A Workflow Enabling the Automated Synthesis, Chain-End Degradation, and Rapid Mass Spectrometry Analysis for Molecular Information Storage in Sequence-Defined Oligourethanes

Abstract

The field of molecular information storage has recently expanded to include abiotic sequence-defined polymers. While robust methods have been developed, there is a current bottleneck in the throughput of this work as information density is increased. Herein, we introduce an automated workflow in which a commercial peptide synthesizer composed of a single XYZ liquid-handling robot was adapted to both synthesize and sequence sequence-defined oligourethanes. Our sequencing method was improved to cut down the number of samples required for each oligomer from 13 to one. Additionally, we introduce the use of desorption electrospray ionization mass spectrometry as our analysis method for sequencing, which allowed for simplified and increased speed of data acquisition. Finally, we created a Python script that is able to reconstruct the sequence information from the MS data in an automated fashion. We demonstrate this new workflow by encoding and decoding a quote from the late Maya Angelou: “When you learn, teach, when you get, give”.