SSD - a free software for designing multimeric mono-, bi- and trivalent shRNAs

Multifunctional rolling circle transcription-based nanomaterials for advanced drug delivery

As the up-and-comer in the development of RNA nanotechnology, RNA nanomaterials based on functionalized rolling circle transcription (RCT) have become promising carriers for drug production and delivery. This is due to RCT technology can self-produce polyvalent tandem nucleic acid prodrugs for intervention in intracellular gene expression and protein production. RNA component strands participating in de novo assembly enable RCT-based nanomaterials to exhibit good mechanical properties, biostability, and biocompatibility as delivery carriers. The biostability makes it to suitable for thermodynamically/kinetically favorable assembly, enzyme resistance and efficient expression in vivo. Controllable RCT system combined with polymers enables customizable and adjustable size, shape, structure, and stoichiometry of RNA building materials, which provide groundwork for the delivery of advanced drugs. Here, we review the assembly strategies and the dynamic regulation of RCT-based nanomaterials, summarize its functional properties referring to the bottom-up design philosophy, and describe its advancements in tumor gene therapy, synergistic chemotherapy, and immunotherapy. Last, we elaborate on the unique and practical value of RCT-based nanomaterials, namely "self-production and self-sale", and their potential challenges in nanotechnology, material science and biomedicine.

Evitar: designing anti-viral RNA therapies against future RNA viruses

MOTIVATION

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the threat of emerging respiratory viruses and has exposed the lack of availability of off-the-shelf therapeutics against new RNA viruses. Previous research has established the potential that siRNAs and RNA-targeting CRISPR have in combating known RNA viruses. However, the feasibility and tools for designing anti-viral RNA therapeutics against future RNA viruses have not yet been established.

RESULTS

We develop the Emerging-Virus-Targeting RNA (Evitar) pipeline for designing anti-viral siRNAs and CRISPR Cas13a guide RNA (gRNA) sequences. Within Evitar, we develop Greedy Algorithm with Redundancy and Similarity-weighted Greedy Algorithm with Redundancy to enhance the performance. Time simulations using known coronavirus genomes deposited as early as 10 years prior to the COVID-19 outbreak show that at least three SARS-CoV-2-targeting siRNAs are among the top 30 pre-designed siRNAs. In addition, among the top 19 pre-designed gRNAs, there are three SARS-CoV-2-targeting Cas13a gRNAs that could be predicted using information from 2011. Before-the-outbreak design is also possible against the MERS-CoV virus and the 2009-H1N1 swine flu virus. Designed siRNAs are further shown to suppress SARS-CoV-2 viral sequences using in vitro reporter assays. Our results support the utility of Evitar to pre-design anti-viral siRNAs/gRNAs against future viruses. Therefore, we propose the development of a collection consisting of roughly 30 pre-designed, safety-tested and off-the-shelf siRNA/CRISPR therapeutics that could accelerate responses to future RNA virus outbreaks.

AVAILABILITY AND IMPLEMENTATION

Codes are available at GitHub (https://github.com/dingyaozhang/Evitar).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A small interfering RNA (siRNA) database for SARS-CoV-2

Coronavirus disease 2019 (COVID-19) rapidly transformed into a global pandemic, for which a demand for developing antivirals capable of targeting the SARS-CoV-2 RNA genome and blocking the activity of its genes has emerged. In this work, we presented a database of SARS-CoV-2 targets for small interference RNA (siRNA) based approaches, aiming to speed the design process by providing a broad set of possible targets and siRNA sequences. The siRNAs sequences are characterized and evaluated by more than 170 features, including thermodynamic information, base context, target genes and alignment information of sequences against the human genome, and diverse SARS-CoV-2 strains, to assess possible bindings to off-target sequences. This dataset is available as a set of four tables, available in a spreadsheet and CSV (Comma-Separated Values) formats, each one corresponding to sequences of 18, 19, 20, and 21 nucleotides length, aiming to meet the diversity of technology and expertise among laboratories around the world. A metadata table (Supplementary Table S1), which describes each feature, is also provided in the aforementioned formats. We hope that this database helps to speed up the development of new target antivirals for SARS-CoV-2, contributing to a possible strategy for a faster and effective response to the COVID-19 pandemic.