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Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity

Frölich, Maximiliane; Hofheinz, Dennis; Meier, Michael A. R.

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.


Verlagsausgabe §
DOI: 10.5445/IR/1000128186
Veröffentlicht am 08.01.2021
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Organische Chemie (IOC)
Institut für Biologische und Chemische Systeme (IBCS)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 12.2020
Sprache Englisch
Identifikator ISSN: 2399-3669
KITopen-ID: 1000128186
HGF-Programm 47.01.01 (POF III, LK 01) Biol.Netzwerke u.Synth.Regulat. ITG+ITC
Erschienen in Communications chemistry
Verlag Nature Research
Band 3
Heft 1
Seiten Art.Nr. 184
Vorab online veröffentlicht am 09.12.2020
Nachgewiesen in Dimensions
Scopus
Web of Science
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