ASPsiRNA: A Resource of ASP-siRNAs Having Therapeutic Potential for Human Genetic Disorders and Algorithm for Prediction of Their Inhibitory Efficacy

Unlocking the potential of RNA-based therapeutics in the lung: current status and future directions

Awareness of RNA-based therapies has increased after the widespread adoption of mRNA vaccines against SARS-CoV-2 during the COVID-19 pandemic. These mRNA vaccines had a significant impact on reducing lung disease and mortality. They highlighted the potential for rapid development of RNA-based therapies and advances in nanoparticle delivery systems. Along with the rapid advancement in RNA biology, including the description of noncoding RNAs as major products of the genome, this success presents an opportunity to highlight the potential of RNA as a therapeutic modality. Here, we review the expanding compendium of RNA-based therapies, their mechanisms of action and examples of application in the lung. The airways provide a convenient conduit for drug delivery to the lungs with decreased systemic exposure. This review will also describe other delivery methods, including local delivery to the pleura and delivery vehicles that can target the lung after systemic administration, each providing access options that are advantageous for a specific application. We present clinical trials of RNA-based therapy in lung disease and potential areas for future directions. This review aims to provide an overview that will bring together researchers and clinicians to advance this burgeoning field.

Epigenome editing in cancer: Advances and challenges for potential therapeutic options

Cancers are diseases caused by genetic and non-genetic environmental factors. Epigenetic alterations, some attributed to non-genetic factors, can lead to cancer development. Epigenetic changes can occur in tumor suppressors or oncogenes, or they may contribute to global cell state changes, making cells abnormal. Recent advances in gene editing technology show potential for cancer treatment. Herein, we will discuss our current knowledge of epigenetic alterations occurring in cancer and epigenetic editing technologies that can be applied to developing therapeutic options.

Development of super-specific epigenome editing by targeted allele-specific DNA methylation

BACKGROUND

Epigenome editing refers to the targeted reprogramming of genomic loci using an EpiEditor which may consist of an sgRNA/dCas9 complex that recruits DNMT3A/3L to the target locus. Methylation of the locus can lead to a modulation of gene expression. Allele-specific DNA methylation (ASM) refers to the targeted methylation delivery only to one allele of a locus. In the context of diseases caused by a dominant mutation, the selective DNA methylation of the mutant allele could be used to repress its expression but retain the functionality of the normal gene.

RESULTS

To set up allele-specific targeted DNA methylation, target regions were selected from hypomethylated CGIs bearing a heterozygous SNP in their promoters in the HEK293 cell line. We aimed at delivering maximum DNA methylation with highest allelic specificity in the targeted regions. Placing SNPs in the PAM or seed regions of the sgRNA, we designed 24 different sgRNAs targeting single alleles in 14 different gene loci. We achieved efficient ASM in multiple cases, such as ISG15, MSH6, GPD1L, MRPL52, PDE8A, NARF, DAP3, and GSPT1, which in best cases led to five to tenfold stronger average DNA methylation at the on-target allele and absolute differences in the DNA methylation gain at on- and off-target alleles of > 50%. In general, loci with the allele discriminatory SNP positioned in the PAM region showed higher success rate of ASM and better specificity. Highest DNA methylation was observed on day 3 after transfection followed by a gradual decline. In selected cases, ASM was stable up to 11 days in HEK293 cells and it led up to a 3.6-fold change in allelic expression ratios.

CONCLUSIONS

We successfully delivered ASM at multiple genomic loci with high specificity, efficiency and stability. This form of super-specific epigenome editing could find applications in the treatment of diseases caused by dominant mutations, because it allows silencing of the mutant allele without repression of the expression of the normal allele thereby minimizing potential side-effects of the treatment.

Major depressive disorder and chronic gastritis: A bidirectional two-sample Mendelian randomization study

OBJECTIVE

Observational studies have posited a strong correlation between chronic gastritis (CG) and major depressive disorder (MDD), but the nature of this association remains uncertain, owing to the challenges of establishing the temporal sequence. The present study sought to elucidate the elusive relationship between CG and MDD by employing a bidirectional two-sample Mendelian randomization (MR) approach.

