Group I introns are catalytic RNAs capable of excising themselves from precursor transcripts without protein-dependent splicing machinery. Their catalytic activity has been harnessed to develop programmable RNA systems with potential applications in targeted RNA repair and transcript replacement. Our research group is developing a Group I intron-based molecular switch that activates translation of a therapeutic payload upon detection of a defined RNA signature within a target cell.
One of the significant challenges facing these technologies is the inefficient translation of Group I intron-spliced transcripts in mammalian cells. We and others have observed that, despite accurate self-splicing and comparable RNA abundance, these transcripts produce approximately 50- to 100-fold less protein than expected. This discrepancy suggests that self-spliced transcripts are recognised by an uncharacterised mammalian RNA quality-control or translational-suppression pathway. To investigate the underlying molecular mechanism, in collaboration with the Burr laboratory, we conducted a genome-wide CRISPR knockout screen in mammalian cells expressing a Group I intron reporter. Cells exhibiting increased reporter protein expression were isolated, and enriched gene knockouts were identified to reveal candidate regulators of the translational repression. This poster will present the results of this screen and subsequent validation experiments aimed at defining the cellular pathways that recognise and regulate Group I intron-spliced transcripts.
This work advances our understanding of how mammalian cells recognise and regulate highly structured, foreign or otherwise unconventional RNAs. Defining pathways that establish persistent translational repression may reveal general principles governing how cells distinguish endogenous transcripts from structurally unusual RNAs without promoting their degradation. These insights may also support the rational design of Group I intron-based therapeutics that evade inhibitory quality-control pathways and achieve more efficient payload expression.