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用于化学数据存储的多功能序列定义的大分子

Multifunctional sequence-defined macromolecules for chemical data storage.

机构信息

Department of Organic and Macromolecular Chemistry, Polymer Chemistry Research Group, Centre of Macromolecular Chemistry (CMaC), Ghent University, Krijgslaan 281 S4bis, 9000, Ghent, Belgium.

Department of Biochemistry and Microbiology, Laboratory for Protein Biochemistry and Biomolecular Engineering, Ghent University, K.L. Ledeganckstraat 35, 9000, Ghent, Belgium.

出版信息

Nat Commun. 2018 Oct 26;9(1):4451. doi: 10.1038/s41467-018-06926-3.

Abstract

Sequence-defined macromolecules consist of a defined chain length (single mass), end-groups, composition and topology and prove promising in application fields such as anti-counterfeiting, biological mimicking and data storage. Here we show the potential use of multifunctional sequence-defined macromolecules as a storage medium. As a proof-of-principle, we describe how short text fragments (human-readable data) and QR codes (machine-readable data) are encoded as a collection of oligomers and how the original data can be reconstructed. The amide-urethane containing oligomers are generated using an automated protecting-group free, two-step iterative protocol based on thiolactone chemistry. Tandem mass spectrometry techniques have been explored to provide detailed analysis of the oligomer sequences. We have developed the generic software tools Chemcoder for encoding/decoding binary data as a collection of multifunctional macromolecules and Chemreader for reconstructing oligomer sequences from mass spectra to automate the process of chemical writing and reading.

摘要

序列定义的大分子由定义的链长(单一质量)、端基、组成和拓扑结构组成,在防伪、生物模拟和数据存储等应用领域有很大的应用潜力。在这里,我们展示了多功能序列定义的大分子作为存储介质的潜在用途。作为原理验证,我们描述了如何将短文本片段(人类可读数据)和 QR 码(机器可读数据)编码为一系列低聚物,以及如何重建原始数据。含酰胺-氨基甲酸酯的低聚物是使用基于硫内酯化学的自动无保护基团、两步迭代协议生成的。串联质谱技术已被用于提供低聚物序列的详细分析。我们开发了通用软件工具 Chemcoder,用于将二进制数据编码/解码为多功能大分子的集合,以及 Chemreader,用于从质谱中重建低聚物序列,以实现化学写入和读取的自动化过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/50c7/6203848/b84588cedac8/41467_2018_6926_Fig1_HTML.jpg

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