An alternative approach to nucleic acid memory.

An alternative approach to nucleic acid memory.
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DOI:
10.1038/s41467-021-22277-y
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发表时间:
2021-04-22
影响因子:
16.6
通讯作者:
Hughes WL
Hughes WL
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Dickinson GD;Mortuza GM;Clay W;Piantanida L;Green CM;Watson C;Hayden EJ;Andersen T;Kuang W;Graugnard E;Zadegan R;Hughes WL

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DNA是非易失性信息存储技术的一个引人注目的替代品,因为它的信息密度,稳定性和能源效率。以前的研究使用人工合成的DNA来存储数据,并使用自动化的下一代测序来读取数据。在这里,我们报告数字核酸存储器(dNAM)的应用程序,需要有限的数据量,具有高信息密度,冗余和拷贝数。在dNAM中,通过选择具有(1)或不具有(0)对接位点结构域的单链DNA的组合来编码数据。当与支架DNA自组装时,订书钉链形成DNA折纸实验板。通过使用DNA-PAINT超分辨率显微镜监测荧光成像探针的结合来读取编码到实验板中的信息。为了提高数据保持能力,采用了一种结合喷泉码和二阶奇偶校验码的多层纠错方案。作为一个原型,十五个折纸编码与“数据是在我们的DNA!”n'进行了分析。每个折纸编码独特的数据液滴,索引,方向和纠错信息。当单个对接点或整个折纸丢失时,纠错算法可以完全恢复消息。与其他基于DNA的数据存储方法不同,阅读dNAM不需要测序。因此,它为探索DNA作为新兴记忆材料的优点和缺点提供了另一条途径。在DNA中编码数据是一种很有前途的高密度数据存储方法。在这里,作者提出了一种原型无测序方法,该方法使用超分辨率显微镜读数的DNA链的空间取向。
DNA is a compelling alternative to non-volatile information storage technologies due to its information density, stability, and energy efficiency. Previous studies have used artificially synthesized DNA to store data and automated next-generation sequencing to read it back. Here, we report digital Nucleic Acid Memory (dNAM) for applications that require a limited amount of data to have high information density, redundancy, and copy number. In dNAM, data is encoded by selecting combinations of single-stranded DNA with (1) or without (0) docking-site domains. When self-assembled with scaffold DNA, staple strands form DNA origami breadboards. Information encoded into the breadboards is read by monitoring the binding of fluorescent imager probes using DNA-PAINT super-resolution microscopy. To enhance data retention, a multi-layer error correction scheme that combines fountain and bi-level parity codes is used. As a prototype, fifteen origami encoded with ‘Data is in our DNA!\n’ are analyzed. Each origami encodes unique data-droplet, index, orientation, and error-correction information. The error-correction algorithms fully recover the message when individual docking sites, or entire origami, are missing. Unlike other approaches to DNA-based data storage, reading dNAM does not require sequencing. As such, it offers an additional path to explore the advantages and disadvantages of DNA as an emerging memory material. Encoding data in DNA is a promising approach to high density data storage. Here the authors present a prototype sequencing-free method that uses the spatial orientation of DNA strands with super-resolution microscopy readout.
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