Precise editing of cellular transcriptomes with sequence-specific RNA targeting tools is crucial for comprehending biological and pathological processes and has the potential to transform various genetic disorders including cancers.
A novel class of prokaryotic RNAi called CRISPR-Cas13 has been recently discovered. These are programmable RNA-guided-RNA-targeting enzymes that exclusively degrade single-stranded RNAs. The long spacer sequence (22-30nt) of Cas13 offers rigorous target recognition compared to classical eukaryotic RNAi and Cas9 tools. Despite this stringent target recognition, some Cas13 orthologues were reported to exhibit collateral nuclease activity that mediates indiscriminate degradation of nearby host RNA molecules, which causes concerns for the system’s specificity. This process was described in bacteria and further harnessed as an ultrasensitive RNA detection tool in vitro. However, human cells have a more complex cellular organization and compartmentalized architecture, which may affect the on-target and collateral activities of Cas13. Currently, the extent of different Cas13 orthologues’ collateral activities in human cells remains unclear in literature.
Here, we aimed to investigate the targeting efficiency and specificity of different Cas13 orthologues in human cells. We used quantitative fluorescence, flow cytometry, cell viability assays, western blotting, transcriptomics, and mass spectrometry to evaluate the on-target, off-target, and collateral nuclease activities of Cas13 enzymes. All Cas13 orthologues we tested demonstrated high on-target silencing activity. Notably, we observed that RfxCas13b displayed a prominent collateral activity directed only against exogenous over-expressed transcripts, while not affecting endogenous protein expression. In contrast, PspCas13b and LwaCas13a orthologues exhibited potent degradation of the target RNA with no detectable collateral activity.
Overall, this study revealed Cas13 enzymes with high targeting fidelity in human cells, highlighting their potential to target oncogenic driver transcripts in cancer research, therapeutics, and beyond. This highly specific and programmable RNA targeting tool can potentially fill the gap in current cancer therapeutics for undruggable targets.