METHODS

We extracted instrumental variants for MDD and CG from published genome-wide association study data, focusing on individuals of primarily European descent. A comprehensive suite of MR estimations and sensitivity analyses was performed to ensure the robustness of the findings. Each outcome database was analyzed separately in both directions.

RESULTS

For MDD and CG, 221 and 5 genetic variants, respectively, were selectively extracted as instrumental variants. The results suggest that MDD is causally associated with an elevated risk of CG (IVW: 23andMe, OR = 1.33; 95% CI = 1.15-1.54; p = 1.06 × 10-4); conversely, no strong evidence was found to corroborate that CG exerts a causal effect on the incidence of MDD (IVW: OR = 1.01; 95% CI = 0.95-1.07; p = 0.68).

CONCLUSIONS

These findings provide novel insights into the causal relationship between CG and MDD, which may have implications for clinical decision-making in patients with MDD and CG.

Boosting therapeutic efficacy of mesenchymal stem cells in pulmonary fibrosis: The role of genetic modification and preconditioning strategies

Pulmonary fibrosis (PF) is the end stage of severe lung diseases, in which the lung parenchyma is replaced by fibrous scar tissue. The result is a remarkable reduction in pulmonary compliance, which may lead to respiratory failure and even death. Idiopathic pulmonary fibrosis (IPF) is the most prevalent form of PF, with no reasonable etiology. However, some factors are believed to be behind the etiology of PF, including prolonged administration of several medications (e.g., bleomycin and amiodarone), environmental contaminant exposure (e.g., gases, asbestos, and silica), and certain systemic diseases (e.g., systemic lupus erythematosus). Despite significant developments in the diagnostic approach to PF in the last few years, efforts to find more effective treatments remain challenging. With their immunomodulatory, anti-inflammatory, and anti-fibrotic properties, stem cells may provide a promising approach for treating a broad spectrum of fibrotic conditions. However, they may lose their biological functions after long-term in vitro culture or exposure to harsh in vivo situations. To overcome these limitations, numerous modification techniques, such as genetic modification, preconditioning, and optimization of cultivation methods for stem cell therapy, have been adopted. Herein, we summarize the previous investigations that have been designed to assess the effects of stem cell preconditioning or genetic modification on the regenerative capacity of stem cells in PF.

AsCRISPR: A Web Server for Allele-Specific Single Guide RNA Design in Precision Medicine

Allele-specific genomic targeting by CRISPR is a versatile strategy that has been increasingly exploited not only in treating inherited dominant diseases and mutation-driven cancers, but also in other important fields such as genome imprinting, haploinsufficiency, and genome loci imaging. Despite its tremendous utilities, few bioinformatic tools have been implemented for the allele-specific purpose of CRISPR. We thus developed AsCRISPR (Allele-specific CRISPR), a comprehensive web tool to aid the design of short-guide RNA (sgRNA) sequences that can discriminate between alleles. AsCRISPR allows users to analyze both their own identified variants and heterozygous single nucleotide polymorphisms and, importantly, output the candidate sgRNAs and their quality control information. To facilitate targeting dominant diseases, AsCRISPR analyzed dominant single nucleotide variants (SNVs) retrieved from ClinVar and OMIM databases, and generated a dominant database of candidate-discriminating sgRNAs that may specifically target the alternative allele for each dominant SNV site. Moreover, a validated database was established, which manually curated the discriminating sgRNAs that were experimentally validated in the mounting literature for multiple allele-specific purposes.

Allele-specific genome targeting in the development of precision medicine

The CRISPR-based genome editing holds immense potential to fix disease-causing mutations, however, must also handle substantial natural genetic variations between individuals. Previous studies have shown that mismatches between the single guide RNA (sgRNA) and genomic DNA may negatively impact sgRNA efficiencies and lead to imprecise specificity prediction. Hence, the genetic variations bring about a great challenge for designing platinum sgRNAs in large human populations. However, they also provide a promising entry for designing allele-specific sgRNAs for the treatment of each individual. The CRISPR system is rather specific, with the potential ability to discriminate between similar alleles, even based on a single nucleotide difference. Genetic variants contribute to the discrimination capabilities, once they generate a novel protospacer adjacent motif (PAM) site or locate in the seed region near an available PAM. Therefore, it can be leveraged to establish allele-specific targeting in numerous dominant human disorders, by selectively ablating the deleterious alleles. So far, allele-specific CRISPR has been increasingly implemented not only in treating dominantly inherited diseases, but also in research areas such as genome imprinting, haploinsufficiency, spatiotemporal loci imaging and immunocompatible manipulations. In this review, we will describe the working principles of allele-specific genome manipulations by virtue of expanding engineering tools of CRISPR. And then we will review new advances in the versatile applications of allele-specific CRISPR targeting in treating human genetic diseases, as well as in a series of other interesting research areas. Lastly, we will discuss their potential therapeutic utilities and considerations in the era of precision medicine.

