submissions passing all tests to be accepted and annotated automatically, without the need for any human (GenBank indexer) intervention. Unlike the previous submission-checking system, VADR is freely available (https://github.com/nawrockie/vadr) for local installation and use. VADR has been used for Norovirus submissions since May 2018 and for Dengue virus submissions since January 2019. Since March 2020, VADR has also been used to check SARS-CoV-2 sequence submissions. Other viruses with high numbers of submissions will be added incrementally. CONCLUSION: VADR improves the speed with which non-flu virus submissions to GenBank can be checked and improves the content and quality of the GenBank annotations. The availability and portability of the software allow researchers to run the GenBank checks prior to submitting their viral sequences, and thereby gain confidence that their submissions will be accepted immediately without the need to correspond with GenBank staff. Reciprocally, the adoption of VADR frees GenBank staff to spend more time on services other than checking routine viral sequence submissions.

RNA genome conservation and secondary structure in SARS-CoV-2 and SARS-related viruses: a first look.

As the COVID-19 outbreak spreads, there is a growing need for a compilation of conserved RNA genome regions in the SARS-CoV-2 virus along with their structural propensities to guide development of antivirals and diagnostics. Here we present a first look at RNA sequence conservation and structural propensities in the SARS-CoV-2 genome. Using sequence alignments spanning a range of betacoronaviruses, we rank genomic regions by RNA sequence conservation, identifying 79 regions of length at least 15 nt as exactly conserved over SARS-related complete genome sequences available near the beginning of the COVID-19 outbreak. We then confirm the conservation of the majority of these genome regions across 739 SARS-CoV-2 sequences subsequently reported from the COVID-19 outbreak, and we present a curated list of 30 "SARS-related-conserved" regions. We find that known RNA structured elements curated as Rfam families and in prior literature are enriched in these conserved genome regions, and we predict additional conserved, stable secondary structures across the viral genome. We provide 106 "SARS-CoV-2-conserved-structured" regions as potential targets for antivirals that bind to structured RNA. We further provide detailed secondary structure models for the extended 5' UTR, frameshifting stimulation element, and 3' UTR. Lastly, we predict regions of the SARS-CoV-2 viral genome that have low propensity for RNA secondary structure and are conserved within SARS-CoV-2 strains. These 59 "SARS-CoV-2-conserved-unstructured" genomic regions may be most easily accessible by hybridization in primer-based diagnostic strategies.