Fine-tuning self-amplifying RNA: unlocking the impact of codon optimization and promoter selection

Introduction: Self-amplifying RNA (saRNA) technology is transforming vaccine and therapeutic development by enabling scalable protein expression.Optimizing its expression requires a deep understanding of genetic design principles, such as codon usage and promoter dynamics.Objectives: This study aimed to explore how these factors influence the expression efficiency of an eGFPencoding saRNA to optimize saRNA platforms. Methodology:We investigated the interplay between codon optimization and subgenomic promoter selection in driving saRNA expression.Three saRNA constructs developed by LATIM were evaluated: V1 (non-optimized, with native TC83 nonstructural proteins [NSPs] and subgenomic promoter 1), V8, and V10 (both with varying levels of codon optimization in NSPs and subgenomic promoter 2. saRNA was synthesized using the MEGAscript kit with post-transcriptional and/or co-transcriptional capping to enhance stability and translation.Transfections were performed in HEK293-derived cells using the TransIT-mRNA reagent, and fluorescence microscopy images were obtained with the EVOS imaging system to assess eGFP expression levels.Results: Results showed that V1 exhibited significantly higher eGFP expression compared to V8 and V10, highlighting the crucial role of native NSP sequences and promoter selection in maximizing translation efficiency.In contrast, constructs with codon-optimized NSPs and subgenomic promoter 2 displayed reduced fluorescence, suggesting that excessive codon optimization disrupts saRNA functionality.To further analyze, we conducted in silico analysis using the Codon Adaptation Index (CAI), comparing our constructs to ARCT-154, a clinically advanced saRNA vaccine.ARCT-154 uses a refined codon optimization strategy, maintaining the native sequence in the early NSP1 region and intensifying optimization downstream, emphasizing the importance of preserving NSP1 regions for optimal saRNA replication and protein expression. Conclusion:These findings highlight the significance of rational sequence design in optimizing saRNAbased technologies.Balancing codon optimization with strategic promoter selection is key to improving saRNA expression for vaccines and therapeutics.This study offers a roadmap for refining saRNA constructs, advancing RNA therapeutics.