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Updated: Jan 8, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

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

Shun Kumano¹, Kazuki Tanaka¹, Shoko Kawakami¹

¹Research & Development Group, Hitachi, Ltd., Tokyo 185-8601, Japan.

Analytical Chemistry

|December 17, 2025

Summary

This study enhances a peptide-barcode method for optimizing messenger RNA (mRNA) therapeutics. The improved method allows for higher-throughput screening of mRNA variants to boost protein expression efficiently.

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Last Updated: Jan 8, 2026

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Multiplexed Single Cell mRNA Sequencing Analysis of Mouse Embryonic Cells

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Published on: January 7, 2020

Area of Science:

Biotechnology
Molecular Biology
Bioinformatics

Background:

Messenger RNA (mRNA) technology offers significant therapeutic potential but faces optimization challenges.
Current methods for optimizing mRNA untranslated regions (UTRs) and codons are low-throughput and rely on trial-and-error.
Previous work introduced a peptide-barcode method for quantifying protein expression from pooled mRNAs, tested with only two variants.

Purpose of the Study:

To extend and validate a peptide-barcode method for high-throughput screening of multiple mRNA variants.
To assess the method's utility in optimizing mRNA constructs by evaluating protein expression levels.
To enable scalable optimization of larger mRNA libraries for therapeutic development.

Main Methods:

Generated nine mRNA variants by combining three 5' UTRs with three codon-modified enhanced green fluorescent protein (eGFP) coding sequences.
Assembled all nine variants in a single Gibson reaction, transcribed them together, and cotransfected into HEK293T cells.
Quantified protein expression using peptide barcodes analyzed via liquid chromatography-mass spectrometry (LC-MS), normalized to nanopore sequencing data.

Main Results:

Successfully assigned at least five distinct peptide barcodes to each of the nine mRNA variants in a pooled library.
Normalization to transcript abundance (via nanopore sequencing) and averaging barcode signals reduced bias.
Achieved a moderate correlation (0.53) with single-transfection controls, demonstrating the method's ability to rank mRNA variants by protein output.

Conclusions:

The enhanced peptide-barcode method can discriminate between mRNA variants with differing protein expression levels in a single pooled experiment.
This approach is valuable for first-pass, rank-order screening, facilitating efficient optimization of mRNA therapeutics.
The peptide-barcode method offers a scalable solution for higher-throughput optimization of extensive mRNA libraries.