Measuring Live-Cell mRNA Translational Dynamics with Split Luminescent Tagging in HEK293 Cells

The swift vaccine development to combat COVID-19 illustrated the potential for messenger RNA (mRNA) therapeutics to transform drug development. Like mature mRNA, in vitro transcribed mRNA possesses the same elements including a 5' cap, untranslated regions (UTRs), coding sequence and a poly(A) tail. Previous work studying the effects these components have on mRNA translation has primarily utilized highly engineered reporter proteins which exhibit efficient translation and protein stability. With the structural elements of each mRNA differentially affecting their translation, it is imperative to identify the optimal design relevant to the therapeutic protein of interest (POI). To enable POI translation characterization, a split luciferase complementation system was employed. A short peptide tag (HiBiT), which can be fused to either terminus of the POI, associates with its complementary heterodimer (LgBiT) to reconstitute enzymatic activity in the presence of a cell-permeable substrate. To date, split luminescent tagging has been primarily used for high-throughput protein turnover studies. We have previously demonstrated how split luminescent tagging can be employed to enable high-throughput quantification of mRNA translation temporally in cellulo in HEK293 cells constitutively expressing the complementary heterodimer. Here, we further demonstrate the versatility of the assay and detail how this assay can be employed for optimizing in vitro transcription to reduce costs. The assay system can uniquely distinguish alterations in structural components whilst highlighting the effects of coding sequence optimization using non-engineered genes. Additionally, we demonstrate that a 4-fold reduction in 5' cap concentration for in vitro transcription results in equivalent translation in cellulo. These findings illustrate how split luminescent tagging can be easily integrated into the mRNA therapeutic workflow, enabling monitoring of real-time mRNA-driven protein expression dynamics in cellulo thereby offering a versatile method for the advancement of mRNA-based therapeutics.