Computational Identification of piRNAs Using Features Based on RNA Sequence, Structure, Thermodynamic and Physicochemical Properties

Rationale

PIWI-interacting RNAs (piRNAs) are a recently-discovered class of small non-coding RNAs (ncRNAs) with a length of 21-35 nucleotides. They play a role in gene expression regulation, transposon silencing, and viral infection inhibition. Once considered as "dark matter" of ncRNAs, piRNAs emerged as important players in multiple cellular functions in different organisms. However, our knowledge of piRNAs is still very limited as many piRNAs have not been yet identified due to lack of robust computational predictive tools.

Methods

To identify novel piRNAs, we developed piRNAPred, an integrated framework for piRNA prediction employing hybrid features like k-mer nucleotide composition, secondary structure, thermodynamic and physicochemical properties. A non-redundant dataset (D³³⁴⁹ or D^1684p+1665n) comprising 1684 experimentally verified piRNAs and 1665 non-piRNA sequences was obtained from piRBase and NONCODE, respectively. These sequences were subjected to the computation of various sequence-structure based features in binary format and trained using different machine learning techniques, of which support vector machine (SVM) performed the best.

Results

During the ten-fold cross-validation approach (10-CV), piRNAPred achieved an overall accuracy of 98.60% with Mathews correlation coefficient (MCC) of 0.97 and receiver operating characteristic (ROC) of 0.99. Furthermore, we achieved a dimensionality reduction of feature space using an attribute selected classifier.

Conclusion

We obtained the highest performance in accurately predicting piRNAs as compared to the current state-of-the-art piRNA predictors. In conclusion, piRNAPred would be helpful to expand the piRNA repertoire, and provide new insights on piRNA functions.

A review on current status of antiviral siRNA

Viral diseases like influenza, AIDS, hepatitis, and Ebola cause severe epidemics worldwide. Along with their resistant strains, new pathogenic viruses continue to be discovered so creating an ongoing need for new antiviral treatments. RNA interference is a cellular gene‐silencing phenomenon in which sequence‐specific degradation of target mRNA is achieved by means of complementary short interfering RNA (siRNA) molecules. Short interfering RNA technology affords a potential tractable strategy to combat viral pathogenesis because siRNAs are specific, easy to design, and can be directed against multiple strains of a virus by targeting their conserved gene regions. In this review, we briefly summarize the current status of siRNA therapy for representative examples from different virus families. In addition, other aspects like their design, delivery, medical significance, bioinformatics resources, and limitations are also discussed.

saRNAdb: Resource of Small Activating RNAs for Up-regulating the Gene Expression

RNA activation (RNAa) is the process of enhancing selective gene expression at transcriptional level using double-stranded RNAs, targeting gene promoter. These RNA molecules are usually 21 nucleotides long and termed as small activating RNAs (saRNAs). They are involved in gene regulation, epigenetics, gain-of-function studies and have potential therapeutic applications for various diseases especially cancer. RNAa is opposite to RNA interference in functionality; however, both processes share some protein machinery. There are many RNA interference centered online resources but no one for saRNAs; therefore, we developed "saRNAdb" database (http://bioinfo.imtech.res.in/manojk/sarna/). It contains 2150 manually curated saRNA entries with detailed information about their nucleotide sequences, activities, corresponding target gene, promoter and other experimental data. Besides, saRNA-promoter binding location, predicted saRNA features, tools (off-target, map) and RNAa-related proteins with their interacting partners are provided. saRNAdb is expected to assist in RNA research especially for nucleic acid-based therapeutics development.