R&D: Reading Mixtures of Uniform Sequence-Defined Macromolecules to Increase Storage Capacity

Communications Chemistry has published an article written by Maximiliane Frölich, Laboratory of Applied Chemistry, Institute of Organic Chemistry (IOC), Karlsruhe Institute of Technology (KIT), Straße am Forum 7, 76131, Karlsruhe, Germany, Dennis Hofheinz, Department of Computer Science, ETH Zürich, Universitätsstrasse 6, 8092, Zürich, Switzerland, and Michael A. R. Meier, Laboratory of Applied Chemistry, Institute of Organic Chemistry (IOC), Karlsruhe Institute of Technology (KIT), Straße am Forum 7, 76131, Karlsruhe, Germany, and Laboratory of Applied Chemistry, Institute of Biological and Chemical Systems–Functional Molecular Systems (IBCS-FMS), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, 76344, Eggenstein-Leopoldshafen, Germany.

Abstract: “In recent years, the field of molecular data storage has emerged from a niche to a vibrant research topic. Herein, we describe a simultaneous and automated read-out of data stored in mixtures of sequence-defined oligomers. Therefore, twelve different sequence-defined tetramers and three hexamers with different mass markers and side chains are successfully synthesised via iterative Passerini three-component reactions and subsequent deprotection steps. By programming a straightforward python script for ESI-MS/MS analysis, it is possible to automatically sequence and thus read-out the information stored in these oligomers within one second. Most importantly, we demonstrate that the use of mass-markers as starting compounds eases MS/MS data interpretation and furthermore allows the unambiguous reading of sequences of mixtures of sequence-defined oligomers. Thus, high data storage capacity considering the field of synthetic macromolecules (up to 64.5 bit in our examples) can be obtained without the need of synthesizing long sequences, but by mixing and simultaneously analysing shorter sequence-defined oligomers.“