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Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity
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 wit...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814948/ https://www.ncbi.nlm.nih.gov/pubmed/36703345 http://dx.doi.org/10.1038/s42004-020-00431-9 |
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author | Frölich, Maximiliane Hofheinz, Dennis Meier, Michael A. R. |
author_facet | Frölich, Maximiliane Hofheinz, Dennis Meier, Michael A. R. |
author_sort | Frölich, Maximiliane |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9814948 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-98149482023-01-10 Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity Frölich, Maximiliane Hofheinz, Dennis Meier, Michael A. R. Commun Chem Article 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. Nature Publishing Group UK 2020-12-09 /pmc/articles/PMC9814948/ /pubmed/36703345 http://dx.doi.org/10.1038/s42004-020-00431-9 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Frölich, Maximiliane Hofheinz, Dennis Meier, Michael A. R. Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title | Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title_full | Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title_fullStr | Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title_full_unstemmed | Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title_short | Reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
title_sort | reading mixtures of uniform sequence-defined macromolecules to increase data storage capacity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814948/ https://www.ncbi.nlm.nih.gov/pubmed/36703345 http://dx.doi.org/10.1038/s42004-020-00431-9 |
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