Design of antiviral AGO2-dependent short hairpin RNAs
The increasing emergence and re-emergence of RNA virus outbreaks underlines the urgent need to develop effective antivirals. RNA interference (RNAi) is a sequence-specific gene silencing mechanism that is triggered by small interference RNAs (siRNAs) or short hairpin RNAs (shRNAs), which exhibit significant promise for antiviral therapy. AGO2-dependent shRNA (agshRNA) generates a single-stranded guide RNA effector and presents significant advantages over traditional siRNA and shRNA. In this study, we applied a logistic regression algorithm to a previously published chemically siRNA efficacy dataset and built a machine learning-based algorithm with high predictive power. Using this algorithm, we designed siRNA sequences targeting diverse RNA viruses, including human enterovirus A71 (EV71), Zika virus (ZIKV), dengue virus 2 (DENV2), mouse hepatitis virus (MHV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and developed them into agshRNAs according to the rule of agshRNA design. These agshRNAs inhibited viral replication in infected cells and their efficiencies of antiviral effects displayed a consistent trend with the score ranking of siRNA sequences predicted by the algorithm. Using the agshRNA targeting EV71 as an example, we showed that the anti-EV71 effect of agshRNA was more potent compared with the corresponding siRNA and shRNA. Moreover, the antiviral effect of agshRNA is dependent on AGO2-processed guide RNA, which can load into the RISC. We also confirmed the antiviral effect of agshRNA in vivo. Together, this work develop a novel approach that combines machine learning-based algorithm and agshRNA design to custom design antiviral agshRNAs with high efficiency. Overall design: To investage sequence feature of processed agshRNA and the loading of agshRNA in AGO2 cell, 293T were transfected with different agshRNAs. Small RNA sequencing were performed to detect processed agshRNA in Input sample and IP sample. To investage the influence of agshRNA designed by our resarch, 293T cell were transfected with agshRNA and agshNC. Transcriptome sequencing was performed to detect the change in cells.