Scaling Peptide-Barcode Approach for Parallel Evaluation of Protein Expression from Multiple mRNA Variants

Messenger RNA (mRNA) technology has revolutionized therapeutic design, yet optimizing untranslated regions (UTRs) and synonymous codons still depends on low-throughput, trial-and-error workflows. We previously reported a peptide-barcode method that quantifies protein expression from pooled mRNAs, but only two variants were tested. For this study, we extend the approach to nine mRNA variants produced by combining three different 5' UTRs with three codon-modified enhanced green fluorescent protein (eGFP) coding sequences. All nine template plasmids were assembled in a single Gibson reaction, transcribed together, and cotransfected into HEK293T cells. At least five distinct ten-residue peptide barcodes were assigned to each mRNA variant in the pooled library. After translation, the barcodes were enzymatically released and analyzed in a single liquid chromatography-mass spectrometry (LC-MS) run. To correct for differences in transcript abundance within the pool, the LC-MS signals were normalized to the corresponding barcode read counts obtained by nanopore sequencing of the same pooled mRNA library. Averaging the barcode signals assigned to each variant partially reduced barcode-specific bias and yielded a moderate correlation coefficient of 0.53 relative to the eGFP fluorescence measured from nine separate single-transfection controls. While not intended for precise quantification, the results indicate that peptide barcoding can discriminate variants with higher protein output within a single pooled experiment and is useful for first-pass, rank-order screening. Thus, this peptide-barcode method provides a scalable route toward higher-throughput optimization of larger mRNA libraries.